Structural constraints in the packaging of bluetongue virus genomic segments

PubMed Central

Burkhardt, Christiane; Sung, Po-Yu; Celma, Cristina C.

2014-01-01

The mechanism used by bluetongue virus (BTV) to ensure the sorting and packaging of its 10 genomic segments is still poorly understood. In this study, we investigated the packaging constraints for two BTV genomic segments from two different serotypes. Segment 4 (S4) of BTV serotype 9 was mutated sequentially and packaging of mutant ssRNAs was investigated by two newly developed RNA packaging assay systems, one in vivo and the other in vitro. Modelling of the mutated ssRNA followed by biochemical data analysis suggested that a conformational motif formed by interaction of the 5′ and 3′ ends of the molecule was necessary and sufficient for packaging. A similar structural signal was also identified in S8 of BTV serotype 1. Furthermore, the same conformational analysis of secondary structures for positive-sense ssRNAs was used to generate a chimeric segment that maintained the putative packaging motif but contained unrelated internal sequences. This chimeric segment was packaged successfully, confirming that the motif identified directs the correct packaging of the segment. PMID:24980574

Segmentation of the heart and major vascular structures in cardiovascular CT images

NASA Astrophysics Data System (ADS)

Peters, J.; Ecabert, O.; Lorenz, C.; von Berg, J.; Walker, M. J.; Ivanc, T. B.; Vembar, M.; Olszewski, M. E.; Weese, J.

2008-03-01

Segmentation of organs in medical images can be successfully performed with shape-constrained deformable models. A surface mesh is attracted to detected image boundaries by an external energy, while an internal energy keeps the mesh similar to expected shapes. Complex organs like the heart with its four chambers can be automatically segmented using a suitable shape variablility model based on piecewise affine degrees of freedom. In this paper, we extend the approach to also segment highly variable vascular structures. We introduce a dedicated framework to adapt an extended mesh model to freely bending vessels. This is achieved by subdividing each vessel into (short) tube-shaped segments ("tubelets"). These are assigned to individual similarity transformations for local orientation and scaling. Proper adaptation is achieved by progressively adapting distal vessel parts to the image only after proximal neighbor tubelets have already converged. In addition, each newly activated tubelet inherits the local orientation and scale of the preceeding one. To arrive at a joint segmentation of chambers and vasculature, we extended a previous model comprising endocardial surfaces of the four chambers, the left ventricular epicardium, and a pulmonary artery trunk. Newly added are the aorta (ascending and descending plus arch), superior and inferior vena cava, coronary sinus, and four pulmonary veins. These vessels are organized as stacks of triangulated rings. This mesh configuration is most suitable to define tubelet segments. On 36 CT data sets reconstructed at several cardiac phases from 17 patients, segmentation accuracies of 0.61-0.80mm are obtained for the cardiac chambers. For the visible parts of the newly added great vessels, surface accuracies of 0.47-1.17mm are obtained (larger errors are asscociated with faintly contrasted venous structures).

Pattern similarity study of functional sites in protein sequences: lysozymes and cystatins

PubMed Central

Nakai, Shuryo; Li-Chan, Eunice CY; Dou, Jinglie

2005-01-01

Background Although it is generally agreed that topography is more conserved than sequences, proteins sharing the same fold can have different functions, while there are protein families with low sequence similarity. An alternative method for profile analysis of characteristic conserved positions of the motifs within the 3D structures may be needed for functional annotation of protein sequences. Using the approach of quantitative structure-activity relationships (QSAR), we have proposed a new algorithm for postulating functional mechanisms on the basis of pattern similarity and average of property values of side-chains in segments within sequences. This approach was used to search for functional sites of proteins belonging to the lysozyme and cystatin families. Results Hydrophobicity and β-turn propensity of reference segments with 3–7 residues were used for the homology similarity search (HSS) for active sites. Hydrogen bonding was used as the side-chain property for searching the binding sites of lysozymes. The profiles of similarity constants and average values of these parameters as functions of their positions in the sequences could identify both active and substrate binding sites of the lysozyme of Streptomyces coelicolor, which has been reported as a new fold enzyme (Cellosyl). The same approach was successfully applied to cystatins, especially for postulating the mechanisms of amyloidosis of human cystatin C as well as human lysozyme. Conclusion Pattern similarity and average index values of structure-related properties of side chains in short segments of three residues or longer were, for the first time, successfully applied for predicting functional sites in sequences. This new approach may be applicable to studying functional sites in un-annotated proteins, for which complete 3D structures are not yet available. PMID:15904486

Automatic segmentation of the facial nerve and chorda tympani using image registration and statistical priors

NASA Astrophysics Data System (ADS)

Noble, Jack H.; Warren, Frank M.; Labadie, Robert F.; Dawant, Benoit M.

2008-03-01

In cochlear implant surgery, an electrode array is permanently implanted in the cochlea to stimulate the auditory nerve and allow deaf people to hear. A minimally invasive surgical technique has recently been proposed--percutaneous cochlear access--in which a single hole is drilled from the skull surface to the cochlea. For the method to be feasible, a safe and effective drilling trajectory must be determined using a pre-operative CT. Segmentation of the structures of the ear would improve trajectory planning safety and efficiency and enable the possibility of automated planning. Two important structures of the ear, the facial nerve and chorda tympani, present difficulties in intensity based segmentation due to their diameter (as small as 1.0 and 0.4 mm) and adjacent inter-patient variable structures of similar intensity in CT imagery. A multipart, model-based segmentation algorithm is presented in this paper that accomplishes automatic segmentation of the facial nerve and chorda tympani. Segmentation results are presented for 14 test ears and are compared to manually segmented surfaces. The results show that mean error in structure wall localization is 0.2 and 0.3 mm for the facial nerve and chorda, proving the method we propose is robust and accurate.

Semiautomatic Segmentation of Glioma on Mobile Devices.

PubMed

Wu, Ya-Ping; Lin, Yu-Song; Wu, Wei-Guo; Yang, Cong; Gu, Jian-Qin; Bai, Yan; Wang, Mei-Yun

2017-01-01

Brain tumor segmentation is the first and the most critical step in clinical applications of radiomics. However, segmenting brain images by radiologists is labor intense and prone to inter- and intraobserver variability. Stable and reproducible brain image segmentation algorithms are thus important for successful tumor detection in radiomics. In this paper, we propose a supervised brain image segmentation method, especially for magnetic resonance (MR) brain images with glioma. This paper uses hard edge multiplicative intrinsic component optimization to preprocess glioma medical image on the server side, and then, the doctors could supervise the segmentation process on mobile devices in their convenient time. Since the preprocessed images have the same brightness for the same tissue voxels, they have small data size (typically 1/10 of the original image size) and simple structure of 4 types of intensity value. This observation thus allows follow-up steps to be processed on mobile devices with low bandwidth and limited computing performance. Experiments conducted on 1935 brain slices from 129 patients show that more than 30% of the sample can reach 90% similarity; over 60% of the samples can reach 85% similarity, and more than 80% of the sample could reach 75% similarity. The comparisons with other segmentation methods also demonstrate both efficiency and stability of the proposed approach.

Self-Similarity of Plasmon Edge Modes on Koch Fractal Antennas.

PubMed

Bellido, Edson P; Bernasconi, Gabriel D; Rossouw, David; Butet, Jérémy; Martin, Olivier J F; Botton, Gianluigi A

2017-11-28

We investigate the plasmonic behavior of Koch snowflake fractal geometries and their possible application as broadband optical antennas. Lithographically defined planar silver Koch fractal antennas were fabricated and characterized with high spatial and spectral resolution using electron energy loss spectroscopy. The experimental data are supported by numerical calculations carried out with a surface integral equation method. Multiple surface plasmon edge modes supported by the fractal structures have been imaged and analyzed. Furthermore, by isolating and reproducing self-similar features in long silver strip antennas, the edge modes present in the Koch snowflake fractals are identified. We demonstrate that the fractal response can be obtained by the sum of basic self-similar segments called characteristic edge units. Interestingly, the plasmon edge modes follow a fractal-scaling rule that depends on these self-similar segments formed in the structure after a fractal iteration. As the size of a fractal structure is reduced, coupling of the modes in the characteristic edge units becomes relevant, and the symmetry of the fractal affects the formation of hybrid modes. This analysis can be utilized not only to understand the edge modes in other planar structures but also in the design and fabrication of fractal structures for nanophotonic applications.

Evolution of semilocal string networks. II. Velocity estimators

NASA Astrophysics Data System (ADS)

Lopez-Eiguren, A.; Urrestilla, J.; Achúcarro, A.; Avgoustidis, A.; Martins, C. J. A. P.

2017-07-01

We continue a comprehensive numerical study of semilocal string networks and their cosmological evolution. These can be thought of as hybrid networks comprised of (nontopological) string segments, whose core structure is similar to that of Abelian Higgs vortices, and whose ends have long-range interactions and behavior similar to that of global monopoles. Our study provides further evidence of a linear scaling regime, already reported in previous studies, for the typical length scale and velocity of the network. We introduce a new algorithm to identify the position of the segment cores. This allows us to determine the length and velocity of each individual segment and follow their evolution in time. We study the statistical distribution of segment lengths and velocities for radiation- and matter-dominated evolution in the regime where the strings are stable. Our segment detection algorithm gives higher length values than previous studies based on indirect detection methods. The statistical distribution shows no evidence of (anti)correlation between the speed and the length of the segments.

DsaV methyltransferase and its isoschizomers contain a conserved segment that is similar to the segment in Hhai methyltransferase that is in contact with DNA bases.

PubMed Central

Gopal, J; Yebra, M J; Bhagwat, A S

1994-01-01

The methyltransferase (MTase) in the DsaV restriction--modification system methylates within 5'-CCNGG sequences. We have cloned the gene for this MTase and determined its sequence. The predicted sequence of the MTase protein contains sequence motifs conserved among all cytosine-5 MTases and is most similar to other MTases that methylate CCNGG sequences, namely M.ScrFI and M.SsoII. All three MTases methylate the internal cytosine within their recognition sequence. The 'variable' region within the three enzymes that methylate CCNGG can be aligned with the sequences of two enzymes that methylate CCWGG sequences. Remarkably, two segments within this region contain significant similarity with the region of M.HhaI that is known to contact DNA bases. These alignments suggest that many cytosine-5 MTases are likely to interact with DNA using a similar structural framework. Images PMID:7971279

Deep learning and shapes similarity for joint segmentation and tracing single neurons in SEM images

NASA Astrophysics Data System (ADS)

Rao, Qiang; Xiao, Chi; Han, Hua; Chen, Xi; Shen, Lijun; Xie, Qiwei

2017-02-01

Extracting the structure of single neurons is critical for understanding how they function within the neural circuits. Recent developments in microscopy techniques, and the widely recognized need for openness and standardization provide a community resource for automated reconstruction of dendritic and axonal morphology of single neurons. In order to look into the fine structure of neurons, we use the Automated Tape-collecting Ultra Microtome Scanning Electron Microscopy (ATUM-SEM) to get images sequence of serial sections of animal brain tissue that densely packed with neurons. Different from other neuron reconstruction method, we propose a method that enhances the SEM images by detecting the neuronal membranes with deep convolutional neural network (DCNN) and segments single neurons by active contour with group shape similarity. We joint the segmentation and tracing together and they interact with each other by alternate iteration that tracing aids the selection of candidate region patch for active contour segmentation while the segmentation provides the neuron geometrical features which improve the robustness of tracing. The tracing model mainly relies on the neuron geometrical features and is updated after neuron being segmented on the every next section. Our method enables the reconstruction of neurons of the drosophila mushroom body which is cut to serial sections and imaged under SEM. Our method provides an elementary step for the whole reconstruction of neuronal networks.

Structure-function relationships of curaremimetic neurotoxin loop 2 and of a structurally similar segment of rabies virus glycoprotein in their interaction with the nicotinic acetylcholine receptor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lentz, T.L.

1991-11-12

Peptides corresponding to portions of curaremimetic neurotoxin loop 2 and to a structurally similar segment of rabies virus glycoprotein were synthetically modified in order to gain information on structure-function relationships of neurotoxin loop 2 interactions with the acetylcholine receptor. Binding of synthetic peptides to the acetylcholine receptor of Torpedo electric organ membranes was assessed by measuring their ability to inhibit the binding of {sup 125}I-{alpha}-bungarotoxin to the receptor. The peptides showing the highest affinity for the receptor were a peptide corresponding to the sequence of loop 2 (residues 25-44) of Ophiophagus hannah (king cobra) toxin b and the structurally similarmore » segment of CVS rabies virus glycoprotein. These affinities were comparable to those of d-tubocurarine and suberyldicholine. These results demonstrate the importance of loop 2 in the neurotoxin interaction with the receptor. N- and C-terminal deletions of the loop 2 peptides and substitution of residues invariant or highly conserved among neurotoxins were performed in order to determine the role of individual residues in binding. Residues 25-40 are the most crucial in the interaction with the acetylcholine receptor. Since this region of the glycoprotein contains residues corresponding to all of the functionally invariant neurotoxin residues, it may interact with the acetylcholine receptor through a mechanism similar to that of the neurotoxins.« less

Improved segmentation of cerebellar structures in children

PubMed Central

Narayanan, Priya Lakshmi; Boonazier, Natalie; Warton, Christopher; Molteno, Christopher D; Joseph, Jesuchristopher; Jacobson, Joseph L; Jacobson, Sandra W; Zöllei, Lilla; Meintjes, Ernesta M

2016-01-01

Background Consistent localization of cerebellar cortex in a standard coordinate system is important for functional studies and detection of anatomical alterations in studies of morphometry. To date, no pediatric cerebellar atlas is available. New method The probabilistic Cape Town Pediatric Cerebellar Atlas (CAPCA18) was constructed in the age-appropriate National Institute of Health Pediatric Database asymmetric template space using manual tracings of 16 cerebellar compartments in 18 healthy children (9–13 years) from Cape Town, South Africa. The individual atlases of the training subjects were also used to implement multi atlas label fusion using multi atlas majority voting (MAMV) and multi atlas generative model (MAGM) approaches. Segmentation accuracy in 14 test subjects was compared for each method to ‘gold standard’ manual tracings. Results Spatial overlap between manual tracings and CAPCA18 automated segmentation was 73% or higher for all lobules in both hemispheres, except VIIb and X. Automated segmentation using MAGM yielded the best segmentation accuracy over all lobules (mean Dice Similarity Coefficient 0.76; range 0.55–0.91). Comparison with existing methods In all lobules, spatial overlap of CAPCA18 segmentations with manual tracings was similar or higher than those obtained with SUIT (spatially unbiased infra-tentorial template), providing additional evidence of the benefits of an age appropriate atlas. MAGM segmentation accuracy was comparable to values reported recently by Park et al. (2014) in adults (across all lobules mean DSC = 0.73, range 0.40–0.89). Conclusions CAPCA18 and the associated multi atlases of the training subjects yield improved segmentation of cerebellar structures in children. PMID:26743973

Clinical evaluation of multi-atlas based segmentation of lymph node regions in head and neck and prostate cancer patients.

PubMed

Sjöberg, Carl; Lundmark, Martin; Granberg, Christoffer; Johansson, Silvia; Ahnesjö, Anders; Montelius, Anders

2013-10-03

Semi-automated segmentation using deformable registration of selected atlas cases consisting of expert segmented patient images has been proposed to facilitate the delineation of lymph node regions for three-dimensional conformal and intensity-modulated radiotherapy planning of head and neck and prostate tumours. Our aim is to investigate if fusion of multiple atlases will lead to clinical workload reductions and more accurate segmentation proposals compared to the use of a single atlas segmentation, due to a more complete representation of the anatomical variations. Atlases for lymph node regions were constructed using 11 head and neck patients and 15 prostate patients based on published recommendations for segmentations. A commercial registration software (Velocity AI) was used to create individual segmentations through deformable registration. Ten head and neck patients, and ten prostate patients, all different from the atlas patients, were randomly chosen for the study from retrospective data. Each patient was first delineated three times, (a) manually by a radiation oncologist, (b) automatically using a single atlas segmentation proposal from a chosen atlas and (c) automatically by fusing the atlas proposals from all cases in the database using the probabilistic weighting fusion algorithm. In a subsequent step a radiation oncologist corrected the segmentation proposals achieved from step (b) and (c) without using the result from method (a) as reference. The time spent for editing the segmentations was recorded separately for each method and for each individual structure. Finally, the Dice Similarity Coefficient and the volume of the structures were used to evaluate the similarity between the structures delineated with the different methods. For the single atlas method, the time reduction compared to manual segmentation was 29% and 23% for head and neck and pelvis lymph nodes, respectively, while editing the fused atlas proposal resulted in time reductions of 49% and 34%. The average volume of the fused atlas proposals was only 74% of the manual segmentation for the head and neck cases and 82% for the prostate cases due to a blurring effect from the fusion process. After editing of the proposals the resulting volume differences were no longer statistically significant, although a slight influence by the proposals could be noticed since the average edited volume was still slightly smaller than the manual segmentation, 9% and 5%, respectively. Segmentation based on fusion of multiple atlases reduces the time needed for delineation of lymph node regions compared to the use of a single atlas segmentation. Even though the time saving is large, the quality of the segmentation is maintained compared to manual segmentation.

Automated segmentation of midbrain structures with high iron content.

PubMed

Garzón, Benjamín; Sitnikov, Rouslan; Bäckman, Lars; Kalpouzos, Grégoria

2018-04-15

The substantia nigra (SN), the subthalamic nucleus (STN), and the red nucleus (RN) are midbrain structures of ample interest in many neuroimaging studies, which may benefit from the availability of automated segmentation methods. The high iron content of these structures awards them high contrast in quantitative susceptibility mapping (QSM) images. We present a novel segmentation method that leverages the information of these images to produce automated segmentations of the SN, STN, and RN. The algorithm builds a map of spatial priors for the structures by non-linearly registering a set of manually-traced training labels to the midbrain. The priors are used to inform a Gaussian mixture model of the image intensities, with smoothness constraints imposed to ensure anatomical plausibility. The method was validated on manual segmentations from a sample of 40 healthy younger and older subjects. Average Dice scores were 0.81 (0.05) for the SN, 0.66 (0.14) for the STN and 0.88 (0.04) for the RN in the left hemisphere, and similar values were obtained for the right hemisphere. In all structures, volumes of manual and automatically obtained segmentations were significantly correlated. The algorithm showed lower accuracy on R 2 * and T 2 -weighted Fluid Attenuated Inversion Recovery (FLAIR) images, which are also sensitive to iron content. To illustrate an application of the method, we show that the automated segmentations were comparable to the manual ones regarding detection of age-related differences to putative iron content. Copyright © 2017 Elsevier Inc. All rights reserved.

Polysaccharide compositions of collenchyma cell walls from celery (Apium graveolens L.) petioles.

PubMed

Chen, Da; Harris, Philip J; Sims, Ian M; Zujovic, Zoran; Melton, Laurence D

2017-06-15

Collenchyma serves as a mechanical support tissue for many herbaceous plants. Previous work based on solid-state NMR and immunomicroscopy suggested collenchyma cell walls (CWs) may have similar polysaccharide compositions to those commonly found in eudicotyledon parenchyma walls, but no detailed chemical analysis was available. In this study, compositions and structures of cell wall polysaccharides of peripheral collenchyma from celery petioles were investigated. This is the first detailed investigation of the cell wall composition of collenchyma from any plant. Celery petioles were found to elongate throughout their length during early growth, but as they matured elongation was increasingly confined to the upper region, until elongation ceased. Mature, fully elongated, petioles were divided into three equal segments, upper, middle and lower, and peripheral collenchyma strands isolated from each. Cell walls (CWs) were prepared from the strands, which also yielded a HEPES buffer soluble fraction. The CWs were sequentially extracted with CDTA, Na 2 CO 3 , 1 M KOH and 4 M KOH. Monosaccharide compositions of the CWs showed that pectin was the most abundant polysaccharide [with homogalacturonan (HG) more abundant than rhamnogalacturonan I (RG-I) and rhamnogalacturonan II (RG-II)], followed by cellulose, and other polysaccharides, mainly xyloglucans, with smaller amounts of heteroxylans and heteromannans. CWs from different segments had similar compositions, but those from the upper segments had slightly more pectin than those from the lower two segments. Further, the pectin in the CWs of the upper segment had a higher degree of methyl esterification than the other segments. In addition to the anticipated water-soluble pectins, the HEPES-soluble fractions surprisingly contained large amounts of heteroxylans. The CDTA and Na 2 CO 3 fractions were rich in HG and RG-I, the 1 M KOH fraction had abundant heteroxylans, the 4 M KOH fraction was rich in xyloglucan and heteromannans, and cellulose was predominant in the final residue. The structures of the xyloglucans, heteroxylans and heteromannans were deduced from the linkage analysis and were similar to those present in most eudicotyledon parenchyma CWs. Cross polarization with magic angle spinning (CP/MAS) NMR spectroscopy showed no apparent difference in the rigid and semi-rigid polysaccharides in the CWs of the three segments. Single-pulse excitation with magic-angle spinning (SPE/MAS) NMR spectroscopy, which detects highly mobile polysaccharides, showed the presence of arabinan, the detailed structure of which varied among the cell walls from the three segments. Celery collenchyma CWs have similar polysaccharide compositions to most eudicotyledon parenchyma CWs. However, celery collenchyma CWs have much higher XG content than celery parenchyma CWs. The degree of methyl esterification of pectin and the structures of the arabinan side chains of RG-I show some variation in the collenchyma CWs from the different segments. Unexpectedly, the HEPES-soluble fraction contained a large amount of heteroxylans.

Interactive lung segmentation in abnormal human and animal chest CT scans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kockelkorn, Thessa T. J. P., E-mail: thessa@isi.uu.nl; Viergever, Max A.; Schaefer-Prokop, Cornelia M.

2014-08-15

Purpose: Many medical image analysis systems require segmentation of the structures of interest as a first step. For scans with gross pathology, automatic segmentation methods may fail. The authors’ aim is to develop a versatile, fast, and reliable interactive system to segment anatomical structures. In this study, this system was used for segmenting lungs in challenging thoracic computed tomography (CT) scans. Methods: In volumetric thoracic CT scans, the chest is segmented and divided into 3D volumes of interest (VOIs), containing voxels with similar densities. These VOIs are automatically labeled as either lung tissue or nonlung tissue. The automatic labeling resultsmore » can be corrected using an interactive or a supervised interactive approach. When using the supervised interactive system, the user is shown the classification results per slice, whereupon he/she can adjust incorrect labels. The system is retrained continuously, taking the corrections and approvals of the user into account. In this way, the system learns to make a better distinction between lung tissue and nonlung tissue. When using the interactive framework without supervised learning, the user corrects all incorrectly labeled VOIs manually. Both interactive segmentation tools were tested on 32 volumetric CT scans of pigs, mice and humans, containing pulmonary abnormalities. Results: On average, supervised interactive lung segmentation took under 9 min of user interaction. Algorithm computing time was 2 min on average, but can easily be reduced. On average, 2.0% of all VOIs in a scan had to be relabeled. Lung segmentation using the interactive segmentation method took on average 13 min and involved relabeling 3.0% of all VOIs on average. The resulting segmentations correspond well to manual delineations of eight axial slices per scan, with an average Dice similarity coefficient of 0.933. Conclusions: The authors have developed two fast and reliable methods for interactive lung segmentation in challenging chest CT images. Both systems do not require prior knowledge of the scans under consideration and work on a variety of scans.« less

Combining watershed and graph cuts methods to segment organs at risk in radiotherapy

NASA Astrophysics Data System (ADS)

Dolz, Jose; Kirisli, Hortense A.; Viard, Romain; Massoptier, Laurent

2014-03-01

Computer-aided segmentation of anatomical structures in medical images is a valuable tool for efficient radiation therapy planning (RTP). As delineation errors highly affect the radiation oncology treatment, it is crucial to delineate geometric structures accurately. In this paper, a semi-automatic segmentation approach for computed tomography (CT) images, based on watershed and graph-cuts methods, is presented. The watershed pre-segmentation groups small areas of similar intensities in homogeneous labels, which are subsequently used as input for the graph-cuts algorithm. This methodology does not require of prior knowledge of the structure to be segmented; even so, it performs well with complex shapes and low intensity. The presented method also allows the user to add foreground and background strokes in any of the three standard orthogonal views - axial, sagittal or coronal - making the interaction with the algorithm easy and fast. Hence, the segmentation information is propagated within the whole volume, providing a spatially coherent result. The proposed algorithm has been evaluated using 9 CT volumes, by comparing its segmentation performance over several organs - lungs, liver, spleen, heart and aorta - to those of manual delineation from experts. A Dicés coefficient higher than 0.89 was achieved in every case. That demonstrates that the proposed approach works well for all the anatomical structures analyzed. Due to the quality of the results, the introduction of the proposed approach in the RTP process will be a helpful tool for organs at risk (OARs) segmentation.

The three-dimensional structure of the native ternary complex of bovine pancreatic procarboxypeptidase A with proproteinase E and chymotrypsinogen C.

PubMed Central

Gomis-Rüth, F X; Gómez, M; Bode, W; Huber, R; Avilés, F X

1995-01-01

The metalloexozymogen procarboxypeptidase A is mainly secreted in ruminants as a ternary complex with zymogens of two serine endoproteinases, chymotrypsinogen C and proproteinase E. The bovine complex has been crystallized, and its molecular structure analysed and refined at 2.6 A resolution to an R factor of 0.198. In this heterotrimer, the activation segment of procarboxypeptidase A essentially clamps the other two subunits, which shield the activation sites of the former from tryptic attack. In contrast, the propeptides of both serine proproteinases are freely accessible to trypsin. This arrangement explains the sequential and delayed activation of the constituent zymogens. Procarboxypeptidase A is virtually identical to the homologous monomeric porcine form. Chymotrypsinogen C displays structural features characteristic for chymotrypsins as well as elastases, except for its activation domain; similar to bovine chymotrypsinogen A, its binding site is not properly formed, while its surface located activation segment is disordered. The proproteinase E structure is fully ordered and strikingly similar to active porcine elastase; its specificity pocket is occluded, while the activation segment is fixed to the molecular surface. This first structure of a native zymogen from the proteinase E/elastase family does not fundamentally differ from the serine proproteinases known so far. Images PMID:7556081

Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.

PubMed

Dolz, Jose; Laprie, Anne; Ken, Soléakhéna; Leroy, Henri-Arthur; Reyns, Nicolas; Massoptier, Laurent; Vermandel, Maximilien

2016-01-01

To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk is required. This task is still manually performed, which is time-consuming and prone to observer variability. To address these issues, and as alternative to atlas-based segmentation methods, machine learning techniques, such as support vector machines (SVM), have been recently presented to segment subcortical structures on magnetic resonance images (MRI). SVM is proposed to segment the brainstem on MRI in multicenter brain cancer context. A dataset composed by 14 adult brain MRI scans is used to evaluate its performance. In addition to spatial and probabilistic information, five different image intensity values (IIVs) configurations are evaluated as features to train the SVM classifier. Segmentation accuracy is evaluated by computing the Dice similarity coefficient (DSC), absolute volumes difference (AVD) and percentage volume difference between automatic and manual contours. Mean DSC for all proposed IIVs configurations ranged from 0.89 to 0.90. Mean AVD values were below 1.5 cm(3), where the value for best performing IIVs configuration was 0.85 cm(3), representing an absolute mean difference of 3.99% with respect to the manual segmented volumes. Results suggest consistent volume estimation and high spatial similarity with respect to expert delineations. The proposed approach outperformed presented methods to segment the brainstem, not only in volume similarity metrics, but also in segmentation time. Preliminary results showed that the approach might be promising for adoption in clinical use.

Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline

PubMed Central

Wang, Jiahui; Vachet, Clement; Rumple, Ashley; Gouttard, Sylvain; Ouziel, Clémentine; Perrot, Emilie; Du, Guangwei; Huang, Xuemei; Gerig, Guido; Styner, Martin

2014-01-01

Automated segmenting and labeling of individual brain anatomical regions, in MRI are challenging, due to the issue of individual structural variability. Although atlas-based segmentation has shown its potential for both tissue and structure segmentation, due to the inherent natural variability as well as disease-related changes in MR appearance, a single atlas image is often inappropriate to represent the full population of datasets processed in a given neuroimaging study. As an alternative for the case of single atlas segmentation, the use of multiple atlases alongside label fusion techniques has been introduced using a set of individual “atlases” that encompasses the expected variability in the studied population. In our study, we proposed a multi-atlas segmentation scheme with a novel graph-based atlas selection technique. We first paired and co-registered all atlases and the subject MR scans. A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph. Finally, weighted majority voting is employed to create the final segmentation over the selected atlases. This multi-atlas segmentation scheme is used to extend a single-atlas-based segmentation toolkit entitled AutoSeg, which is an open-source, extensible C++ based software pipeline employing BatchMake for its pipeline scripting, developed at the Neuro Image Research and Analysis Laboratories of the University of North Carolina at Chapel Hill. AutoSeg performs N4 intensity inhomogeneity correction, rigid registration to a common template space, automated brain tissue classification based skull-stripping, and the multi-atlas segmentation. The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans. The AutoSeg achieved mean Dice coefficients of 81.73% for the subcortical structures. PMID:24567717

Discriminative confidence estimation for probabilistic multi-atlas label fusion.

PubMed

Benkarim, Oualid M; Piella, Gemma; González Ballester, Miguel Angel; Sanroma, Gerard

2017-12-01

Quantitative neuroimaging analyses often rely on the accurate segmentation of anatomical brain structures. In contrast to manual segmentation, automatic methods offer reproducible outputs and provide scalability to study large databases. Among existing approaches, multi-atlas segmentation has recently shown to yield state-of-the-art performance in automatic segmentation of brain images. It consists in propagating the labelmaps from a set of atlases to the anatomy of a target image using image registration, and then fusing these multiple warped labelmaps into a consensus segmentation on the target image. Accurately estimating the contribution of each atlas labelmap to the final segmentation is a critical step for the success of multi-atlas segmentation. Common approaches to label fusion either rely on local patch similarity, probabilistic statistical frameworks or a combination of both. In this work, we propose a probabilistic label fusion framework based on atlas label confidences computed at each voxel of the structure of interest. Maximum likelihood atlas confidences are estimated using a supervised approach, explicitly modeling the relationship between local image appearances and segmentation errors produced by each of the atlases. We evaluate different spatial pooling strategies for modeling local segmentation errors. We also present a novel type of label-dependent appearance features based on atlas labelmaps that are used during confidence estimation to increase the accuracy of our label fusion. Our approach is evaluated on the segmentation of seven subcortical brain structures from the MICCAI 2013 SATA Challenge dataset and the hippocampi from the ADNI dataset. Overall, our results indicate that the proposed label fusion framework achieves superior performance to state-of-the-art approaches in the majority of the evaluated brain structures and shows more robustness to registration errors. Copyright © 2017 Elsevier B.V. All rights reserved.

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

Comparative analysis of the L, M, and S RNA segments of Crimean-Congo haemorrhagic fever virus isolates from southern Africa.

PubMed

Goedhals, Dominique; Bester, Phillip A; Paweska, Janusz T; Swanepoel, Robert; Burt, Felicity J

2015-05-01

Crimean-Congo haemorrhagic fever virus (CCHFV) is a member of the Bunyaviridae family with a tripartite, negative sense RNA genome. This study used predictive software to analyse the L (large), M (medium), and S (small) segments of 14 southern African CCHFV isolates. The OTU-like cysteine protease domain and the RdRp domain of the L segment are highly conserved among southern African CCHFV isolates. The M segment encodes the structural glycoproteins, GN and GC, and the non-structural glycoproteins which are post-translationally cleaved at highly conserved furin and subtilase SKI-1 cleavage sites. All of the sites previously identified were shown to be conserved among southern African CCHFV isolates. The heavily O-glycosylated N-terminal variable mucin-like domain of the M segment shows the highest sequence variability of the CCHFV proteins. Five transmembrane domains are predicted in the M segment polyprotein resulting in three regions internal to and three regions external to the membrane across the G(N), NS(M) and G(C) glycoproteins. The corroboration of conserved genome domains and sequence identity among geographically diverse isolates may assist in the identification of protein function and pathogenic mechanisms, as well as the identification of potential targets for antiviral therapy and vaccine design. As detailed functional studies are lacking for many of the CCHFV proteins, identification of functional domains by prediction of protein structure, and identification of amino acid level similarity to functionally characterised proteins of related viruses or viruses with similar pathogenic mechanisms are a necessary step for selection of areas for further study. © 2015 Wiley Periodicals, Inc.

Two-dimensional sup 1 H NMR studies on HPr protein from Staphylococcus aureus: Complete sequential assignments and secondary structure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalbitzer, H.R.; Neidig, K.P.; Hengstenberg, W.

1991-11-19

Complete sequence-specific assignments of the {sup 1}H NMR spectrum of HPr protein from Staphylococcus aureus were obtained by two-dimensional NMR methods. Important secondary structure elements that can be derived from the observed nuclear Overhauser effects are a large antiparallel {beta}-pleated sheet consisting of four strands, A, B, C, D, a segment S{sub AB} consisting of an extended region around the active-center histidine (His-15) and an {alpha}-helix, a half-turn between strands B and C, a segment S{sub CD} which shows no typical secondary structure, and the {alpha}-helical, C-terminal segment S{sub term}. These general structural features are similar to those found earliermore » in HPr proteins from different microorganisms such as Escherichia coli, Bacillus subtilis, and Streptococcus faecalis.« less

Validation tools for image segmentation

NASA Astrophysics Data System (ADS)

Padfield, Dirk; Ross, James

2009-02-01

A large variety of image analysis tasks require the segmentation of various regions in an image. For example, segmentation is required to generate accurate models of brain pathology that are important components of modern diagnosis and therapy. While the manual delineation of such structures gives accurate information, the automatic segmentation of regions such as the brain and tumors from such images greatly enhances the speed and repeatability of quantifying such structures. The ubiquitous need for such algorithms has lead to a wide range of image segmentation algorithms with various assumptions, parameters, and robustness. The evaluation of such algorithms is an important step in determining their effectiveness. Therefore, rather than developing new segmentation algorithms, we here describe validation methods for segmentation algorithms. Using similarity metrics comparing the automatic to manual segmentations, we demonstrate methods for optimizing the parameter settings for individual cases and across a collection of datasets using the Design of Experiment framework. We then employ statistical analysis methods to compare the effectiveness of various algorithms. We investigate several region-growing algorithms from the Insight Toolkit and compare their accuracy to that of a separate statistical segmentation algorithm. The segmentation algorithms are used with their optimized parameters to automatically segment the brain and tumor regions in MRI images of 10 patients. The validation tools indicate that none of the ITK algorithms studied are able to outperform with statistical significance the statistical segmentation algorithm although they perform reasonably well considering their simplicity.

Genes encoding Xenopus laevis Ig L chains: Implications for the evolution of [kappa] and [lambda] chains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zezza, D.J.; Stewart, S.E.; Steiner, L.A.

1992-12-15

Xenopus laevis Ig contain two distinct types of L chains, designated [rho] or L1 and [sigma] or L2. The authors have analyzed Xenopus genomic DNA by Southern blotting with cDNA probes specific for L1 V and C regions. Many fragments hybridized to the V probe, but only one or two fragments hybridized to the C probe. Corresponding C, J, and V gene segments were identified on clones isolated from a genomic library prepared from the same DNA. One clone contains a C gene segment separated from a J gene segment by an intron of 3.4 kb. The J and Cmore » gene segments are nearly identical in sequence to cDNA clones analyzed previously. The C segment is somewhat more similar and the J segment considerably more similar in sequence to the corresponding segments of mammalian [kappa] chains than to those of mammalian [lambda] chains. Upstream of the J segment is a typical recombination signal sequence with a spacer of 23 bp, as in J[kappa]. A second clone from the library contains four V gene segments, separated by 2.1 to 3.6 kb. Two of these, V1 and V3, have the expected structural and regulatory features of V genes, and are very similar in sequence to each other and to mammalian V[kappa]. A third gene segment, V2, resembles V1 and V3 in its coding region and nearby 5[prime]-flanking region, but diverges in sequence 5[prime] to position [minus]95 with loss of the octamer promoter element. The fourth V-like segment is similar to the others at the 3[prime]-end, but upstream of codon 64 bears no resemblance in sequence to any Ig V region. All four V segments have typical recombination signal sequences with 12-bp spacers at their 3[prime]-ends, as in V[kappa]. Taken together, the data suggest that Xenopus L1 L chain genes are members of the [kappa] gene family. 80 refs., 9 figs.« less

Structure of the human protein kinase MPSK1 reveals an atypical activation loop architecture.

PubMed

Eswaran, Jeyanthy; Bernad, Antonio; Ligos, Jose M; Guinea, Barbara; Debreczeni, Judit E; Sobott, Frank; Parker, Sirlester A; Najmanovich, Rafael; Turk, Benjamin E; Knapp, Stefan

2008-01-01

The activation segment of protein kinases is structurally highly conserved and central to regulation of kinase activation. Here we report an atypical activation segment architecture in human MPSK1 comprising a beta sheet and a large alpha-helical insertion. Sequence comparisons suggested that similar activation segments exist in all members of the MPSK1 family and in MAST kinases. The consequence of this nonclassical activation segment on substrate recognition was studied using peptide library screens that revealed a preferred substrate sequence of X-X-P/V/I-phi-H/Y-T*-N/G-X-X-X (phi is an aliphatic residue). In addition, we identified the GTPase DRG1 as an MPSK1 interaction partner and specific substrate. The interaction domain in DRG1 was mapped to the N terminus, leading to recruitment and phosphorylation at Thr100 within the GTPase domain. The presented data reveal an atypical kinase structural motif and suggest a role of MPSK1 regulating DRG1, a GTPase involved in regulation of cellular growth.

Along-axis segmentation and isostasy in the Western rift, East Africa

NASA Astrophysics Data System (ADS)

Upcott, N. M.; Mukasa, R. K.; Ebinger, C. J.; Karner, G. D.

1996-02-01

Structural variations along the southern sectors of the Western rift, East Africa, have previously been described, but subsurface structures in the northern sector (Uganda, Zaire) are virtually unknown. Our aims are to investigate the along-axis segmentation of the northern sector, thereby adding to the structural picture of the Western rift, and to study the isostatic compensation of the varying rift morphology along the sector's length. This study describes the first gravity survey to be carried out on the shallow Lake Albert, forward models of these and existing gravity data, and the results from inverse modeling of existing aeromagnetic data designed to delimit border and transfer fault systems. Our tectonic model shows that the northern rift sector is segmented along-axis into five 25 to 65-km-wide, 80 to 100-km-long rift segments, characterized by closed-contour Bouguer anomaly lows, and bounded by steep gravity, aeromagnetic, and topographic/bathymetric gradients. Werner and Euler deconvolution results and gravity anomaly data reveal that some faulted basins are separated by structural highs and cross-rift ramps or faults and suggest sedimentary basin depths of 4-6 km. Forward modeling of structural and free-air gravity profiles across individual basins and flanks using a model that assumes flexural compensation also suggests sediment thicknesses of up to 5.5 km, similar to the estimates from magnetic data. The basin and flank morphology can be explained by 6-9 km of extension of a lithosphere with an effective elastic thickness (Te) of 25 km (equivalent to a flexural rigidity of 1.4 × 1023 N m), similar to results in other Western rift basins. Potential field data and lithospheric strength estimates in the Western rift system show small along-axis variations in lithospheric structure, regardless of the presence or absence of Cenozoic magmatism.

Automatic segmentation of male pelvic anatomy on computed tomography images: a comparison with multiple observers in the context of a multicentre clinical trial.

PubMed

Geraghty, John P; Grogan, Garry; Ebert, Martin A

2013-04-30

This study investigates the variation in segmentation of several pelvic anatomical structures on computed tomography (CT) between multiple observers and a commercial automatic segmentation method, in the context of quality assurance and evaluation during a multicentre clinical trial. CT scans of two prostate cancer patients ('benchmarking cases'), one high risk (HR) and one intermediate risk (IR), were sent to multiple radiotherapy centres for segmentation of prostate, rectum and bladder structures according to the TROG 03.04 "RADAR" trial protocol definitions. The same structures were automatically segmented using iPlan software for the same two patients, allowing structures defined by automatic segmentation to be quantitatively compared with those defined by multiple observers. A sample of twenty trial patient datasets were also used to automatically generate anatomical structures for quantitative comparison with structures defined by individual observers for the same datasets. There was considerable agreement amongst all observers and automatic segmentation of the benchmarking cases for bladder (mean spatial variations < 0.4 cm across the majority of image slices). Although there was some variation in interpretation of the superior-inferior (cranio-caudal) extent of rectum, human-observer contours were typically within a mean 0.6 cm of automatically-defined contours. Prostate structures were more consistent for the HR case than the IR case with all human observers segmenting a prostate with considerably more volume (mean +113.3%) than that automatically segmented. Similar results were seen across the twenty sample datasets, with disagreement between iPlan and observers dominant at the prostatic apex and superior part of the rectum, which is consistent with observations made during quality assurance reviews during the trial. This study has demonstrated quantitative analysis for comparison of multi-observer segmentation studies. For automatic segmentation algorithms based on image-registration as in iPlan, it is apparent that agreement between observer and automatic segmentation will be a function of patient-specific image characteristics, particularly for anatomy with poor contrast definition. For this reason, it is suggested that automatic registration based on transformation of a single reference dataset adds a significant systematic bias to the resulting volumes and their use in the context of a multicentre trial should be carefully considered.

Segmentation of knee MRI using structure enhanced local phase filtering

NASA Astrophysics Data System (ADS)

Lim, Mikhiel; Hacihaliloglu, Ilker

2016-03-01

The segmentation of bone surfaces from magnetic resonance imaging (MRI) data has applications in the quanti- tative measurement of knee osteoarthritis, surgery planning for patient specific total knee arthroplasty and its subsequent fabrication of artificial implants. However, due to the problems associated with MRI imaging such as low contrast between bone and surrounding tissues, noise, bias fields, and the partial volume effect, segmentation of bone surfaces continues to be a challenging operation. In this paper, a new framework is presented for the enhancement of knee MRI scans prior to segmentation in order to obtain high contrast bone images. During the first stage, a new contrast enhanced relative total variation (RTV) regularization method is used in order to remove textural noise from the bone structures and surrounding soft tissue interface. This salient bone edge information is further enhanced using a sparse gradient counting method based on L0 gradient minimization, which globally controls how many non-zero gradients are resulted in order to approximate prominent bone structures in a structure-sparsity-management manner. The last stage of the framework involves incorporation of local phase bone boundary information in order to provide an intensity invariant enhancement of contrast between the bone and surrounding soft tissue. The enhanced images are segmented using a fast random walker algorithm. Validation against expert segmentation was performed on 10 clinical knee MRI images, and achieved a mean dice similarity coefficient (DSC) of 0.975.

Stability of local secondary structure determines selectivity of viral RNA chaperones.

PubMed

Bravo, Jack P K; Borodavka, Alexander; Barth, Anders; Calabrese, Antonio N; Mojzes, Peter; Cockburn, Joseph J B; Lamb, Don C; Tuma, Roman

2018-05-18

To maintain genome integrity, segmented double-stranded RNA viruses of the Reoviridae family must accurately select and package a complete set of up to a dozen distinct genomic RNAs. It is thought that the high fidelity segmented genome assembly involves multiple sequence-specific RNA-RNA interactions between single-stranded RNA segment precursors. These are mediated by virus-encoded non-structural proteins with RNA chaperone-like activities, such as rotavirus (RV) NSP2 and avian reovirus σNS. Here, we compared the abilities of NSP2 and σNS to mediate sequence-specific interactions between RV genomic segment precursors. Despite their similar activities, NSP2 successfully promotes inter-segment association, while σNS fails to do so. To understand the mechanisms underlying such selectivity in promoting inter-molecular duplex formation, we compared RNA-binding and helix-unwinding activities of both proteins. We demonstrate that octameric NSP2 binds structured RNAs with high affinity, resulting in efficient intramolecular RNA helix disruption. Hexameric σNS oligomerizes into an octamer that binds two RNAs, yet it exhibits only limited RNA-unwinding activity compared to NSP2. Thus, the formation of intersegment RNA-RNA interactions is governed by both helix-unwinding capacity of the chaperones and stability of RNA structure. We propose that this protein-mediated RNA selection mechanism may underpin the high fidelity assembly of multi-segmented RNA genomes in Reoviridae.

Automatic segmentation of solitary pulmonary nodules based on local intensity structure analysis and 3D neighborhood features in 3D chest CT images

NASA Astrophysics Data System (ADS)

Chen, Bin; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2012-03-01

This paper presents a solitary pulmonary nodule (SPN) segmentation method based on local intensity structure analysis and neighborhood feature analysis in chest CT images. Automated segmentation of SPNs is desirable for a chest computer-aided detection/diagnosis (CAS) system since a SPN may indicate early stage of lung cancer. Due to the similar intensities of SPNs and other chest structures such as blood vessels, many false positives (FPs) are generated by nodule detection methods. To reduce such FPs, we introduce two features that analyze the relation between each segmented nodule candidate and it neighborhood region. The proposed method utilizes a blob-like structure enhancement (BSE) filter based on Hessian analysis to augment the blob-like structures as initial nodule candidates. Then a fine segmentation is performed to segment much more accurate region of each nodule candidate. FP reduction is mainly addressed by investigating two neighborhood features based on volume ratio and eigenvector of Hessian that are calculates from the neighborhood region of each nodule candidate. We evaluated the proposed method by using 40 chest CT images, include 20 standard-dose CT images that we randomly chosen from a local database and 20 low-dose CT images that were randomly chosen from a public database: LIDC. The experimental results revealed that the average TP rate of proposed method was 93.6% with 12.3 FPs/case.

[The private vaccines market in Brazil: privatization of public health].

PubMed

Temporão, José Gomes

2003-01-01

The main objective of this article is to analyze the vaccines market in Brazil, which is characterized as consisting of two segments with distinct practices and logics: the public segment, focused on supply within the Unified National Health System (SUS) and the private segment, organized around private clinics, physicians' offices, and similar private health facilities. The private vaccines market segment, studied here for the first time, is characterized in relation to the supply and demand structure. Historical aspects of its structure are analyzed, based on the creation of one of the first immunization clinics in the country. The attempt was to analyze this segment in relation to its economic dimensions (imports and sales), principal manufacturers, and products marketed. It economic size proved much greater than initially hypothesized. The figures allow one to view it as one of the main segments in the pharmaceutical industry in Brazil as measured by sales volume. One detects the penetration of a privatizing logic in a sphere that has always been essentially public, thereby introducing into the SUS a new space for disregarding the principles of equity and universality.

Local-global alignment for finding 3D similarities in protein structures

DOEpatents

Zemla, Adam T [Brentwood, CA

2011-09-20

A method of finding 3D similarities in protein structures of a first molecule and a second molecule. The method comprises providing preselected information regarding the first molecule and the second molecule. Comparing the first molecule and the second molecule using Longest Continuous Segments (LCS) analysis. Comparing the first molecule and the second molecule using Global Distance Test (GDT) analysis. Comparing the first molecule and the second molecule using Local Global Alignment Scoring function (LGA_S) analysis. Verifying constructed alignment and repeating the steps to find the regions of 3D similarities in protein structures.

Automatic segmentation of brain MRIs and mapping neuroanatomy across the human lifespan

NASA Astrophysics Data System (ADS)

Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Rueckert, Daniel; Aljabar, Paul; Hajnal, Joseph V.; Hammers, Alexander

2009-02-01

A robust model for the automatic segmentation of human brain images into anatomically defined regions across the human lifespan would be highly desirable, but such structural segmentations of brain MRI are challenging due to age-related changes. We have developed a new method, based on established algorithms for automatic segmentation of young adults' brains. We used prior information from 30 anatomical atlases, which had been manually segmented into 83 anatomical structures. Target MRIs came from 80 subjects (~12 individuals/decade) from 20 to 90 years, with equal numbers of men, women; data from two different scanners (1.5T, 3T), using the IXI database. Each of the adult atlases was registered to each target MR image. By using additional information from segmentation into tissue classes (GM, WM and CSF) to initialise the warping based on label consistency similarity before feeding this into the previous normalised mutual information non-rigid registration, the registration became robust enough to accommodate atrophy and ventricular enlargement with age. The final segmentation was obtained by combination of the 30 propagated atlases using decision fusion. Kernel smoothing was used for modelling the structural volume changes with aging. Example linear correlation coefficients with age were, for lateral ventricular volume, rmale=0.76, rfemale=0.58 and, for hippocampal volume, rmale=-0.6, rfemale=-0.4 (allρ<0.01).

Perception of English Intonation by English, Spanish, and Chinese Listeners

ERIC Educational Resources Information Center

Grabe, Esther; Rosner, Burton S.; Garcia-Albea, Jose E.; Zhou, Xiaolin

2003-01-01

Native language affects the perception of segmental phonetic structure, of stress, and of semantic and pragmatic effects of intonation. Similarly, native language might influence the perception of similarities and differences among intonation contours. To test this hypothesis, a cross-language experiment was conducted. An English utterance was…

Segmentation of hepatic artery in multi-phase liver CT using directional dilation and connectivity analysis

NASA Astrophysics Data System (ADS)

Wang, Lei; Schnurr, Alena-Kathrin; Zidowitz, Stephan; Georgii, Joachim; Zhao, Yue; Razavi, Mohammad; Schwier, Michael; Hahn, Horst K.; Hansen, Christian

2016-03-01

Segmentation of hepatic arteries in multi-phase computed tomography (CT) images is indispensable in liver surgery planning. During image acquisition, the hepatic artery is enhanced by the injection of contrast agent. The enhanced signals are often not stably acquired due to non-optimal contrast timing. Other vascular structure, such as hepatic vein or portal vein, can be enhanced as well in the arterial phase, which can adversely affect the segmentation results. Furthermore, the arteries might suffer from partial volume effects due to their small diameter. To overcome these difficulties, we propose a framework for robust hepatic artery segmentation requiring a minimal amount of user interaction. First, an efficient multi-scale Hessian-based vesselness filter is applied on the artery phase CT image, aiming to enhance vessel structures with specified diameter range. Second, the vesselness response is processed using a Bayesian classifier to identify the most probable vessel structures. Considering the vesselness filter normally performs not ideally on the vessel bifurcations or the segments corrupted by noise, two vessel-reconnection techniques are proposed. The first technique uses a directional morphological operator to dilate vessel segments along their centerline directions, attempting to fill the gap between broken vascular segments. The second technique analyzes the connectivity of vessel segments and reconnects disconnected segments and branches. Finally, a 3D vessel tree is reconstructed. The algorithm has been evaluated using 18 CT images of the liver. To quantitatively measure the similarities between segmented and reference vessel trees, the skeleton coverage and mean symmetric distance are calculated to quantify the agreement between reference and segmented vessel skeletons, resulting in an average of 0:55+/-0:27 and 12:7+/-7:9 mm (mean standard deviation), respectively.

Segmentation of 3D microPET images of the rat brain via the hybrid gaussian mixture method with kernel density estimation.

PubMed

Chen, Tai-Been; Chen, Jyh-Cheng; Lu, Henry Horng-Shing

2012-01-01

Segmentation of positron emission tomography (PET) is typically achieved using the K-Means method or other approaches. In preclinical and clinical applications, the K-Means method needs a prior estimation of parameters such as the number of clusters and appropriate initialized values. This work segments microPET images using a hybrid method combining the Gaussian mixture model (GMM) with kernel density estimation. Segmentation is crucial to registration of disordered 2-deoxy-2-fluoro-D-glucose (FDG) accumulation locations with functional diagnosis and to estimate standardized uptake values (SUVs) of region of interests (ROIs) in PET images. Therefore, simulation studies are conducted to apply spherical targets to evaluate segmentation accuracy based on Tanimoto's definition of similarity. The proposed method generates a higher degree of similarity than the K-Means method. The PET images of a rat brain are used to compare the segmented shape and area of the cerebral cortex by the K-Means method and the proposed method by volume rendering. The proposed method provides clearer and more detailed activity structures of an FDG accumulation location in the cerebral cortex than those by the K-Means method.

Some methods of encoding simple visual images for use with a sparse distributed memory, with applications to character recognition

NASA Technical Reports Server (NTRS)

Jaeckel, Louis A.

1989-01-01

To study the problems of encoding visual images for use with a Sparse Distributed Memory (SDM), I consider a specific class of images- those that consist of several pieces, each of which is a line segment or an arc of a circle. This class includes line drawings of characters such as letters of the alphabet. I give a method of representing a segment of an arc by five numbers in a continuous way; that is, similar arcs have similar representations. I also give methods for encoding these numbers as bit strings in an approximately continuous way. The set of possible segments and arcs may be viewed as a five-dimensional manifold M, whose structure is like a Mobious strip. An image, considered to be an unordered set of segments and arcs, is therefore represented by a set of points in M - one for each piece. I then discuss the problem of constructing a preprocessor to find the segments and arcs in these images, although a preprocessor has not been developed. I also describe a possible extension of the representation.

Automatic Text Decomposition and Structuring.

ERIC Educational Resources Information Center

Salton, Gerard; And Others

1996-01-01

Text similarity measurements are used to determine relationships between natural-language texts and text excerpts. The resulting linked hypertext maps can be broken down into text segments and themes used to identify different text types and structures, leading to improved information access and utilization. Examples are provided for text…

FragFit: a web-application for interactive modeling of protein segments into cryo-EM density maps.

PubMed

Tiemann, Johanna K S; Rose, Alexander S; Ismer, Jochen; Darvish, Mitra D; Hilal, Tarek; Spahn, Christian M T; Hildebrand, Peter W

2018-05-21

Cryo-electron microscopy (cryo-EM) is a standard method to determine the three-dimensional structures of molecular complexes. However, easy to use tools for modeling of protein segments into cryo-EM maps are sparse. Here, we present the FragFit web-application, a web server for interactive modeling of segments of up to 35 amino acids length into cryo-EM density maps. The fragments are provided by a regularly updated database containing at the moment about 1 billion entries extracted from PDB structures and can be readily integrated into a protein structure. Fragments are selected based on geometric criteria, sequence similarity and fit into a given cryo-EM density map. Web-based molecular visualization with the NGL Viewer allows interactive selection of fragments. The FragFit web-application, accessible at http://proteinformatics.de/FragFit, is free and open to all users, without any login requirements.

Fast and robust segmentation of the striatum using deep convolutional neural networks.

PubMed

Choi, Hongyoon; Jin, Kyong Hwan

2016-12-01

Automated segmentation of brain structures is an important task in structural and functional image analysis. We developed a fast and accurate method for the striatum segmentation using deep convolutional neural networks (CNN). T1 magnetic resonance (MR) images were used for our CNN-based segmentation, which require neither image feature extraction nor nonlinear transformation. We employed two serial CNN, Global and Local CNN: The Global CNN determined approximate locations of the striatum. It performed a regression of input MR images fitted to smoothed segmentation maps of the striatum. From the output volume of Global CNN, cropped MR volumes which included the striatum were extracted. The cropped MR volumes and the output volumes of Global CNN were used for inputs of Local CNN. Local CNN predicted the accurate label of all voxels. Segmentation results were compared with a widely used segmentation method, FreeSurfer. Our method showed higher Dice Similarity Coefficient (DSC) (0.893±0.017 vs. 0.786±0.015) and precision score (0.905±0.018 vs. 0.690±0.022) than FreeSurfer-based striatum segmentation (p=0.06). Our approach was also tested using another independent dataset, which showed high DSC (0.826±0.038) comparable with that of FreeSurfer. Comparison with existing method Segmentation performance of our proposed method was comparable with that of FreeSurfer. The running time of our approach was approximately three seconds. We suggested a fast and accurate deep CNN-based segmentation for small brain structures which can be widely applied to brain image analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative Analysis Of Three-dimensional Branching Systems From X-ray Computed Microtomography Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKinney, Adriana L.; Varga, Tamas

Branching structures such as lungs, blood vessels and plant roots play a critical role in life. Growth, structure, and function of these branching structures have an immense effect on our lives. Therefore, quantitative size information on such structures in their native environment is invaluable for studying their growth and the effect of the environment on them. X-ray computed tomography (XCT) has been an effective tool for in situ imaging and analysis of branching structures. We developed a costless tool that approximates the surface and volume of branching structures. Our methodology of noninvasive imaging, segmentation and extraction of quantitative information ismore » demonstrated through the analysis of a plant root in its soil medium from 3D tomography data. XCT data collected on a grass specimen was used to visualize its root structure. A suite of open-source software was employed to segment the root from the soil and determine its isosurface, which was used to calculate its volume and surface. This methodology of processing 3D data is applicable to other branching structures even when the structure of interest is of similar x-ray attenuation to its environment and difficulties arise with sample segmentation.« less

Regional deep hyperthermia: impact of observer variability in CT-based manual tissue segmentation on simulated temperature distribution

NASA Astrophysics Data System (ADS)

Aklan, Bassim; Hartmann, Josefin; Zink, Diana; Siavooshhaghighi, Hadi; Merten, Ricarda; Putz, Florian; Ott, Oliver; Fietkau, Rainer; Bert, Christoph

2017-06-01

The aim of this study was to systematically investigate the influence of the inter- and intra-observer segmentation variation of tumors and organs at risk on the simulated temperature coverage of the target. CT scans of six patients with tumors in the pelvic region acquired for radiotherapy treatment planning were used for hyperthermia treatment planning. To study the effect of inter-observer variation, three observers manually segmented in the CT images of each patient the following structures: fat, muscle, bone and the bladder. The gross tumor volumes (GTV) were contoured by three radiation oncology residents and used as the hyperthermia target volumes. For intra-observer variation, one of the observers of each group contoured the structures of each patient three times with a time span of one week between the segmentations. Moreover, the impact of segmentation variations in organs at risk (OARs) between the three inter-observers was investigated on simulated temperature distributions using only one GTV. The spatial overlap between individual segmentations was assessed by the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Additionally, the temperatures T90/T10 delivered to 90%/10% of the GTV, respectively, were assessed for each observer combination. The results of the segmentation similarity evaluation showed that the DSC of the inter-observer variation of fat, muscle, the bladder, bone and the target was 0.68  ±  0.12, 0.88  ±  0.05, 0.73  ±  0.14, 0.91  ±  0.04 and 0.64  ±  0.11, respectively. Similar results were found for the intra-observer variation. The MSD results were similar to the DSCs for both observer variations. A statistically significant difference (p  <  0.05) was found for T90 and T10 in the predicted target temperature due to the observer variability. The conclusion is that intra- and inter-observer variations have a significant impact on the temperature coverage of the target. Furthermore, OARs, such as bone and the bladder, may essentially influence the homogeneity of the simulated target temperature distribution.

Dynamical simulation of E-ELT segmented primary mirror

NASA Astrophysics Data System (ADS)

Sedghi, B.; Muller, M.; Bauvir, B.

2011-09-01

The dynamical behavior of the primary mirror (M1) has an important impact on the control of the segments and the performance of the telescope. Control of large segmented mirrors with a large number of actuators and sensors and multiple control loops in real life is a challenging problem. In virtual life, modeling, simulation and analysis of the M1 bears similar difficulties and challenges. In order to capture the dynamics of the segment subunits (high frequency modes) and the telescope back structure (low frequency modes), high order dynamical models with a very large number of inputs and outputs need to be simulated. In this paper, different approaches for dynamical modeling and simulation of the M1 segmented mirror subject to various perturbations, e.g. sensor noise, wind load, vibrations, earthquake are presented.

Segmentation of white rat sperm image

NASA Astrophysics Data System (ADS)

Bai, Weiguo; Liu, Jianguo; Chen, Guoyuan

2011-11-01

The segmentation of sperm image exerts a profound influence in the analysis of sperm morphology, which plays a significant role in the research of animals' infertility and reproduction. To overcome the microscope image's properties of low contrast and highly polluted noise, and to get better segmentation results of sperm image, this paper presents a multi-scale gradient operator combined with a multi-structuring element for the micro-spermatozoa image of white rat, as the multi-scale gradient operator can smooth the noise of an image, while the multi-structuring element can retain more shape details of the sperms. Then, we use the Otsu method to segment the modified gradient image whose gray scale processed is strong in sperms and weak in the background, converting it into a binary sperm image. As the obtained binary image owns impurities that are not similar with sperms in the shape, we choose a form factor to filter those objects whose form factor value is larger than the select critical value, and retain those objects whose not. And then, we can get the final binary image of the segmented sperms. The experiment shows this method's great advantage in the segmentation of the micro-spermatozoa image.

A novel pipeline for adrenal tumour segmentation.

PubMed

Koyuncu, Hasan; Ceylan, Rahime; Erdogan, Hasan; Sivri, Mesut

2018-06-01

Adrenal tumours occur on adrenal glands surrounded by organs and osteoid. These tumours can be categorized as either functional, non-functional, malign, or benign. Depending on their appearance in the abdomen, adrenal tumours can arise from one adrenal gland (unilateral) or from both adrenal glands (bilateral) and can connect with other organs, including the liver, spleen, pancreas, etc. This connection phenomenon constitutes the most important handicap against adrenal tumour segmentation. Size change, variety of shape, diverse location, and low contrast (similar grey values between the various tissues) are other disadvantages compounding segmentation difficulty. Few studies have considered adrenal tumour segmentation, and no significant improvement has been achieved for unilateral, bilateral, adherent, or noncohesive tumour segmentation. There is also no recognised segmentation pipeline or method for adrenal tumours including different shape, size, or location information. This study proposes an adrenal tumour segmentation (ATUS) pipeline designed to eliminate the above disadvantages for adrenal tumour segmentation. ATUS incorporates a number of image methods, including contrast limited adaptive histogram equalization, split and merge based on quadtree decomposition, mean shift segmentation, large grey level eliminator, and region growing. Performance assessment of ATUS was realised on 32 arterial and portal phase computed tomography images using six metrics: dice, jaccard, sensitivity, specificity, accuracy, and structural similarity index. ATUS achieved remarkable segmentation performance, and was not affected by the discussed handicaps, on particularly adherence to other organs, with success rates of 83.06%, 71.44%, 86.44%, 99.66%, 99.43%, and 98.51% for the metrics, respectively, for images including sufficient contrast uptake. The proposed ATUS system realises detailed adrenal tumour segmentation, and avoids known disadvantages preventing accurate segmentation. Copyright © 2018 Elsevier B.V. All rights reserved.

Hair segmentation using adaptive threshold from edge and branch length measures.

PubMed

Lee, Ian; Du, Xian; Anthony, Brian

2017-10-01

Non-invasive imaging techniques allow the monitoring of skin structure and diagnosis of skin diseases in clinical applications. However, hair in skin images hampers the imaging and classification of the skin structure of interest. Although many hair segmentation methods have been proposed for digital hair removal, a major challenge in hair segmentation remains in detecting hairs that are thin, overlapping, of similar contrast or color to underlying skin, or overlaid on highly-textured skin structure. To solve the problem, we present an automatic hair segmentation method that uses edge density (ED) and mean branch length (MBL) to measure hair. First, hair is detected by the integration of top-hat transform and modified second-order Gaussian filter. Second, we employ a robust adaptive threshold of ED and MBL to generate a hair mask. Third, the hair mask is refined by k-NN classification of hair and skin pixels. The proposed algorithm was tested using two datasets of healthy skin images and lesion images respectively. These datasets were taken from different imaging platforms in various illumination levels and varying skin colors. We compared the hair detection and segmentation results from our algorithm and six other hair segmentation methods of state of the art. Our method exhibits high value of sensitivity: 75% and specificity: 95%, which indicates significantly higher accuracy and better balance between true positive and false positive detection than the other methods. Published by Elsevier Ltd.

Brain vascular image segmentation based on fuzzy local information C-means clustering

NASA Astrophysics Data System (ADS)

Hu, Chaoen; Liu, Xia; Liang, Xiao; Hui, Hui; Yang, Xin; Tian, Jie

2017-02-01

Light sheet fluorescence microscopy (LSFM) is a powerful optical resolution fluorescence microscopy technique which enables to observe the mouse brain vascular network in cellular resolution. However, micro-vessel structures are intensity inhomogeneity in LSFM images, which make an inconvenience for extracting line structures. In this work, we developed a vascular image segmentation method by enhancing vessel details which should be useful for estimating statistics like micro-vessel density. Since the eigenvalues of hessian matrix and its sign describes different geometric structure in images, which enable to construct vascular similarity function and enhance line signals, the main idea of our method is to cluster the pixel values of the enhanced image. Our method contained three steps: 1) calculate the multiscale gradients and the differences between eigenvalues of Hessian matrix. 2) In order to generate the enhanced microvessels structures, a feed forward neural network was trained by 2.26 million pixels for dealing with the correlations between multi-scale gradients and the differences between eigenvalues. 3) The fuzzy local information c-means clustering (FLICM) was used to cluster the pixel values in enhance line signals. To verify the feasibility and effectiveness of this method, mouse brain vascular images have been acquired by a commercial light-sheet microscope in our lab. The experiment of the segmentation method showed that dice similarity coefficient can reach up to 85%. The results illustrated that our approach extracting line structures of blood vessels dramatically improves the vascular image and enable to accurately extract blood vessels in LSFM images.

Fully-automated approach to hippocampus segmentation using a graph-cuts algorithm combined with atlas-based segmentation and morphological opening.

PubMed

Kwak, Kichang; Yoon, Uicheul; Lee, Dong-Kyun; Kim, Geon Ha; Seo, Sang Won; Na, Duk L; Shim, Hack-Joon; Lee, Jong-Min

2013-09-01

The hippocampus has been known to be an important structure as a biomarker for Alzheimer's disease (AD) and other neurological and psychiatric diseases. However, it requires accurate, robust and reproducible delineation of hippocampal structures. In this study, an automated hippocampal segmentation method based on a graph-cuts algorithm combined with atlas-based segmentation and morphological opening was proposed. First of all, the atlas-based segmentation was applied to define initial hippocampal region for a priori information on graph-cuts. The definition of initial seeds was further elaborated by incorporating estimation of partial volume probabilities at each voxel. Finally, morphological opening was applied to reduce false positive of the result processed by graph-cuts. In the experiments with twenty-seven healthy normal subjects, the proposed method showed more reliable results (similarity index=0.81±0.03) than the conventional atlas-based segmentation method (0.72±0.04). Also as for segmentation accuracy which is measured in terms of the ratios of false positive and false negative, the proposed method (precision=0.76±0.04, recall=0.86±0.05) produced lower ratios than the conventional methods (0.73±0.05, 0.72±0.06) demonstrating its plausibility for accurate, robust and reliable segmentation of hippocampus. Copyright © 2013 Elsevier Inc. All rights reserved.

Fully automated reconstruction of three-dimensional vascular tree structures from two orthogonal views using computational algorithms and productionrules

NASA Astrophysics Data System (ADS)

Liu, Iching; Sun, Ying

1992-10-01

A system for reconstructing 3-D vascular structure from two orthogonally projected images is presented. The formidable problem of matching segments between two views is solved using knowledge of the epipolar constraint and the similarity of segment geometry and connectivity. The knowledge is represented in a rule-based system, which also controls the operation of several computational algorithms for tracking segments in each image, representing 2-D segments with directed graphs, and reconstructing 3-D segments from matching 2-D segment pairs. Uncertain reasoning governs the interaction between segmentation and matching; it also provides a framework for resolving the matching ambiguities in an iterative way. The system was implemented in the C language and the C Language Integrated Production System (CLIPS) expert system shell. Using video images of a tree model, the standard deviation of reconstructed centerlines was estimated to be 0.8 mm (1.7 mm) when the view direction was parallel (perpendicular) to the epipolar plane. Feasibility of clinical use was shown using x-ray angiograms of a human chest phantom. The correspondence of vessel segments between two views was accurate. Computational time for the entire reconstruction process was under 30 s on a workstation. A fully automated system for two-view reconstruction that does not require the a priori knowledge of vascular anatomy is demonstrated.

Random walks based multi-image segmentation: Quasiconvexity results and GPU-based solutions

PubMed Central

Collins, Maxwell D.; Xu, Jia; Grady, Leo; Singh, Vikas

2012-01-01

We recast the Cosegmentation problem using Random Walker (RW) segmentation as the core segmentation algorithm, rather than the traditional MRF approach adopted in the literature so far. Our formulation is similar to previous approaches in the sense that it also permits Cosegmentation constraints (which impose consistency between the extracted objects from ≥ 2 images) using a nonparametric model. However, several previous nonparametric cosegmentation methods have the serious limitation that they require adding one auxiliary node (or variable) for every pair of pixels that are similar (which effectively limits such methods to describing only those objects that have high entropy appearance models). In contrast, our proposed model completely eliminates this restrictive dependence –the resulting improvements are quite significant. Our model further allows an optimization scheme exploiting quasiconvexity for model-based segmentation with no dependence on the scale of the segmented foreground. Finally, we show that the optimization can be expressed in terms of linear algebra operations on sparse matrices which are easily mapped to GPU architecture. We provide a highly specialized CUDA library for Cosegmentation exploiting this special structure, and report experimental results showing these advantages. PMID:25278742

Hippocampus segmentation using locally weighted prior based level set

NASA Astrophysics Data System (ADS)

Achuthan, Anusha; Rajeswari, Mandava

2015-12-01

Segmentation of hippocampus in the brain is one of a major challenge in medical image segmentation due to its' imaging characteristics, with almost similar intensity between another adjacent gray matter structure, such as amygdala. The intensity similarity has causes the hippocampus to have weak or fuzzy boundaries. With this main challenge being demonstrated by hippocampus, a segmentation method that relies on image information alone may not produce accurate segmentation results. Therefore, it is needed an assimilation of prior information such as shape and spatial information into existing segmentation method to produce the expected segmentation. Previous studies has widely integrated prior information into segmentation methods. However, the prior information has been utilized through a global manner integration, and this does not reflect the real scenario during clinical delineation. Therefore, in this paper, a locally integrated prior information into a level set model is presented. This work utilizes a mean shape model to provide automatic initialization for level set evolution, and has been integrated as prior information into the level set model. The local integration of edge based information and prior information has been implemented through an edge weighting map that decides at voxel level which information need to be observed during a level set evolution. The edge weighting map shows which corresponding voxels having sufficient edge information. Experiments shows that the proposed integration of prior information locally into a conventional edge-based level set model, known as geodesic active contour has shown improvement of 9% in averaged Dice coefficient.

Segmentation of DTI based on tensorial morphological gradient

NASA Astrophysics Data System (ADS)

Rittner, Leticia; de Alencar Lotufo, Roberto

2009-02-01

This paper presents a segmentation technique for diffusion tensor imaging (DTI). This technique is based on a tensorial morphological gradient (TMG), defined as the maximum dissimilarity over the neighborhood. Once this gradient is computed, the tensorial segmentation problem becomes an scalar one, which can be solved by conventional techniques, such as watershed transform and thresholding. Similarity functions, namely the dot product, the tensorial dot product, the J-divergence and the Frobenius norm, were compared, in order to understand their differences regarding the measurement of tensor dissimilarities. The study showed that the dot product and the tensorial dot product turned out to be inappropriate for computation of the TMG, while the Frobenius norm and the J-divergence were both capable of measuring tensor dissimilarities, despite the distortion of Frobenius norm, since it is not an affine invariant measure. In order to validate the TMG as a solution for DTI segmentation, its computation was performed using distinct similarity measures and structuring elements. TMG results were also compared to fractional anisotropy. Finally, synthetic and real DTI were used in the method validation. Experiments showed that the TMG enables the segmentation of DTI by watershed transform or by a simple choice of a threshold. The strength of the proposed segmentation method is its simplicity and robustness, consequences of TMG computation. It enables the use, not only of well-known algorithms and tools from the mathematical morphology, but also of any other segmentation method to segment DTI, since TMG computation transforms tensorial images in scalar ones.

Automated boundary detection of the optic disc and layer segmentation of the peripapillary retina in volumetric structural and angiographic optical coherence tomography.

PubMed

Zang, Pengxiao; Gao, Simon S; Hwang, Thomas S; Flaxel, Christina J; Wilson, David J; Morrison, John C; Huang, David; Li, Dengwang; Jia, Yali

2017-03-01

To improve optic disc boundary detection and peripapillary retinal layer segmentation, we propose an automated approach for structural and angiographic optical coherence tomography. The algorithm was performed on radial cross-sectional B-scans. The disc boundary was detected by searching for the position of Bruch's membrane opening, and retinal layer boundaries were detected using a dynamic programming-based graph search algorithm on each B-scan without the disc region. A comparison of the disc boundary using our method with that determined by manual delineation showed good accuracy, with an average Dice similarity coefficient ≥0.90 in healthy eyes and eyes with diabetic retinopathy and glaucoma. The layer segmentation accuracy in the same cases was on average less than one pixel (3.13 μm).

Automated boundary detection of the optic disc and layer segmentation of the peripapillary retina in volumetric structural and angiographic optical coherence tomography

PubMed Central

Zang, Pengxiao; Gao, Simon S.; Hwang, Thomas S.; Flaxel, Christina J.; Wilson, David J.; Morrison, John C.; Huang, David; Li, Dengwang; Jia, Yali

2017-01-01

To improve optic disc boundary detection and peripapillary retinal layer segmentation, we propose an automated approach for structural and angiographic optical coherence tomography. The algorithm was performed on radial cross-sectional B-scans. The disc boundary was detected by searching for the position of Bruch’s membrane opening, and retinal layer boundaries were detected using a dynamic programming-based graph search algorithm on each B-scan without the disc region. A comparison of the disc boundary using our method with that determined by manual delineation showed good accuracy, with an average Dice similarity coefficient ≥0.90 in healthy eyes and eyes with diabetic retinopathy and glaucoma. The layer segmentation accuracy in the same cases was on average less than one pixel (3.13 μm). PMID:28663830

Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.

PubMed

Fu, Min; Wu, Wenming; Hong, Xiafei; Liu, Qiuhua; Jiang, Jialin; Ou, Yaobin; Zhao, Yupei; Gong, Xinqi

2018-04-24

Efficient computational recognition and segmentation of target organ from medical images are foundational in diagnosis and treatment, especially about pancreas cancer. In practice, the diversity in appearance of pancreas and organs in abdomen, makes detailed texture information of objects important in segmentation algorithm. According to our observations, however, the structures of previous networks, such as the Richer Feature Convolutional Network (RCF), are too coarse to segment the object (pancreas) accurately, especially the edge. In this paper, we extend the RCF, proposed to the field of edge detection, for the challenging pancreas segmentation, and put forward a novel pancreas segmentation network. By employing multi-layer up-sampling structure replacing the simple up-sampling operation in all stages, the proposed network fully considers the multi-scale detailed contexture information of object (pancreas) to perform per-pixel segmentation. Additionally, using the CT scans, we supply and train our network, thus get an effective pipeline. Working with our pipeline with multi-layer up-sampling model, we achieve better performance than RCF in the task of single object (pancreas) segmentation. Besides, combining with multi scale input, we achieve the 76.36% DSC (Dice Similarity Coefficient) value in testing data. The results of our experiments show that our advanced model works better than previous networks in our dataset. On the other words, it has better ability in catching detailed contexture information. Therefore, our new single object segmentation model has practical meaning in computational automatic diagnosis.

Automatic segmentation and quantification of the cardiac structures from non-contrast-enhanced cardiac CT scans

NASA Astrophysics Data System (ADS)

Shahzad, Rahil; Bos, Daniel; Budde, Ricardo P. J.; Pellikaan, Karlijn; Niessen, Wiro J.; van der Lugt, Aad; van Walsum, Theo

2017-05-01

Early structural changes to the heart, including the chambers and the coronary arteries, provide important information on pre-clinical heart disease like cardiac failure. Currently, contrast-enhanced cardiac computed tomography angiography (CCTA) is the preferred modality for the visualization of the cardiac chambers and the coronaries. In clinical practice not every patient undergoes a CCTA scan; many patients receive only a non-contrast-enhanced calcium scoring CT scan (CTCS), which has less radiation dose and does not require the administration of contrast agent. Quantifying cardiac structures in such images is challenging, as they lack the contrast present in CCTA scans. Such quantification would however be relevant, as it enables population based studies with only a CTCS scan. The purpose of this work is therefore to investigate the feasibility of automatic segmentation and quantification of cardiac structures viz whole heart, left atrium, left ventricle, right atrium, right ventricle and aortic root from CTCS scans. A fully automatic multi-atlas-based segmentation approach is used to segment the cardiac structures. Results show that the segmentation overlap between the automatic method and that of the reference standard have a Dice similarity coefficient of 0.91 on average for the cardiac chambers. The mean surface-to-surface distance error over all the cardiac structures is 1.4+/- 1.7 mm. The automatically obtained cardiac chamber volumes using the CTCS scans have an excellent correlation when compared to the volumes in corresponding CCTA scans, a Pearson correlation coefficient (R) of 0.95 is obtained. Our fully automatic method enables large-scale assessment of cardiac structures on non-contrast-enhanced CT scans.

The π-Electron Delocalization in 2-Oxazolines Revisited: Quantification and Comparison with Its Analogue in Esters

PubMed Central

Fimberger, Martin; Luef, Klaus P.; Payerl, Claudia; Fischer, Roland C.; Stelzer, Franz; Kállay, Mihály; Wiesbrock, Frank

2015-01-01

The single crystal X-ray analysis of the ester-functionalized 2-oxazoline, methyl 3-(4,5-dihydrooxazol-2-yl)propanoate, revealed π-electron delocalization along the N–C–O segment in the 2-oxazoline pentacycle to significant extent, which is comparable to its counterpart along the O–C–O segment in the ester. Quantum chemical calculations based on the experimental X-ray geometry of the molecule supported the conjecture that the N–C–O segment has a delocalized electronic structure similar to an ester group. The calculated bond orders were 1.97 and 1.10 for the N=C and C–O bonds, and the computed partial charges for the nitrogen and oxygen atoms of −0.43 and −0.44 were almost identical. In the ester group, the bond orders were 1.94 and 1.18 for the C–O bonds, while the partial charges of the oxygen atom are −0.49 and −0.41, which demonstrates the similar electronic structure of the N–C–O and O–C–O segments. In 2-oxazolines, despite the higher electronegativity of the oxygen atom (compared to the nitrogen atom), the charges of the hetero atoms oxygen and nitrogen are equalized due to the delocalization, and it also means that a cationic attack on the nitrogen is possible, enabling regioselectivity during the initiation of the cationic ring-opening polymerization of 2-oxazoline monomers, which is a prerequisite for the synthesis of materials with well-defined structures. PMID:28184258

Experimental investigation of the crashworthiness of scaled composite sailplane fuselages

NASA Technical Reports Server (NTRS)

Kampf, Karl-Peter; Crawley, Edward F.; Hansman, R. John, Jr.

1989-01-01

The crash dynamics and energy absorption of composite sailplane fuselage segments undergoing nose-down impact were investigated. More than 10 quarter-scale structurally similar test articles, typical of high-performance sailplane designs, were tested. Fuselages segments were fabricated of combinations of fiberglass, graphite, Kevlar, and Spectra fabric materials. Quasistatic and dynamic tests were conducted. The quasistatic tests were found to replicate the strain history and failure modes observed in the dynamic tests. Failure modes of the quarter-scale model were qualitatively compared with full-scale crash evidence and quantitatively compared with current design criteria. By combining material and structural improvements, substantial increases in crashworthiness were demonstrated.

Structure and kinematics of segment-scale crustal accretion processes in Iceland and implications for analogous mid-ocean ridge systems

NASA Astrophysics Data System (ADS)

Siler, Drew Lorenz

2011-12-01

The sub-surface geologic structure of the crust is controlled by the magmatic and tectonic processes that construct the crust during plate spreading. As a result, geologic structure provides constraints on the processes that occur during plate spreading. The crust of the Skagi region of northern Iceland, where this study was focused, was accreted by magmatic construction to Iceland ˜7-10 Ma and subsequently glacially eroded, exhuming ˜1-3 km of structural relief. Continuous spreading-parallel and spreading-orthogonal mountain ranges expose the crust accreted at discrete spreading segments, the fundamental intervals upon which plate spreading and crustal accretion occur. As a result, Skagi is an ideal location to employ geologic structure analysis to study magmatic rifting processes. Within spreading segments structural patterns vary significantly between segment centers and distal fissure swarms. While segment centers are characterized by focused magmatic construction and km-scale sub-volcanic subsidence, fissure swarms are characterized by limited magmatic construction, minor sub-axial subsidence and lateral dike injection. Such along-strike variation indicates that both magma in the upper crust and gabbroic material in the lower crust must be redistributed along-strike within spreading segments during plate spreading. Material flow is directed from beneath segment centers towards distal fissure swarms. At the regional scale, each spreading segment is a structurally discrete interval of Iceland's Neovolcanic Zone. As a result of west-northwestward movement of Iceland relative to the Iceland hotspot, the rift zone axis has progressively relocated to the east-southeast with time, leaving a series of abandoned rift zones throughout western Iceland. A compilation of published K/Ar and 40Ar/39Ar age data and geologic data from across northern Iceland shows that rift relocation occurs via frequent (2-3 Ma), small-scale (˜20 km) rift propagations rather than rare, 100s of km 'rift jumps' as is conventional models suggest. The structure relationships we define in the Icelandic crust are similar to that of other magmatic rift systems including Mid-Ocean Ridges, continental rifts and ancient volcanic rift margins. As such, we suggest that many of the crustal accretion processes we have inferred from Icelandic data may be important in these analogous environments as well.

Towards Structural Analysis of Audio Recordings in the Presence of Musical Variations

NASA Astrophysics Data System (ADS)

Müller, Meinard; Kurth, Frank

2006-12-01

One major goal of structural analysis of an audio recording is to automatically extract the repetitive structure or, more generally, the musical form of the underlying piece of music. Recent approaches to this problem work well for music, where the repetitions largely agree with respect to instrumentation and tempo, as is typically the case for popular music. For other classes of music such as Western classical music, however, musically similar audio segments may exhibit significant variations in parameters such as dynamics, timbre, execution of note groups, modulation, articulation, and tempo progression. In this paper, we propose a robust and efficient algorithm for audio structure analysis, which allows to identify musically similar segments even in the presence of large variations in these parameters. To account for such variations, our main idea is to incorporate invariance at various levels simultaneously: we design a new type of statistical features to absorb microvariations, introduce an enhanced local distance measure to account for local variations, and describe a new strategy for structure extraction that can cope with the global variations. Our experimental results with classical and popular music show that our algorithm performs successfully even in the presence of significant musical variations.

On the necessity of dissecting sequence similarity scores into segment-specific contributions for inferring protein homology, function prediction and annotation

PubMed Central

2014-01-01

Background Protein sequence similarities to any types of non-globular segments (coiled coils, low complexity regions, transmembrane regions, long loops, etc. where either positional sequence conservation is the result of a very simple, physically induced pattern or rather integral sequence properties are critical) are pertinent sources for mistaken homologies. Regretfully, these considerations regularly escape attention in large-scale annotation studies since, often, there is no substitute to manual handling of these cases. Quantitative criteria are required to suppress events of function annotation transfer as a result of false homology assignments. Results The sequence homology concept is based on the similarity comparison between the structural elements, the basic building blocks for conferring the overall fold of a protein. We propose to dissect the total similarity score into fold-critical and other, remaining contributions and suggest that, for a valid homology statement, the fold-relevant score contribution should at least be significant on its own. As part of the article, we provide the DissectHMMER software program for dissecting HMMER2/3 scores into segment-specific contributions. We show that DissectHMMER reproduces HMMER2/3 scores with sufficient accuracy and that it is useful in automated decisions about homology for instructive sequence examples. To generalize the dissection concept for cases without 3D structural information, we find that a dissection based on alignment quality is an appropriate surrogate. The approach was applied to a large-scale study of SMART and PFAM domains in the space of seed sequences and in the space of UniProt/SwissProt. Conclusions Sequence similarity core dissection with regard to fold-critical and other contributions systematically suppresses false hits and, additionally, recovers previously obscured homology relationships such as the one between aquaporins and formate/nitrite transporters that, so far, was only supported by structure comparison. PMID:24890864

Self-organising mixture autoregressive model for non-stationary time series modelling.

PubMed

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

Statistical model of laminar structure for atlas-based segmentation of the fetal brain from in utero MR images

NASA Astrophysics Data System (ADS)

Habas, Piotr A.; Kim, Kio; Chandramohan, Dharshan; Rousseau, Francois; Glenn, Orit A.; Studholme, Colin

2009-02-01

Recent advances in MR and image analysis allow for reconstruction of high-resolution 3D images from clinical in utero scans of the human fetal brain. Automated segmentation of tissue types from MR images (MRI) is a key step in the quantitative analysis of brain development. Conventional atlas-based methods for adult brain segmentation are limited in their ability to accurately delineate complex structures of developing tissues from fetal MRI. In this paper, we formulate a novel geometric representation of the fetal brain aimed at capturing the laminar structure of developing anatomy. The proposed model uses a depth-based encoding of tissue occurrence within the fetal brain and provides an additional anatomical constraint in a form of a laminar prior that can be incorporated into conventional atlas-based EM segmentation. Validation experiments are performed using clinical in utero scans of 5 fetal subjects at gestational ages ranging from 20.5 to 22.5 weeks. Experimental results are evaluated against reference manual segmentations and quantified in terms of Dice similarity coefficient (DSC). The study demonstrates that the use of laminar depth-encoded tissue priors improves both the overall accuracy and precision of fetal brain segmentation. Particular refinement is observed in regions of the parietal and occipital lobes where the DSC index is improved from 0.81 to 0.82 for cortical grey matter, from 0.71 to 0.73 for the germinal matrix, and from 0.81 to 0.87 for white matter.

Salient object detection: manifold-based similarity adaptation approach

NASA Astrophysics Data System (ADS)

Zhou, Jingbo; Ren, Yongfeng; Yan, Yunyang; Gao, Shangbing

2014-11-01

A saliency detection algorithm based on manifold-based similarity adaptation is proposed. The proposed algorithm is divided into three steps. First, we segment an input image into superpixels, which are represented as the nodes in a graph. Second, a new similarity measurement is used in the proposed algorithm. The weight matrix of the graph, which indicates the similarities between the nodes, uses a similarity-based method. It also captures the manifold structure of the image patches, in which the graph edges are determined in a data adaptive manner in terms of both similarity and manifold structure. Then, we use local reconstruction method as a diffusion method to obtain the saliency maps. The objective function in the proposed method is based on local reconstruction, with which estimated weights capture the manifold structure. Experiments on four bench-mark databases demonstrate the accuracy and robustness of the proposed method.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, J; Balter, P; Court, L

Purpose: To evaluate the performance of commercially available automatic segmentation tools built into treatment planning systems (TPS) in terms of their segmentation accuracy and flexibility in customization. Methods: Twelve head-and-neck cancer patients and twelve thoracic cancer patients were retrospectively selected to benchmark the model-based segmentation (MBS) and atlas-based segmentation (ABS) in RayStation TPS and the Smart Probabilistic Image Contouring Engine (SPICE) in Pinnacle TPS. Multi-atlas contouring service (MACS) that was developed in-house as a plug-in of Pinnacle TPS was evaluated as well. Manual contours used in clinic were reviewed and modified for consistency and served as ground truth for themore » evaluation. Head-and-neck evaluation included six regions of interest (ROIs): left and right parotid glands, brainstem, spinal cord, mandible, and submandibular glands. Thoracic evaluation includes seven ROIs: left and right lungs, spinal cord, heart, esophagus, and left and right brachial plexus. Auto-segmented contours were compared with the manual contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Results: In head- and-neck evaluation, only mandible has a high accuracy in all segmentations (DSC>85%); SPICE achieved DSC>70% for parotid glands; MACS achieved this for both parotid glands and submandibular glands; and RayStation ABS achieved this for spinal cord. In thoracic evaluation, SPICE achieved the best in lung and heart segmentation, while MACS achieved the best for all other structures. The less distinguishable structures on CT images, such as brainstem, spinal cord, parotid glands, submandibular glands, esophagus, and brachial plexus, showed great variability in different segmentation tools (mostly DSC<70% and MSD>3mm). The template for RayStation ABS can be easily customized by users, while RayStation MBS and SPICE rely on the vendors to provide the templates/models. Conclusion: Great variability was observed in different segmentation tools applied to different structures. These commercially-available segmentation tools should be carefully evaluated before clinical use.« less

A shape-based segmentation method for mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen

2013-07-01

Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well.

Automated methods for hippocampus segmentation: the evolution and a review of the state of the art.

PubMed

Dill, Vanderson; Franco, Alexandre Rosa; Pinho, Márcio Sarroglia

2015-04-01

The segmentation of the hippocampus in Magnetic Resonance Imaging (MRI) has been an important procedure to diagnose and monitor several clinical situations. The precise delineation of the borders of this brain structure makes it possible to obtain a measure of the volume and estimate its shape, which can be used to diagnose some diseases, such as Alzheimer's disease, schizophrenia and epilepsy. As the manual segmentation procedure in three-dimensional images is highly time consuming and the reproducibility is low, automated methods introduce substantial gains. On the other hand, the implementation of those methods is a challenge because of the low contrast of this structure in relation to the neighboring areas of the brain. Within this context, this research presents a review of the evolution of automatized methods for the segmentation of the hippocampus in MRI. Many proposed methods for segmentation of the hippocampus have been published in leading journals in the medical image processing area. This paper describes these methods presenting the techniques used and quantitatively comparing the methods based on Dice Similarity Coefficient. Finally, we present an evaluation of those methods considering the degree of user intervention, computational cost, segmentation accuracy and feasibility of application in a clinical routine.

3D model retrieval method based on mesh segmentation

NASA Astrophysics Data System (ADS)

Gan, Yuanchao; Tang, Yan; Zhang, Qingchen

2012-04-01

In the process of feature description and extraction, current 3D model retrieval algorithms focus on the global features of 3D models but ignore the combination of global and local features of the model. For this reason, they show less effective performance to the models with similar global shape and different local shape. This paper proposes a novel algorithm for 3D model retrieval based on mesh segmentation. The key idea is to exact the structure feature and the local shape feature of 3D models, and then to compares the similarities of the two characteristics and the total similarity between the models. A system that realizes this approach was built and tested on a database of 200 objects and achieves expected results. The results show that the proposed algorithm improves the precision and the recall rate effectively.

Multi-atlas based segmentation using probabilistic label fusion with adaptive weighting of image similarity measures.

PubMed

Sjöberg, C; Ahnesjö, A

2013-06-01

Label fusion multi-atlas approaches for image segmentation can give better segmentation results than single atlas methods. We present a multi-atlas label fusion strategy based on probabilistic weighting of distance maps. Relationships between image similarities and segmentation similarities are estimated in a learning phase and used to derive fusion weights that are proportional to the probability for each atlas to improve the segmentation result. The method was tested using a leave-one-out strategy on a database of 21 pre-segmented prostate patients for different image registrations combined with different image similarity scorings. The probabilistic weighting yields results that are equal or better compared to both fusion with equal weights and results using the STAPLE algorithm. Results from the experiments demonstrate that label fusion by weighted distance maps is feasible, and that probabilistic weighted fusion improves segmentation quality more the stronger the individual atlas segmentation quality depends on the corresponding registered image similarity. The regions used for evaluation of the image similarity measures were found to be more important than the choice of similarity measure. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Complex evolutionary footprints revealed in an analysis of reused protein segments of diverse lengths

PubMed Central

Nepomnyachiy, Sergey; Ben-Tal, Nir; Kolodny, Rachel

2017-01-01

Proteins share similar segments with one another. Such “reused parts”—which have been successfully incorporated into other proteins—are likely to offer an evolutionary advantage over de novo evolved segments, as most of the latter will not even have the capacity to fold. To systematically explore the evolutionary traces of segment “reuse” across proteins, we developed an automated methodology that identifies reused segments from protein alignments. We search for “themes”—segments of at least 35 residues of similar sequence and structure—reused within representative sets of 15,016 domains [Evolutionary Classification of Protein Domains (ECOD) database] or 20,398 chains [Protein Data Bank (PDB)]. We observe that theme reuse is highly prevalent and that reuse is more extensive when the length threshold for identifying a theme is lower. Structural domains, the best characterized form of reuse in proteins, are just one of many complex and intertwined evolutionary traces. Others include long themes shared among a few proteins, which encompass and overlap with shorter themes that recur in numerous proteins. The observed complexity is consistent with evolution by duplication and divergence, and some of the themes might include descendants of ancestral segments. The observed recursive footprints, where the same amino acid can simultaneously participate in several intertwined themes, could be a useful concept for protein design. Data are available at http://trachel-srv.cs.haifa.ac.il/rachel/ppi/themes/. PMID:29078314

Formation of rings from segments of HeLa-cell nuclear deoxyribonucleic acid

PubMed Central

Hardman, Norman

1974-01-01

Duplex segments of HeLa-cell nuclear DNA were generated by cleavage with DNA restriction endonuclease from Haemophilus influenzae. About 20–25% of the DNA segments produced, when partly degraded with exonuclease III and annealed, were found to form rings visible in the electron microscope. A further 5% of the DNA segments formed structures that were branched in configuration. Similar structures were generated from HeLa-cell DNA, without prior treatment with restriction endonuclease, when the complementary polynucleotide chains were exposed by exonuclease III action at single-chain nicks. After exposure of an average single-chain length of 1400 nucleotides per terminus at nicks in HeLa-cell DNA by exonuclease III, followed by annealing, the physical length of ring closures was estimated and found to be 0.02–0.1μm, or 50–300 base pairs. An almost identical distribution of lengths was recorded for the regions of complementary base sequence responsible for branch formation. It is proposed that most of the rings and branches are formed from classes of reiterated base sequence with an average length of 180 base pairs arranged intermittenly in HeLa-cell DNA. From the rate of formation of branched structures when HeLa-cell DNA segments were heat-denatured and annealed, it is estimated that the reiterated sequences are in families containing approximately 2400–24000 copies. ImagesPLATE 2PLATE 1 PMID:4462738

Voxel classification based airway tree segmentation

NASA Astrophysics Data System (ADS)

Lo, Pechin; de Bruijne, Marleen

2008-03-01

This paper presents a voxel classification based method for segmenting the human airway tree in volumetric computed tomography (CT) images. In contrast to standard methods that use only voxel intensities, our method uses a more complex appearance model based on a set of local image appearance features and Kth nearest neighbor (KNN) classification. The optimal set of features for classification is selected automatically from a large set of features describing the local image structure at several scales. The use of multiple features enables the appearance model to differentiate between airway tree voxels and other voxels of similar intensities in the lung, thus making the segmentation robust to pathologies such as emphysema. The classifier is trained on imperfect segmentations that can easily be obtained using region growing with a manual threshold selection. Experiments show that the proposed method results in a more robust segmentation that can grow into the smaller airway branches without leaking into emphysematous areas, and is able to segment many branches that are not present in the training set.

Probabilistic brain tissue segmentation in neonatal magnetic resonance imaging.

PubMed

Anbeek, Petronella; Vincken, Koen L; Groenendaal, Floris; Koeman, Annemieke; van Osch, Matthias J P; van der Grond, Jeroen

2008-02-01

A fully automated method has been developed for segmentation of four different structures in the neonatal brain: white matter (WM), central gray matter (CEGM), cortical gray matter (COGM), and cerebrospinal fluid (CSF). The segmentation algorithm is based on information from T2-weighted (T2-w) and inversion recovery (IR) scans. The method uses a K nearest neighbor (KNN) classification technique with features derived from spatial information and voxel intensities. Probabilistic segmentations of each tissue type were generated. By applying thresholds on these probability maps, binary segmentations were obtained. These final segmentations were evaluated by comparison with a gold standard. The sensitivity, specificity, and Dice similarity index (SI) were calculated for quantitative validation of the results. High sensitivity and specificity with respect to the gold standard were reached: sensitivity >0.82 and specificity >0.9 for all tissue types. Tissue volumes were calculated from the binary and probabilistic segmentations. The probabilistic segmentation volumes of all tissue types accurately estimated the gold standard volumes. The KNN approach offers valuable ways for neonatal brain segmentation. The probabilistic outcomes provide a useful tool for accurate volume measurements. The described method is based on routine diagnostic magnetic resonance imaging (MRI) and is suitable for large population studies.

Sparse intervertebral fence composition for 3D cervical vertebra segmentation

NASA Astrophysics Data System (ADS)

Liu, Xinxin; Yang, Jian; Song, Shuang; Cong, Weijian; Jiao, Peifeng; Song, Hong; Ai, Danni; Jiang, Yurong; Wang, Yongtian

2018-06-01

Statistical shape models are capable of extracting shape prior information, and are usually utilized to assist the task of segmentation of medical images. However, such models require large training datasets in the case of multi-object structures, and it also is difficult to achieve satisfactory results for complex shapes. This study proposed a novel statistical model for cervical vertebra segmentation, called sparse intervertebral fence composition (SiFC), which can reconstruct the boundary between adjacent vertebrae by modeling intervertebral fences. The complex shape of the cervical spine is replaced by a simple intervertebral fence, which considerably reduces the difficulty of cervical segmentation. The final segmentation results are obtained by using a 3D active contour deformation model without shape constraint, which substantially enhances the recognition capability of the proposed method for objects with complex shapes. The proposed segmentation framework is tested on a dataset with CT images from 20 patients. A quantitative comparison against corresponding reference vertebral segmentation yields an overall mean absolute surface distance of 0.70 mm and a dice similarity index of 95.47% for cervical vertebral segmentation. The experimental results show that the SiFC method achieves competitive cervical vertebral segmentation performances, and completely eliminates inter-process overlap.

Understanding dengue virus capsid protein disordered N-Terminus and pep14-23-based inhibition.

PubMed

Faustino, André F; Guerra, Gabriela M; Huber, Roland G; Hollmann, Axel; Domingues, Marco M; Barbosa, Glauce M; Enguita, Francisco J; Bond, Peter J; Castanho, Miguel A R B; Da Poian, Andrea T; Almeida, Fabio C L; Santos, Nuno C; Martins, Ivo C

2015-02-20

Dengue virus (DENV) infection affects millions of people and is becoming a major global disease for which there is no specific available treatment. pep14-23 is a recently designed peptide, based on a conserved segment of DENV capsid (C) protein. It inhibits the interaction of DENV C with host intracellular lipid droplets (LDs), which is crucial for viral replication. Combining bioinformatics and biophysics, here, we analyzed pep14-23 structure and ability to bind different phospholipids, relating that information with the full-length DENV C. We show that pep14-23 acquires α-helical conformation upon binding to negatively charged phospholipid membranes, displaying an asymmetric charge distribution structural arrangement. Structure prediction for the N-terminal segment reveals four viable homodimer orientations that alternatively shield or expose the DENV C hydrophobic pocket. Taken together, these findings suggest a new biological role for the disordered N-terminal region, which may function as an autoinhibitory domain mediating DENV C interaction with its biological targets. The results fit with our current understanding of DENV C and pep14-23 structure and function, paving the way for similar approaches to understanding disordered proteins and improved peptidomimetics drug development strategies against DENV and similar Flavivirus infections.

Quantitative Comparison of 21 Protocols for Labeling Hippocampal Subfields and Parahippocampal Subregions in In Vivo MRI: Towards a Harmonized Segmentation Protocol

PubMed Central

Yushkevich, Paul A.; Amaral, Robert S. C.; Augustinack, Jean C.; Bender, Andrew R.; Bernstein, Jeffrey D.; Boccardi, Marina; Bocchetta, Martina; Burggren, Alison C.; Carr, Valerie A.; Chakravarty, M. Mallar; Chetelat, Gael; Daugherty, Ana M.; Davachi, Lila; Ding, Song-Lin; Ekstrom, Arne; Geerlings, Mirjam I.; Hassan, Abdul; Huang, Yushan; Iglesias, Eugenio; La Joie, Renaud; Kerchner, Geoffrey A.; LaRocque, Karen F.; Libby, Laura A.; Malykhin, Nikolai; Mueller, Susanne G.; Olsen, Rosanna K.; Palombo, Daniela J.; Parekh, Mansi B; Pluta, John B.; Preston, Alison R.; Pruessner, Jens C.; Ranganath, Charan; Raz, Naftali; Schlichting, Margaret L.; Schoemaker, Dorothee; Singh, Sachi; Stark, Craig E. L.; Suthana, Nanthia; Tompary, Alexa; Turowski, Marta M.; Van Leemput, Koen; Wagner, Anthony D.; Wang, Lei; Winterburn, Julie L.; Wisse, Laura E.M.; Yassa, Michael A.; Zeineh, Michael M.

2015-01-01

OBJECTIVE An increasing number of human in vivo magnetic resonance imaging (MRI) studies have focused on examining the structure and function of the subfields of the hippocampal formation (the dentate gyrus, CA fields 1–3, and the subiculum) and subregions of the parahippocampal gyrus (entorhinal, perirhinal, and parahippocampal cortices). The ability to interpret the results of such studies and to relate them to each other would be improved if a common standard existed for labeling hippocampal subfields and parahippocampal subregions. Currently, research groups label different subsets of structures and use different rules, landmarks, and cues to define their anatomical extents. This paper characterizes, both qualitatively and quantitatively, the variability in the existing manual segmentation protocols for labeling hippocampal and parahippocampal substructures in MRI, with the goal of guiding subsequent work on developing a harmonized substructure segmentation protocol. METHOD MRI scans of a single healthy adult human subject were acquired both at 3 Tesla and 7 Tesla. Representatives from 21 research groups applied their respective manual segmentation protocols to the MRI modalities of their choice. The resulting set of 21 segmentations was analyzed in a common anatomical space to quantify similarity and identify areas of agreement. RESULTS The differences between the 21 protocols include the region within which segmentation is performed, the set of anatomical labels used, and the extents of specific anatomical labels. The greatest overall disagreement among the protocols is at the CA1/subiculum boundary, and disagreement across all structures is greatest in the anterior portion of the hippocampal formation relative to the body and tail. CONCLUSIONS The combined examination of the 21 protocols in the same dataset suggests possible strategies towards developing a harmonized subfield segmentation protocol and facilitates comparison between published studies. PMID:25596463

Lung tumor segmentation in PET images using graph cuts.

PubMed

Ballangan, Cherry; Wang, Xiuying; Fulham, Michael; Eberl, Stefan; Feng, David Dagan

2013-03-01

The aim of segmentation of tumor regions in positron emission tomography (PET) is to provide more accurate measurements of tumor size and extension into adjacent structures, than is possible with visual assessment alone and hence improve patient management decisions. We propose a segmentation energy function for the graph cuts technique to improve lung tumor segmentation with PET. Our segmentation energy is based on an analysis of the tumor voxels in PET images combined with a standardized uptake value (SUV) cost function and a monotonic downhill SUV feature. The monotonic downhill feature avoids segmentation leakage into surrounding tissues with similar or higher PET tracer uptake than the tumor and the SUV cost function improves the boundary definition and also addresses situations where the lung tumor is heterogeneous. We evaluated the method in 42 clinical PET volumes from patients with non-small cell lung cancer (NSCLC). Our method improves segmentation and performs better than region growing approaches, the watershed technique, fuzzy-c-means, region-based active contour and tumor customized downhill. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Late-Variscan Tectonic Inheritance and Salt Tectonics Interplay in the Central Lusitanian Basin

NASA Astrophysics Data System (ADS)

Nogueira, Carlos R.; Marques, Fernando O.

2017-04-01

Tectonic inheritance and salt structures can play an important role in the tectono-sedimentary evolution of basins. The Alpine regional stress field in west Iberia had a horizontal maximum compressive stress striking approximately NNW-SSE, related to the Late Miocene inversion event. However, this stress field cannot produce a great deal of the observed and mapped structures in the Lusitanian Basin. Moreover, many observed structures show a trend similar to well-known basement fault systems. The Central Lusitanian basin shows an interesting tectonic structure, the Montejunto structure, generally assigned to this inversion event. Therefore, special attention was paid to: (1) basement control of important observed structures; and (2) diapir tectonics (vertical maximum compressive stress), which can be responsible for significant vertical movements. Based on fieldwork, tectonic analysis and interpretation of geological maps (Portuguese Geological Survey, 1:50000 scale) and geophysical data, our work shows: (1) the Montejunto structure is a composite structure comprising an antiform with a curved hinge and middle Jurassic core, and bounding main faults; (2) the antiform can be divided into three main segments: (i) a northern segment with NNE-SSW trend showing W-dipping bedding bounded at the eastern border by a NNE-SSW striking fault, (ii) a curved central segment, showing the highest topography, with a middle Jurassic core and radial dipping bedding, (iii) a western segment with ENE-WSW trend comprising an antiform with a steeper northern limb and periclinal termination towards WSW, bounded to the south by ENE-WSW reverse faulting, (3) both fold and fault trends at the northern and western segments are parallel to well-known basement faults related to late-Variscan strike-slip systems with NNE-SSW and ENE-WSW trends; (4) given the orientation of Alpine maximum compressive stress, the northern segment border fault should be mostly sinistral strike-slip and the western segment border fault should be a pure thrust; (5) uplift along the northern and central segments may point out to the presence of a salt diapir at depth, aiding vertical movement and local uplift of the structure; (6) geometry of seismic units of the neighboring basins is consistent with halokinesis related to the antiform growth during the Jurassic; (7) sedimentary filling of the neighbouring basins shows relationship to antiform development and growth into a structural high before the Late Miocene Alpine event. These data suggest that: (1) pre-existing basement faults and their reactivation played important role on the development of Montejunto complex tectonic structure; (2) important vertical movements occurred as the result of regional and local (diapir) tectonics; (3) subsidence in neighbouring basins may have promoted maturation, and possible targets with strong potential for hydrocarbon trapping and accumulation may have also developed; (4) diapir tectonics initiated before the Cretaceous; (5) given the topography, and the geometry and inferred kinematics of all segments, it seems that the Montejunto structure formed in a restraining bend controlled by inherited late-Variscan basement faults.

The Properties of Outer Retinal Band Three Investigated With Adaptive-Optics Optical Coherence Tomography.

PubMed

Jonnal, Ravi S; Gorczynska, Iwona; Migacz, Justin V; Azimipour, Mehdi; Zawadzki, Robert J; Werner, John S

2017-09-01

Optical coherence tomography's (OCT) third outer retinal band has been attributed to the zone of interdigitation between RPE cells and cone outer segments. The purpose of this paper is to investigate the structure of this band with adaptive optics (AO)-OCT. Using AO-OCT, images were obtained from two subjects. Axial structure was characterized by measuring band 3 thickness and separation between bands 2 and 3 in segmented cones. Lateral structure was characterized by correlation of band 3 with band 2 and comparison of their power spectra. Band thickness and separation were also measured in a clinical OCT image of one subject. Band 3 thickness ranged from 4.3 to 6.4 μm. Band 2 correlations ranged between 0.35 and 0.41 and power spectra of both bands confirmed peak frequencies that agree with histologic density measurements. In clinical images, band 3 thickness was between 14 and 19 μm. Measurements of AO-OCT of interband distance were lower than our corresponding clinical OCT measurements. Band 3 originates from a structure with axial extent similar to a single surface. Correlation with band 2 suggests an origin within the cone photoreceptor. These two observations indicate that band 3 corresponds predominantly to cone outer segment tips (COST). Conventional OCT may overestimate both the thickness of band 3 and outer segment length.

The Properties of Outer Retinal Band Three Investigated With Adaptive-Optics Optical Coherence Tomography

PubMed Central

Jonnal, Ravi S.; Gorczynska, Iwona; Migacz, Justin V.; Azimipour, Mehdi; Zawadzki, Robert J.; Werner, John S.

2017-01-01

Purpose Optical coherence tomography's (OCT) third outer retinal band has been attributed to the zone of interdigitation between RPE cells and cone outer segments. The purpose of this paper is to investigate the structure of this band with adaptive optics (AO)-OCT. Methods Using AO-OCT, images were obtained from two subjects. Axial structure was characterized by measuring band 3 thickness and separation between bands 2 and 3 in segmented cones. Lateral structure was characterized by correlation of band 3 with band 2 and comparison of their power spectra. Band thickness and separation were also measured in a clinical OCT image of one subject. Results Band 3 thickness ranged from 4.3 to 6.4 μm. Band 2 correlations ranged between 0.35 and 0.41 and power spectra of both bands confirmed peak frequencies that agree with histologic density measurements. In clinical images, band 3 thickness was between 14 and 19 μm. Measurements of AO-OCT of interband distance were lower than our corresponding clinical OCT measurements. Conclusions Band 3 originates from a structure with axial extent similar to a single surface. Correlation with band 2 suggests an origin within the cone photoreceptor. These two observations indicate that band 3 corresponds predominantly to cone outer segment tips (COST). Conventional OCT may overestimate both the thickness of band 3 and outer segment length. PMID:28877320

A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT.

PubMed

Xu, Ziyue; Bagci, Ulas; Foster, Brent; Mansoor, Awais; Udupa, Jayaram K; Mollura, Daniel J

2015-08-01

Inflammatory and infectious lung diseases commonly involve bronchial airway structures and morphology, and these abnormalities are often analyzed non-invasively through high resolution computed tomography (CT) scans. Assessing airway wall surfaces and the lumen are of great importance for diagnosing pulmonary diseases. However, obtaining high accuracy from a complete 3-D airway tree structure can be quite challenging. The airway tree structure has spiculated shapes with multiple branches and bifurcation points as opposed to solid single organ or tumor segmentation tasks in other applications, hence, it is complex for manual segmentation as compared with other tasks. For computerized methods, a fundamental challenge in airway tree segmentation is the highly variable intensity levels in the lumen area, which often causes a segmentation method to leak into adjacent lung parenchyma through blurred airway walls or soft boundaries. Moreover, outer wall definition can be difficult due to similar intensities of the airway walls and nearby structures such as vessels. In this paper, we propose a computational framework to accurately quantify airways through (i) a novel hybrid approach for precise segmentation of the lumen, and (ii) two novel methods (a spatially constrained Markov random walk method (pseudo 3-D) and a relative fuzzy connectedness method (3-D)) to estimate the airway wall thickness. We evaluate the performance of our proposed methods in comparison with mostly used algorithms using human chest CT images. Our results demonstrate that, on publicly available data sets and using standard evaluation criteria, the proposed airway segmentation method is accurate and efficient as compared with the state-of-the-art methods, and the airway wall estimation algorithms identified the inner and outer airway surfaces more accurately than the most widely applied methods, namely full width at half maximum and phase congruency. Copyright © 2015. Published by Elsevier B.V.

Hedgehog signaling regulates segment formation in the annelid Platynereis.

PubMed

Dray, Nicolas; Tessmar-Raible, Kristin; Le Gouar, Martine; Vibert, Laura; Christodoulou, Foteini; Schipany, Katharina; Guillou, Aurélien; Zantke, Juliane; Snyman, Heidi; Béhague, Julien; Vervoort, Michel; Arendt, Detlev; Balavoine, Guillaume

2010-07-16

Annelids and arthropods share a similar segmented organization of the body whose evolutionary origin remains unclear. The Hedgehog signaling pathway, prominent in arthropod embryonic segment patterning, has not been shown to have a similar function outside arthropods. We show that the ligand Hedgehog, the receptor Patched, and the transcription factor Gli are all expressed in striped patterns before the morphological appearance of segments in the annelid Platynereis dumerilii. Treatments with small molecules antagonistic to Hedgehog signaling disrupt segment formation. Platynereis Hedgehog is not necessary to establish early segment patterns but is required to maintain them. The molecular similarity of segment patterning functions of the Hedgehog pathway in an annelid and in arthropods supports a common origin of segmentation in protostomes.

Isolation of a Novel Fusogenic Orthoreovirus from Eucampsipoda africana Bat Flies in South Africa

PubMed Central

Jansen van Vuren, Petrus; Wiley, Michael; Palacios, Gustavo; Storm, Nadia; McCulloch, Stewart; Markotter, Wanda; Birkhead, Monica; Kemp, Alan; Paweska, Janusz T.

2016-01-01

We report on the isolation of a novel fusogenic orthoreovirus from bat flies (Eucampsipoda africana) associated with Egyptian fruit bats (Rousettus aegyptiacus) collected in South Africa. Complete sequences of the ten dsRNA genome segments of the virus, tentatively named Mahlapitsi virus (MAHLV), were determined. Phylogenetic analysis places this virus into a distinct clade with Baboon orthoreovirus, Bush viper reovirus and the bat-associated Broome virus. All genome segments of MAHLV contain a 5' terminal sequence (5'-GGUCA) that is unique to all currently described viruses of the genus. The smallest genome segment is bicistronic encoding for a 14 kDa protein similar to p14 membrane fusion protein of Bush viper reovirus and an 18 kDa protein similar to p16 non-structural protein of Baboon orthoreovirus. This is the first report on isolation of an orthoreovirus from an arthropod host associated with bats, and phylogenetic and sequence data suggests that MAHLV constitutes a new species within the Orthoreovirus genus. PMID:27011199

Genetic Structure of Avian Influenza Viruses from Ducks of the Atlantic Flyway of North America

PubMed Central

Huang, Yanyan; Wille, Michelle; Dobbin, Ashley; Walzthöni, Natasha M.; Robertson, Gregory J.; Ojkic, Davor; Whitney, Hugh; Lang, Andrew S.

2014-01-01

Wild birds, including waterfowl such as ducks, are reservoir hosts of influenza A viruses. Despite the increased number of avian influenza virus (AIV) genome sequences available, our understanding of AIV genetic structure and transmission through space and time in waterfowl in North America is still limited. In particular, AIVs in ducks of the Atlantic flyway of North America have not been thoroughly investigated. To begin to address this gap, we analyzed 109 AIV genome sequences from ducks in the Atlantic flyway to determine their genetic structure and to document the extent of gene flow in the context of sequences from other locations and other avian and mammalian host groups. The analyses included 25 AIVs from ducks from Newfoundland, Canada, from 2008–2011 and 84 available reference duck AIVs from the Atlantic flyway from 2006–2011. A vast diversity of viral genes and genomes was identified in the 109 viruses. The genetic structure differed amongst the 8 viral segments with predominant single lineages found for the PB2, PB1 and M segments, increased diversity found for the PA, NP and NS segments (2, 3 and 3 lineages, respectively), and the highest diversity found for the HA and NA segments (12 and 9 lineages, respectively). Identification of inter-hemispheric transmissions was rare with only 2% of the genes of Eurasian origin. Virus transmission between ducks and other bird groups was investigated, with 57.3% of the genes having highly similar (≥99% nucleotide identity) genes detected in birds other than ducks. Transmission between North American flyways has been frequent and 75.8% of the genes were highly similar to genes found in other North American flyways. However, the duck AIV genes did display spatial distribution bias, which was demonstrated by the different population sizes of specific viral genes in one or two neighbouring flyways compared to more distant flyways. PMID:24498009

Characterizing protein conformations by correlation analysis of coarse-grained contact matrices.

PubMed

Lindsay, Richard J; Siess, Jan; Lohry, David P; McGee, Trevor S; Ritchie, Jordan S; Johnson, Quentin R; Shen, Tongye

2018-01-14

We have developed a method to capture the essential conformational dynamics of folded biopolymers using statistical analysis of coarse-grained segment-segment contacts. Previously, the residue-residue contact analysis of simulation trajectories was successfully applied to the detection of conformational switching motions in biomolecular complexes. However, the application to large protein systems (larger than 1000 amino acid residues) is challenging using the description of residue contacts. Also, the residue-based method cannot be used to compare proteins with different sequences. To expand the scope of the method, we have tested several coarse-graining schemes that group a collection of consecutive residues into a segment. The definition of these segments may be derived from structural and sequence information, while the interaction strength of the coarse-grained segment-segment contacts is a function of the residue-residue contacts. We then perform covariance calculations on these coarse-grained contact matrices. We monitored how well the principal components of the contact matrices is preserved using various rendering functions. The new method was demonstrated to assist the reduction of the degrees of freedom for describing the conformation space, and it potentially allows for the analysis of a system that is approximately tenfold larger compared with the corresponding residue contact-based method. This method can also render a family of similar proteins into the same conformational space, and thus can be used to compare the structures of proteins with different sequences.

A shape prior-based MRF model for 3D masseter muscle segmentation

NASA Astrophysics Data System (ADS)

Majeed, Tahir; Fundana, Ketut; Lüthi, Marcel; Beinemann, Jörg; Cattin, Philippe

2012-02-01

Medical image segmentation is generally an ill-posed problem that can only be solved by incorporating prior knowledge. The ambiguities arise due to the presence of noise, weak edges, imaging artifacts, inhomogeneous interior and adjacent anatomical structures having similar intensity profile as the target structure. In this paper we propose a novel approach to segment the masseter muscle using the graph-cut incorporating additional 3D shape priors in CT datasets, which is robust to noise; artifacts; and shape deformations. The main contribution of this paper is in translating the 3D shape knowledge into both unary and pairwise potentials of the Markov Random Field (MRF). The segmentation task is casted as a Maximum-A-Posteriori (MAP) estimation of the MRF. Graph-cut is then used to obtain the global minimum which results in the segmentation of the masseter muscle. The method is tested on 21 CT datasets of the masseter muscle, which are noisy with almost all possessing mild to severe imaging artifacts such as high-density artifacts caused by e.g. the very common dental fillings and dental implants. We show that the proposed technique produces clinically acceptable results to the challenging problem of muscle segmentation, and further provide a quantitative and qualitative comparison with other methods. We statistically show that adding additional shape prior into both unary and pairwise potentials can increase the robustness of the proposed method in noisy datasets.

Characterizing protein conformations by correlation analysis of coarse-grained contact matrices

NASA Astrophysics Data System (ADS)

Lindsay, Richard J.; Siess, Jan; Lohry, David P.; McGee, Trevor S.; Ritchie, Jordan S.; Johnson, Quentin R.; Shen, Tongye

2018-01-01

We have developed a method to capture the essential conformational dynamics of folded biopolymers using statistical analysis of coarse-grained segment-segment contacts. Previously, the residue-residue contact analysis of simulation trajectories was successfully applied to the detection of conformational switching motions in biomolecular complexes. However, the application to large protein systems (larger than 1000 amino acid residues) is challenging using the description of residue contacts. Also, the residue-based method cannot be used to compare proteins with different sequences. To expand the scope of the method, we have tested several coarse-graining schemes that group a collection of consecutive residues into a segment. The definition of these segments may be derived from structural and sequence information, while the interaction strength of the coarse-grained segment-segment contacts is a function of the residue-residue contacts. We then perform covariance calculations on these coarse-grained contact matrices. We monitored how well the principal components of the contact matrices is preserved using various rendering functions. The new method was demonstrated to assist the reduction of the degrees of freedom for describing the conformation space, and it potentially allows for the analysis of a system that is approximately tenfold larger compared with the corresponding residue contact-based method. This method can also render a family of similar proteins into the same conformational space, and thus can be used to compare the structures of proteins with different sequences.

A coarse-to-fine approach for pericardial effusion localization and segmentation in chest CT scans

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Chellamuthu, Karthik; Lu, Le; Bagheri, Mohammadhadi; Summers, Ronald M.

2018-02-01

Pericardial effusion on CT scans demonstrates very high shape and volume variability and very low contrast to adjacent structures. This inhibits traditional automated segmentation methods from achieving high accuracies. Deep neural networks have been widely used for image segmentation in CT scans. In this work, we present a two-stage method for pericardial effusion localization and segmentation. For the first step, we localize the pericardial area from the entire CT volume, providing a reliable bounding box for the more refined segmentation step. A coarse-scaled holistically-nested convolutional networks (HNN) model is trained on entire CT volume. The resulting HNN per-pixel probability maps are then threshold to produce a bounding box covering the pericardial area. For the second step, a fine-scaled HNN model is trained only on the bounding box region for effusion segmentation to reduce the background distraction. Quantitative evaluation is performed on a dataset of 25 CT scans of patient (1206 images) with pericardial effusion. The segmentation accuracy of our two-stage method, measured by Dice Similarity Coefficient (DSC), is 75.59+/-12.04%, which is significantly better than the segmentation accuracy (62.74+/-15.20%) of only using the coarse-scaled HNN model.

Structure of a nanobody-stabilized active state of the β(2) adrenoceptor.

PubMed

Rasmussen, Søren G F; Choi, Hee-Jung; Fung, Juan Jose; Pardon, Els; Casarosa, Paola; Chae, Pil Seok; Devree, Brian T; Rosenbaum, Daniel M; Thian, Foon Sun; Kobilka, Tong Sun; Schnapp, Andreas; Konetzki, Ingo; Sunahara, Roger K; Gellman, Samuel H; Pautsch, Alexander; Steyaert, Jan; Weis, William I; Kobilka, Brian K

2011-01-13

G protein coupled receptors (GPCRs) exhibit a spectrum of functional behaviours in response to natural and synthetic ligands. Recent crystal structures provide insights into inactive states of several GPCRs. Efforts to obtain an agonist-bound active-state GPCR structure have proven difficult due to the inherent instability of this state in the absence of a G protein. We generated a camelid antibody fragment (nanobody) to the human β(2) adrenergic receptor (β(2)AR) that exhibits G protein-like behaviour, and obtained an agonist-bound, active-state crystal structure of the receptor-nanobody complex. Comparison with the inactive β(2)AR structure reveals subtle changes in the binding pocket; however, these small changes are associated with an 11 Å outward movement of the cytoplasmic end of transmembrane segment 6, and rearrangements of transmembrane segments 5 and 7 that are remarkably similar to those observed in opsin, an active form of rhodopsin. This structure provides insights into the process of agonist binding and activation.

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

PubMed

Pereira, Sergio; Pinto, Adriano; Alves, Victor; Silva, Carlos A

2016-05-01

Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this paper, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3 ×3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against overfitting, given the fewer number of weights in the network. We also investigated the use of intensity normalization as a pre-processing step, which though not common in CNN-based segmentation methods, proved together with data augmentation to be very effective for brain tumor segmentation in MRI images. Our proposal was validated in the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013), obtaining simultaneously the first position for the complete, core, and enhancing regions in Dice Similarity Coefficient metric (0.88, 0.83, 0.77) for the Challenge data set. Also, it obtained the overall first position by the online evaluation platform. We also participated in the on-site BRATS 2015 Challenge using the same model, obtaining the second place, with Dice Similarity Coefficient metric of 0.78, 0.65, and 0.75 for the complete, core, and enhancing regions, respectively.

3D exemplar-based random walks for tooth segmentation from cone-beam computed tomography images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pei, Yuru, E-mail: peiyuru@cis.pku.edu.cn; Ai, Xin

Purpose: Tooth segmentation is an essential step in acquiring patient-specific dental geometries from cone-beam computed tomography (CBCT) images. Tooth segmentation from CBCT images is still a challenging task considering the comparatively low image quality caused by the limited radiation dose, as well as structural ambiguities from intercuspation and nearby alveolar bones. The goal of this paper is to present and discuss the latest accomplishments in semisupervised tooth segmentation with adaptive 3D shape constraints. Methods: The authors propose a 3D exemplar-based random walk method of tooth segmentation from CBCT images. The proposed method integrates semisupervised label propagation and regularization by 3Dmore » exemplar registration. To begin with, the pure random walk method is to get an initial segmentation of the teeth, which tends to be erroneous because of the structural ambiguity of CBCT images. And then, as an iterative refinement, the authors conduct a regularization by using 3D exemplar registration, as well as label propagation by random walks with soft constraints, to improve the tooth segmentation. In the first stage of the iteration, 3D exemplars with well-defined topologies are adapted to fit the tooth contours, which are obtained from the random walks based segmentation. The soft constraints on voxel labeling are defined by shape-based foreground dentine probability acquired by the exemplar registration, as well as the appearance-based probability from a support vector machine (SVM) classifier. In the second stage, the labels of the volume-of-interest (VOI) are updated by the random walks with soft constraints. The two stages are optimized iteratively. Instead of the one-shot label propagation in the VOI, an iterative refinement process can achieve a reliable tooth segmentation by virtue of exemplar-based random walks with adaptive soft constraints. Results: The proposed method was applied for tooth segmentation of twenty clinically captured CBCT images. Three metrics, including the Dice similarity coefficient (DSC), the Jaccard similarity coefficient (JSC), and the mean surface deviation (MSD), were used to quantitatively analyze the segmentation of anterior teeth including incisors and canines, premolars, and molars. The segmentation of the anterior teeth achieved a DSC up to 98%, a JSC of 97%, and an MSD of 0.11 mm compared with manual segmentation. For the premolars, the average values of DSC, JSC, and MSD were 98%, 96%, and 0.12 mm, respectively. The proposed method yielded a DSC of 95%, a JSC of 89%, and an MSD of 0.26 mm for molars. Aside from the interactive definition of label priors by the user, automatic tooth segmentation can be achieved in an average of 1.18 min. Conclusions: The proposed technique enables an efficient and reliable tooth segmentation from CBCT images. This study makes it clinically practical to segment teeth from CBCT images, thus facilitating pre- and interoperative uses of dental morphologies in maxillofacial and orthodontic treatments.« less

3D exemplar-based random walks for tooth segmentation from cone-beam computed tomography images.

PubMed

Pei, Yuru; Ai, Xingsheng; Zha, Hongbin; Xu, Tianmin; Ma, Gengyu

2016-09-01

Tooth segmentation is an essential step in acquiring patient-specific dental geometries from cone-beam computed tomography (CBCT) images. Tooth segmentation from CBCT images is still a challenging task considering the comparatively low image quality caused by the limited radiation dose, as well as structural ambiguities from intercuspation and nearby alveolar bones. The goal of this paper is to present and discuss the latest accomplishments in semisupervised tooth segmentation with adaptive 3D shape constraints. The authors propose a 3D exemplar-based random walk method of tooth segmentation from CBCT images. The proposed method integrates semisupervised label propagation and regularization by 3D exemplar registration. To begin with, the pure random walk method is to get an initial segmentation of the teeth, which tends to be erroneous because of the structural ambiguity of CBCT images. And then, as an iterative refinement, the authors conduct a regularization by using 3D exemplar registration, as well as label propagation by random walks with soft constraints, to improve the tooth segmentation. In the first stage of the iteration, 3D exemplars with well-defined topologies are adapted to fit the tooth contours, which are obtained from the random walks based segmentation. The soft constraints on voxel labeling are defined by shape-based foreground dentine probability acquired by the exemplar registration, as well as the appearance-based probability from a support vector machine (SVM) classifier. In the second stage, the labels of the volume-of-interest (VOI) are updated by the random walks with soft constraints. The two stages are optimized iteratively. Instead of the one-shot label propagation in the VOI, an iterative refinement process can achieve a reliable tooth segmentation by virtue of exemplar-based random walks with adaptive soft constraints. The proposed method was applied for tooth segmentation of twenty clinically captured CBCT images. Three metrics, including the Dice similarity coefficient (DSC), the Jaccard similarity coefficient (JSC), and the mean surface deviation (MSD), were used to quantitatively analyze the segmentation of anterior teeth including incisors and canines, premolars, and molars. The segmentation of the anterior teeth achieved a DSC up to 98%, a JSC of 97%, and an MSD of 0.11 mm compared with manual segmentation. For the premolars, the average values of DSC, JSC, and MSD were 98%, 96%, and 0.12 mm, respectively. The proposed method yielded a DSC of 95%, a JSC of 89%, and an MSD of 0.26 mm for molars. Aside from the interactive definition of label priors by the user, automatic tooth segmentation can be achieved in an average of 1.18 min. The proposed technique enables an efficient and reliable tooth segmentation from CBCT images. This study makes it clinically practical to segment teeth from CBCT images, thus facilitating pre- and interoperative uses of dental morphologies in maxillofacial and orthodontic treatments.

Comparison of atlas-based techniques for whole-body bone segmentation.

PubMed

Arabi, Hossein; Zaidi, Habib

2017-02-01

We evaluate the accuracy of whole-body bone extraction from whole-body MR images using a number of atlas-based segmentation methods. The motivation behind this work is to find the most promising approach for the purpose of MRI-guided derivation of PET attenuation maps in whole-body PET/MRI. To this end, a variety of atlas-based segmentation strategies commonly used in medical image segmentation and pseudo-CT generation were implemented and evaluated in terms of whole-body bone segmentation accuracy. Bone segmentation was performed on 23 whole-body CT/MR image pairs via leave-one-out cross validation procedure. The evaluated segmentation techniques include: (i) intensity averaging (IA), (ii) majority voting (MV), (iii) global and (iv) local (voxel-wise) weighting atlas fusion frameworks implemented utilizing normalized mutual information (NMI), normalized cross-correlation (NCC) and mean square distance (MSD) as image similarity measures for calculating the weighting factors, along with other atlas-dependent algorithms, such as (v) shape-based averaging (SBA) and (vi) Hofmann's pseudo-CT generation method. The performance evaluation of the different segmentation techniques was carried out in terms of estimating bone extraction accuracy from whole-body MRI using standard metrics, such as Dice similarity (DSC) and relative volume difference (RVD) considering bony structures obtained from intensity thresholding of the reference CT images as the ground truth. Considering the Dice criterion, global weighting atlas fusion methods provided moderate improvement of whole-body bone segmentation (DSC= 0.65 ± 0.05) compared to non-weighted IA (DSC= 0.60 ± 0.02). The local weighed atlas fusion approach using the MSD similarity measure outperformed the other strategies by achieving a DSC of 0.81 ± 0.03 while using the NCC and NMI measures resulted in a DSC of 0.78 ± 0.05 and 0.75 ± 0.04, respectively. Despite very long computation time, the extracted bone obtained from both SBA (DSC= 0.56 ± 0.05) and Hofmann's methods (DSC= 0.60 ± 0.02) exhibited no improvement compared to non-weighted IA. Finding the optimum parameters for implementation of the atlas fusion approach, such as weighting factors and image similarity patch size, have great impact on the performance of atlas-based segmentation approaches. The voxel-wise atlas fusion approach exhibited excellent performance in terms of cancelling out the non-systematic registration errors leading to accurate and reliable segmentation results. Denoising and normalization of MR images together with optimization of the involved parameters play a key role in improving bone extraction accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.

Hierarchical Multi-atlas Label Fusion with Multi-scale Feature Representation and Label-specific Patch Partition

PubMed Central

Wu, Guorong; Kim, Minjeong; Sanroma, Gerard; Wang, Qian; Munsell, Brent C.; Shen, Dinggang

2014-01-01

Multi-atlas patch-based label fusion methods have been successfully used to improve segmentation accuracy in many important medical image analysis applications. In general, to achieve label fusion a single target image is first registered to several atlas images, after registration a label is assigned to each target point in the target image by determining the similarity between the underlying target image patch (centered at the target point) and the aligned image patch in each atlas image. To achieve the highest level of accuracy during the label fusion process it’s critical the chosen patch similarity measurement accurately captures the tissue/shape appearance of the anatomical structure. One major limitation of existing state-of-the-art label fusion methods is that they often apply a fixed size image patch throughout the entire label fusion procedure. Doing so may severely affect the fidelity of the patch similarity measurement, which in turn may not adequately capture complex tissue appearance patterns expressed by the anatomical structure. To address this limitation, we advance state-of-the-art by adding three new label fusion contributions: First, each image patch now characterized by a multi-scale feature representation that encodes both local and semi-local image information. Doing so will increase the accuracy of the patch-based similarity measurement. Second, to limit the possibility of the patch-based similarity measurement being wrongly guided by the presence of multiple anatomical structures in the same image patch, each atlas image patch is further partitioned into a set of label-specific partial image patches according to the existing labels. Since image information has now been semantically divided into different patterns, these new label-specific atlas patches make the label fusion process more specific and flexible. Lastly, in order to correct target points that are mislabeled during label fusion, a hierarchically approach is used to improve the label fusion results. In particular, a coarse-to-fine iterative label fusion approach is used that gradually reduces the patch size. To evaluate the accuracy of our label fusion approach, the proposed method was used to segment the hippocampus in the ADNI dataset and 7.0 tesla MR images, sub-cortical regions in LONI LBPA40 dataset, mid-brain regions in SATA dataset from MICCAI 2013 segmentation challenge, and a set of key internal gray matter structures in IXI dataset. In all experiments, the segmentation results of the proposed hierarchical label fusion method with multi-scale feature representations and label-specific atlas patches are more accurate than several well-known state-of-the-art label fusion methods. PMID:25463474

On a common circle: natural scenes and Gestalt rules.

PubMed

Sigman, M; Cecchi, G A; Gilbert, C D; Magnasco, M O

2001-02-13

To understand how the human visual system analyzes images, it is essential to know the structure of the visual environment. In particular, natural images display consistent statistical properties that distinguish them from random luminance distributions. We have studied the geometric regularities of oriented elements (edges or line segments) present in an ensemble of visual scenes, asking how much information the presence of a segment in a particular location of the visual scene carries about the presence of a second segment at different relative positions and orientations. We observed strong long-range correlations in the distribution of oriented segments that extend over the whole visual field. We further show that a very simple geometric rule, cocircularity, predicts the arrangement of segments in natural scenes, and that different geometrical arrangements show relevant differences in their scaling properties. Our results show similarities to geometric features of previous physiological and psychophysical studies. We discuss the implications of these findings for theories of early vision.

The Structure of the Plakin Domain of Plectin Reveals an Extended Rod-like Shape*

PubMed Central

Carballido, Ana M.

2016-01-01

Plakins are large multi-domain proteins that interconnect cytoskeletal structures. Plectin is a prototypical plakin that tethers intermediate filaments to membrane-associated complexes. Most plakins contain a plakin domain formed by up to nine spectrin repeats (SR1–SR9) and an SH3 domain. The plakin domains of plectin and other plakins harbor binding sites for junctional proteins. We have combined x-ray crystallography with small angle x-ray scattering (SAXS) to elucidate the structure of the plakin domain of plectin, extending our previous analysis of the SR1 to SR5 region. Two crystal structures of the SR5-SR6 region allowed us to characterize its uniquely wide inter-repeat conformational variability. We also report the crystal structures of the SR7-SR8 region, refined to 1.8 Å, and the SR7–SR9 at lower resolution. The SR7–SR9 region, which is conserved in all other plakin domains, forms a rigid segment stabilized by uniquely extensive inter-repeat contacts mediated by unusually long helices in SR8 and SR9. Using SAXS we show that in solution the SR3–SR6 and SR7–SR9 regions are rod-like segments and that SR3–SR9 of plectin has an extended shape with a small central kink. Other plakins, such as bullous pemphigoid antigen 1 and microtubule and actin cross-linking factor 1, are likely to have similar extended plakin domains. In contrast, desmoplakin has a two-segment structure with a central flexible hinge. The continuous versus segmented structures of the plakin domains of plectin and desmoplakin give insight into how different plakins might respond to tension and transmit mechanical signals. PMID:27413182

Tectonic Deformation Pattern along the Longmen Shan Fault Zone in Eastern Tibet: Insights from Focal Mechanisms of the Wenchuan and Lushan Earthquake Sequences, Southwestern China

NASA Astrophysics Data System (ADS)

Yi, G.; Vallage, A.; Klinger, Y.; Long, F.; Wang, S.

2017-12-01

760 ML≥3.5 aftershocks of the 2008 Wenchuan earthquake, the 2013 Lushan mainshock and its 87 ML≥3.5 aftershocks were selected to obtain focal mechanism solutions from CAP waveform inversion method (Zhu and Helmberger, 1996), along with strain rosette (Amelung and King, 1997) and Areal strain (As) (Vallage et al., 2014), we aimed to analyze the tectonic deformation pattern along the Longmen Shan (LMS) fault zone, southwestern China. The As values show that 93% compressional earthquakes for the Lushan sequence are of pure thrust for the southern segment of the LMS fault zone, while only 50% compressional and nearly 40% of strike-slip and oblique-thrust events for the Wenchuan sequence reflect the strike-slip component increase on the central-northern segment of the LMS fault zone, meaning many different faults responsible for the Wenchuan aftershock activity. The strain rosettes with purely NW-trending compressional white lobe for the entire 87 aftershocks and 4 different classes of magnitudes are very similar to that of the Lushan mainshock. We infer that the geological structures for the southern segment are of thrust faulting under NW compressional deformation. The strain rosettes exhibit self-similarity in terms of orientation and shape for all classes, reflecting that the deformation pattern of the southern segment is independent with earthquake size, and suggesting that each class is representative of the overall deformation for the southern segment. We obtained EW-oriented pure compressional strain rosette of the entire 760 aftershocks and NW-oriented white lobe with small NE-oriented black lobe of the Wenchuan mainshock, and this difference may reflect different tectonic deformation pattern during the co-seismic and post-seismic stages. The deformation segmentation along the Wenchuan coseismic surface rupture is also evidenced from the different orientation of strain rosettes, i.e., NW for the southern area, NE for the central and NNW for the northern parts. The above inferences indicate a very complicated tectonic deformation pattern related to the complex geological structure. The segment of the northern aftershock area without ruptures behaves an oblique compressional deformation.

Surface cracks as a long-term record of Andean plate boundary segmentation

NASA Astrophysics Data System (ADS)

Loveless, J. P.; Allmendinger, R. W.; Pritchard, M. E.

2007-12-01

Meter-scale surface cracks throughout the northern Chilean and southern Peruvian forearcs provide a long-term record of seismic segmentation along the Andean plate boundary. The cracks, mapped on high-resolution satellite imagery, show strong preferred orientations over large regions and the mean strikes of cracks vary systematically as a function of position along the margin. The spatial scale of this variation suggests that stress fields operating with similar dimensions, namely those produced by strong subduction zone earthquakes, are primarily responsible for crack evolution. The orientations of cracks are consistent with the static and dynamic coseismic stress fields calculated for several recent and historical earthquakes on distinct segments of the subduction interface. Field observations indicate that the cracks have experienced multiple episodes of opening and proximal age evidence suggests that they represent deformation as old as several hundred thousand years. We invert the crack orientation data to solve for plausible slip distributions on the Iquique, Chile segment of the margin (19°--23° S), which last ruptured in a M~8--9 event in 1877. We find that concentrations of coseismic slip resolved by the inversion coincide spatially with negative gravity anomalies, consistent with recent studies correlating subduction zone earthquake slip with forearc structure. These results suggest that distinct seismic segments or asperities on the subduction interface define characteristic earthquakes with rupture dimensions and magnitudes that are similar over many seismic cycles.

Surface cracks as a long-term record of Andean plate boundary segmentation

NASA Astrophysics Data System (ADS)

Loveless, J. P.; Allmendinger, R. W.; Pritchard, M. E.

2004-12-01

Meter-scale surface cracks throughout the northern Chilean and southern Peruvian forearcs provide a long-term record of seismic segmentation along the Andean plate boundary. The cracks, mapped on high-resolution satellite imagery, show strong preferred orientations over large regions and the mean strikes of cracks vary systematically as a function of position along the margin. The spatial scale of this variation suggests that stress fields operating with similar dimensions, namely those produced by strong subduction zone earthquakes, are primarily responsible for crack evolution. The orientations of cracks are consistent with the static and dynamic coseismic stress fields calculated for several recent and historical earthquakes on distinct segments of the subduction interface. Field observations indicate that the cracks have experienced multiple episodes of opening and proximal age evidence suggests that they represent deformation as old as several hundred thousand years. We invert the crack orientation data to solve for plausible slip distributions on the Iquique, Chile segment of the margin (19°--23° S), which last ruptured in a M~8--9 event in 1877. We find that concentrations of coseismic slip resolved by the inversion coincide spatially with negative gravity anomalies, consistent with recent studies correlating subduction zone earthquake slip with forearc structure. These results suggest that distinct seismic segments or asperities on the subduction interface define characteristic earthquakes with rupture dimensions and magnitudes that are similar over many seismic cycles.

Segmentation of histological images and fibrosis identification with a convolutional neural network.

PubMed

Fu, Xiaohang; Liu, Tong; Xiong, Zhaohan; Smaill, Bruce H; Stiles, Martin K; Zhao, Jichao

2018-07-01

Segmentation of histological images is one of the most crucial tasks for many biomedical analyses involving quantification of certain tissue types, such as fibrosis via Masson's trichrome staining. However, challenges are posed by the high variability and complexity of structural features in such images, in addition to imaging artifacts. Further, the conventional approach of manual thresholding is labor-intensive, and highly sensitive to inter- and intra-image intensity variations. An accurate and robust automated segmentation method is of high interest. We propose and evaluate an elegant convolutional neural network (CNN) designed for segmentation of histological images, particularly those with Masson's trichrome stain. The network comprises 11 successive convolutional - rectified linear unit - batch normalization layers. It outperformed state-of-the-art CNNs on a dataset of cardiac histological images (labeling fibrosis, myocytes, and background) with a Dice similarity coefficient of 0.947. With 100 times fewer (only 300,000) trainable parameters than the state-of-the-art, our CNN is less susceptible to overfitting, and is efficient. Additionally, it retains image resolution from input to output, captures fine-grained details, and can be trained end-to-end smoothly. To the best of our knowledge, this is the first deep CNN tailored to the problem of concern, and may potentially be extended to solve similar segmentation tasks to facilitate investigations into pathology and clinical treatment. Copyright © 2018 Elsevier Ltd. All rights reserved.

TH-CD-206-02: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in MR Images Using Patch-Based Anatomical Signature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, X; Jani, A; Rossi, P

Purpose: MRI has shown promise in identifying prostate tumors with high sensitivity and specificity for the detection of prostate cancer. Accurate segmentation of the prostate plays a key role various tasks: to accurately localize prostate boundaries for biopsy needle placement and radiotherapy, to initialize multi-modal registration algorithms or to obtain the region of interest for computer-aided detection of prostate cancer. However, manual segmentation during biopsy or radiation therapy can be time consuming and subject to inter- and intra-observer variation. This study’s purpose it to develop an automated method to address this technical challenge. Methods: We present an automated multi-atlas segmentationmore » for MR prostate segmentation using patch-based label fusion. After an initial preprocessing for all images, all the atlases are non-rigidly registered to a target image. And then, the resulting transformation is used to propagate the anatomical structure labels of the atlas into the space of the target image. The top L similar atlases are further chosen by measuring intensity and structure difference in the region of interest around prostate. Finally, using voxel weighting based on patch-based anatomical signature, the label that the majority of all warped labels predict for each voxel is used for the final segmentation of the target image. Results: This segmentation technique was validated with a clinical study of 13 patients. The accuracy of our approach was assessed using the manual segmentation (gold standard). The mean volume Dice Overlap Coefficient was 89.5±2.9% between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D MRI-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning label fusion framework, demonstrated its clinical feasibility, and validated its accuracy. This segmentation technique could be a useful tool in image-guided interventions for prostate-cancer diagnosis and treatment.« less

Automatic segmentation of mandible in panoramic x-ray.

PubMed

Abdi, Amir Hossein; Kasaei, Shohreh; Mehdizadeh, Mojdeh

2015-10-01

As the panoramic x-ray is the most common extraoral radiography in dentistry, segmentation of its anatomical structures facilitates diagnosis and registration of dental records. This study presents a fast and accurate method for automatic segmentation of mandible in panoramic x-rays. In the proposed four-step algorithm, a superior border is extracted through horizontal integral projections. A modified Canny edge detector accompanied by morphological operators extracts the inferior border of the mandible body. The exterior borders of ramuses are extracted through a contour tracing method based on the average model of mandible. The best-matched template is fetched from the atlas of mandibles to complete the contour of left and right processes. The algorithm was tested on a set of 95 panoramic x-rays. Evaluating the results against manual segmentations of three expert dentists showed that the method is robust. It achieved an average performance of [Formula: see text] in Dice similarity, specificity, and sensitivity.

Structure of the San Andreas Fault Zone in the Salton Trough Region of Southern California: A Comparison with San Andreas Fault Structure in the Loma Prieta Area of Central California

NASA Astrophysics Data System (ADS)

Fuis, G. S.; Catchings, R.; Scheirer, D. S.; Goldman, M.; Zhang, E.; Bauer, K.

2016-12-01

The San Andreas fault (SAF) in the northern Salton Trough, or Coachella Valley, in southern California, appears non-vertical and non-planar. In cross section, it consists of a steeply dipping segment (75 deg dip NE) from the surface to 6- to 9-km depth, and a moderately dipping segment below 6- to 9-km depth (50-55 deg dip NE). It also appears to branch upward into a flower-like structure beginning below about 10-km depth. Images of the SAF zone in the Coachella Valley have been obtained from analysis of steep reflections, earthquakes, modeling of potential-field data, and P-wave tomography. Review of seismological and geodetic research on the 1989 M 6.9 Loma Prieta earthquake, in central California (e.g., U.S. Geological Survey Professional Paper 1550), shows several features of SAF zone structure similar to those seen in the northern Salton Trough. Aftershocks in the Loma Prieta epicentral area form two chief clusters, a tabular zone extending from 18- to 9-km depth and a complex cluster above 5-km depth. The deeper cluster has been interpreted to surround the chief rupture plane, which dips 65-70 deg SW. When double-difference earthquake locations are plotted, the shallower cluster contains tabular subclusters that appear to connect the main rupture with the surface traces of the Sargent and Berrocal faults. In addition, a diffuse cluster may surround a steep to vertical fault connecting the main rupture to the surface trace of the SAF. These interpreted fault connections from the main rupture to surface fault traces appear to define a flower-like structure, not unlike that seen above the moderately dipping segment of the SAF in the Coachella Valley. But importantly, the SAF, interpreted here to include the main rupture plane, appears segmented, as in the Coachella Valley, with a moderately dipping segment below 9-km depth and a steep to vertical segment above that depth. We hope to clarify fault-zone structure in the Loma Prieta area by reanalyzing active-source data collected after the earthquake for steep reflections.

Stacking denoising auto-encoders in a deep network to segment the brainstem on MRI in brain cancer patients: A clinical study.

PubMed

Dolz, Jose; Betrouni, Nacim; Quidet, Mathilde; Kharroubi, Dris; Leroy, Henri A; Reyns, Nicolas; Massoptier, Laurent; Vermandel, Maximilien

2016-09-01

Delineation of organs at risk (OARs) is a crucial step in surgical and treatment planning in brain cancer, where precise OARs volume delineation is required. However, this task is still often manually performed, which is time-consuming and prone to observer variability. To tackle these issues a deep learning approach based on stacking denoising auto-encoders has been proposed to segment the brainstem on magnetic resonance images in brain cancer context. Additionally to classical features used in machine learning to segment brain structures, two new features are suggested. Four experts participated in this study by segmenting the brainstem on 9 patients who underwent radiosurgery. Analysis of variance on shape and volume similarity metrics indicated that there were significant differences (p<0.05) between the groups of manual annotations and automatic segmentations. Experimental evaluation also showed an overlapping higher than 90% with respect to the ground truth. These results are comparable, and often higher, to those of the state of the art segmentation methods but with a considerably reduction of the segmentation time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-channel MRI segmentation of eye structures and tumors using patient-specific features

PubMed Central

Ciller, Carlos; De Zanet, Sandro; Kamnitsas, Konstantinos; Maeder, Philippe; Glocker, Ben; Munier, Francis L.; Rueckert, Daniel; Thiran, Jean-Philippe

2017-01-01

Retinoblastoma and uveal melanoma are fast spreading eye tumors usually diagnosed by using 2D Fundus Image Photography (Fundus) and 2D Ultrasound (US). Diagnosis and treatment planning of such diseases often require additional complementary imaging to confirm the tumor extend via 3D Magnetic Resonance Imaging (MRI). In this context, having automatic segmentations to estimate the size and the distribution of the pathological tissue would be advantageous towards tumor characterization. Until now, the alternative has been the manual delineation of eye structures, a rather time consuming and error-prone task, to be conducted in multiple MRI sequences simultaneously. This situation, and the lack of tools for accurate eye MRI analysis, reduces the interest in MRI beyond the qualitative evaluation of the optic nerve invasion and the confirmation of recurrent malignancies below calcified tumors. In this manuscript, we propose a new framework for the automatic segmentation of eye structures and ocular tumors in multi-sequence MRI. Our key contribution is the introduction of a pathological eye model from which Eye Patient-Specific Features (EPSF) can be computed. These features combine intensity and shape information of pathological tissue while embedded in healthy structures of the eye. We assess our work on a dataset of pathological patient eyes by computing the Dice Similarity Coefficient (DSC) of the sclera, the cornea, the vitreous humor, the lens and the tumor. In addition, we quantitatively show the superior performance of our pathological eye model as compared to the segmentation obtained by using a healthy model (over 4% DSC) and demonstrate the relevance of our EPSF, which improve the final segmentation regardless of the classifier employed. PMID:28350816

SOV_refine: A further refined definition of segment overlap score and its significance for protein structure similarity.

PubMed

Liu, Tong; Wang, Zheng

2018-01-01

The segment overlap score (SOV) has been used to evaluate the predicted protein secondary structures, a sequence composed of helix (H), strand (E), and coil (C), by comparing it with the native or reference secondary structures, another sequence of H, E, and C. SOV's advantage is that it can consider the size of continuous overlapping segments and assign extra allowance to longer continuous overlapping segments instead of only judging from the percentage of overlapping individual positions as Q3 score does. However, we have found a drawback from its previous definition, that is, it cannot ensure increasing allowance assignment when more residues in a segment are further predicted accurately. A new way of assigning allowance has been designed, which keeps all the advantages of the previous SOV score definitions and ensures that the amount of allowance assigned is incremental when more elements in a segment are predicted accurately. Furthermore, our improved SOV has achieved a higher correlation with the quality of protein models measured by GDT-TS score and TM-score, indicating its better abilities to evaluate tertiary structure quality at the secondary structure level. We analyzed the statistical significance of SOV scores and found the threshold values for distinguishing two protein structures (SOV_refine  > 0.19) and indicating whether two proteins are under the same CATH fold (SOV_refine > 0.94 and > 0.90 for three- and eight-state secondary structures respectively). We provided another two example applications, which are when used as a machine learning feature for protein model quality assessment and comparing different definitions of topologically associating domains. We proved that our newly defined SOV score resulted in better performance. The SOV score can be widely used in bioinformatics research and other fields that need to compare two sequences of letters in which continuous segments have important meanings. We also generalized the previous SOV definitions so that it can work for sequences composed of more than three states (e.g., it can work for the eight-state definition of protein secondary structures). A standalone software package has been implemented in Perl with source code released. The software can be downloaded from http://dna.cs.miami.edu/SOV/.

Structural analysis of the human fibroblast growth factor receptor 4 kinase.

PubMed

Lesca, E; Lammens, A; Huber, R; Augustin, M

2014-11-11

The family of fibroblast growth factor receptors (FGFRs) plays an important and well-characterized role in a variety of pathological disorders. FGFR4 is involved in myogenesis and muscle regeneration. Mutations affecting the kinase domain of FGFR4 may cause cancer, for example, breast cancer or rhabdomyosarcoma. Whereas FGFR1-FGFR3 have been structurally characterized, the structure of the FGFR4 kinase domain has not yet been reported. In this study, we present four structures of the kinase domain of FGFR4, in its apo-form and in complex with different types of small-molecule inhibitors. The two apo-FGFR4 kinase domain structures show an activation segment similar in conformation to an autoinhibitory segment observed in the hepatocyte growth factor receptor kinase but different from the known structures of other FGFR kinases. The structures of FGFR4 in complex with the type I inhibitor Dovitinib and the type II inhibitor Ponatinib reveal the molecular interactions with different types of kinase inhibitors and may assist in the design and development of FGFR4 inhibitors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Image segmentation by hierarchial agglomeration of polygons using ecological statistics

DOEpatents

Prasad, Lakshman; Swaminarayan, Sriram

2013-04-23

A method for rapid hierarchical image segmentation based on perceptually driven contour completion and scene statistics is disclosed. The method begins with an initial fine-scale segmentation of an image, such as obtained by perceptual completion of partial contours into polygonal regions using region-contour correspondences established by Delaunay triangulation of edge pixels as implemented in VISTA. The resulting polygons are analyzed with respect to their size and color/intensity distributions and the structural properties of their boundaries. Statistical estimates of granularity of size, similarity of color, texture, and saliency of intervening boundaries are computed and formulated into logical (Boolean) predicates. The combined satisfiability of these Boolean predicates by a pair of adjacent polygons at a given segmentation level qualifies them for merging into a larger polygon representing a coarser, larger-scale feature of the pixel image and collectively obtains the next level of polygonal segments in a hierarchy of fine-to-coarse segmentations. The iterative application of this process precipitates textured regions as polygons with highly convolved boundaries and helps distinguish them from objects which typically have more regular boundaries. The method yields a multiscale decomposition of an image into constituent features that enjoy a hierarchical relationship with features at finer and coarser scales. This provides a traversable graph structure from which feature content and context in terms of other features can be derived, aiding in automated image understanding tasks. The method disclosed is highly efficient and can be used to decompose and analyze large images.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Automatic co-segmentation of lung tumor based on random forest in PET-CT images

NASA Astrophysics Data System (ADS)

Jiang, Xueqing; Xiang, Dehui; Zhang, Bin; Zhu, Weifang; Shi, Fei; Chen, Xinjian

2016-03-01

In this paper, a fully automatic method is proposed to segment the lung tumor in clinical 3D PET-CT images. The proposed method effectively combines PET and CT information to make full use of the high contrast of PET images and superior spatial resolution of CT images. Our approach consists of three main parts: (1) initial segmentation, in which spines are removed in CT images and initial connected regions achieved by thresholding based segmentation in PET images; (2) coarse segmentation, in which monotonic downhill function is applied to rule out structures which have similar standardized uptake values (SUV) to the lung tumor but do not satisfy a monotonic property in PET images; (3) fine segmentation, random forests method is applied to accurately segment the lung tumor by extracting effective features from PET and CT images simultaneously. We validated our algorithm on a dataset which consists of 24 3D PET-CT images from different patients with non-small cell lung cancer (NSCLC). The average TPVF, FPVF and accuracy rate (ACC) were 83.65%, 0.05% and 99.93%, respectively. The correlation analysis shows our segmented lung tumor volumes has strong correlation ( average 0.985) with the ground truth 1 and ground truth 2 labeled by a clinical expert.

Structure and Dynamics Ionic Block co-Polymer Melts: Computational Study

NASA Astrophysics Data System (ADS)

Aryal, Dipak; Perahia, Dvora; Grest, Gary S.

Tethering ionomer blocks into co-polymers enables engineering of polymeric systems designed to encompass transport while controlling structure. Here the structure and dynamics of symmetric pentablock copolymers melts are probed by fully atomistic molecular dynamics simulations. The center block consists of randomly sulfonated polystyrene with sulfonation fractions f = 0 to 0.55 tethered to a hydrogenated polyisoprene (PI), end caped with poly(t-butyl styrene). We find that melts with f = 0.15 and 0.30 consist of isolated ionic clusters whereas melts with f = 0.55 exhibit a long-range percolating ionic network. Similar to polystyrene sulfonate, a small number of ionic clusters slow the mobility of the center of mass of the co-polymer, however, formation of the ionic clusters is slower and they are often intertwined with PI segments. Surprisingly, the segmental dynamics of the other blocks are also affected. NSF DMR-1611136; NERSC; Palmetto Cluster Clemson University; Kraton Polymers US, LLC.

Automated and simultaneous fovea center localization and macula segmentation using the new dynamic identification and classification of edges model.

PubMed

Onal, Sinan; Chen, Xin; Satamraju, Veeresh; Balasooriya, Maduka; Dabil-Karacal, Humeyra

2016-07-01

Detecting the position of retinal structures, including the fovea center and macula, in retinal images plays a key role in diagnosing eye diseases such as optic nerve hypoplasia, amblyopia, diabetic retinopathy, and macular edema. However, current detection methods are unreliable for infants or certain ethnic populations. Thus, a methodology is proposed here that may be useful for infants and across ethnicities that automatically localizes the fovea center and segments the macula on digital fundus images. First, dark structures and bright artifacts are removed from the input image using preprocessing operations, and the resulting image is transformed to polar space. Second, the fovea center is identified, and the macula region is segmented using the proposed dynamic identification and classification of edges (DICE) model. The performance of the method was evaluated using 1200 fundus images obtained from the relatively large, diverse, and publicly available Messidor database. In 96.1% of these 1200 cases, the distance between the fovea center identified manually by ophthalmologists and automatically using the proposed method remained within 0 to 8 pixels. The dice similarity index comparing the manually obtained results with those of the model for macula segmentation was 96.12% for these 1200 cases. Thus, the proposed method displayed a high degree of accuracy. The methodology using the DICE model is unique and advantageous over previously reported methods because it simultaneously determines the fovea center and segments the macula region without using any structural information, such as optic disc or blood vessel location, and it may prove useful for all populations, including infants.

Evaluation of an improved technique for lumen path definition and lumen segmentation of atherosclerotic vessels in CT angiography.

PubMed

van Velsen, Evert F S; Niessen, Wiro J; de Weert, Thomas T; de Monyé, Cécile; van der Lugt, Aad; Meijering, Erik; Stokking, Rik

2007-07-01

Vessel image analysis is crucial when considering therapeutical options for (cardio-) vascular diseases. Our method, VAMPIRE (Vascular Analysis using Multiscale Paths Inferred from Ridges and Edges), involves two parts: a user defines a start- and endpoint upon which a lumen path is automatically defined, and which is used for initialization; the automatic segmentation of the vessel lumen on computed tomographic angiography (CTA) images. Both parts are based on the detection of vessel-like structures by analyzing intensity, edge, and ridge information. A multi-observer evaluation study was performed to compare VAMPIRE with a conventional method on the CTA data of 15 patients with carotid artery stenosis. In addition to the start- and endpoint, the two radiologists required on average 2.5 (SD: 1.9) additional points to define a lumen path when using the conventional method, and 0.1 (SD: 0.3) when using VAMPIRE. The segmentation results were quantitatively evaluated using Similarity Indices, which were slightly lower between VAMPIRE and the two radiologists (respectively 0.90 and 0.88) compared with the Similarity Index between the radiologists (0.92). The evaluation shows that the improved definition of a lumen path requires minimal user interaction, and that using this path as initialization leads to good automatic lumen segmentation results.

Structure and Sensilla of the Mouthparts of the Spotted Lanternfly Lycorma delicatula (Hemiptera: Fulgoromorpha: Fulgoridae), a Polyphagous Invasive Planthopper

PubMed Central

Hao, Yanan; Dietrich, Christopher H.; Dai, Wu

2016-01-01

Mouthparts are among the most important sensory and feeding structures in insects and comparative morphological study may help explain differences in feeding behavior and diet breadth among species. The spotted lanternfly Lycorma delicatula (White) (Hemiptera: Fulgoromorpha: Fulgoridae) is a polyphagous agricultural pest originating in China, recently established and becoming widespread in Korea, and more recently introduced into eastern North America. It causes severe economic damage by sucking phloem sap and the sugary excrement produced by nymphs and adults serves as a medium for sooty mold. To facilitate future study of feeding mechanisms in this insect, the fine-structural morphology of mouthparts focusing on the distribution of sensilla located on the labium in adult L. delicatula was observed using a scanning electron microscope. The mouthparts consist of a small cone-shaped labrum, a tubular labium and a stylet fascicle consisting of two inner interlocked maxillary stylets partially surrounded by two shorter mandibular stylets similar to those found in other hemipteran insects. The five-segmented labium is unusual (most other Fulgoromorpha have four segments) and is provided with several types of sensilla and cuticular processes situated on the apex of its distal labial segment. In general, nine types of sensilla were found on the mouthparts. Six types of sensilla and four types of cuticular processes are present on sensory fields of the labial apex. The proposed taxonomic and functional significance of the sensilla are discussed. Morphological similarities in the interlocking mechanism of the stylets suggest a relationship between Fulgoromorpha and Heteroptera. PMID:27253390

Multiresolution texture models for brain tumor segmentation in MRI.

PubMed

Iftekharuddin, Khan M; Ahmed, Shaheen; Hossen, Jakir

2011-01-01

In this study we discuss different types of texture features such as Fractal Dimension (FD) and Multifractional Brownian Motion (mBm) for estimating random structures and varying appearance of brain tissues and tumors in magnetic resonance images (MRI). We use different selection techniques including KullBack - Leibler Divergence (KLD) for ranking different texture and intensity features. We then exploit graph cut, self organizing maps (SOM) and expectation maximization (EM) techniques to fuse selected features for brain tumors segmentation in multimodality T1, T2, and FLAIR MRI. We use different similarity metrics to evaluate quality and robustness of these selected features for tumor segmentation in MRI for real pediatric patients. We also demonstrate a non-patient-specific automated tumor prediction scheme by using improved AdaBoost classification based on these image features.

Statistical Validation of Automatic Methods for Hippocampus Segmentation in MR Images of Epileptic Patients

PubMed Central

Hosseini, Mohammad-Parsa; Nazem-Zadeh, Mohammad R.; Pompili, Dario; Soltanian-Zadeh, Hamid

2015-01-01

Hippocampus segmentation is a key step in the evaluation of mesial Temporal Lobe Epilepsy (mTLE) by MR images. Several automated segmentation methods have been introduced for medical image segmentation. Because of multiple edges, missing boundaries, and shape changing along its longitudinal axis, manual outlining still remains the benchmark for hippocampus segmentation, which however, is impractical for large datasets due to time constraints. In this study, four automatic methods, namely FreeSurfer, Hammer, Automatic Brain Structure Segmentation (ABSS), and LocalInfo segmentation, are evaluated to find the most accurate and applicable method that resembles the bench-mark of hippocampus. Results from these four methods are compared against those obtained using manual segmentation for T1-weighted images of 157 symptomatic mTLE patients. For performance evaluation of automatic segmentation, Dice coefficient, Hausdorff distance, Precision, and Root Mean Square (RMS) distance are extracted and compared. Among these four automated methods, ABSS generates the most accurate results and the reproducibility is more similar to expert manual outlining by statistical validation. By considering p-value<0.05, the results of performance measurement for ABSS reveal that, Dice is 4%, 13%, and 17% higher, Hausdorff is 23%, 87%, and 70% lower, precision is 5%, -5%, and 12% higher, and RMS is 19%, 62%, and 65% lower compared to LocalInfo, FreeSurfer, and Hammer, respectively. PMID:25571043

The Hissar–Alay and the Pamirs: Deep-Seated Structure, Geodynamic Model, and Experimental Evidence

NASA Astrophysics Data System (ADS)

Leonov, M. G.; Rybin, A. K.; Batalev, V. Yu.; Matyukov, V. E.; Shchelochkov, G. G.

2018-03-01

The structural and geodynamic features of the Pamirs and the Hissar-Alay have been revealed based on geological and geophysical evidence supplemented by experimental data. It has been shown that both the Pamirs and the Hissar-Alay are geodynamic systems, the formation of which is related to interference of two geodynamic regimes: (i) global orogeny covering extensive territories of Eurasia and determining their similarity and (ii) regional regimes differing for the Pamirs and the Alay, which act independently within Central Asian and Apline-Himalayan mobile belts, respectively. The Pamirs do not act as an indentor during the formation of structure of the Hissar-Alay and areas to the north. It is stated that the Pamir-Alay segment of Asia is a reflection of the geodynamic countermotion setting (3D flow of mountain masses) of several distinct segments of the continental lithosphere, while the Pamirs are an intracontinental subduction domain at the surface, which represents a special tectonic-geodynamic type of structures.

Numerical reconstruction of Late-Cenosoic evolution of normal-fault scarps in Baikal Rift Zone

NASA Astrophysics Data System (ADS)

Byzov, Leonid; San'kov, Vladimir

2014-05-01

Numerical landscape development modeling has recently become a popular tool in geo-logic and geomorphic investigations. We employed this technique to reconstruct Late-Cenosoic evolution of Baikal Rift Zone mountains. The objects of research were Barguzin Range and Svyatoy Nos Upland. These structures are formed under conditions of crustal extension and bounded by active normal faults. In our experiments we used instruments, engineered by Greg Tucker (University of Colo-rado) - CHILD (Channel-Hillslope Integrated Landscape Development) and 'Bedrock Fault Scarp'. First program allowed constructing the complex landscape model considering tectonic uplift, fluvial and hillslope processes; second program is used for more accurate simulating of triangular facet evolution. In general, our experiments consisted in testing of tectonic parameters, and climatic char-acteristic, erosion and diffusion properties, hydraulic geometry were practically constant except for some special runs. Numerous experiments, with various scenarios of development, showed that Barguzin range and Svyatoy Nos Upland has many common features. These structures characterized by internal differentiation, which appear in height and shape of slopes. At the same time, individual segments of these objects are very similar - this conclusion refers to most developing parts, with pronounced facets and V-shaped valleys. Accordingly modelling, these landscapes are in a steady state and are undergoing a uplift with rate 0,4 mm/yr since Early Pliocene (this solution accords with AFT-dating). Lower segments of Barguzin Range and Svyatoy Nos Upland also have some general fea-tures, but the reasons of such similarity probably are different. In particular, southern segment of Svyatoy Nos Upland, which characterized by relative high slope with very weak incision, may be formed as result very rapid fault movement or catastrophic landslide. On the other hand, a lower segment of Barguzin Range (Ulun segment, for example) probably has small height and relative weak incision over later beginning of uplift.

Crypto-rhombomeres of the mouse medulla oblongata, defined by molecular and morphological features.

PubMed

Tomás-Roca, Laura; Corral-San-Miguel, Rubén; Aroca, Pilar; Puelles, Luis; Marín, Faustino

2016-03-01

The medulla oblongata is the caudal portion of the vertebrate hindbrain. It contains major ascending and descending fiber tracts as well as several motor and interneuron populations, including neural centers that regulate the visceral functions and the maintenance of bodily homeostasis. In the avian embryo, it has been proposed that the primordium of this region is subdivided into five segments or crypto-rhombomeres (r7-r11), which were defined according to either their parameric position relative to intersomitic boundaries (Cambronero and Puelles, in J Comp Neurol 427:522-545, 2000) or a stepped expression of Hox genes (Marín et al., in Dev Biol 323:230-247, 2008). In the present work, we examine the implied similar segmental organization of the mouse medulla oblongata. To this end, we analyze the expression pattern of Hox genes from groups 3 to 8, comparing them to the expression of given cytoarchitectonic and molecular markers, from mid-gestational to perinatal stages. As a result of this approach, we conclude that the mouse medulla oblongata is segmentally organized, similarly as in avian embryos. Longitudinal structures such as the nucleus of the solitary tract, the dorsal vagal motor nucleus, the hypoglossal motor nucleus, the descending trigeminal and vestibular columns, or the reticular formation appear subdivided into discrete segmental units. Additionally, our analysis identified an internal molecular organization of the migrated pontine nuclei that reflects a differential segmental origin of their neurons as assessed by Hox gene expression.

Clones from a shooty tobacco crown gall tumor I: deletions, rearrangements and amplifications resulting in irregular T-DNA structures and organizations.

PubMed

Peerbolte, R; Leenhouts, K; Hooykaas-van Slogteren, G M; Hoge, J H; Wullems, G J; Schilperoort, R A

1986-07-01

Transformed clones from a shooty tobacco crown gall tumor, induced byAgrobacterium tumefaciens strain LBA1501, having a Tn1831 insertion in the auxin locus, were investigated for their T-DNA structure and expression. In addition to clones with the expected phenotype, i.e. phytohormone autonomy, regeneration of non-rooting shoots and octopine synthesis (Aut(+)Reg(+)Ocs(+) 'type I' clones), clones were obtained with an aberrant phenotype. Among these were the Aut(-)Reg(-)Ocs(+) 'type II' clones. Two shooty type I clones and three type II callus clones (all randomly chosen) as well as a rooting shoot regenerated from a type II clone via a high kinetin treatment, all had a T-DNA structure which differed significantly from 'regular' T-DNA structures. No Tn1831 DNA sequences were detected in these clones. The two type I clones were identical: they both contained the same highly truncated T-DNA segments. One TL-DNA segment of approximately 0.7 kb, originating form the left part of the TL-region, was present at one copy per diploid tobacco genome. Another segment with a maximum size of about 7 kb was derived from the right hand part of the TL-region and was present at minimally two copies. Three copies of a truncated TR-DNA segment were detected, probably starting at the right TR-DNA border repeat and ending halfway the regular TR-region. Indications have been obtained that at least some of the T-DNA segments are closely linked, sometimes via intervening plant DNA sequences. The type I clones harbored TL-DNA transcripts 4, 6a/b and 3 as well as TR-DNA transcript 0'. The type II clones harbored three to six highly truncated T-DNA segments, originating from the right part of the TL-region. In addition they had TR-DNA segments, similar to those of the type I clones. On Northern blots TR-DNA transcripts 0' and 1' were detected as well as the TL-DNA transcripts 3 and 6a/b and an 1800 bp hybrid transcript (tr.Y) containing gene 6b sequences. Possible origins of the observed irregularities in T-DNA structures are discussed in relation to fidelity of transformation of plant cells viaAgrobacterium.

Myocardial Rupture in Acute Myocardial Infarction: Mechanistic Explanation Based on the Ventricular Myocardial Band Hypothesis.

PubMed

Vargas-Barron, Jesús; Antunez-Montes, Omar-Yassef; Roldán, Francisco-Javier; Aranda-Frausto, Alberto; González-Pacheco, Hector; Romero-Cardenas, Ángel; Zabalgoitia, Miguel

2015-01-01

Torrent-Guasp explains the structure of the ventricular myocardium by means of a helical muscular band. Our primary purpose was to demonstrate the utility of echocardiography in human and porcine hearts in identifying the segments of the myocardial band. The second purpose was to evaluate the relation of the topographic distribution of the myocardial band with some post-myocardial infarction ruptures. Five porcine and one human heart without cardiopathy were dissected and the ventricular myocardial segments were color-coded for illustration and reconstruction purposes. These segments were then correlated to the conventional echocardiographic images. Afterwards in three cases with post-myocardial infarction rupture, a correlation of the topographic location of the rupture with the distribution of the ventricular band was made. The human ventricular band does not show any differences from the porcine band, which confirms the similarities of the four segments; these segments could be identified by echocardiography. In three cases with myocardial rupture, a correlation of the intra-myocardial dissection with the distribution of the ventricular band was observed. Echocardiography is helpful in identifying the myocardial band segments as well as the correlation with the topographic distribution of some myocardial post-infarction ruptures.

a Super Voxel-Based Riemannian Graph for Multi Scale Segmentation of LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Li, Minglei

2018-04-01

Automatically segmenting LiDAR points into respective independent partitions has become a topic of great importance in photogrammetry, remote sensing and computer vision. In this paper, we cast the problem of point cloud segmentation as a graph optimization problem by constructing a Riemannian graph. The scale space of the observed scene is explored by an octree-based over-segmentation with different depths. The over-segmentation produces many super voxels which restrict the structure of the scene and will be used as nodes of the graph. The Kruskal coordinates are used to compute edge weights that are proportional to the geodesic distance between nodes. Then we compute the edge-weight matrix in which the elements reflect the sectional curvatures associated with the geodesic paths between super voxel nodes on the scene surface. The final segmentation results are generated by clustering similar super voxels and cutting off the weak edges in the graph. The performance of this method was evaluated on LiDAR point clouds for both indoor and outdoor scenes. Additionally, extensive comparisons to state of the art techniques show that our algorithm outperforms on many metrics.

Automatic cerebrospinal fluid segmentation in non-contrast CT images using a 3D convolutional network

NASA Astrophysics Data System (ADS)

Patel, Ajay; van de Leemput, Sil C.; Prokop, Mathias; van Ginneken, Bram; Manniesing, Rashindra

2017-03-01

Segmentation of anatomical structures is fundamental in the development of computer aided diagnosis systems for cerebral pathologies. Manual annotations are laborious, time consuming and subject to human error and observer variability. Accurate quantification of cerebrospinal fluid (CSF) can be employed as a morphometric measure for diagnosis and patient outcome prediction. However, segmenting CSF in non-contrast CT images is complicated by low soft tissue contrast and image noise. In this paper we propose a state-of-the-art method using a multi-scale three-dimensional (3D) fully convolutional neural network (CNN) to automatically segment all CSF within the cranial cavity. The method is trained on a small dataset comprised of four manually annotated cerebral CT images. Quantitative evaluation of a separate test dataset of four images shows a mean Dice similarity coefficient of 0.87 +/- 0.01 and mean absolute volume difference of 4.77 +/- 2.70 %. The average prediction time was 68 seconds. Our method allows for fast and fully automated 3D segmentation of cerebral CSF in non-contrast CT, and shows promising results despite a limited amount of training data.

Three validation metrics for automated probabilistic image segmentation of brain tumours

PubMed Central

Zou, Kelly H.; Wells, William M.; Kikinis, Ron; Warfield, Simon K.

2005-01-01

SUMMARY The validity of brain tumour segmentation is an important issue in image processing because it has a direct impact on surgical planning. We examined the segmentation accuracy based on three two-sample validation metrics against the estimated composite latent gold standard, which was derived from several experts’ manual segmentations by an EM algorithm. The distribution functions of the tumour and control pixel data were parametrically assumed to be a mixture of two beta distributions with different shape parameters. We estimated the corresponding receiver operating characteristic curve, Dice similarity coefficient, and mutual information, over all possible decision thresholds. Based on each validation metric, an optimal threshold was then computed via maximization. We illustrated these methods on MR imaging data from nine brain tumour cases of three different tumour types, each consisting of a large number of pixels. The automated segmentation yielded satisfactory accuracy with varied optimal thresholds. The performances of these validation metrics were also investigated via Monte Carlo simulation. Extensions of incorporating spatial correlation structures using a Markov random field model were considered. PMID:15083482

An improved FSL-FIRST pipeline for subcortical gray matter segmentation to study abnormal brain anatomy using quantitative susceptibility mapping (QSM).

PubMed

Feng, Xiang; Deistung, Andreas; Dwyer, Michael G; Hagemeier, Jesper; Polak, Paul; Lebenberg, Jessica; Frouin, Frédérique; Zivadinov, Robert; Reichenbach, Jürgen R; Schweser, Ferdinand

2017-06-01

Accurate and robust segmentation of subcortical gray matter (SGM) nuclei is required in many neuroimaging applications. FMRIB's Integrated Registration and Segmentation Tool (FIRST) is one of the most popular software tools for automated subcortical segmentation based on T 1 -weighted (T1w) images. In this work, we demonstrate that FIRST tends to produce inaccurate SGM segmentation results in the case of abnormal brain anatomy, such as present in atrophied brains, due to a poor spatial match of the subcortical structures with the training data in the MNI space as well as due to insufficient contrast of SGM structures on T1w images. Consequently, such deviations from the average brain anatomy may introduce analysis bias in clinical studies, which may not always be obvious and potentially remain unidentified. To improve the segmentation of subcortical nuclei, we propose to use FIRST in combination with a special Hybrid image Contrast (HC) and Non-Linear (nl) registration module (HC-nlFIRST), where the hybrid image contrast is derived from T1w images and magnetic susceptibility maps to create subcortical contrast that is similar to that in the Montreal Neurological Institute (MNI) template. In our approach, a nonlinear registration replaces FIRST's default linear registration, yielding a more accurate alignment of the input data to the MNI template. We evaluated our method on 82 subjects with particularly abnormal brain anatomy, selected from a database of >2000 clinical cases. Qualitative and quantitative analyses revealed that HC-nlFIRST provides improved segmentation compared to the default FIRST method. Copyright © 2017 Elsevier Inc. All rights reserved.

Pharmacological and histological examinations of regional differences of guinea-pig lung: a role of pleural surface smooth muscle in lung strip contraction.

PubMed Central

Wong, W. S.; Bloomquist, S. L.; Bendele, A. M.; Fleisch, J. H.

1992-01-01

1. Parenchymal lung strip preparations have been widely used as an in vitro model of peripheral airway smooth muscle. The present study examined functional responses of 4 consecutive guinea-pig lung parenchymal strips isolated from the central region (segment 1) to the distal edge (segment 4) of the lower lung lobe. The middle two segments were designated as segments 2 and 3. 2. Lung segments 1 and 4 exhibited significantly greater contraction than the other 2 segments to KCl when responses were expressed as mg force per mg tissue weight. Contractile responses to bronchospastic agents including histamine, carbachol, endothelin-1, leukotrienes (LT) B4 and D4, and the thromboxane A2-mimetic U46619 demonstrated no significant difference in EC50 values among the 4 lung segments. 3. Contractile responses of segments 1 and 4 to antigen-challenge (ovalbumin), ionophore A23187 and substance P were significantly greater than the other 2 segments with respect to either sensitivity or maximum responsiveness. 4. U46619-induced contractions of the 4 lung segments were relaxed in similar manner by papaverine and theophylline up to 100%, salbutamol up to 80%, and sodium nitroprusside by only 20%. In contrast, sodium nitroprusside markedly reversed U46619-induced contraction of pulmonary arterial rings and bronchial rings. 5. Histological studies identified 2-4 layers of smooth muscle cells underlying the lung pleural surface. Mast cells were prominent in this area. Moreover, morphometric studies showed that segment 4 possessed the least amount of smooth muscle structures from bronchial/bronchiolar wall and vasculatures as compared to the other 3 segments, and a significant difference in this respect was evident between segment 1 and segment 4.(ABSTRACT TRUNCATED AT 250 WORDS) Images Figure 1 Figure 6 PMID:1378341

An approach to analyze the breast tissues in infrared images using nonlinear adaptive level sets and Riesz transform features.

PubMed

Prabha, S; Suganthi, S S; Sujatha, C M

2015-01-01

Breast thermography is a potential imaging method for the early detection of breast cancer. The pathological conditions can be determined by measuring temperature variations in the abnormal breast regions. Accurate delineation of breast tissues is reported as a challenging task due to inherent limitations of infrared images such as low contrast, low signal to noise ratio and absence of clear edges. Segmentation technique is attempted to delineate the breast tissues by detecting proper lower breast boundaries and inframammary folds. Characteristic features are extracted to analyze the asymmetrical thermal variations in normal and abnormal breast tissues. An automated analysis of thermal variations of breast tissues is attempted using nonlinear adaptive level sets and Riesz transform. Breast thermal images are initially subjected to Stein's unbiased risk estimate based orthonormal wavelet denoising. These denoised images are enhanced using contrast-limited adaptive histogram equalization method. The breast tissues are then segmented using non-linear adaptive level set method. The phase map of enhanced image is integrated into the level set framework for final boundary estimation. The segmented results are validated against the corresponding ground truth images using overlap and regional similarity metrics. The segmented images are further processed with Riesz transform and structural texture features are derived from the transformed coefficients to analyze pathological conditions of breast tissues. Results show that the estimated average signal to noise ratio of denoised images and average sharpness of enhanced images are improved by 38% and 6% respectively. The interscale consideration adopted in the denoising algorithm is able to improve signal to noise ratio by preserving edges. The proposed segmentation framework could delineate the breast tissues with high degree of correlation (97%) between the segmented and ground truth areas. Also, the average segmentation accuracy and sensitivity are found to be 98%. Similarly, the maximum regional overlap between segmented and ground truth images obtained using volume similarity measure is observed to be 99%. Directionality as a feature, showed a considerable difference between normal and abnormal tissues which is found to be 11%. The proposed framework for breast thermal image analysis that is aided with necessary preprocessing is found to be useful in assisting the early diagnosis of breast abnormalities.

Structural setting and kinematics of Nubian fault system, SE Western Desert, Egypt: An example of multi-reactivated intraplate strike-slip faults

NASA Astrophysics Data System (ADS)

Sakran, Shawky; Said, Said Mohamed

2018-02-01

Detailed surface geological mapping and subsurface seismic interpretation have been integrated to unravel the structural style and kinematic history of the Nubian Fault System (NFS). The NFS consists of several E-W Principal Deformation Zones (PDZs) (e.g. Kalabsha fault). Each PDZ is defined by spectacular E-W, WNW and ENE dextral strike-slip faults, NNE sinistral strike-slip faults, NE to ENE folds, and NNW normal faults. Each fault zone has typical self-similar strike-slip architecture comprising multi-scale fault segments. Several multi-scale uplifts and basins were developed at the step-over zones between parallel strike-slip fault segments as a result of local extension or contraction. The NNE faults consist of right-stepping sinistral strike-slip fault segments (e.g. Sin El Kiddab fault). The NNE sinistral faults extend for long distances ranging from 30 to 100 kms and cut one or two E-W PDZs. Two nearly perpendicular strike-slip tectonic regimes are recognized in the NFS; an inactive E-W Late Cretaceous - Early Cenozoic dextral transpression and an active NNE sinistral shear.

Atlas-based automatic segmentation of head and neck organs at risk and nodal target volumes: a clinical validation.

PubMed

Daisne, Jean-François; Blumhofer, Andreas

2013-06-26

Intensity modulated radiotherapy for head and neck cancer necessitates accurate definition of organs at risk (OAR) and clinical target volumes (CTV). This crucial step is time consuming and prone to inter- and intra-observer variations. Automatic segmentation by atlas deformable registration may help to reduce time and variations. We aim to test a new commercial atlas algorithm for automatic segmentation of OAR and CTV in both ideal and clinical conditions. The updated Brainlab automatic head and neck atlas segmentation was tested on 20 patients: 10 cN0-stages (ideal population) and 10 unselected N-stages (clinical population). Following manual delineation of OAR and CTV, automatic segmentation of the same set of structures was performed and afterwards manually corrected. Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Maximal Surface Distance (MSD) were calculated for "manual to automatic" and "manual to corrected" volumes comparisons. In both groups, automatic segmentation saved about 40% of the corresponding manual segmentation time. This effect was more pronounced for OAR than for CTV. The edition of the automatically obtained contours significantly improved DSC, ASD and MSD. Large distortions of normal anatomy or lack of iodine contrast were the limiting factors. The updated Brainlab atlas-based automatic segmentation tool for head and neck Cancer patients is timesaving but still necessitates review and corrections by an expert.

A Fast Method for the Segmentation of Synaptic Junctions and Mitochondria in Serial Electron Microscopic Images of the Brain.

PubMed

Márquez Neila, Pablo; Baumela, Luis; González-Soriano, Juncal; Rodríguez, Jose-Rodrigo; DeFelipe, Javier; Merchán-Pérez, Ángel

2016-04-01

Recent electron microscopy (EM) imaging techniques permit the automatic acquisition of a large number of serial sections from brain samples. Manual segmentation of these images is tedious, time-consuming and requires a high degree of user expertise. Therefore, there is considerable interest in developing automatic segmentation methods. However, currently available methods are computationally demanding in terms of computer time and memory usage, and to work properly many of them require image stacks to be isotropic, that is, voxels must have the same size in the X, Y and Z axes. We present a method that works with anisotropic voxels and that is computationally efficient allowing the segmentation of large image stacks. Our approach involves anisotropy-aware regularization via conditional random field inference and surface smoothing techniques to improve the segmentation and visualization. We have focused on the segmentation of mitochondria and synaptic junctions in EM stacks from the cerebral cortex, and have compared the results to those obtained by other methods. Our method is faster than other methods with similar segmentation results. Our image regularization procedure introduces high-level knowledge about the structure of labels. We have also reduced memory requirements with the introduction of energy optimization in overlapping partitions, which permits the regularization of very large image stacks. Finally, the surface smoothing step improves the appearance of three-dimensional renderings of the segmented volumes.

Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer

NASA Astrophysics Data System (ADS)

Luiza Bondar, M.; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

2013-08-01

For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer.

PubMed

Bondar, M Luiza; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

2013-08-07

For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

Rosacea assessment by erythema index and principal component analysis segmentation maps

NASA Astrophysics Data System (ADS)

Kuzmina, Ilona; Rubins, Uldis; Saknite, Inga; Spigulis, Janis

2017-12-01

RGB images of rosacea were analyzed using segmentation maps of principal component analysis (PCA) and erythema index (EI). Areas of segmented clusters were compared to Clinician's Erythema Assessment (CEA) values given by two dermatologists. The results show that visible blood vessels are segmented more precisely on maps of the erythema index and the third principal component (PC3). In many cases, a distribution of clusters on EI and PC3 maps are very similar. Mean values of clusters' areas on these maps show a decrease of the area of blood vessels and erythema and an increase of lighter skin area after the therapy for the patients with diagnosis CEA = 2 on the first visit and CEA=1 on the second visit. This study shows that EI and PC3 maps are more useful than the maps of the first (PC1) and second (PC2) principal components for indicating vascular structures and erythema on the skin of rosacea patients and therapy monitoring.

Automated segmentation of thyroid gland on CT images with multi-atlas label fusion and random classification forest

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Chang, Kevin; Kim, Lauren; Turkbey, Evrim; Lu, Le; Yao, Jianhua; Summers, Ronald

2015-03-01

The thyroid gland plays an important role in clinical practice, especially for radiation therapy treatment planning. For patients with head and neck cancer, radiation therapy requires a precise delineation of the thyroid gland to be spared on the pre-treatment planning CT images to avoid thyroid dysfunction. In the current clinical workflow, the thyroid gland is normally manually delineated by radiologists or radiation oncologists, which is time consuming and error prone. Therefore, a system for automated segmentation of the thyroid is desirable. However, automated segmentation of the thyroid is challenging because the thyroid is inhomogeneous and surrounded by structures that have similar intensities. In this work, the thyroid gland segmentation is initially estimated by multi-atlas label fusion algorithm. The segmentation is refined by supervised statistical learning based voxel labeling with a random forest algorithm. Multiatlas label fusion (MALF) transfers expert-labeled thyroids from atlases to a target image using deformable registration. Errors produced by label transfer are reduced by label fusion that combines the results produced by all atlases into a consensus solution. Then, random forest (RF) employs an ensemble of decision trees that are trained on labeled thyroids to recognize features. The trained forest classifier is then applied to the thyroid estimated from the MALF by voxel scanning to assign the class-conditional probability. Voxels from the expert-labeled thyroids in CT volumes are treated as positive classes; background non-thyroid voxels as negatives. We applied this automated thyroid segmentation system to CT scans of 20 patients. The results showed that the MALF achieved an overall 0.75 Dice Similarity Coefficient (DSC) and the RF classification further improved the DSC to 0.81.

Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.

PubMed

Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

2018-06-01

To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively. Graphical abstract ᅟ.

A Folding Zone in the Ribosomal Exit Tunnel for Kv1.3 Helix Formation

PubMed Central

Tu, LiWei; Deutsch, Carol

2010-01-01

SUMMARY Although it is now clear that protein secondary structure can be acquired early, while the nascent peptide resides within the ribosomal exit tunnel, the principles governing folding of native polytopic proteins have not yet been elucidated. We now report an extensive investigation of native Kv1.3, a voltage-gated K+ channel, including transmembrane and linker segments synthesized in sequence. These native segments form helices vectorially (N- to C-terminus) only in a permissive vestibule located in the last 20Å of the tunnel. Native linker sequences similarly fold in this vestibule. Finally, secondary structure acquired in the ribosome is retained in the translocon. These findings emerge from accessibility studies of a diversity of native transmembrane and linker sequences and may therefore be applicable to protein biogenesis in general. PMID:20060838

High-precision relocation of induced seismicity in the geothermal system below St. Gallen (Switzerland)

NASA Astrophysics Data System (ADS)

Diehl, Tobias; Kraft, Toni; Eduard, Kissling; Nicholas, Deichmann; Clinton, John; Wiemer, Stefan

2014-05-01

From July to November 2013 a sequence of more than 850 events, of which more than 340 could be located, was triggered in a planned hydrothermal system below the city of St. Gallen in eastern Switzerland. Seismicity initiated on July 14 and the maximum Ml in the sequence was 3.5, comparable in size with the Ml 3.4 event induced by stimulation below Basel in 2006. To improve absolute locations of the sequence, more than 1000 P and S wave arrivals were inverted for hypocenters and 1D velocity structure. Vp of 5.6-5.8 km/s and a Vp/Vs ratio of 1.82-1.9 in the source region indicate a limestone or shale-type composition and a comparison with a lithological model from a 3D seismic model suggests that the seismically active streak (height up to 400 m) is within the Mesozoic layer. To resolve the fine structure of the induced seismicity, we applied waveform cross-correlation and double-difference algorithms. The results image a NE-SW striking lineament, consistent with a left-lateral fault plane derived from first motion polarities and moment tensor inversions. A spatio-temporal analysis of the relocated seismicity shows that, during first acid jobs on July 17, microseismicity propagated towards southwest over the entire future Ml 3.5 rupture plane. The almost vertical focal plane associated with the Ml 3.5 event of July 20 is well imaged by the seismicity. The area of the ruptured fault is approximately 675x400 m. Seismicity images a change in focal depths along strike, which correlates with a kink or bend in the mapped fault system northeast of the Ml 3.5 event. This change might indicate structural differences or a segmentation of the fault. Following the Ml 3.5 event, seismicity propagated along strike to the northeast, in a region without any mapped faults, indicating a continuation of the fault segment. Seismicity on this segment occurred in September and October. A complete rupture of the NE segment would have the potential to produce a magnitude larger than 3.0. Similarity of waveforms suggests that an Ml 3.2 in 1987 and an Ml 2.2 event in 1993 occurred on a similar structure with a similar slip direction as the Ml 3.5 event. It appears that the fault zone targeted by the geothermal project is not only oriented favourably for rupture relative to the regional stress field, but is also close to failure.

Three-dimensional crystal structure of recombinant murine interferon-beta.

PubMed Central

Senda, T; Shimazu, T; Matsuda, S; Kawano, G; Shimizu, H; Nakamura, K T; Mitsui, Y

1992-01-01

The crystal structure of recombinant murine interferon-beta (IFN-beta) has been solved by the multiple isomorphous replacement method and refined to an R-factor of 20.5% against 2.6 A X-ray diffraction data. The structure shows a variant of the alpha-helix bundle with a new chain-folding topology, which seems to represent a basic structural framework of all the IFN-alpha and IFN-beta molecules belonging to the type I family. Functionally important segments of the polypeptide chain, as implied through numerous gene manipulation studies carried out so far, are spatially clustered indicating the binding site(s) to the receptor(s). Comparison of the present structure with those of other alpha-helical cytokine proteins, including porcine growth hormone, interleukin 2 and interferon gamma, indicated either a topological similarity in chain folding or a similar spatial arrangement of the alpha-helices. Images PMID:1505514

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences.

PubMed

Mizianty, Marcin J; Kurgan, Lukasz

2009-12-13

Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences. The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes. The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at http://biomine.ece.ualberta.ca/MODAS/.

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences

PubMed Central

2009-01-01

Background Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences. Results The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes. Conclusions The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at http://biomine.ece.ualberta.ca/MODAS/. PMID:20003388

Cellular automata segmentation of the boundary between the compacta of vertebral bodies and surrounding structures

NASA Astrophysics Data System (ADS)

Egger, Jan; Nimsky, Christopher

2016-03-01

Due to the aging population, spinal diseases get more and more common nowadays; e.g., lifetime risk of osteoporotic fracture is 40% for white women and 13% for white men in the United States. Thus the numbers of surgical spinal procedures are also increasing with the aging population and precise diagnosis plays a vital role in reducing complication and recurrence of symptoms. Spinal imaging of vertebral column is a tedious process subjected to interpretation errors. In this contribution, we aim to reduce time and error for vertebral interpretation by applying and studying the GrowCut - algorithm for boundary segmentation between vertebral body compacta and surrounding structures. GrowCut is a competitive region growing algorithm using cellular automata. For our study, vertebral T2-weighted Magnetic Resonance Imaging (MRI) scans were first manually outlined by neurosurgeons. Then, the vertebral bodies were segmented in the medical images by a GrowCut-trained physician using the semi-automated GrowCut-algorithm. Afterwards, results of both segmentation processes were compared using the Dice Similarity Coefficient (DSC) and the Hausdorff Distance (HD) which yielded to a DSC of 82.99+/-5.03% and a HD of 18.91+/-7.2 voxel, respectively. In addition, the times have been measured during the manual and the GrowCut segmentations, showing that a GrowCutsegmentation - with an average time of less than six minutes (5.77+/-0.73) - is significantly shorter than a pure manual outlining.

Comparative performance evaluation of automated segmentation methods of hippocampus from magnetic resonance images of temporal lobe epilepsy patients.

PubMed

Hosseini, Mohammad-Parsa; Nazem-Zadeh, Mohammad-Reza; Pompili, Dario; Jafari-Khouzani, Kourosh; Elisevich, Kost; Soltanian-Zadeh, Hamid

2016-01-01

Segmentation of the hippocampus from magnetic resonance (MR) images is a key task in the evaluation of mesial temporal lobe epilepsy (mTLE) patients. Several automated algorithms have been proposed although manual segmentation remains the benchmark. Choosing a reliable algorithm is problematic since structural definition pertaining to multiple edges, missing and fuzzy boundaries, and shape changes varies among mTLE subjects. Lack of statistical references and guidance for quantifying the reliability and reproducibility of automated techniques has further detracted from automated approaches. The purpose of this study was to develop a systematic and statistical approach using a large dataset for the evaluation of automated methods and establish a method that would achieve results better approximating those attained by manual tracing in the epileptogenic hippocampus. A template database of 195 (81 males, 114 females; age range 32-67 yr, mean 49.16 yr) MR images of mTLE patients was used in this study. Hippocampal segmentation was accomplished manually and by two well-known tools (FreeSurfer and hammer) and two previously published methods developed at their institution [Automatic brain structure segmentation (ABSS) and LocalInfo]. To establish which method was better performing for mTLE cases, several voxel-based, distance-based, and volume-based performance metrics were considered. Statistical validations of the results using automated techniques were compared with the results of benchmark manual segmentation. Extracted metrics were analyzed to find the method that provided a more similar result relative to the benchmark. Among the four automated methods, ABSS generated the most accurate results. For this method, the Dice coefficient was 5.13%, 14.10%, and 16.67% higher, Hausdorff was 22.65%, 86.73%, and 69.58% lower, precision was 4.94%, -4.94%, and 12.35% higher, and the root mean square (RMS) was 19.05%, 61.90%, and 65.08% lower than LocalInfo, FreeSurfer, and hammer, respectively. The Bland-Altman similarity analysis revealed a low bias for the ABSS and LocalInfo techniques compared to the others. The ABSS method for automated hippocampal segmentation outperformed other methods, best approximating what could be achieved by manual tracing. This study also shows that four categories of input data can cause automated segmentation methods to fail. They include incomplete studies, artifact, low signal-to-noise ratio, and inhomogeneity. Different scanner platforms and pulse sequences were considered as means by which to improve reliability of the automated methods. Other modifications were specially devised to enhance a particular method assessed in this study.

Comparative performance evaluation of automated segmentation methods of hippocampus from magnetic resonance images of temporal lobe epilepsy patients

PubMed Central

Hosseini, Mohammad-Parsa; Nazem-Zadeh, Mohammad-Reza; Pompili, Dario; Jafari-Khouzani, Kourosh; Elisevich, Kost; Soltanian-Zadeh, Hamid

2016-01-01

Purpose: Segmentation of the hippocampus from magnetic resonance (MR) images is a key task in the evaluation of mesial temporal lobe epilepsy (mTLE) patients. Several automated algorithms have been proposed although manual segmentation remains the benchmark. Choosing a reliable algorithm is problematic since structural definition pertaining to multiple edges, missing and fuzzy boundaries, and shape changes varies among mTLE subjects. Lack of statistical references and guidance for quantifying the reliability and reproducibility of automated techniques has further detracted from automated approaches. The purpose of this study was to develop a systematic and statistical approach using a large dataset for the evaluation of automated methods and establish a method that would achieve results better approximating those attained by manual tracing in the epileptogenic hippocampus. Methods: A template database of 195 (81 males, 114 females; age range 32–67 yr, mean 49.16 yr) MR images of mTLE patients was used in this study. Hippocampal segmentation was accomplished manually and by two well-known tools (FreeSurfer and hammer) and two previously published methods developed at their institution [Automatic brain structure segmentation (ABSS) and LocalInfo]. To establish which method was better performing for mTLE cases, several voxel-based, distance-based, and volume-based performance metrics were considered. Statistical validations of the results using automated techniques were compared with the results of benchmark manual segmentation. Extracted metrics were analyzed to find the method that provided a more similar result relative to the benchmark. Results: Among the four automated methods, ABSS generated the most accurate results. For this method, the Dice coefficient was 5.13%, 14.10%, and 16.67% higher, Hausdorff was 22.65%, 86.73%, and 69.58% lower, precision was 4.94%, −4.94%, and 12.35% higher, and the root mean square (RMS) was 19.05%, 61.90%, and 65.08% lower than LocalInfo, FreeSurfer, and hammer, respectively. The Bland–Altman similarity analysis revealed a low bias for the ABSS and LocalInfo techniques compared to the others. Conclusions: The ABSS method for automated hippocampal segmentation outperformed other methods, best approximating what could be achieved by manual tracing. This study also shows that four categories of input data can cause automated segmentation methods to fail. They include incomplete studies, artifact, low signal-to-noise ratio, and inhomogeneity. Different scanner platforms and pulse sequences were considered as means by which to improve reliability of the automated methods. Other modifications were specially devised to enhance a particular method assessed in this study. PMID:26745947

Major Variations in HIV-1 Capsid Assembly Morphologies Involve Minor Variations in Molecular Structures of Structurally Ordered Protein Segments*

PubMed Central

Lu, Jun-Xia; Bayro, Marvin J.; Tycko, Robert

2016-01-01

We present the results of solid state nuclear magnetic resonance (NMR) experiments on HIV-1 capsid protein (CA) assemblies with three different morphologies, namely wild-type CA (WT-CA) tubes with 35–60 nm diameters, planar sheets formed by the Arg18-Leu mutant (R18L-CA), and R18L-CA spheres with 20–100 nm diameters. The experiments are intended to elucidate molecular structural variations that underlie these variations in CA assembly morphology. We find that multidimensional solid state NMR spectra of 15N,13C-labeled CA assemblies are remarkably similar for the three morphologies, with only small differences in 15N and 13C chemical shifts, no significant differences in NMR line widths, and few differences in the number of detectable NMR cross-peaks. Thus, the pronounced differences in morphology do not involve major differences in the conformations and identities of structurally ordered protein segments. Instead, morphological variations are attributable to variations in conformational distributions within disordered segments, which do not contribute to the solid state NMR spectra. Variations in solid state NMR signals from certain amino acid side chains are also observed, suggesting differences in the intermolecular dimerization interface between curved and planar CA lattices, as well as possible differences in intramolecular helix-helix packing. PMID:27129282

Metric Learning for Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Characterization of basin concrete in support of structural integrity demonstration for extended storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duncan, A.

Concrete core samples from C basin were characterized through material testing and analysis to verify the design inputs for structural analysis of the L Basin and to evaluate the type and extent of changes in the material condition of the concrete under extended service for fuel storage. To avoid the impact on operations, core samples were not collected from L area, but rather, several concrete core samples were taken from the C Basin prior to its closure. C basin was selected due to its similar environmental exposure and service history compared to L Basin. The microstructure and chemical composition ofmore » the concrete exposed to the water was profiled from the water surface into the wall to evaluate the impact and extent of exposure. No significant leaching of concrete components was observed. Ingress of carbonation or deleterious species was determined to be insignificant. No evidence of alkali-silica reactions (ASR) was observed. Ettringite was observed to form throughout the structure (in air voids or pores); however, the sulfur content was measured to be consistent with the initial concrete that was used to construct the facility. Similar ettringite trends were observed in the interior segments of the core samples. The compressive strength of the concrete at the mid-wall of the basin was measured, and similar microstructural analysis was conducted on these materials post compression testing. The microstructure was determined to be similar to near-surface segments of the core samples. The average strength was 4148 psi, which is well-above the design strength of 2500 psi. The analyses showed that phase alterations and minor cracking in a microstructure did not affect the design specification for the concrete.« less

SU-E-J-129: Atlas Development for Cardiac Automatic Contouring Using Multi-Atlas Segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, R; Yang, J; Pan, T

Purpose: To develop a set of atlases for automatic contouring of cardiac structures to determine heart radiation dose and the associated toxicity. Methods: Six thoracic cancer patients with both contrast and non-contrast CT images were acquired for this study. Eight radiation oncologists manually and independently delineated cardiac contours on the non-contrast CT by referring to the fused contrast CT and following the RTOG 1106 atlas contouring guideline. Fifteen regions of interest (ROIs) were delineated, including heart, four chambers, four coronary arteries, pulmonary artery and vein, inferior and superior vena cava, and ascending and descending aorta. Individual expert contours were fusedmore » using the simultaneous truth and performance level estimation (STAPLE) algorithm for each ROI and each patient. The fused contours became atlases for an in-house multi-atlas segmentation. Using leave-one-out test, we generated auto-segmented contours for each ROI and each patient. The auto-segmented contours were compared with the fused contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Results: Inter-observer variability was not obvious for heart, chambers, and aorta but was large for other structures that were not clearly distinguishable on CT image. The average DSC between individual expert contours and the fused contours were less than 50% for coronary arteries and pulmonary vein, and the average MSD were greater than 4.0 mm. The largest MSD of expert contours deviating from the fused contours was 2.5 cm. The mean DSC and MSD of auto-segmented contours were within one standard deviation of expert contouring variability except the right coronary artery. The coronary arteries, vena cava, and pulmonary vein had DSC<70% and MSD>3.0 mm. Conclusion: A set of cardiac atlases was created for cardiac automatic contouring, the accuracy of which was comparable to the variability in expert contouring. However, substantial modification may need for auto-segmented contours of indistinguishable small structures.« less

The Uses of Student Market Segmentation Techniques in College Recruitment. AIR Forum Paper 1978.

ERIC Educational Resources Information Center

Spiro, Louis M.

Student market segmentation separates prospective college students into subgroups with similar characteristics, the most commonly used being geography, demography, attitudes, and behavior. Recruitment efforts can then focus on student segments similar to the present student body or on other students that might be attracted. The goal is to make…

Mexican Infrared-Optical New Technology Telescope: The TIM project

NASA Astrophysics Data System (ADS)

Salas, L.

1998-11-01

The scientific goals for TIM are an image quality of 0.25", consistent with the seeing at our site, optimization for the infrared as many scientific programs are going in that region of the spectrum, a M1 diameter in excess of 6.5 meters and a field of view limited to 10 arc minutes. Practical reasons, such as the limited funding available and the requirement of mexican financial agencies that the telescope should be built and installed in Mexico, lead us to decide for a segmented telescope, with a single secondary mirror, a single cassegrain focus and a light high stifness tubular structure. ALthough we are still working on the conceptual design of the telescope, there are some concepts that we are pursuing. The optical desing (M1+M2) is Ritchey-Cretien type with an hyperbolic primary 7.8 m od F/1.5 and a 0.9 m diameter f/15 secondary mirror. This will give a plate scale of 1.7 "/mm. This is 0.03 "/pix in direct mode, enough for AO goals. As for direct imaging, a factor of 5 reduction with 20 cm diam optical components would be able to produce 5' fields on a 2048, 20 microns type detector with 0.17"/pix. This implies that, with the use of auxiliary optics which is a common need for each particular instrument anyway, a wide variety of needs can be accomodated with a single secondary mirror. Choping for infrared observations would however introduce a additional cost in the secondary mirror. Alternatively the use of cold tertiary choping mirror is currently under study. The M1+M2 design currently aquires d80 of 0.17" in a 5' field without correction and 1" in a 10' field, that would require a field correcting lens. The M1 mirror will be segmented into 19 1.8 m diameter segments. There are 4 kinds of segments, the central, which we have kept to provide a reference for phasing, 6 more segments for the first ring and 12 in the outer ring, of two different kinds. The spacing between the segments is 5 mm, enough to reduce the inter-segment thermal background to half a percent of a 99\\% reflectivity primary mirror. The width of the segments was decided to be 7.5 cm, similar to keck's, noting also that the self weight deflections of this segment are sligthly inferior (more rigid) than the NTT mirror as defined by Willson et al. Due to this increased rigidity, and to a more homogeneous distribution, while the NTT mirror is supported in 78 points, the Keck segments are supported by 36. We have decreased this number of support points to 19 in our design, but using extended actuators (airbags) that distribute the support force and that together support most of the area of the segment. The current design allows also the inclusion of wind buffeting actuators, and position actuators at the edges of each segment. Position control of each segment is accomplished by electromechanical and piezo actuators, that thanks to the force actuators, only have to act on a reduced portion of the weigth of each segment. The hard points can be located at the edge of the segment and provide common reference for neighboor segments as well. The telescope structure is being designed by finite element analysis. It is an alt-az mount with cassegrain focus instruments only. The structure is being designed as a high stiffnes, low weigth tubular structure. The upper tube is a two tier design with eigen-frequencies larger than 12.9 Htz. The elevation ring is also being designed as a tubular structure obtaining so far eigen-frecuencies of 12.6. In the combined structure the first eigenfrequency goes down to 8 Hz, but it is a rigid rotation about the elevation axis, and so it is not structural. The second eigenfrequency is a bending of the secondary structure at 8.5 hz, and other designs of the secondary vanes are being sttudied to increment this frequency. The third eigenfrequency is the first real eigen-frequency of the structure and occurs at 13hz. Maximum deflections by gravity are 2.2 mm for the telescope tube at horizon while at zenith its only of 0.7mm. The total weigth of the structure, optics and a few instruments is expected to be around 80 tons. More information can be obtained at our web site: http://hussongs.astrosen.unam.mx/~tim/

Raman Spectroscopy Adds Complementary Detail to the High-Resolution X-Ray Crystal Structure of Photosynthetic PsbP from Spinacia oleracea

PubMed Central

Lapkouski, Mikalai; Hofbauerova, Katerina; Sovova, Zofie; Ettrichova, Olga; González-Pérez, Sergio; Dulebo, Alexander; Kaftan, David; Kuta Smatanova, Ivana; Revuelta, Jose L.; Arellano, Juan B.; Carey, Jannette; Ettrich, Rüdiger

2012-01-01

Raman microscopy permits structural analysis of protein crystals in situ in hanging drops, allowing for comparison with Raman measurements in solution. Nevertheless, the two methods sometimes reveal subtle differences in structure that are often ascribed to the water layer surrounding the protein. The novel method of drop-coating deposition Raman spectropscopy (DCDR) exploits an intermediate phase that, although nominally “dry,” has been shown to preserve protein structural features present in solution. The potential of this new approach to bridge the structural gap between proteins in solution and in crystals is explored here with extrinsic protein PsbP of photosystem II from Spinacia oleracea. In the high-resolution (1.98 Å) x-ray crystal structure of PsbP reported here, several segments of the protein chain are present but unresolved. Analysis of the three kinds of Raman spectra of PsbP suggests that most of the subtle differences can indeed be attributed to the water envelope, which is shown here to have a similar Raman intensity in glassy and crystal states. Using molecular dynamics simulations cross-validated by Raman solution data, two unresolved segments of the PsbP crystal structure were modeled as loops, and the amino terminus was inferred to contain an additional beta segment. The complete PsbP structure was compared with that of the PsbP-like protein CyanoP, which plays a more peripheral role in photosystem II function. The comparison suggests possible interaction surfaces of PsbP with higher-plant photosystem II. This work provides the first complete structural picture of this key protein, and it represents the first systematic comparison of Raman data from solution, glassy, and crystalline states of a protein. PMID:23071614

Shape regularized active contour based on dynamic programming for anatomical structure segmentation

NASA Astrophysics Data System (ADS)

Yu, Tianli; Luo, Jiebo; Singhal, Amit; Ahuja, Narendra

2005-04-01

We present a method to incorporate nonlinear shape prior constraints into segmenting different anatomical structures in medical images. Kernel space density estimation (KSDE) is used to derive the nonlinear shape statistics and enable building a single model for a class of objects with nonlinearly varying shapes. The object contour is coerced by image-based energy into the correct shape sub-distribution (e.g., left or right lung), without the need for model selection. In contrast to an earlier algorithm that uses a local gradient-descent search (susceptible to local minima), we propose an algorithm that iterates between dynamic programming (DP) and shape regularization. DP is capable of finding an optimal contour in the search space that maximizes a cost function related to the difference between the interior and exterior of the object. To enforce the nonlinear shape prior, we propose two shape regularization methods, global and local regularization. Global regularization is applied after each DP search to move the entire shape vector in the shape space in a gradient descent fashion to the position of probable shapes learned from training. The regularized shape is used as the starting shape for the next iteration. Local regularization is accomplished through modifying the search space of the DP. The modified search space only allows a certain amount of deformation of the local shape from the starting shape. Both regularization methods ensure the consistency between the resulted shape with the training shapes, while still preserving DP"s ability to search over a large range and avoid local minima. Our algorithm was applied to two different segmentation tasks for radiographic images: lung field and clavicle segmentation. Both applications have shown that our method is effective and versatile in segmenting various anatomical structures under prior shape constraints; and it is robust to noise and local minima caused by clutter (e.g., blood vessels) and other similar structures (e.g., ribs). We believe that the proposed algorithm represents a major step in the paradigm shift to object segmentation under nonlinear shape constraints.

Cerebella segmentation on MR images of pediatric patients with medulloblastoma

NASA Astrophysics Data System (ADS)

Shan, Zu Y.; Ji, Qing; Glass, John; Gajjar, Amar; Reddick, Wilburn E.

2005-04-01

In this study, an automated method has been developed to identify the cerebellum from T1-weighted MR brain images of patients with medulloblastoma. A new objective function that is similar to Gibbs free energy in classic physics was defined; and the brain structure delineation was viewed as a process of minimizing Gibbs free energy. We used a rigid-body registration and an active contour (snake) method to minimize the Gibbs free energy in this study. The method was applied to 20 patient data sets to generate cerebellum images and volumetric results. The generated cerebellum images were compared with two manually drawn results. Strong correlations were found between the automatically and manually generated volumetric results, the correlation coefficients with each of manual results were 0.971 and 0.974, respectively. The average Jaccard similarities with each of two manual results were 0.89 and 0.88, respectively. The average Kappa indexes with each of two manual results were 0.94 and 0.93, respectively. These results showed this method was both robust and accurate for cerebellum segmentation. The method may be applied to various research and clinical investigation in which cerebellum segmentation and quantitative MR measurement of cerebellum are needed.

Auto-segmentation of normal and target structures in head and neck CT images: a feature-driven model-based approach.

PubMed

Qazi, Arish A; Pekar, Vladimir; Kim, John; Xie, Jason; Breen, Stephen L; Jaffray, David A

2011-11-01

Intensity modulated radiation therapy (IMRT) allows greater control over dose distribution, which leads to a decrease in radiation related toxicity. IMRT, however, requires precise and accurate delineation of the organs at risk and target volumes. Manual delineation is tedious and suffers from both interobserver and intraobserver variability. State of the art auto-segmentation methods are either atlas-based, model-based or hybrid however, robust fully automated segmentation is often difficult due to the insufficient discriminative information provided by standard medical imaging modalities for certain tissue types. In this paper, the authors present a fully automated hybrid approach which combines deformable registration with the model-based approach to accurately segment normal and target tissues from head and neck CT images. The segmentation process starts by using an average atlas to reliably identify salient landmarks in the patient image. The relationship between these landmarks and the reference dataset serves to guide a deformable registration algorithm, which allows for a close initialization of a set of organ-specific deformable models in the patient image, ensuring their robust adaptation to the boundaries of the structures. Finally, the models are automatically fine adjusted by our boundary refinement approach which attempts to model the uncertainty in model adaptation using a probabilistic mask. This uncertainty is subsequently resolved by voxel classification based on local low-level organ-specific features. To quantitatively evaluate the method, they auto-segment several organs at risk and target tissues from 10 head and neck CT images. They compare the segmentations to the manual delineations outlined by the expert. The evaluation is carried out by estimating two common quantitative measures on 10 datasets: volume overlap fraction or the Dice similarity coefficient (DSC), and a geometrical metric, the median symmetric Hausdorff distance (HD), which is evaluated slice-wise. They achieve an average overlap of 93% for the mandible, 91% for the brainstem, 83% for the parotids, 83% for the submandibular glands, and 74% for the lymph node levels. Our automated segmentation framework is able to segment anatomy in the head and neck region with high accuracy within a clinically-acceptable segmentation time.

Towards quantitative imaging: stability of fully automated nodule segmentation across varied dose levels and reconstruction parameters in a low-dose CT screening patient cohort

NASA Astrophysics Data System (ADS)

Wahi-Anwar, M. Wasil; Emaminejad, Nastaran; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael F.

2018-02-01

Quantitative imaging in lung cancer CT seeks to characterize nodules through quantitative features, usually from a region of interest delineating the nodule. The segmentation, however, can vary depending on segmentation approach and image quality, which can affect the extracted feature values. In this study, we utilize a fully-automated nodule segmentation method - to avoid reader-influenced inconsistencies - to explore the effects of varied dose levels and reconstruction parameters on segmentation. Raw projection CT images from a low-dose screening patient cohort (N=59) were reconstructed at multiple dose levels (100%, 50%, 25%, 10%), two slice thicknesses (1.0mm, 0.6mm), and a medium kernel. Fully-automated nodule detection and segmentation was then applied, from which 12 nodules were selected. Dice similarity coefficient (DSC) was used to assess the similarity of the segmentation ROIs of the same nodule across different reconstruction and dose conditions. Nodules at 1.0mm slice thickness and dose levels of 25% and 50% resulted in DSC values greater than 0.85 when compared to 100% dose, with lower dose leading to a lower average and wider spread of DSC values. At 0.6mm, the increased bias and wider spread of DSC values from lowering dose were more pronounced. The effects of dose reduction on DSC for CAD-segmented nodules were similar in magnitude to reducing the slice thickness from 1.0mm to 0.6mm. In conclusion, variation of dose and slice thickness can result in very different segmentations because of noise and image quality. However, there exists some stability in segmentation overlap, as even at 1mm, an image with 25% of the lowdose scan still results in segmentations similar to that seen in a full-dose scan.

Image segmentation using joint spatial-intensity-shape features: application to CT lung nodule segmentation

NASA Astrophysics Data System (ADS)

Ye, Xujiong; Siddique, Musib; Douiri, Abdel; Beddoe, Gareth; Slabaugh, Greg

2009-02-01

Automatic segmentation of medical images is a challenging problem due to the complexity and variability of human anatomy, poor contrast of the object being segmented, and noise resulting from the image acquisition process. This paper presents a novel feature-guided method for the segmentation of 3D medical lesions. The proposed algorithm combines 1) a volumetric shape feature (shape index) based on high-order partial derivatives; 2) mean shift clustering in a joint spatial-intensity-shape (JSIS) feature space; and 3) a modified expectation-maximization (MEM) algorithm on the mean shift mode map to merge the neighboring regions (modes). In such a scenario, the volumetric shape feature is integrated into the process of the segmentation algorithm. The joint spatial-intensity-shape features provide rich information for the segmentation of the anatomic structures or lesions (tumors). The proposed method has been evaluated on a clinical dataset of thoracic CT scans that contains 68 nodules. A volume overlap ratio between each segmented nodule and the ground truth annotation is calculated. Using the proposed method, the mean overlap ratio over all the nodules is 0.80. On visual inspection and using a quantitative evaluation, the experimental results demonstrate the potential of the proposed method. It can properly segment a variety of nodules including juxta-vascular and juxta-pleural nodules, which are challenging for conventional methods due to the high similarity of intensities between the nodules and their adjacent tissues. This approach could also be applied to lesion segmentation in other anatomies, such as polyps in the colon.

Improving Brain Magnetic Resonance Image (MRI) Segmentation via a Novel Algorithm based on Genetic and Regional Growth

PubMed Central

A., Javadpour; A., Mohammadi

2016-01-01

Background Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging. Objective This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel algorithm based on genetic and regional growth. Methods Among medical imaging methods, brains MRI segmentation is important due to high contrast of non-intrusive soft tissue and high spatial resolution. Size variations of brain tissues are often accompanied by various diseases such as Alzheimer’s disease. As our knowledge about the relation between various brain diseases and deviation of brain anatomy increases, MRI segmentation is exploited as the first step in early diagnosis. In this paper, regional growth method and auto-mate selection of initial points by genetic algorithm is used to introduce a new method for MRI segmentation. Primary pixels and similarity criterion are automatically by genetic algorithms to maximize the accuracy and validity in image segmentation. Results By using genetic algorithms and defining the fixed function of image segmentation, the initial points for the algorithm were found. The proposed algorithms are applied to the images and results are manually selected by regional growth in which the initial points were compared. The results showed that the proposed algorithm could reduce segmentation error effectively. Conclusion The study concluded that the proposed algorithm could reduce segmentation error effectively and help us to diagnose brain diseases. PMID:27672629

Automated segmentation of the prostate in 3D MR images using a probabilistic atlas and a spatially constrained deformable model.

PubMed

Martin, Sébastien; Troccaz, Jocelyne; Daanenc, Vincent

2010-04-01

The authors present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. The approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a common reference. These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. The segmentation is then realized through a two stage procedure. In the first stage, the processed image is registered to the probabilistic atlas. Subsequently, a probabilistic segmentation is obtained by mapping the probabilistic map of the atlas to the patient's anatomy. In the second stage, a deformable surface evolves toward the prostate boundaries by merging information coming from the probabilistic segmentation, an image feature model and a statistical shape model. During the evolution of the surface, the probabilistic segmentation allows the introduction of a spatial constraint that prevents the deformable surface from leaking in an unlikely configuration. The proposed method is evaluated on 36 exams that were manually segmented by a single expert. A median Dice similarity coefficient of 0.86 and an average surface error of 2.41 mm are achieved. By merging prior knowledge, the presented method achieves a robust and completely automatic segmentation of the prostate in MR images. Results show that the use of a spatial constraint is useful to increase the robustness of the deformable model comparatively to a deformable surface that is only driven by an image appearance model.

Evaluation of Road Performance Based on International Roughness Index and Falling Weight Deflectometer

NASA Astrophysics Data System (ADS)

Hasanuddin; Setyawan, A.; Yulianto, B.

2018-03-01

Assessment to the performance of road pavement is deemed necessary to improve the management quality of road maintenance and rehabilitation. This research to evaluate the road base on functional and structural and recommendations handling done. Assessing the pavement performance is conducted with functional and structural evaluation. Functional evaluation of pavement is based on the value of IRI (International Roughness Index) which among others is derived from reading NAASRA for analysis and recommended road handling. Meanwhile, structural evaluation of pavement is done by analyzing deflection value based on FWD (Falling Weight Deflectometer) data resulting in SN (Structural Number) value. The analysis will result in SN eff (Structural Number Effective) and SN f (Structural Number Future) value obtained from comparing SN eff to SN f value that leads to SCI (Structural Condition Index) value. SCI value implies the possible recommendation for handling pavement. The study done to Simpang Tuan-Batas Kota Jambi road segment was based on functional analysis. The study indicated that the road segment split into 12 segments in which segment 1, 3, 5, 7, 9, and 11 were of regular maintenance, segment 2, 4, 8, 10, 12 belonged to periodic maintenance, and segment 6 was of rehabilitation. The structural analysis resulted in 8 segments consisting of segment 1 and 2 recommended for regular maintenance, segment 3, 4, 5, and 7 for functional overlay, and 6 and 8 were of structural overlay.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez, Jose A.; Ivanova, Magdalena I.; Sawaya, Michael R.

We report that the protein α-synuclein is the main component of Lewy bodies, the neuron-associated aggregates seen in Parkinson disease and other neurodegenerative pathologies. An 11-residue segment, which we term NACore, appears to be responsible for amyloid formation and cytotoxicity of human α-synuclein. Here we describe crystals of NACore that have dimensions smaller than the wavelength of visible light and thus are invisible by optical microscopy. As the crystals are thousands of times too small for structure determination by synchrotron X-ray diffraction, we use micro-electron diffraction to determine the structure at atomic resolution. The 1.4 Å resolution structure demonstrates thatmore » this method can determine previously unknown protein structures and here yields, to our knowledge, the highest resolution achieved by any cryo-electron microscopy method to date. The structure exhibits protofibrils built of pairs of face-to-face β-sheets. X-ray fibre diffraction patterns show the similarity of NACore to toxic fibrils of full-length α-synuclein. Finally, the NACore structure, together with that of a second segment, inspires a model for most of the ordered portion of the toxic, full-length α-synuclein fibril, presenting opportunities for the design of inhibitors of α-synuclein fibrils.« less

Multiple Hypotheses Image Segmentation and Classification With Application to Dietary Assessment

PubMed Central

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

2016-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier’s confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback. PMID:25561457

Multiple hypotheses image segmentation and classification with application to dietary assessment.

PubMed

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J; Delp, Edward J

2015-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier's confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback.

SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, L; Zhou, Z; Wang, J

Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directlymore » connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.« less

Continental Scale Vegetation Structure Mapping Using Field Calibrated Landsat, ALOS Palsar And GLAS ICESat

NASA Astrophysics Data System (ADS)

Scarth, P.; Phinn, S. R.; Armston, J.; Lucas, R.

2015-12-01

Vertical plant profiles are important descriptors of canopy structure and are used to inform models of biomass, biodiversity and fire risk. In Australia, an approach has been developed to produce large area maps of vertical plant profiles by extrapolating waveform lidar estimates of vertical plant profiles from ICESat/GLAS using large area segmentation of ALOS PALSAR and Landsat satellite image products. The main assumption of this approach is that the vegetation height profiles are consistent across the segments defined from ALOS PALSAR and Landsat image products. More than 1500 field sites were used to develop an index of fractional cover using Landsat data. A time series of the green fraction was used to calculate the persistent green fraction continuously across the landscape. This was fused with ALOS PALSAR L-band Fine Beam Dual polarisation 25m data and used to segment the Australian landscapes. K-means clustering then grouped the segments with similar cover and backscatter into approximately 1000 clusters. Where GLAS-ICESat footprints intersected these clusters, canopy profiles were extracted and aggregated to produce a mean vertical vegetation profile for each cluster that was used to derive mean canopy and understorey height, depth and density. Due to the large number of returns, these retrievals are near continuous across the landscape, enabling them to be used for inventory and modelling applications. To validate this product, a radiative transfer model was adapted to map directional gap probability from airborne waveform lidar datasets to retrieve vertical plant profiles Comparison over several test sites show excellent agreement and work is underway to extend the analysis to improve national biomass mapping. The integration of the three datasets provide options for future operational monitoring of structure and AGB across large areas for quantifying carbon dynamics, structural change and biodiversity.

Cone structure in patients with usher syndrome type III and mutations in the Clarin 1 gene.

PubMed

Ratnam, Kavitha; Västinsalo, Hanna; Roorda, Austin; Sankila, Eeva-Marja K; Duncan, Jacque L

2013-01-01

To study macular structure and function in patients with Usher syndrome type III (USH3) caused by mutations in the Clarin 1 gene (CLRN1). High-resolution macular images were obtained by adaptive optics scanning laser ophthalmoscopy and spectral domain optical coherence tomography in 3 patients with USH3 and were compared with those of age-similar control subjects. Vision function measures included best-corrected visual acuity, kinetic and static perimetry, and full-field electroretinography. Coding regions of the CLRN1 gene were sequenced. CLRN1 mutations were present in all the patients; a 20-year-old man showed compound heterozygous mutations (p.N48K and p.S188X), and 2 unrelated women aged 25 and 32 years had homozygous mutations (p.N48K). Best-corrected visual acuity ranged from 20/16 to 20/40, with scotomas beginning at 3° eccentricity. The inner segment-outer segment junction or the inner segment ellipsoid band was disrupted within 1° to 4° of the fovea, and the foveal inner and outer segment layers were significantly thinner than normal. Cones near the fovea in patients 1 and 2 showed normal spacing, and the preserved region ended abruptly. Retinal pigment epithelial cells were visible in patient 3 where cones were lost. Cones were observed centrally but not in regions with scotomas, and retinal pigment epithelial cells were visible in regions without cones in patients with CLRN1 mutations. High-resolution measures of retinal structure demonstrate patterns of cone loss associated with CLRN1 mutations. These findings provide insight into the effect of CLRN1 mutations on macular cone structure, which has implications for the development of treatments for USH3. clinicaltrials.gov Identifier: NCT00254605.

Phonotactics, Neighborhood Activation, and Lexical Access for Spoken Words

PubMed Central

Vitevitch, Michael S.; Luce, Paul A.; Pisoni, David B.; Auer, Edward T.

2012-01-01

Probabilistic phonotactics refers to the relative frequencies of segments and sequences of segments in spoken words. Neighborhood density refers to the number of words that are phonologically similar to a given word. Despite a positive correlation between phonotactic probability and neighborhood density, nonsense words with high probability segments and sequences are responded to more quickly than nonsense words with low probability segments and sequences, whereas real words occurring in dense similarity neighborhoods are responded to more slowly than real words occurring in sparse similarity neighborhoods. This contradiction may be resolved by hypothesizing that effects of probabilistic phonotactics have a sublexical focus and that effects of similarity neighborhood density have a lexical focus. The implications of this hypothesis for models of spoken word recognition are discussed. PMID:10433774

Off- and Along-Axis Slow Spreading Ridge Segment Characters: Insights From 3d Thermal Modeling

NASA Astrophysics Data System (ADS)

Gac, S.; Tisseau, C.; Dyment, J.

2001-12-01

Many observations along the Mid-Atlantic Ridge segments suggest a correlation between surface characters (length, axial morphology) and the thermal state of the segment. Thibaud et al. (1998) classify segments according to their thermal state: "colder" segments shorter than 30 km show a weak magmatic activity, and "hotter" segments as long as 90 km show a robust magmatic activity. The existence of such a correlation suggests that the thermal structure of a slow spreading ridge segment explains most of the surface observations. Here we test the physical coherence of such an integrated thermal model and evaluate it quantitatively. The different kinds of segment would constitute different phases in a segment evolution, the segment evolving progressively from a "colder" to a "hotter" so to a "colder" state. Here we test the consistency of such an evolution scheme. To test these hypotheses we have developed a 3D numerical model for the thermal structure and evolution of a slow spreading ridge segment. The thermal structure is controlled by the geometry and the dimensions of a permanently hot zone, imposed beneath the segment center, where is simulated the adiabatic ascent of magmatic material. To compare the model with the observations several geophysic quantities which depend on the thermal state are simulated: crustal thickness variations along axis, gravity anomalies (reflecting density variations) and earthquake maximum depth (corresponding to the 750° C isotherm depth). The thermal structure of a particular segment is constrained by comparing the simulated quantities to the real ones. Considering realistic magnetization parameters, the magnetic anomalies generated from the same thermal structure and evolution reproduce the observed magnetic anomaly amplitude variations along the segment. The thermal structures accounting for observations are determined for each kind of segment (from "colder" to "hotter"). The evolution of the thermal structure from the "colder" to the "hotter" segments gives credence to a temporal relationship between the different kinds of segment. The resulting thermal evolution model of slow spreading ridge segments may explain the rhomboedric shapes observed off-axis.

Seismicity and plate tectonics in south central Alaska

NASA Technical Reports Server (NTRS)

Van Wormer, J. D.; Davies, J.; Gedney, L.

1974-01-01

Hypocenter distribution shows that the Benioff zone associated with the Aleutian arc terminates in interior Alaska some 75 km north of the Denali fault. There appears to be a break in the subducting Pacific plate in the Yentna River-Prince William Sound area which separates two seismically independent blocks, similar to the segmented structure reported for the central Aleutian arc.

Automatic and manual segmentation of healthy retinas using high-definition optical coherence tomography.

PubMed

Golbaz, Isabelle; Ahlers, Christian; Goesseringer, Nina; Stock, Geraldine; Geitzenauer, Wolfgang; Prünte, Christian; Schmidt-Erfurth, Ursula Margarethe

2011-03-01

This study compared automatic- and manual segmentation modalities in the retina of healthy eyes using high-definition optical coherence tomography (HD-OCT). Twenty retinas in 20 healthy individuals were examined using an HD-OCT system (Carl Zeiss Meditec, Inc.). Three-dimensional imaging was performed with an axial resolution of 6 μm at a maximum scanning speed of 25,000 A-scans/second. Volumes of 6 × 6 × 2 mm were scanned. Scans were analysed using a matlab-based algorithm and a manual segmentation software system (3D-Doctor). The volume values calculated by the two methods were compared. Statistical analysis revealed a high correlation between automatic and manual modes of segmentation. The automatic mode of measuring retinal volume and the corresponding three-dimensional images provided similar results to the manual segmentation procedure. Both methods were able to visualize retinal and subretinal features accurately. This study compared two methods of assessing retinal volume using HD-OCT scans in healthy retinas. Both methods were able to provide realistic volumetric data when applied to raster scan sets. Manual segmentation methods represent an adequate tool with which to control automated processes and to identify clinically relevant structures, whereas automatic procedures will be needed to obtain data in larger patient populations. © 2009 The Authors. Journal compilation © 2009 Acta Ophthalmol.

Identification and experimental validation of damping ratios of different human body segments through anthropometric vibratory model in standing posture.

PubMed

Gupta, T C

2007-08-01

A 15 degrees of freedom lumped parameter vibratory model of human body is developed, for vertical mode vibrations, using anthropometric data of the 50th percentile US male. The mass and stiffness of various segments are determined from the elastic modulii of bones and tissues and from the anthropometric data available, assuming the shape of all the segments is ellipsoidal. The damping ratio of each segment is estimated on the basis of the physical structure of the body in a particular posture. Damping constants of various segments are calculated from these damping ratios. The human body is modeled as a linear spring-mass-damper system. The optimal values of the damping ratios of the body segments are estimated, for the 15 degrees of freedom model of the 50th percentile US male, by comparing the response of the model with the experimental response. Formulating a similar vibratory model of the 50th percentile Indian male and comparing the frequency response of the model with the experimental response of the same group of subjects validate the modeling procedure. A range of damping ratios has been considered to develop a vibratory model, which can predict the vertical harmonic response of the human body.

Platelet adhesion and human umbilical vein endothelial cell cytocompatibility of biodegradable segmented polyurethanes prepared with 4,4'-methylene bis(cyclohexyl isocyanate), poly(caprolactone) diol and butanediol or dithioerythritol as chain extenders.

PubMed

Chan-Chan, L H; Vargas-Coronado, R F; Cervantes-Uc, J M; Cauich-Rodríguez, J V; Rath, R; Phelps, E A; García, A J; San Román Del Barrio, J; Parra, J; Merhi, Y; Tabrizian, M

2013-08-01

Biodegradable segmented polyurethanes were prepared with poly(caprolactone) diol as a soft segment, 4,4'-methylene bis(cyclohexyl isocyanate) (HMDI) and either butanediol or dithioerythritol as chain extenders. Platelet adhesion was similar in all segmented polyurethanes studied and not different from Tecoflex® although an early stage of activation was observed on biodegradable segmented polyurethane prepared with dithioerythritol. Relative viability was higher than 80% on human umbilical vein endothelial cells in contact with biodegradable segmented polyurethane extracts after 1, 2 and 7 days. Furthermore, both biodegradable segmented polyurethane materials supported human umbilical vein endothelial cell adhesion, spreading, and viability similar to Tecoflex® medical-grade polyurethane. These biodegradable segmented polyurethanes represent promising materials for cardiovascular applications.

Neutralisation of a single voltage sensor affects gating determinants in all four pore-forming S6 segments of Ca(V)1.2: a cooperative gating model.

PubMed

Beyl, Stanislav; Depil, Katrin; Hohaus, Annette; Stary-Weinzinger, Anna; Linder, Tobias; Timin, Eugen; Hering, Steffen

2012-10-01

Voltage sensors trigger the closed-open transitions in the pore of voltage-gated ion channels. To probe the transmission of voltage sensor signalling to the channel pore of Ca(V)1.2, we investigated how elimination of positive charges in the S4 segments (charged residues were replaced by neutral glutamine) modulates gating perturbations induced by mutations in pore-lining S6 segments. Neutralisation of all positively charged residues in IIS4 produced a functional channel (IIS4(N)), while replacement of the charged residues in IS4, IIIS4 and IVS4 segments resulted in nonfunctional channels. The IIS4(N) channel displayed activation kinetics similar to wild type. Mutations in a highly conserved structure motif on S6 segments ("GAGA ring": G432W in IS6, A780T in IIS6, G1193T in IIIS6 and A1503G in IVS6) induce strong left-shifted activation curves and decelerated channel deactivation kinetics. When IIS4(N) was combined with these mutations, the activation curves were shifted back towards wild type and current kinetics were accelerated. In contrast, 12 other mutations adjacent to the GAGA ring in IS6-IVS6, which also affect activation gating, were not rescued by IIS4(N). Thus, the rescue of gating distortions in segments IS6-IVS6 by IIS4(N) is highly position-specific. Thermodynamic cycle analysis supports the hypothesis that IIS4 is energetically coupled with the distantly located GAGA residues. We speculate that conformational changes caused by neutralisation of IIS4 are not restricted to domain II (IIS6) but are transmitted to gating structures in domains I, III and IV via the GAGA ring.

Segmentation of left ventricle myocardium in porcine cardiac cine MR images using a hybrid of fully convolutional neural networks and convolutional LSTM

NASA Astrophysics Data System (ADS)

Zhang, Dongqing; Icke, Ilknur; Dogdas, Belma; Parimal, Sarayu; Sampath, Smita; Forbes, Joseph; Bagchi, Ansuman; Chin, Chih-Liang; Chen, Antong

2018-03-01

In the development of treatments for cardiovascular diseases, short axis cardiac cine MRI is important for the assessment of various structural and functional properties of the heart. In short axis cardiac cine MRI, Cardiac properties including the ventricle dimensions, stroke volume, and ejection fraction can be extracted based on accurate segmentation of the left ventricle (LV) myocardium. One of the most advanced segmentation methods is based on fully convolutional neural networks (FCN) and can be successfully used to do segmentation in cardiac cine MRI slices. However, the temporal dependency between slices acquired at neighboring time points is not used. Here, based on our previously proposed FCN structure, we proposed a new algorithm to segment LV myocardium in porcine short axis cardiac cine MRI by incorporating convolutional long short-term memory (Conv-LSTM) to leverage the temporal dependency. In this approach, instead of processing each slice independently in a conventional CNN-based approach, the Conv-LSTM architecture captures the dynamics of cardiac motion over time. In a leave-one-out experiment on 8 porcine specimens (3,600 slices), the proposed approach was shown to be promising by achieving average mean Dice similarity coefficient (DSC) of 0.84, Hausdorff distance (HD) of 6.35 mm, and average perpendicular distance (APD) of 1.09 mm when compared with manual segmentations, which improved the performance of our previous FCN-based approach (average mean DSC=0.84, HD=6.78 mm, and APD=1.11 mm). Qualitatively, our model showed robustness against low image quality and complications in the surrounding anatomy due to its ability to capture the dynamics of cardiac motion.

Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, Zhye, E-mail: yin@ge.com; De Man, Bruno; Yao, Yangyang

Purpose: Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. Methods: The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies tomore » achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. Results: In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors’ pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtained with the proposed strategy. Conclusions: The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.« less

A pediatric brain structure atlas from T1-weighted MR images

NASA Astrophysics Data System (ADS)

Shan, Zuyao Y.; Parra, Carlos; Ji, Qing; Ogg, Robert J.; Zhang, Yong; Laningham, Fred H.; Reddick, Wilburn E.

2006-03-01

In this paper, we have developed a digital atlas of the pediatric human brain. Human brain atlases, used to visualize spatially complex structures of the brain, are indispensable tools in model-based segmentation and quantitative analysis of brain structures. However, adult brain atlases do not adequately represent the normal maturational patterns of the pediatric brain, and the use of an adult model in pediatric studies may introduce substantial bias. Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1 weighted MR data set of a 9 year old, right-handed girl. Furthermore, we extracted and simplified boundary surfaces of 25 manually defined brain structures (cortical and subcortical) based on surface curvature. Higher curvature surfaces were simplified with more reference points; lower curvature surfaces, with fewer. We constructed a 3D triangular mesh model for each structure by triangulation of the structure's reference points. Kappa statistics (cortical, 0.97; subcortical, 0.91) indicated substantial similarities between the mesh-defined and the original volumes. Our brain atlas and structural mesh models (www.stjude.org/BrainAtlas) can be used to plan treatment, to conduct knowledge and modeldriven segmentation, and to analyze the shapes of brain structures in pediatric patients.

A multiresolution prostate representation for automatic segmentation in magnetic resonance images.

PubMed

Alvarez, Charlens; Martínez, Fabio; Romero, Eduardo

2017-04-01

Accurate prostate delineation is necessary in radiotherapy processes for concentrating the dose onto the prostate and reducing side effects in neighboring organs. Currently, manual delineation is performed over magnetic resonance imaging (MRI) taking advantage of its high soft tissue contrast property. Nevertheless, as human intervention is a consuming task with high intra- and interobserver variability rates, (semi)-automatic organ delineation tools have emerged to cope with these challenges, reducing the time spent for these tasks. This work presents a multiresolution representation that defines a novel metric and allows to segment a new prostate by combining a set of most similar prostates in a dataset. The proposed method starts by selecting the set of most similar prostates with respect to a new one using the proposed multiresolution representation. This representation characterizes the prostate through a set of salient points, extracted from a region of interest (ROI) that encloses the organ and refined using structural information, allowing to capture main relevant features of the organ boundary. Afterward, the new prostate is automatically segmented by combining the nonrigidly registered expert delineations associated to the previous selected similar prostates using a weighted patch-based strategy. Finally, the prostate contour is smoothed based on morphological operations. The proposed approach was evaluated with respect to the expert manual segmentation under a leave-one-out scheme using two public datasets, obtaining averaged Dice coefficients of 82% ± 0.07 and 83% ± 0.06, and demonstrating a competitive performance with respect to atlas-based state-of-the-art methods. The proposed multiresolution representation provides a feature space that follows a local salient point criteria and a global rule of the spatial configuration among these points to find out the most similar prostates. This strategy suggests an easy adaptation in the clinical routine, as supporting tool for annotation. © 2017 American Association of Physicists in Medicine.

Techniques on semiautomatic segmentation using the Adobe Photoshop

NASA Astrophysics Data System (ADS)

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae

2005-04-01

The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.

Structural analysis of vibroacoustical processes

NASA Technical Reports Server (NTRS)

Gromov, A. P.; Myasnikov, L. L.; Myasnikova, Y. N.; Finagin, B. A.

1973-01-01

The method of automatic identification of acoustical signals, by means of the segmentation was used to investigate noises and vibrations in machines and mechanisms, for cybernetic diagnostics. The structural analysis consists of presentation of a noise or vibroacoustical signal as a sequence of segments, determined by the time quantization, in which each segment is characterized by specific spectral characteristics. The structural spectrum is plotted as a histogram of the segments, also as a relation of the probability density of appearance of a segment to the segment type. It is assumed that the conditions of ergodic processes are maintained.

Whole-Genome Analysis of a Novel Fish Reovirus (MsReV) Discloses Aquareovirus Genomic Structure Relationship with Host in Saline Environments.

PubMed

Chen, Zhong-Yuan; Gao, Xiao-Chan; Zhang, Qi-Ya

2015-08-03

Aquareoviruses are serious pathogens of aquatic animals. Here, genome characterization and functional gene analysis of a novel aquareovirus, largemouth bass Micropterus salmoides reovirus (MsReV), was described. It comprises 11 dsRNA segments (S1-S11) covering 24,024 bp, and encodes 12 putative proteins including the inclusion forming-related protein NS87 and the fusion-associated small transmembrane (FAST) protein NS22. The function of NS22 was confirmed by expression in fish cells. Subsequently, MsReV was compared with two representative aquareoviruses, saltwater fish turbot Scophthalmus maximus reovirus (SMReV) and freshwater fish grass carp reovirus strain 109 (GCReV-109). MsReV NS87 and NS22 genes have the same structure and function with those of SMReV, whereas GCReV-109 is either missing the coiled-coil region in NS79 or the gene-encoding NS22. Significant similarities are also revealed among equivalent genome segments between MsReV and SMReV, but a difference is found between MsReV and GCReV-109. Furthermore, phylogenetic analysis showed that 13 aquareoviruses could be divided into freshwater and saline environments subgroups, and MsReV was closely related to SMReV in saline environments. Consequently, these viruses from hosts in saline environments have more genomic structural similarities than the viruses from hosts in freshwater. This is the first study of the relationships between aquareovirus genomic structure and their host environments.

Inhibition of 2,4-dichlorophenoxyacetic acid-stimulated elongation of pea stem segments by a xyloglucan oligosaccharide

DOE Office of Scientific and Technical Information (OSTI.GOV)

York, W.S.; Darvill, A.G.; Albersheim, P.

1984-06-01

Xyloglucan, isolated from the soluble extracellular polysaccharides of suspension-cultured sycamore (Acer pseudoplatanus) cells, was digested with an endo-..beta..-1,4-glucanase purified from the culture fluid of Trichoderma viride. A nonasaccharide-rich Bio-Gel P-2 fraction of this digest inhibited 2,4-dichlorophenoxyacetic-acid-stimulated elongation of etiolated pea stem segments. The inhibitory activity of this oligosaccharide fraction exhibited a well-define concentraction optimum between 10/sup -2/ and 10/sup -1/ micrograms per milliliter. Another fraction of the same xyloglucan digest, rich in a structurally related heptasaccharide, did not, at similar concentrations, significantly inhibit the elongation. 11 references, 3 figures.

Evaluation of non-rigid registration parameters for atlas-based segmentation of CT images of human cochlea

NASA Astrophysics Data System (ADS)

Elfarnawany, Mai; Alam, S. Riyahi; Agrawal, Sumit K.; Ladak, Hanif M.

2017-02-01

Cochlear implant surgery is a hearing restoration procedure for patients with profound hearing loss. In this surgery, an electrode is inserted into the cochlea to stimulate the auditory nerve and restore the patient's hearing. Clinical computed tomography (CT) images are used for planning and evaluation of electrode placement, but their low resolution limits the visualization of internal cochlear structures. Therefore, high resolution micro-CT images are used to develop atlas-based segmentation methods to extract these nonvisible anatomical features in clinical CT images. Accurate registration of the high and low resolution CT images is a prerequisite for reliable atlas-based segmentation. In this study, we evaluate and compare different non-rigid B-spline registration parameters using micro-CT and clinical CT images of five cadaveric human cochleae. The varying registration parameters are cost function (normalized correlation (NC), mutual information and mean square error), interpolation method (linear, windowed-sinc and B-spline) and sampling percentage (1%, 10% and 100%). We compare the registration results visually and quantitatively using the Dice similarity coefficient (DSC), Hausdorff distance (HD) and absolute percentage error in cochlear volume. Using MI or MSE cost functions and linear or windowed-sinc interpolation resulted in visually undesirable deformation of internal cochlear structures. Quantitatively, the transforms using 100% sampling percentage yielded the highest DSC and smallest HD (0.828+/-0.021 and 0.25+/-0.09mm respectively). Therefore, B-spline registration with cost function: NC, interpolation: B-spline and sampling percentage: moments 100% can be the foundation of developing an optimized atlas-based segmentation algorithm of intracochlear structures in clinical CT images.

Segmentation and texture analysis of structural biomarkers using neighborhood-clustering-based level set in MRI of the schizophrenic brain.

PubMed

Latha, Manohar; Kavitha, Ganesan

2018-02-03

Schizophrenia (SZ) is a psychiatric disorder that especially affects individuals during their adolescence. There is a need to study the subanatomical regions of SZ brain on magnetic resonance images (MRI) based on morphometry. In this work, an attempt was made to analyze alterations in structure and texture patterns in images of the SZ brain using the level-set method and Laws texture features. T1-weighted MRI of the brain from Center of Biomedical Research Excellence (COBRE) database were considered for analysis. Segmentation was carried out using the level-set method. Geometrical and Laws texture features were extracted from the segmented brain stem, corpus callosum, cerebellum, and ventricle regions to analyze pattern changes in SZ. The level-set method segmented multiple brain regions, with higher similarity and correlation values compared with an optimized method. The geometric features obtained from regions of the corpus callosum and ventricle showed significant variation (p < 0.00001) between normal and SZ brain. Laws texture feature identified a heterogeneous appearance in the brain stem, corpus callosum and ventricular regions, and features from the brain stem were correlated with Positive and Negative Syndrome Scale (PANSS) score (p < 0.005). A framework of geometric and Laws texture features obtained from brain subregions can be used as a supplement for diagnosis of psychiatric disorders.

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

PubMed

Shukla, Rahul; Dragotti, Pier Luigi; Do, Minh N; Vetterli, Martin

2005-03-01

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoang Duc, Albert K., E-mail: albert.hoangduc.ucl@gmail.com; McClelland, Jamie; Modat, Marc

Purpose: The aim of this study was to assess whether clinically acceptable segmentations of organs at risk (OARs) in head and neck cancer can be obtained automatically and efficiently using the novel “similarity and truth estimation for propagated segmentations” (STEPS) compared to the traditional “simultaneous truth and performance level estimation” (STAPLE) algorithm. Methods: First, 6 OARs were contoured by 2 radiation oncologists in a dataset of 100 patients with head and neck cancer on planning computed tomography images. Each image in the dataset was then automatically segmented with STAPLE and STEPS using those manual contours. Dice similarity coefficient (DSC) wasmore » then used to compare the accuracy of these automatic methods. Second, in a blind experiment, three separate and distinct trained physicians graded manual and automatic segmentations into one of the following three grades: clinically acceptable as determined by universal delineation guidelines (grade A), reasonably acceptable for clinical practice upon manual editing (grade B), and not acceptable (grade C). Finally, STEPS segmentations graded B were selected and one of the physicians manually edited them to grade A. Editing time was recorded. Results: Significant improvements in DSC can be seen when using the STEPS algorithm on large structures such as the brainstem, spinal canal, and left/right parotid compared to the STAPLE algorithm (all p < 0.001). In addition, across all three trained physicians, manual and STEPS segmentation grades were not significantly different for the brainstem, spinal canal, parotid (right/left), and optic chiasm (all p > 0.100). In contrast, STEPS segmentation grades were lower for the eyes (p < 0.001). Across all OARs and all physicians, STEPS produced segmentations graded as well as manual contouring at a rate of 83%, giving a lower bound on this rate of 80% with 95% confidence. Reduction in manual interaction time was on average 61% and 93% when automatic segmentations did and did not, respectively, require manual editing. Conclusions: The STEPS algorithm showed better performance than the STAPLE algorithm in segmenting OARs for radiotherapy of the head and neck. It can automatically produce clinically acceptable segmentation of OARs, with results as relevant as manual contouring for the brainstem, spinal canal, the parotids (left/right), and optic chiasm. A substantial reduction in manual labor was achieved when using STEPS even when manual editing was necessary.« less

A structural-alphabet-based strategy for finding structural motifs across protein families

PubMed Central

Wu, Chih Yuan; Chen, Yao Chi; Lim, Carmay

2010-01-01

Proteins with insignificant sequence and overall structure similarity may still share locally conserved contiguous structural segments; i.e. structural/3D motifs. Most methods for finding 3D motifs require a known motif to search for other similar structures or functionally/structurally crucial residues. Here, without requiring a query motif or essential residues, a fully automated method for discovering 3D motifs of various sizes across protein families with different folds based on a 16-letter structural alphabet is presented. It was applied to structurally non-redundant proteins bound to DNA, RNA, obligate/non-obligate proteins as well as free DNA-binding proteins (DBPs) and proteins with known structures but unknown function. Its usefulness was illustrated by analyzing the 3D motifs found in DBPs. A non-specific motif was found with a ‘corner’ architecture that confers a stable scaffold and enables diverse interactions, making it suitable for binding not only DNA but also RNA and proteins. Furthermore, DNA-specific motifs present ‘only’ in DBPs were discovered. The motifs found can provide useful guidelines in detecting binding sites and computational protein redesign. PMID:20525797

Efficient graph-cut tattoo segmentation

NASA Astrophysics Data System (ADS)

Kim, Joonsoo; Parra, Albert; Li, He; Delp, Edward J.

2015-03-01

Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related crimes. Many tattoo image retrieval systems have been described. In a retrieval system tattoo segmentation is an important step for retrieval accuracy since segmentation removes background information in a tattoo image. Existing segmentation methods do not extract the tattoo very well when the background includes textures and color similar to skin tones. In this paper we describe a tattoo segmentation approach by determining skin pixels in regions near the tattoo. In these regions graph-cut segmentation using a skin color model and a visual saliency map is used to find skin pixels. After segmentation we determine which set of skin pixels are connected with each other that form a closed contour including a tattoo. The regions surrounded by the closed contours are considered tattoo regions. Our method segments tattoos well when the background includes textures and color similar to skin.

The Time Course of Segmentation and Cue-Selectivity in the Human Visual Cortex

PubMed Central

Appelbaum, Lawrence G.; Ales, Justin M.; Norcia, Anthony M.

2012-01-01

Texture discontinuities are a fundamental cue by which the visual system segments objects from their background. The neural mechanisms supporting texture-based segmentation are therefore critical to visual perception and cognition. In the present experiment we employ an EEG source-imaging approach in order to study the time course of texture-based segmentation in the human brain. Visual Evoked Potentials were recorded to four types of stimuli in which periodic temporal modulation of a central 3° figure region could either support figure-ground segmentation, or have identical local texture modulations but not produce changes in global image segmentation. The image discontinuities were defined either by orientation or phase differences across image regions. Evoked responses to these four stimuli were analyzed both at the scalp and on the cortical surface in retinotopic and functional regions-of-interest (ROIs) defined separately using fMRI on a subject-by-subject basis. Texture segmentation (tsVEP: segmenting versus non-segmenting) and cue-specific (csVEP: orientation versus phase) responses exhibited distinctive patterns of activity. Alternations between uniform and segmented images produced highly asymmetric responses that were larger after transitions from the uniform to the segmented state. Texture modulations that signaled the appearance of a figure evoked a pattern of increased activity starting at ∼143 ms that was larger in V1 and LOC ROIs, relative to identical modulations that didn't signal figure-ground segmentation. This segmentation-related activity occurred after an initial response phase that did not depend on the global segmentation structure of the image. The two cue types evoked similar tsVEPs up to 230 ms when they differed in the V4 and LOC ROIs. The evolution of the response proceeded largely in the feed-forward direction, with only weak evidence for feedback-related activity. PMID:22479566

Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches.

PubMed

Le Troter, Arnaud; Fouré, Alexandre; Guye, Maxime; Confort-Gouny, Sylviane; Mattei, Jean-Pierre; Gondin, Julien; Salort-Campana, Emmanuelle; Bendahan, David

2016-04-01

Atlas-based segmentation is a powerful method for automatic structural segmentation of several sub-structures in many organs. However, such an approach has been very scarcely used in the context of muscle segmentation, and so far no study has assessed such a method for the automatic delineation of individual muscles of the quadriceps femoris (QF). In the present study, we have evaluated a fully automated multi-atlas method and a semi-automated single-atlas method for the segmentation and volume quantification of the four muscles of the QF and for the QF as a whole. The study was conducted in 32 young healthy males, using high-resolution magnetic resonance images (MRI) of the thigh. The multi-atlas-based segmentation method was conducted in 25 subjects. Different non-linear registration approaches based on free-form deformable (FFD) and symmetric diffeomorphic normalization algorithms (SyN) were assessed. Optimal parameters of two fusion methods, i.e., STAPLE and STEPS, were determined on the basis of the highest Dice similarity index (DSI) considering manual segmentation (MSeg) as the ground truth. Validation and reproducibility of this pipeline were determined using another MRI dataset recorded in seven healthy male subjects on the basis of additional metrics such as the muscle volume similarity values, intraclass coefficient, and coefficient of variation. Both non-linear registration methods (FFD and SyN) were also evaluated as part of a single-atlas strategy in order to assess longitudinal muscle volume measurements. The multi- and the single-atlas approaches were compared for the segmentation and the volume quantification of the four muscles of the QF and for the QF as a whole. Considering each muscle of the QF, the DSI of the multi-atlas-based approach was high 0.87 ± 0.11 and the best results were obtained with the combination of two deformation fields resulting from the SyN registration method and the STEPS fusion algorithm. The optimal variables for FFD and SyN registration methods were four templates and a kernel standard deviation ranging between 5 and 8. The segmentation process using a single-atlas-based method was more robust with DSI values higher than 0.9. From the vantage of muscle volume measurements, the multi-atlas-based strategy provided acceptable results regarding the QF muscle as a whole but highly variable results regarding individual muscle. On the contrary, the performance of the single-atlas-based pipeline for individual muscles was highly comparable to the MSeg, thereby indicating that this method would be adequate for longitudinal tracking of muscle volume changes in healthy subjects. In the present study, we demonstrated that both multi-atlas and single-atlas approaches were relevant for the segmentation of individual muscles of the QF in healthy subjects. Considering muscle volume measurements, the single-atlas method provided promising perspectives regarding longitudinal quantification of individual muscle volumes.

Process for structural geologic analysis of topography and point data

DOEpatents

Eliason, Jay R.; Eliason, Valerie L. C.

1987-01-01

A quantitative method of geologic structural analysis of digital terrain data is described for implementation on a computer. Assuming selected valley segments are controlled by the underlying geologic structure, topographic lows in the terrain data, defining valley bottoms, are detected, filtered and accumulated into a series line segments defining contiguous valleys. The line segments are then vectorized to produce vector segments, defining valley segments, which may be indicative of the underlying geologic structure. Coplanar analysis is performed on vector segment pairs to determine which vectors produce planes which represent underlying geologic structure. Point data such as fracture phenomena which can be related to fracture planes in 3-dimensional space can be analyzed to define common plane orientation and locations. The vectors, points, and planes are displayed in various formats for interpretation.

SU-E-J-238: Monitoring Lymph Node Volumes During Radiotherapy Using Semi-Automatic Segmentation of MRI Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Veeraraghavan, H; Tyagi, N; Riaz, N

2014-06-01

Purpose: Identification and image-based monitoring of lymph nodes growing due to disease, could be an attractive alternative to prophylactic head and neck irradiation. We evaluated the accuracy of the user-interactive Grow Cut algorithm for volumetric segmentation of radiotherapy relevant lymph nodes from MRI taken weekly during radiotherapy. Method: The algorithm employs user drawn strokes in the image to volumetrically segment multiple structures of interest. We used a 3D T2-wturbo spin echo images with an isotropic resolution of 1 mm3 and FOV of 492×492×300 mm3 of head and neck cancer patients who underwent weekly MR imaging during the course of radiotherapy.more » Various lymph node (LN) levels (N2, N3, N4'5) were individually contoured on the weekly MR images by an expert physician and used as ground truth in our study. The segmentation results were compared with the physician drawn lymph nodes based on DICE similarity score. Results: Three head and neck patients with 6 weekly MR images were evaluated. Two patients had level 2 LN drawn and one patient had level N2, N3 and N4'5 drawn on each MR image. The algorithm took an average of a minute to segment the entire volume (512×512×300 mm3). The algorithm achieved an overall DICE similarity score of 0.78. The time taken for initializing and obtaining the volumetric mask was about 5 mins for cases with only N2 LN and about 15 mins for the case with N2,N3 and N4'5 level nodes. The longer initialization time for the latter case was due to the need for accurate user inputs to separate overlapping portions of the different LN. The standard deviation in segmentation accuracy at different time points was utmost 0.05. Conclusions: Our initial evaluation of the grow cut segmentation shows reasonably accurate and consistent volumetric segmentations of LN with minimal user effort and time.« less

SU-C-BRA-06: Automatic Brain Tumor Segmentation for Stereotactic Radiosurgery Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Stojadinovic, S; Jiang, S

Purpose: Stereotactic radiosurgery (SRS), which delivers a potent dose of highly conformal radiation to the target in a single fraction, requires accurate tumor delineation for treatment planning. We present an automatic segmentation strategy, that synergizes intensity histogram thresholding, super-voxel clustering, and level-set based contour evolving methods to efficiently and accurately delineate SRS brain tumors on contrast-enhance T1-weighted (T1c) Magnetic Resonance Images (MRI). Methods: The developed auto-segmentation strategy consists of three major steps. Firstly, tumor sites are localized through 2D slice intensity histogram scanning. Then, super voxels are obtained through clustering the corresponding voxels in 3D with reference to the similaritymore » metrics composited from spatial distance and intensity difference. The combination of the above two could generate the initial contour surface. Finally, a localized region active contour model is utilized to evolve the surface to achieve the accurate delineation of the tumors. The developed method was evaluated on numerical phantom data, synthetic BRATS (Multimodal Brain Tumor Image Segmentation challenge) data, and clinical patients’ data. The auto-segmentation results were quantitatively evaluated by comparing to ground truths with both volume and surface similarity metrics. Results: DICE coefficient (DC) was performed as a quantitative metric to evaluate the auto-segmentation in the numerical phantom with 8 tumors. DCs are 0.999±0.001 without noise, 0.969±0.065 with Rician noise and 0.976±0.038 with Gaussian noise. DC, NMI (Normalized Mutual Information), SSIM (Structural Similarity) and Hausdorff distance (HD) were calculated as the metrics for the BRATS and patients’ data. Assessment of BRATS data across 25 tumor segmentation yield DC 0.886±0.078, NMI 0.817±0.108, SSIM 0.997±0.002, and HD 6.483±4.079mm. Evaluation on 8 patients with total 14 tumor sites yield DC 0.872±0.070, NMI 0.824±0.078, SSIM 0.999±0.001, and HD 5.926±6.141mm. Conclusion: The developed automatic segmentation strategy, which yields accurate brain tumor delineation in evaluation cases, is promising for its application in SRS treatment planning.« less

Homeotic genes and the arthropod head: Expression patterns of the labial, proboscipedia, and Deformed genes in crustaceans and insects

PubMed Central

Abzhanov, Arhat; Kaufman, Thomas C.

1999-01-01

cDNA fragments of the homologues of the Drosophila head homeotic genes labial (lab), proboscipedia (pb), and Deformed (Dfd) have been isolated from the crustacean Porcellio scaber. Because the accumulation domains of the head homeotic complex (Hox) genes had not been previously reported for crustaceans, we studied the expression patterns of these genes in P. scaber embryos by using in situ hybridization. The P. scaber lab homologue is expressed in the developing second antennal segment and its appendages. This expression domain in crustaceans and in the homologous intercalary segment of insects suggests that the lab gene specified this metamere in the last common ancestor of these two groups. The expression domain of the P. scaber pb gene is in the posterior part of the second antennal segment. This domain, in contrast to that in insects, is colinear with the domains of other head genes in P. scaber, and it differs from the insect pb gene expression domain in the posterior mouthparts, suggesting that the insect and crustacean patterns evolved independently from a broader ancestral domain similar to that found in modern chelicerates. P. scaber Dfd is expressed in the mandibular segment and paragnaths (a pair of ventral mouthpart structures associated with the stomodeum) and differs from insects, where expression is in the mandibular and maxillary segments. Thus, like pb, Dfd shows a divergent Hox gene deployment. We conclude that homologous structures of the mandibulate head display striking differences in their underlying developmental programs related to Hox gene expression. PMID:10468590

Segmented molecular design of self-healing proteinaceous materials

NASA Astrophysics Data System (ADS)

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C.

2015-09-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure-property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

Segmented molecular design of self-healing proteinaceous materials.

PubMed

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C

2015-09-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure-property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

A possible source mechanism of the 1946 Unimak Alaska far-field tsunami, uplift of the mid-slope terrace above a splay fault zone

USGS Publications Warehouse

von Huene, Roland E.; Miller, John J.; Klaeschen, Dirk; Dartnell, Peter

2016-01-01

In 1946, megathrust seismicity along the Unimak segment of the Alaska subduction zone generated the largest ever recorded Alaska/Aleutian tsunami. The tsunami severely damaged Pacific islands and coastal areas from Alaska to Antarctica. It is the charter member of “tsunami” earthquakes that produce outsized far-field tsunamis for the recorded magnitude. Its source mechanisms were unconstrained by observations because geophysical data for the Unimak segment were sparse and of low resolution. Reprocessing of legacy geophysical data reveals a deep water, high-angle reverse or splay thrust fault zone that leads megathrust slip upward to the mid-slope terrace seafloor rather than along the plate boundary toward the trench axis. Splay fault uplift elevates the outer mid-slope terrace and its inner area subsides. Multibeam bathymetry along the splay fault zone shows recent but undated seafloor disruption. The structural configuration of the nearby Semidi segment is similar to that of the Unimak segment, portending generation of a future large tsunami directed toward the US West coast.

A Possible Source Mechanism of the 1946 Unimak Alaska Far-Field Tsunami: Uplift of the Mid-Slope Terrace Above a Splay Fault Zone

NASA Astrophysics Data System (ADS)

von Huene, Roland; Miller, John J.; Klaeschen, Dirk; Dartnell, Peter

2016-12-01

In 1946, megathrust seismicity along the Unimak segment of the Alaska subduction zone generated the largest ever recorded Alaska/Aleutian tsunami. The tsunami severely damaged Pacific islands and coastal areas from Alaska to Antarctica. It is the charter member of "tsunami" earthquakes that produce outsized far-field tsunamis for the recorded magnitude. Its source mechanisms were unconstrained by observations because geophysical data for the Unimak segment were sparse and of low resolution. Reprocessing of legacy geophysical data reveals a deep water, high-angle reverse or splay thrust fault zone that leads megathrust slip upward to the mid-slope terrace seafloor rather than along the plate boundary toward the trench axis. Splay fault uplift elevates the outer mid-slope terrace and its inner area subsides. Multibeam bathymetry along the splay fault zone shows recent but undated seafloor disruption. The structural configuration of the nearby Semidi segment is similar to that of the Unimak segment, portending generation of a future large tsunami directed toward the US West coast.

Structure of the toxic core of α-synuclein from invisible crystals

DOE PAGES

Rodriguez, Jose A.; Ivanova, Magdalena I.; Sawaya, Michael R.; ...

2015-09-09

We report that the protein α-synuclein is the main component of Lewy bodies, the neuron-associated aggregates seen in Parkinson disease and other neurodegenerative pathologies. An 11-residue segment, which we term NACore, appears to be responsible for amyloid formation and cytotoxicity of human α-synuclein. Here we describe crystals of NACore that have dimensions smaller than the wavelength of visible light and thus are invisible by optical microscopy. As the crystals are thousands of times too small for structure determination by synchrotron X-ray diffraction, we use micro-electron diffraction to determine the structure at atomic resolution. The 1.4 Å resolution structure demonstrates thatmore » this method can determine previously unknown protein structures and here yields, to our knowledge, the highest resolution achieved by any cryo-electron microscopy method to date. The structure exhibits protofibrils built of pairs of face-to-face β-sheets. X-ray fibre diffraction patterns show the similarity of NACore to toxic fibrils of full-length α-synuclein. Finally, the NACore structure, together with that of a second segment, inspires a model for most of the ordered portion of the toxic, full-length α-synuclein fibril, presenting opportunities for the design of inhibitors of α-synuclein fibrils.« less

Corpus callosum segmentation using deep neural networks with prior information from multi-atlas images

NASA Astrophysics Data System (ADS)

Park, Gilsoon; Hong, Jinwoo; Lee, Jong-Min

2018-03-01

In human brain, Corpus Callosum (CC) is the largest white matter structure, connecting between right and left hemispheres. Structural features such as shape and size of CC in midsagittal plane are of great significance for analyzing various neurological diseases, for example Alzheimer's disease, autism and epilepsy. For quantitative and qualitative studies of CC in brain MR images, robust segmentation of CC is important. In this paper, we present a novel method for CC segmentation. Our approach is based on deep neural networks and the prior information generated from multi-atlas images. Deep neural networks have recently shown good performance in various image processing field. Convolutional neural networks (CNN) have shown outstanding performance for classification and segmentation in medical image fields. We used convolutional neural networks for CC segmentation. Multi-atlas based segmentation model have been widely used in medical image segmentation because atlas has powerful information about the target structure we want to segment, consisting of MR images and corresponding manual segmentation of the target structure. We combined the prior information, such as location and intensity distribution of target structure (i.e. CC), made from multi-atlas images in CNN training process for more improving training. The CNN with prior information showed better segmentation performance than without.

Old document image segmentation using the autocorrelation function and multiresolution analysis

NASA Astrophysics Data System (ADS)

Mehri, Maroua; Gomez-Krämer, Petra; Héroux, Pierre; Mullot, Rémy

2013-01-01

Recent progress in the digitization of heterogeneous collections of ancient documents has rekindled new challenges in information retrieval in digital libraries and document layout analysis. Therefore, in order to control the quality of historical document image digitization and to meet the need of a characterization of their content using intermediate level metadata (between image and document structure), we propose a fast automatic layout segmentation of old document images based on five descriptors. Those descriptors, based on the autocorrelation function, are obtained by multiresolution analysis and used afterwards in a specific clustering method. The method proposed in this article has the advantage that it is performed without any hypothesis on the document structure, either about the document model (physical structure), or the typographical parameters (logical structure). It is also parameter-free since it automatically adapts to the image content. In this paper, firstly, we detail our proposal to characterize the content of old documents by extracting the autocorrelation features in the different areas of a page and at several resolutions. Then, we show that is possible to automatically find the homogeneous regions defined by similar indices of autocorrelation without knowledge about the number of clusters using adapted hierarchical ascendant classification and consensus clustering approaches. To assess our method, we apply our algorithm on 316 old document images, which encompass six centuries (1200-1900) of French history, in order to demonstrate the performance of our proposal in terms of segmentation and characterization of heterogeneous corpus content. Moreover, we define a new evaluation metric, the homogeneity measure, which aims at evaluating the segmentation and characterization accuracy of our methodology. We find a 85% of mean homogeneity accuracy. Those results help to represent a document by a hierarchy of layout structure and content, and to define one or more signatures for each page, on the basis of a hierarchical representation of homogeneous blocks and their topology.

Nanowire structures and electrical devices

DOEpatents

Bezryadin, Alexey; Remeika, Mikas

2010-07-06

The present invention provides structures and devices comprising conductive segments and conductance constricting segments of a nanowire, such as metallic, superconducting or semiconducting nanowire. The present invention provides structures and devices comprising conductive nanowire segments and conductance constricting nanowire segments having accurately selected phases including crystalline and amorphous states, compositions, morphologies and physical dimensions, including selected cross sectional dimensions, shapes and lengths along the length of a nanowire. Further, the present invention provides methods of processing nanowires capable of patterning a nanowire to form a plurality of conductance constricting segments having selected positions along the length of a nanowire, including conductance constricting segments having reduced cross sectional dimensions and conductance constricting segments comprising one or more insulating materials such as metal oxides.

The minimal structure containing the band 3 anion transport site. A 35Cl NMR study.

PubMed

Falke, J J; Kanes, K J; Chan, S I

1985-10-25

35Cl NMR, which enables observation of chloride binding to the anion transport site on band 3, is used in the present study to determine the minimal structure containing the intact transport site. Removal of cytoskeletal and other nonintegral membrane proteins, or removal of the 40-kDa cytoskeletal domain of band 3, each leave the transport site intact. Similarly, cleavage of the 52-kDa transport domain into 17- and 35-kDa fragments by chymotrypsin leaves the transport site intact. Extensive proteolysis by papain reduces the integral red cell membrane proteins to their transmembrane segments. Papain treatment removes approximately 60% of the extramembrane portion of the transport domain and produces small fragments primarily in the range 3-7 kDa, with 5 kDa being most predominant. Papain treatment damages, but does not destroy, chloride binding to the transport site; thus, the minimal structure containing the transport site is composed solely of transmembrane segments. In short, the results are completely consistent with a picture in which the transport site is buried in the membrane where it is protected from proteolysis; the transmembrane segments that surround the transport site are held together by strong attractive forces within the bilayer; and the transport site is accessed by solution chloride via an anion channel leading from the transport site to the solution.

Growth and linkage of the quaternary Ubrique Normal Fault Zone, Western Gibraltar Arc: role on the along-strike relief segmentation

NASA Astrophysics Data System (ADS)

Jiménez-Bonilla, Alejandro; Balanya, Juan Carlos; Exposito, Inmaculada; Diaz-Azpiroz, Manuel; Barcos, Leticia

2015-04-01

Strain partitioning modes within migrating orogenic arcs may result in arc-parallel stretching that produces along-strike structural and topographic discontinuities. In the Western Gibraltar Arc, arc-parallel stretching has operated from the Lower Miocene up to recent times. In this study, we have reviewed the Colmenar Fault, located at the SW end of the Subbetic ranges, previously interpreted as a Middle Miocene low-angle normal fault. Our results allow to identify younger normal fault segments, to analyse their kinematics, growth and segment linkage, and to discuss its role on the structural and relief drop at regional scale. The Colmenar Fault is folded by post-Serravallian NE-SW buckle folds. Both the SW-dipping fault surfaces and the SW-plunging fold axes contribute to the structural relief drop toward the SW. Nevertheless, at the NW tip of the Colmenar Fault, we have identified unfolded normal faults cutting quaternary soils. They are grouped into a N110˚E striking brittle deformation band 15km long and until 3km wide (hereafter Ubrique Normal Fault Zone; UNFZ). The UNFZ is divided into three sectors: (a) The western tip zone is formed by normal faults which usually dip to the SW and whose slip directions vary between N205˚E and N225˚E. These segments are linked to each other by left-lateral oblique faults interpreted as transfer faults. (b) The central part of the UNFZ is composed of a single N115˚E striking fault segment 2,4km long. Slip directions are around N190˚E and the estimated throw is 1,25km. The fault scarp is well-conserved reaching up to 400m in its central part and diminishing to 200m at both segment terminations. This fault segment is linked to the western tip by an overlap zone characterized by tilted blocks limited by high-angle NNE-SSW and WNW-ESE striking faults interpreted as "box faults" [1]. (c) The eastern tip zone is formed by fault segments with oblique slip which also contribute to the downthrown of the SW block. This kinematic pattern seems to be related to other strike-slip fault systems developed to the E of the UNFZ. The structural revision together with updated kinematic data suggest that the Colmenar Fault is cut and downthrown by a younger normal fault zone, the UNFZ, which would have contributed to accommodate arc-parallel stretching until the Quaternary. This stretching provokes along-strike relief segmentation, being the UNFZ the main fault zone causing the final drop of the Subbetic ranges towards the SW within the Western Gibraltar Arc. Our results show displacement variations in each fault segment of the UNFZ, diminishing to their tips. This suggests fault segment linkage finally evolved to build the nearly continuous current fault zone. The development of current large through-going faults linked inside the UNFZ is similar to those ones simulated in some numerical modelling of rift systems [2]. Acknowledgements: RNM-415 and CGL-2013-46368-P [1]Peacock, D.C.P., Knipe, R.J., Sanderson, D.J., 2000. Glossary of normal faults. Journal Structural Geology, 22, 291-305. [2]Cowie, P.A., Gupta, S., Dawers, N.H., 2000. Implications of fault array evolution for synrift depocentre development: insights from a numerical fault growth model. Basin Research, 12, 241-261.

Identification of uncommon objects in containers

DOEpatents

Bremer, Peer-Timo; Kim, Hyojin; Thiagarajan, Jayaraman J.

2017-09-12

A system for identifying in an image an object that is commonly found in a collection of images and for identifying a portion of an image that represents an object based on a consensus analysis of segmentations of the image. The system collects images of containers that contain objects for generating a collection of common objects within the containers. To process the images, the system generates a segmentation of each image. The image analysis system may also generate multiple segmentations for each image by introducing variations in the selection of voxels to be merged into a segment. The system then generates clusters of the segments based on similarity among the segments. Each cluster represents a common object found in the containers. Once the clustering is complete, the system may be used to identify common objects in images of new containers based on similarity between segments of images and the clusters.

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

PubMed

Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

2018-02-19

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

The anterior segment disorder autosomal dominant keratitis is linked to the Aniridia/PAX-6 gene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mirzayans, F.; Pearce, W.G.; Mah, T.S.

1994-09-01

Autosomal dominant keratitis (ADK) is an eye disease characterized by anterior stromal corneal opacification and vascularization in the peripheral cornea. Progression into the central cornea may compromise visual acuity. Other anterior segment features include minimal radial defects of the iris stroma. Posterior segment involvement is characterized by foveal hypoplasia with minimal effect on visual acuity. Aniridia is a second autosomal dominantly inherited ocular disorder defined by structural defects of the iris, frequently severe enough to cause an almost complete absence of iris. This may be accompanied by other anterior segment manifestations, including cataract and keratitis. Posterior segment involvement in aniridiamore » is characterized by foveal hypoplasia resulting in a highly variable impairment of visual acuity, often with nystagmus. Aniridia is usually inherited as an autosomal dominant disease and occurs in 1 in 50,000 to 100,000 people. Aniridia has been shown to result from mutations in PAX-6, a gene thought to regulate fetal eye development. The similar clinical findings in ADK and aniridia, with the similar patterns of inheritance, compelled us to investigate if these two ocular disorders are variants of the same genetic disorder. We have tested for linkage between PAX-6 and ADK within an ADK family with 33 members over four generations, including 11 affected individuals. Linkage studies reveal that D11S914 (located within 3 cM of PAX-6) does not recombine with ADK (LOD score 3.61; {theta} = 0.00), consistent with PAX-6 mutations being responsible for ADK. Direct sequencing of PAX-6 RT-PCR products from ADK patients is underway to identify the mutation within the PAX-6 gene that results in ADK. The linkage of PAX-6 with ADK, along with a recent report that mutations in PAX-6 also underlie Peter`s anomaly, implicates PAX-6 widely in anterior segment malformations.« less

Topology polymorphism graph for lung tumor segmentation in PET-CT images.

PubMed

Cui, Hui; Wang, Xiuying; Zhou, Jianlong; Eberl, Stefan; Yin, Yong; Feng, Dagan; Fulham, Michael

2015-06-21

Accurate lung tumor segmentation is problematic when the tumor boundary or edge, which reflects the advancing edge of the tumor, is difficult to discern on chest CT or PET. We propose a 'topo-poly' graph model to improve identification of the tumor extent. Our model incorporates an intensity graph and a topology graph. The intensity graph provides the joint PET-CT foreground similarity to differentiate the tumor from surrounding tissues. The topology graph is defined on the basis of contour tree to reflect the inclusion and exclusion relationship of regions. By taking into account different topology relations, the edges in our model exhibit topological polymorphism. These polymorphic edges in turn affect the energy cost when crossing different topology regions under a random walk framework, and hence contribute to appropriate tumor delineation. We validated our method on 40 patients with non-small cell lung cancer where the tumors were manually delineated by a clinical expert. The studies were separated into an 'isolated' group (n = 20) where the lung tumor was located in the lung parenchyma and away from associated structures / tissues in the thorax and a 'complex' group (n = 20) where the tumor abutted / involved a variety of adjacent structures and had heterogeneous FDG uptake. The methods were validated using Dice's similarity coefficient (DSC) to measure the spatial volume overlap and Hausdorff distance (HD) to compare shape similarity calculated as the maximum surface distance between the segmentation results and the manual delineations. Our method achieved an average DSC of 0.881 ± 0.046 and HD of 5.311 ± 3.022 mm for the isolated cases and DSC of 0.870 ± 0.038 and HD of 9.370 ± 3.169 mm for the complex cases. Student's t-test showed that our model outperformed the other methods (p-values <0.05).

Segmented molecular design of self-healing proteinaceous materials

PubMed Central

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C.

2015-01-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure–property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials. PMID:26323335

Genealogy of an ancient protein family: the Sirtuins, a family of disordered members.

PubMed

Costantini, Susan; Sharma, Ankush; Raucci, Raffaele; Costantini, Maria; Autiero, Ida; Colonna, Giovanni

2013-03-05

Sirtuins genes are widely distributed by evolution and have been found in eubacteria, archaea and eukaryotes. While prokaryotic and archeal species usually have one or two sirtuin homologs, in humans as well as in eukaryotes we found multiple versions and in mammals this family is comprised of seven different homologous proteins being all NAD-dependent de-acylases. 3D structures of human SIRT2, SIRT3, and SIRT5 revealed the overall conformation of the conserved core domain but they were unable to give a structural information about the presence of very flexible and dynamically disordered regions, the role of which is still structurally and functionally unclear. Recently, we modeled the 3D-structure of human SIRT1, the most studied member of this family, that unexpectedly emerged as a member of the intrinsically disordered proteins with its long disordered terminal arms. Despite clear similarities in catalytic cores between the human sirtuins little is known of the general structural characteristics of these proteins. The presence of disorder in human SIRT1 and the propensity of these proteins in promoting molecular interactions make it important to understand the underlying mechanisms of molecular recognition that reasonably should involve terminal segments. The mechanism of recognition, in turn, is a prerequisite for the understanding of any functional activity. Aim of this work is to understand what structural properties are shared among members of this family in humans as well as in other organisms. We have studied the distribution of the structural features of N- and C-terminal segments of sirtuins in all known organisms to draw their evolutionary histories by taking into account average length of terminal segments, amino acid composition, intrinsic disorder, presence of charged stretches, presence of putative phosphorylation sites, flexibility, and GC content of genes. Finally, we have carried out a comprehensive analysis of the putative phosphorylation sites in human sirtuins confirming those sites already known experimentally for human SIRT1 and 2 as well as extending their topology to all the family to get feedback of their physiological functions and cellular localization. Our results highlight that the terminal segments of the majority of sirtuins possess a number of structural features and chemical and physical properties that strongly support their involvement in activities of recognition and interaction with other protein molecules. We also suggest how a multisite phosphorylation provides a possible mechanism by which flexible and intrinsically disordered segments of a sirtuin supported by the presence of positively or negatively charged stretches might enhance the strength and specificity of interaction with a particular molecular partner.

Vessel segmentation in 4D arterial spin labeling magnetic resonance angiography images of the brain

NASA Astrophysics Data System (ADS)

Phellan, Renzo; Lindner, Thomas; Falcão, Alexandre X.; Forkert, Nils D.

2017-03-01

4D arterial spin labeling magnetic resonance angiography (4D ASL MRA) is a non-invasive and safe modality for cerebrovascular imaging procedures. It uses the patient's magnetically labeled blood as intrinsic contrast agent, so that no external contrast media is required. It provides important 3D structure and blood flow information but a sufficient cerebrovascular segmentation is important since it can help clinicians to analyze and diagnose vascular diseases faster, and with higher confidence as compared to simple visual rating of raw ASL MRA images. This work presents a new method for automatic cerebrovascular segmentation in 4D ASL MRA images of the brain. In this process images are denoised, corresponding image label/control image pairs of the 4D ASL MRA sequences are subtracted, and temporal intensity averaging is used to generate a static representation of the vascular system. After that, sets of vessel and background seeds are extracted and provided as input for the image foresting transform algorithm to segment the vascular system. Four 4D ASL MRA datasets of the brain arteries of healthy subjects and corresponding time-of-flight (TOF) MRA images were available for this preliminary study. For evaluation of the segmentation results of the proposed method, the cerebrovascular system was automatically segmented in the high-resolution TOF MRA images using a validated algorithm and the segmentation results were registered to the 4D ASL datasets. Corresponding segmentation pairs were compared using the Dice similarity coefficient (DSC). On average, a DSC of 0.9025 was achieved, indicating that vessels can be extracted successfully from 4D ASL MRA datasets by the proposed segmentation method.

Improving Spleen Volume Estimation via Computer Assisted Segmentation on Clinically Acquired CT Scans

PubMed Central

Xu, Zhoubing; Gertz, Adam L.; Burke, Ryan P.; Bansal, Neil; Kang, Hakmook; Landman, Bennett A.; Abramson, Richard G.

2016-01-01

OBJECTIVES Multi-atlas fusion is a promising approach for computer-assisted segmentation of anatomical structures. The purpose of this study was to evaluate the accuracy and time efficiency of multi-atlas segmentation for estimating spleen volumes on clinically-acquired CT scans. MATERIALS AND METHODS Under IRB approval, we obtained 294 deidentified (HIPAA-compliant) abdominal CT scans on 78 subjects from a recent clinical trial. We compared five pipelines for obtaining splenic volumes: Pipeline 1–manual segmentation of all scans, Pipeline 2–automated segmentation of all scans, Pipeline 3–automated segmentation of all scans with manual segmentation for outliers on a rudimentary visual quality check, Pipelines 4 and 5–volumes derived from a unidimensional measurement of craniocaudal spleen length and three-dimensional splenic index measurements, respectively. Using Pipeline 1 results as ground truth, the accuracy of Pipelines 2–5 (Dice similarity coefficient [DSC], Pearson correlation, R-squared, and percent and absolute deviation of volume from ground truth) were compared for point estimates of splenic volume and for change in splenic volume over time. Time cost was also compared for Pipelines 1–5. RESULTS Pipeline 3 was dominant in terms of both accuracy and time cost. With a Pearson correlation coefficient of 0.99, average absolute volume deviation 23.7 cm3, and 1 minute per scan, Pipeline 3 yielded the best results. The second-best approach was Pipeline 5, with a Pearson correlation coefficient 0.98, absolute deviation 46.92 cm3, and 1 minute 30 seconds per scan. Manual segmentation (Pipeline 1) required 11 minutes per scan. CONCLUSION A computer-automated segmentation approach with manual correction of outliers generated accurate splenic volumes with reasonable time efficiency. PMID:27519156

Correlation-based discrimination between cardiac tissue and blood for segmentation of 3D echocardiographic images

NASA Astrophysics Data System (ADS)

Saris, Anne E. C. M.; Nillesen, Maartje M.; Lopata, Richard G. P.; de Korte, Chris L.

2013-03-01

Automated segmentation of 3D echocardiographic images in patients with congenital heart disease is challenging, because the boundary between blood and cardiac tissue is poorly defined in some regions. Cardiologists mentally incorporate movement of the heart, using temporal coherence of structures to resolve ambiguities. Therefore, we investigated the merit of temporal cross-correlation for automated segmentation over the entire cardiac cycle. Optimal settings for maximum cross-correlation (MCC) calculation, based on a 3D cross-correlation based displacement estimation algorithm, were determined to obtain the best contrast between blood and myocardial tissue over the entire cardiac cycle. Resulting envelope-based as well as RF-based MCC values were used as additional external force in a deformable model approach, to segment the left-ventricular cavity in entire systolic phase. MCC values were tested against, and combined with, adaptive filtered, demodulated RF-data. Segmentation results were compared with manually segmented volumes using a 3D Dice Similarity Index (3DSI). Results in 3D pediatric echocardiographic images sequences (n = 4) demonstrate that incorporation of temporal information improves segmentation. The use of MCC values, either alone or in combination with adaptive filtered, demodulated RF-data, resulted in an increase of the 3DSI in 75% of the cases (average 3DSI increase: 0.71 to 0.82). Results might be further improved by optimizing MCC-contrast locally, in regions with low blood-tissue contrast. Reducing underestimation of the endocardial volume due to MCC processing scheme (choice of window size) and consequential border-misalignment, could also lead to more accurate segmentations. Furthermore, increasing the frame rate will also increase MCC-contrast and thus improve segmentation.

A prior feature SVM – MRF based method for mouse brain segmentation

PubMed Central

Wu, Teresa; Bae, Min Hyeok; Zhang, Min; Pan, Rong; Badea, Alexandra

2012-01-01

We introduce an automated method, called prior feature Support Vector Machine- Markov Random Field (pSVMRF), to segment three-dimensional mouse brain Magnetic Resonance Microscopy (MRM) images. Our earlier work, extended MRF (eMRF) integrated Support Vector Machine (SVM) and Markov Random Field (MRF) approaches, leading to improved segmentation accuracy; however, the computation of eMRF is very expensive, which may limit its performance on segmentation and robustness. In this study pSVMRF reduces training and testing time for SVM, while boosting segmentation performance. Unlike the eMRF approach, where MR intensity information and location priors are linearly combined, pSVMRF combines this information in a nonlinear fashion, and enhances the discriminative ability of the algorithm. We validate the proposed method using MR imaging of unstained and actively stained mouse brain specimens, and compare segmentation accuracy with two existing methods: eMRF and MRF. C57BL/6 mice are used for training and testing, using cross validation. For formalin fixed C57BL/6 specimens, pSVMRF outperforms both eMRF and MRF. The segmentation accuracy for C57BL/6 brains, stained or not, was similar for larger structures like hippocampus and caudate putamen, (~87%), but increased substantially for smaller regions like susbtantia nigra (from 78.36% to 91.55%), and anterior commissure (from ~50% to ~80%). To test segmentation robustness against increased anatomical variability we add two strains, BXD29 and a transgenic mouse model of Alzheimer’s Disease. Segmentation accuracy for new strains is 80% for hippocampus, and caudate putamen, indicating that pSVMRF is a promising approach for phenotyping mouse models of human brain disorders. PMID:21988893

A prior feature SVM-MRF based method for mouse brain segmentation.

PubMed

Wu, Teresa; Bae, Min Hyeok; Zhang, Min; Pan, Rong; Badea, Alexandra

2012-02-01

We introduce an automated method, called prior feature Support Vector Machine-Markov Random Field (pSVMRF), to segment three-dimensional mouse brain Magnetic Resonance Microscopy (MRM) images. Our earlier work, extended MRF (eMRF) integrated Support Vector Machine (SVM) and Markov Random Field (MRF) approaches, leading to improved segmentation accuracy; however, the computation of eMRF is very expensive, which may limit its performance on segmentation and robustness. In this study pSVMRF reduces training and testing time for SVM, while boosting segmentation performance. Unlike the eMRF approach, where MR intensity information and location priors are linearly combined, pSVMRF combines this information in a nonlinear fashion, and enhances the discriminative ability of the algorithm. We validate the proposed method using MR imaging of unstained and actively stained mouse brain specimens, and compare segmentation accuracy with two existing methods: eMRF and MRF. C57BL/6 mice are used for training and testing, using cross validation. For formalin fixed C57BL/6 specimens, pSVMRF outperforms both eMRF and MRF. The segmentation accuracy for C57BL/6 brains, stained or not, was similar for larger structures like hippocampus and caudate putamen, (~87%), but increased substantially for smaller regions like susbtantia nigra (from 78.36% to 91.55%), and anterior commissure (from ~50% to ~80%). To test segmentation robustness against increased anatomical variability we add two strains, BXD29 and a transgenic mouse model of Alzheimer's disease. Segmentation accuracy for new strains is 80% for hippocampus, and caudate putamen, indicating that pSVMRF is a promising approach for phenotyping mouse models of human brain disorders. Copyright © 2011 Elsevier Inc. All rights reserved.

Segmentation of dermatoscopic images by frequency domain filtering and k-means clustering algorithms.

PubMed

Rajab, Maher I

2011-11-01

Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, in an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early and non-invasive diagnosis of coetaneous melanomas. This paper proposes two image segmentation algorithms based on frequency domain processing and k-means clustering/fuzzy k-means clustering. The two methods are capable of segmenting and extracting the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. As a pre-processing step, Fourier low-pass filtering is applied to reduce the surrounding noise in a skin lesion image. A quantitative comparison of the techniques is enabled by the use of synthetic skin lesion images that model lesions covered with hair to which Gaussian noise is added. The proposed techniques are also compared with an established optimal-based thresholding skin-segmentation method. It is demonstrated that for lesions with a range of different border irregularity properties, the k-means clustering and fuzzy k-means clustering segmentation methods provide the best performance over a range of signal to noise ratios. The proposed segmentation techniques are also demonstrated to have similar performance when tested on real skin lesions representing high-resolution ELM images. This study suggests that the segmentation results obtained using a combination of low-pass frequency filtering and k-means or fuzzy k-means clustering are superior to the result that would be obtained by using k-means or fuzzy k-means clustering segmentation methods alone. © 2011 John Wiley & Sons A/S.

Apparatus and method for plasma processing of SRF cavities

NASA Astrophysics Data System (ADS)

Upadhyay, J.; Im, Do; Peshl, J.; Bašović, M.; Popović, S.; Valente-Feliciano, A.-M.; Phillips, L.; Vušković, L.

2016-05-01

An apparatus and a method are described for plasma etching of the inner surface of superconducting radio frequency (SRF) cavities. Accelerator SRF cavities are formed into a variable-diameter cylindrical structure made of bulk niobium, for resonant generation of the particle accelerating field. The etch rate non-uniformity due to depletion of the radicals has been overcome by the simultaneous movement of the gas flow inlet and the inner electrode. An effective shape of the inner electrode to reduce the plasma asymmetry for the coaxial cylindrical rf plasma reactor is determined and implemented in the cavity processing method. The processing was accomplished by moving axially the inner electrode and the gas flow inlet in a step-wise way to establish segmented plasma columns. The test structure was a pillbox cavity made of steel of similar dimension to the standard SRF cavity. This was adopted to experimentally verify the plasma surface reaction on cylindrical structures with variable diameter using the segmented plasma generation approach. The pill box cavity is filled with niobium ring- and disk-type samples and the etch rate of these samples was measured.

Nanoscale Structure of Urethane/Urea Elastomeric Films

NASA Astrophysics Data System (ADS)

Reis, Dennys; Trindade, Ana C.; Godinho, Maria Helena; Silva, Laura C.; do Carmo Gonçalves, Maria; Neto, Antônio M. Figueiredo

2017-02-01

The nanostructure of urethane/urea elastomeric membranes was investigated by small-angle X-ray scattering (SAXS) in order to establish relationships between their structure and mechanical properties. The networks were made up of polypropylene oxide (PPO) and polybutadiene (PB) segments. The structural differences were investigated in two types of membranes with the same composition but with different thermal treatment after casting. Type I was cured at 70-80 °C and type II at 20 °C. Both membranes showed similar phase separation by TEM, with nanodomains rich in PB or PPO and 25 nm dimensions. The main difference between type I and type II membranes was found by SAXS. The type I membrane spectra showed, besides a broad band at a 27-nm q value (modulus of the scattering vector), an extra band at 6 nm, which was not observed in the type II membrane. The SAXS spectra were interpreted in terms of PPO, PB soft segments, and urethane/urea links, as well as hard moiety segregation in the reaction medium. This additional segregation ( q = 7 nm), although subtle, results in diverse mechanical behavior of in both membranes.

Crystal structure of the V(D)J recombinase RAG1–RAG2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Min-Sung; Lapkouski, Mikalai; Yang, Wei

2016-04-29

V(D)J recombination in the vertebrate immune system generates a highly diverse population of immunoglobulins and T-cell receptors by combinatorial joining of segments of coding DNA. The RAG1–RAG2 protein complex initiates this site-specific recombination by cutting DNA at specific sites flanking the coding segments. Here we report the crystal structure of the mouse RAG1–RAG2 complex at 3.2 Å resolution. The 230-kilodalton RAG1–RAG2 heterotetramer is ‘Y-shaped’, with the amino-terminal domains of the two RAG1 chains forming an intertwined stalk. Each RAG1–RAG2 heterodimer composes one arm of the ‘Y’, with the active site in the middle and RAG2 at its tip. The RAG1–RAG2more » structure rationalizes more than 60 mutations identified in immunodeficient patients, as well as a large body of genetic and biochemical data. The architectural similarity between RAG1 and the hairpin-forming transposases Hermes and Tn5 suggests the evolutionary conservation of these DNA rearrangements.« less

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

PubMed

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Automated condition-invariable neurite segmentation and synapse classification using textural analysis-based machine-learning algorithms

PubMed Central

Kandaswamy, Umasankar; Rotman, Ziv; Watt, Dana; Schillebeeckx, Ian; Cavalli, Valeria; Klyachko, Vitaly

2013-01-01

High-resolution live-cell imaging studies of neuronal structure and function are characterized by large variability in image acquisition conditions due to background and sample variations as well as low signal-to-noise ratio. The lack of automated image analysis tools that can be generalized for varying image acquisition conditions represents one of the main challenges in the field of biomedical image analysis. Specifically, segmentation of the axonal/dendritic arborizations in brightfield or fluorescence imaging studies is extremely labor-intensive and still performed mostly manually. Here we describe a fully automated machine-learning approach based on textural analysis algorithms for segmenting neuronal arborizations in high-resolution brightfield images of live cultured neurons. We compare performance of our algorithm to manual segmentation and show that it combines 90% accuracy, with similarly high levels of specificity and sensitivity. Moreover, the algorithm maintains high performance levels under a wide range of image acquisition conditions indicating that it is largely condition-invariable. We further describe an application of this algorithm to fully automated synapse localization and classification in fluorescence imaging studies based on synaptic activity. Textural analysis-based machine-learning approach thus offers a high performance condition-invariable tool for automated neurite segmentation. PMID:23261652

Segmenting patients and physicians using preferences from discrete choice experiments.

PubMed

Deal, Ken

2014-01-01

People often form groups or segments that have similar interests and needs and seek similar benefits from health providers. Health organizations need to understand whether the same health treatments, prevention programs, services, and products should be applied to everyone in the relevant population or whether different treatments need to be provided to each of several segments that are relatively homogeneous internally but heterogeneous among segments. Our objective was to explain the purposes, benefits, and methods of segmentation for health organizations, and to illustrate the process of segmenting health populations based on preference coefficients from a discrete choice conjoint experiment (DCE) using an example study of prevention of cyberbullying among university students. We followed a two-level procedure for investigating segmentation incorporating several methods for forming segments in Level 1 using DCE preference coefficients and testing their quality, reproducibility, and usability by health decision makers. Covariates (demographic, behavioral, lifestyle, and health state variables) were included in Level 2 to further evaluate quality and to support the scoring of large databases and developing typing tools for assigning those in the relevant population, but not in the sample, to the segments. Several segmentation solution candidates were found during the Level 1 analysis, and the relationship of the preference coefficients to the segments was investigated using predictive methods. Those segmentations were tested for their quality and reproducibility and three were found to be very close in quality. While one seemed better than others in the Level 1 analysis, another was very similar in quality and proved ultimately better in predicting segment membership using covariates in Level 2. The two segments in the final solution were profiled for attributes that would support the development and acceptance of cyberbullying prevention programs among university students. Those segments were very different-where one wanted substantial penalties against cyberbullies and were willing to devote time to a prevention program, while the other felt no need to be involved in prevention and wanted only minor penalties. Segmentation recognizes key differences in why patients and physicians prefer different health programs and treatments. A viable segmentation solution may lead to adapting prevention programs and treatments for each targeted segment and/or to educating and communicating to better inform those in each segment of the program/treatment benefits. Segment members' revealed preferences showing behavioral changes provide the ultimate basis for evaluating the segmentation benefits to the health organization.

Inter-segmental motions of the foot: differences between younger and older healthy adult females.

PubMed

Lee, Dong Yeon; Seo, Sang Gyo; Kim, Eo Jin; Lee, Doo Jae; Bae, Kee Jeong; Lee, Kyoung Min; Choi, In Ho

2017-01-01

Although accumulative evidence exists that support the applicability of multi-segmental foot models (MFMs) in evaluating foot motion in various pathologic conditions, little is known of the effect of aging on inter-segmental foot motion. The objective of this study was to evaluate differences in inter-segmental motion of the foot between older and younger adult healthy females during gait using a MFM with 15-marker set. One hundred symptom-free females, who had no radiographic evidence of osteoarthritis, were evaluated using MFM with 15-marker set. They were divided into young ( n  = 50, 20-35 years old) and old ( n  = 50, 60-69 years old) groups. Coefficients of multiple correlations were evaluated to assess the similarity of kinematic curve. Inter-segmental angles (hindfoot, forefoot, and hallux) were calculated at each gait phase. To evaluate the effect of gait speed on intersegmental foot motion, subgroup analysis was performed according to the similar speed of walking. Kinematic curves showed good or excellent similarity in most parameters. Range of motion in the sagittal ( p  < 0.001) and transverse ( p  = 0.001) plane of the hallux, and sagittal ( p  = 0.023) plane of the forefoot was lower in older females. The dorsiflexion ( p  = 0.001) of the hallux at terminal stance and pre-swing phases was significantly lower in older females. When we compared young and older females with similar speed, these differences remained. Although the overall kinematic pattern was similar between young and older females, reduced range of inter-segmental motion was observed in the older group. Our results suggest that age-related changes need to be considered in studies evaluating inter-segmental motion of the foot.

Assessing the viability of situationally driven segmentation opportunities in the health care market.

PubMed

Gehrt, K C; Pinto, M B

1993-01-01

The impact of situational factors has typically been investigated in the context of goods marketing. Very few studies have investigated the influence of situational factors on services marketing. This study demonstrates the importance of situational influence on services marketing by delineating a consumer-based, situationally characterized competitive market structure for health care services. The competitive structure of the health care market is delineated in terms of the similarity/substitutability of the three-factor, situational characterizations of ten health care alternatives. The general marketing implications of the market-structure delineation procedure and the health care-specific implications of the findings are discussed.

Computation-Guided Backbone Grafting of a Discontinuous Motif onto a Protein Scaffold

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azoitei, Mihai L.; Correia, Bruno E.; Ban, Yih-En Andrew

2012-02-07

The manipulation of protein backbone structure to control interaction and function is a challenge for protein engineering. We integrated computational design with experimental selection for grafting the backbone and side chains of a two-segment HIV gp120 epitope, targeted by the cross-neutralizing antibody b12, onto an unrelated scaffold protein. The final scaffolds bound b12 with high specificity and with affinity similar to that of gp120, and crystallographic analysis of a scaffold bound to b12 revealed high structural mimicry of the gp120-b12 complex structure. The method can be generalized to design other functional proteins through backbone grafting.

Line drawing extraction from gray level images by feature integration

NASA Astrophysics Data System (ADS)

Yoo, Hoi J.; Crevier, Daniel; Lepage, Richard; Myler, Harley R.

1994-10-01

We describe procedures that extract line drawings from digitized gray level images, without use of domain knowledge, by modeling preattentive and perceptual organization functions of the human visual system. First, edge points are identified by standard low-level processing, based on the Canny edge operator. Edge points are then linked into single-pixel thick straight- line segments and circular arcs: this operation serves to both filter out isolated and highly irregular segments, and to lump the remaining points into a smaller number of structures for manipulation by later stages of processing. The next stages consist in linking the segments into a set of closed boundaries, which is the system's definition of a line drawing. According to the principles of Gestalt psychology, closure allows us to organize the world by filling in the gaps in a visual stimulation so as to perceive whole objects instead of disjoint parts. To achieve such closure, the system selects particular features or combinations of features by methods akin to those of preattentive processing in humans: features include gaps, pairs of straight or curved parallel lines, L- and T-junctions, pairs of symmetrical lines, and the orientation and length of single lines. These preattentive features are grouped into higher-level structures according to the principles of proximity, similarity, closure, symmetry, and feature conjunction. Achieving closure may require supplying missing segments linking contour concavities. Choices are made between competing structures on the basis of their overall compliance with the principles of closure and symmetry. Results include clean line drawings of curvilinear manufactured objects. The procedures described are part of a system called VITREO (viewpoint-independent 3-D recognition and extraction of objects).

Structure of the Mecl Repressor from Staphylococcus aureus in Complex with the Cognate DNA Operator of mec

DOE Office of Scientific and Technical Information (OSTI.GOV)

Safo,M.; Ko, T.; Musayev, F.

The dimeric repressor MecI regulates the mecA gene that encodes the penicillin-binding protein PBP-2a in methicillin-resistant Staphylococcus aureus (MRSA). MecI is similar to BlaI, the repressor for the blaZ gene of {beta}-lactamase. MecI and BlaI can bind to both operator DNA sequences. The crystal structure of MecI in complex with the 32 base-pair cognate DNA of mec was determined to 3.8 Angstroms resolution. MecI is a homodimer and each monomer consists of a compact N-terminal winged-helix domain, which binds to DNA, and a loosely packed C-terminal helical domain, which intertwines with its counter-monomer. The crystal contains horizontal layers of virtualmore » DNA double helices extending in three directions, which are separated by perpendicular DNA segments. Each DNA segment is bound to two MecI dimers. Similar to the BlaI-mec complex, but unlike the MecI-bla complex, the MecI repressors bind to both sides of the mec DNA dyad that contains four conserved sequences of TACA/TGTA. The results confirm the up-and-down binding to the mec operator, which may account for cooperative effect of the repressor.« less

Pulmonary parenchyma segmentation in thin CT image sequences with spectral clustering and geodesic active contour model based on similarity

NASA Astrophysics Data System (ADS)

He, Nana; Zhang, Xiaolong; Zhao, Juanjuan; Zhao, Huilan; Qiang, Yan

2017-07-01

While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic active contour model that is geodesic active contour model based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.

Superpixel-based segmentation of muscle fibers in multi-channel microscopy.

PubMed

Nguyen, Binh P; Heemskerk, Hans; So, Peter T C; Tucker-Kellogg, Lisa

2016-12-05

Confetti fluorescence and other multi-color genetic labelling strategies are useful for observing stem cell regeneration and for other problems of cell lineage tracing. One difficulty of such strategies is segmenting the cell boundaries, which is a very different problem from segmenting color images from the real world. This paper addresses the difficulties and presents a superpixel-based framework for segmentation of regenerated muscle fibers in mice. We propose to integrate an edge detector into a superpixel algorithm and customize the method for multi-channel images. The enhanced superpixel method outperforms the original and another advanced superpixel algorithm in terms of both boundary recall and under-segmentation error. Our framework was applied to cross-section and lateral section images of regenerated muscle fibers from confetti-fluorescent mice. Compared with "ground-truth" segmentations, our framework yielded median Dice similarity coefficients of 0.92 and higher. Our segmentation framework is flexible and provides very good segmentations of multi-color muscle fibers. We anticipate our methods will be useful for segmenting a variety of tissues in confetti fluorecent mice and in mice with similar multi-color labels.

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word "data-mining" is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word “data-mining” is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

Sequence Segmentation with changeptGUI.

PubMed

Tasker, Edward; Keith, Jonathan M

2017-01-01

Many biological sequences have a segmental structure that can provide valuable clues to their content, structure, and function. The program changept is a tool for investigating the segmental structure of a sequence, and can also be applied to multiple sequences in parallel to identify a common segmental structure, thus providing a method for integrating multiple data types to identify functional elements in genomes. In the previous edition of this book, a command line interface for changept is described. Here we present a graphical user interface for this package, called changeptGUI. This interface also includes tools for pre- and post-processing of data and results to facilitate investigation of the number and characteristics of segment classes.

Automated segmentation of murine lung tumors in x-ray micro-CT images

NASA Astrophysics Data System (ADS)

Swee, Joshua K. Y.; Sheridan, Clare; de Bruin, Elza; Downward, Julian; Lassailly, Francois; Pizarro, Luis

2014-03-01

Recent years have seen micro-CT emerge as a means of providing imaging analysis in pre-clinical study, with in-vivo micro-CT having been shown to be particularly applicable to the examination of murine lung tumors. Despite this, existing studies have involved substantial human intervention during the image analysis process, with the use of fully-automated aids found to be almost non-existent. We present a new approach to automate the segmentation of murine lung tumors designed specifically for in-vivo micro-CT-based pre-clinical lung cancer studies that addresses the specific requirements of such study, as well as the limitations human-centric segmentation approaches experience when applied to such micro-CT data. Our approach consists of three distinct stages, and begins by utilizing edge enhancing and vessel enhancing non-linear anisotropic diffusion filters to extract anatomy masks (lung/vessel structure) in a pre-processing stage. Initial candidate detection is then performed through ROI reduction utilizing obtained masks and a two-step automated segmentation approach that aims to extract all disconnected objects within the ROI, and consists of Otsu thresholding, mathematical morphology and marker-driven watershed. False positive reduction is finally performed on initial candidates through random-forest-driven classification using the shape, intensity, and spatial features of candidates. We provide validation of our approach using data from an associated lung cancer study, showing favorable results both in terms of detection (sensitivity=86%, specificity=89%) and structural recovery (Dice Similarity=0.88) when compared against manual specialist annotation.

Altered lumbar spine structure, biochemistry and biomechanical properties in a canine model of mucopolysaccharidosis type VII

PubMed Central

Smith, Lachlan J; Martin, John T; Szczesny, Spencer E; Ponder, Katherine P; Haskins, Mark E; Elliott, Dawn M

2010-01-01

Mucopolysaccharidosis VII (MPS VII) is a lysosomal storage disorder characterized by a deficiency in β-glucuronidase activity, leading to systemic accumulation of poorly degraded glycosaminoglycans (GAG). Along with other morbidities, MPS VII is associated with paediatric spinal deformity. The objective of this study was to examine potential associations between abnormal lumbar spine matrix structure and composition in MPS VII, and spine segment and tissue-level mechanical properties, using a naturally occurring canine model with a similar clinical phenotype to the human form of the disorder. Segments from juvenile MPS VII and unaffected dogs were allocated to: radiography, gross morphology, histology, biochemistry, and mechanical testing. MPS VII spines had radiolucent lesions in the vertebral body epiphyses. Histologically, this corresponded to a GAG-rich cartilaginous region in place of bone, and elevated GAG staining was seen in the annulus fibrosus. Biochemically, MPS VII samples had elevated GAG in the outer annulus fibrosus and epiphyses, low calcium in the epiphyses, and high water content in all regions except the nucleus pulposus. MPS VII spine segments had higher range of motion and lower stiffness than controls. Endplate indentation stiffness and failure loads were significantly lower in MPS VII samples, while annulus fibrosus tensile mechanical properties were normal. Vertebral body lesions in MPS VII spines suggest a failure to convert cartilage to bone during development. Low stiffness in these regions likely contributes to mechanical weakness in motion segments and is a potential factor in the progression of spinal deformity. PMID:19918911

Complete genomic sequence of an infectious pancreatic necrosis virus isolated from rainbow trout (Oncorhynchus mykiss) in China.

PubMed

Ji, Feng; Zhao, Jing-Zhuang; Liu, Miao; Lu, Tong-Yan; Liu, Hong-Bai; Yin, Jiasheng; Xu, Li-Ming

2017-04-01

Infectious pancreatic necrosis (IPN) is a significant disease of farmed salmonids resulting in direct economic losses due to high mortality in China. However, no gene sequence of any Chinese infectious pancreatic necrosis virus (IPNV) isolates was available. In the study, moribund rainbow trout fry samples were collected during an outbreak of IPN in Yunnan province of southwest China in 2013. An IPNV was isolated and tentatively named ChRtm213. We determined the full genome sequence of the IPNV ChRtm213 and compared it with previously identified IPNV sequences worldwide. The sequences of different structural and non-structural protein genes were compared to those of other aquatic birnaviruses sequenced to date. The results indicated that the complete genome sequence of ChRtm213 strain contains a segment A (3099 nucleotides) coding a polyprotein VP2-VP4-VP3, and a segment B (2789 nucleotides) coding a RNA-dependent RNA polymerase VP1. The phylogenetic analyses showed that ChRtm213 strain fell within genogroup 1, serotype A9 (Jasper), having similarities of 96.3% (segment A) and 97.3% (segment B) with the IPNV strain AM98 from Japan. The results suggest that the Chinese IPNV isolate has relative closer relationship with Japanese IPNV strains. The sequence of ChRtm213 was the first gene sequence of IPNV isolates in China. This study provided a robust reference for diagnosis and/or control of IPNV prevalent in China.

Automatic lung segmentation using control feedback system: morphology and texture paradigm.

PubMed

Noor, Norliza M; Than, Joel C M; Rijal, Omar M; Kassim, Rosminah M; Yunus, Ashari; Zeki, Amir A; Anzidei, Michele; Saba, Luca; Suri, Jasjit S

2015-03-01

Interstitial Lung Disease (ILD) encompasses a wide array of diseases that share some common radiologic characteristics. When diagnosing such diseases, radiologists can be affected by heavy workload and fatigue thus decreasing diagnostic accuracy. Automatic segmentation is the first step in implementing a Computer Aided Diagnosis (CAD) that will help radiologists to improve diagnostic accuracy thereby reducing manual interpretation. Automatic segmentation proposed uses an initial thresholding and morphology based segmentation coupled with feedback that detects large deviations with a corrective segmentation. This feedback is analogous to a control system which allows detection of abnormal or severe lung disease and provides a feedback to an online segmentation improving the overall performance of the system. This feedback system encompasses a texture paradigm. In this study we studied 48 males and 48 female patients consisting of 15 normal and 81 abnormal patients. A senior radiologist chose the five levels needed for ILD diagnosis. The results of segmentation were displayed by showing the comparison of the automated and ground truth boundaries (courtesy of ImgTracer™ 1.0, AtheroPoint™ LLC, Roseville, CA, USA). The left lung's performance of segmentation was 96.52% for Jaccard Index and 98.21% for Dice Similarity, 0.61 mm for Polyline Distance Metric (PDM), -1.15% for Relative Area Error and 4.09% Area Overlap Error. The right lung's performance of segmentation was 97.24% for Jaccard Index, 98.58% for Dice Similarity, 0.61 mm for PDM, -0.03% for Relative Area Error and 3.53% for Area Overlap Error. The segmentation overall has an overall similarity of 98.4%. The segmentation proposed is an accurate and fully automated system.

Accurate segmenting of cervical tumors in PET imaging based on similarity between adjacent slices.

PubMed

Chen, Liyuan; Shen, Chenyang; Zhou, Zhiguo; Maquilan, Genevieve; Thomas, Kimberly; Folkert, Michael R; Albuquerque, Kevin; Wang, Jing

2018-06-01

Because in PET imaging cervical tumors are close to the bladder with high capacity for the secreted 18 FDG tracer, conventional intensity-based segmentation methods often misclassify the bladder as a tumor. Based on the observation that tumor position and area do not change dramatically from slice to slice, we propose a two-stage scheme that facilitates segmentation. In the first stage, we used a graph-cut based algorithm to obtain initial contouring of the tumor based on local similarity information between voxels; this was achieved through manual contouring of the cervical tumor on one slice. In the second stage, initial tumor contours were fine-tuned to more accurate segmentation by incorporating similarity information on tumor shape and position among adjacent slices, according to an intensity-spatial-distance map. Experimental results illustrate that the proposed two-stage algorithm provides a more effective approach to segmenting cervical tumors in 3D 18 FDG PET images than the benchmarks used for comparison. Copyright © 2018 Elsevier Ltd. All rights reserved.

Wavelet energy-guided level set-based active contour: a segmentation method to segment highly similar regions.

PubMed

Achuthan, Anusha; Rajeswari, Mandava; Ramachandram, Dhanesh; Aziz, Mohd Ezane; Shuaib, Ibrahim Lutfi

2010-07-01

This paper introduces an approach to perform segmentation of regions in computed tomography (CT) images that exhibit intra-region intensity variations and at the same time have similar intensity distributions with surrounding/adjacent regions. In this work, we adapt a feature computed from wavelet transform called wavelet energy to represent the region information. The wavelet energy is embedded into a level set model to formulate the segmentation model called wavelet energy-guided level set-based active contour (WELSAC). The WELSAC model is evaluated using several synthetic and CT images focusing on tumour cases, which contain regions demonstrating the characteristics of intra-region intensity variations and having high similarity in intensity distributions with the adjacent regions. The obtained results show that the proposed WELSAC model is able to segment regions of interest in close correspondence with the manual delineation provided by the medical experts and to provide a solution for tumour detection. Copyright 2010 Elsevier Ltd. All rights reserved.

Individual bone structure segmentation and labeling from low-dose chest CT

NASA Astrophysics Data System (ADS)

Liu, Shuang; Xie, Yiting; Reeves, Anthony P.

2017-03-01

The segmentation and labeling of the individual bones serve as the first step to the fully automated measurement of skeletal characteristics and the detection of abnormalities such as skeletal deformities, osteoporosis, and vertebral fractures. Moreover, the identified landmarks on the segmented bone structures can potentially provide relatively reliable location reference to other non-rigid human organs, such as breast, heart and lung, thereby facilitating the corresponding image analysis and registration. A fully automated anatomy-directed framework for the segmentation and labeling of the individual bone structures from low-dose chest CT is presented in this paper. The proposed system consists of four main stages: First, both clavicles are segmented and labeled by fitting a piecewise cylindrical envelope. Second, the sternum is segmented under the spatial constraints provided by the segmented clavicles. Third, all ribs are segmented and labeled based on 3D region growing within the volume of interest defined with reference to the spinal canal centerline and lungs. Fourth, the individual thoracic vertebrae are segmented and labeled by image intensity based analysis in the spatial region constrained by the previously segmented bone structures. The system performance was validated with 1270 lowdose chest CT scans through visual evaluation. Satisfactory performance was obtained respectively in 97.1% cases for the clavicle segmentation and labeling, in 97.3% cases for the sternum segmentation, in 97.2% cases for the rib segmentation, in 94.2% cases for the rib labeling, in 92.4% cases for vertebra segmentation and in 89.9% cases for the vertebra labeling.

Segmenting Broadcast News Audiences in the New Media Environment.

ERIC Educational Resources Information Center

Wicks, Robert H.

1989-01-01

Examines the "benefit segmentation model," a marketing strategy for local news media which is capable of sorting consumers into discrete segments interested in similar salient product attributes or benefits. Concludes that benefit segmentation may provide a means by which news programmers may respond to their audience. (RS)

Segmentation of the pectoral muscle in breast MR images using structure tensor and deformable model

NASA Astrophysics Data System (ADS)

Lee, Myungeun; Kim, Jong Hyo

2012-02-01

Recently, breast MR images have been used in wider clinical area including diagnosis, treatment planning, and treatment response evaluation, which requests quantitative analysis and breast tissue segmentation. Although several methods have been proposed for segmenting MR images, segmenting out breast tissues robustly from surrounding structures in a wide range of anatomical diversity still remains challenging. Therefore, in this paper, we propose a practical and general-purpose approach for segmenting the pectoral muscle boundary based on the structure tensor and deformable model. The segmentation work flow comprises four key steps: preprocessing, detection of the region of interest (ROI) within the breast region, segmenting the pectoral muscle and finally extracting and refining the pectoral muscle boundary. From experimental results we show that the proposed method can segment the pectoral muscle robustly in diverse patient cases. In addition, the proposed method will allow the application of the quantification research for various breast images.

Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

PubMed

Liyanage, Kishan Andre; Steward, Christopher; Moffat, Bradford Armstrong; Opie, Nicholas Lachlan; Rind, Gil Simon; John, Sam Emmanuel; Ronayne, Stephen; May, Clive Newton; O'Brien, Terence John; Milne, Marjorie Eileen; Oxley, Thomas James

2016-01-01

Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution) MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap) to 1 (complete overlap). For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

A novel method for unsteady flow field segmentation based on stochastic similarity of direction

NASA Astrophysics Data System (ADS)

Omata, Noriyasu; Shirayama, Susumu

2018-04-01

Recent developments in fluid dynamics research have opened up the possibility for the detailed quantitative understanding of unsteady flow fields. However, the visualization techniques currently in use generally provide only qualitative insights. A method for dividing the flow field into physically relevant regions of interest can help researchers quantify unsteady fluid behaviors. Most methods at present compare the trajectories of virtual Lagrangian particles. The time-invariant features of an unsteady flow are also frequently of interest, but the Lagrangian specification only reveals time-variant features. To address these challenges, we propose a novel method for the time-invariant spatial segmentation of an unsteady flow field. This segmentation method does not require Lagrangian particle tracking but instead quantitatively compares the stochastic models of the direction of the flow at each observed point. The proposed method is validated with several clustering tests for 3D flows past a sphere. Results show that the proposed method reveals the time-invariant, physically relevant structures of an unsteady flow.

Custom-made composite scaffolds for segmental defect repair in long bones.

PubMed

Reichert, Johannes C; Wullschleger, Martin E; Cipitria, Amaia; Lienau, Jasmin; Cheng, Tan K; Schütz, Michael A; Duda, Georg N; Nöth, Ulrich; Eulert, Jochen; Hutmacher, Dietmar W

2011-08-01

Current approaches for segmental bone defect reconstruction are restricted to autografts and allografts which possess osteoconductive, osteoinductive and osteogenic properties, but face significant disadvantages. The objective of this study was to compare the regenerative potential of scaffolds with different material composition but similar mechanical properties to autologous bone graft from the iliac crest in an ovine segmental defect model. After 12 weeks, in vivo specimens were analysed by X-ray imaging, torsion testing, micro-computed tomography and histology to assess amount, strength and structure of the newly formed bone. The highest amounts of bone neoformation with highest torsional moment values were observed in the autograft group and the lowest in the medical grade polycaprolactone and tricalcium phosphate composite group. The study results suggest that scaffolds based on aliphatic polyesters and ceramics, which are considered biologically inactive materials, induce only limited new bone formation but could be an equivalent alternative to autologous bone when combined with a biologically active stimulus such as bone morphogenetic proteins.

Boundary segmentation for fluorescence microscopy using steerable filters

NASA Astrophysics Data System (ADS)

Ho, David Joon; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2017-02-01

Fluorescence microscopy is used to image multiple subcellular structures in living cells which are not readily observed using conventional optical microscopy. Moreover, two-photon microscopy is widely used to image structures deeper in tissue. Recent advancement in fluorescence microscopy has enabled the generation of large data sets of images at different depths, times, and spectral channels. Thus, automatic object segmentation is necessary since manual segmentation would be inefficient and biased. However, automatic segmentation is still a challenging problem as regions of interest may not have well defined boundaries as well as non-uniform pixel intensities. This paper describes a method for segmenting tubular structures in fluorescence microscopy images of rat kidney and liver samples using adaptive histogram equalization, foreground/background segmentation, steerable filters to capture directional tendencies, and connected-component analysis. The results from several data sets demonstrate that our method can segment tubular boundaries successfully. Moreover, our method has better performance when compared to other popular image segmentation methods when using ground truth data obtained via manual segmentation.

The umbilical and paraumbilical veins of man.

PubMed

Martin, B F; Tudor, R G

1980-03-01

During its transit through the umbilicus structural changes occur in the thick wall of the extra-abdominal segment of the umbilical vein whereby the components of the intra-abdominal segment acquire an essentially longitudinal direction and become arranged in fibro-elastic and fibro-muscular zones. The vein lumen becomes largely obliterated by asymmetrical proliferation of loose subendothelial conective tissue. The latter forms a new inner zone within which a small segment of the lumen persists in an eccentric position. This residual lumen transmits blood to the portal system from paraumbilical and systemic sources, and is retained in the upper part of the vein, even in old age. A similar process of lumen closure is observed in the ductus venosus. In early childhood the lower third of the vein undergoes breakdown, with fatty infiltration, resulting in its complete division into vascular fibro-elastic strands, and in old age some breakdown occurs in the outermost part of the wall of the upper two thirds. The paraumbilical veins are thick-walled and of similar structure to the umbilical vein. Together they constitute an accessory portal system which is confined between the layers of the falciform ligament and is in communication with the veins of the ventral abdominal wall. The constituents form an ascending series, namely, Burow's veins, the umbilical vein, and Sappey's inferior and superior veins. The main channel of Sappey's inferior veins may be the remnant of the right umbilical vein since it communicates with the right rectus sheath and often communicates directly with the portal system within the right lobe of the liver. The results are of significance in relation to clinical usage of the umbilical vein.

Hidden Markov model approach for identifying the modular framework of the protein backbone.

PubMed

Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

1999-12-01

The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

The laryngeal primordium and epithelial lamina. A new interpretation.

PubMed Central

Sañudo, J R; Domenech-Mateu, J M

1990-01-01

The laryngeal primordium is present in both the laryngotracheal sulcus (LTS) and the primitive pulmonary sac (PPS). Its early period of development may be subdivided into two phases. The first phase (Stage 11) is represented by what is traditionally referred to as the LTS, located directly beneath the PP4 on the ventral wall of the foregut (primary segment), and by the PPS which is situated at its caudal end. The LTS will represent the primordium of the upper or membranous infraglottic cavity region; whereas the PPS, will give rise not only to the bronchial tree, but also to the primordium of the trachea and the lower or cartilaginous region of the infraglottic cavity. The second phase (Stages 13 and 14) is distinguished by the cranial growth of the LTS above the PP4 and therefore by its absorption into the floor of the primitive pharynx in the mesobranchial area (secondary segment), which will develop into the primordium of the vestibule of the larynx. Similarly, we observed that in the development of the laryngeal cavity there are two temporally and spatially separate epithelial structures: the epithelial septum and the epithelial lamina. In this respect we differ from other authors who are of the opinion that there is a single structure (the epithelial lamina). The epithelial septum is a primary structure responsible for the final configuration of the LTS, as it contributes to the development of the lower end of the primary segment of the LTS and also to the creation of the secondary segment. The epithelial lamina is a secondary structure which appears inside the LTS as a result of pressure exerted by the mesenchyme on its lateral walls, without having any effect on the morphogenesis of the LTS. Images Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 PMID:2081706

Cone Structure in Patients With Usher Syndrome Type III and Mutations in the Clarin 1 Gene

PubMed Central

Ratnam, Kavitha; Västinsalo, Hanna; Roorda, Austin; Sankila, Eeva-Marja K.; Duncan, Jacque L.

2015-01-01

Objective To study macular structure and function in patients with Usher syndrome type III (USH3) caused by mutations in the Clarin 1 gene (CLRN1). Methods High-resolution macular images were obtained by adaptive optics scanning laser ophthalmoscopy and spectral domain optical coherence tomography in 3 patients with USH3 and were compared with those of age-similar control subjects. Vision function measures included best-corrected visual acuity, kinetic and static perimetry, and full-field electroretinography. Coding regions of the CLRN1 gene were sequenced. Results CLRN1 mutations were present in all the patients; a 20-year-old man showed compound heterozygous mutations (p.N48K and p.S188X), and 2 unrelated women aged 25 and 32 years had homozygous mutations (p.N48K). Best-corrected visual acuity ranged from 20/16 to 20/40, with scotomas beginning at 3° eccentricity. The inner segment-outer segment junction or the inner segment ellipsoid band was disrupted within 1° to 4° of the fovea, and the foveal inner and outer segment layers were significantly thinner than normal. Cones near the fovea in patients 1 and 2 showed normal spacing, and the preserved region ended abruptly. Retinal pigment epithelial cells were visible in patient 3 where cones were lost. Conclusions Cones were observed centrally but not in regions with scotomas, and retinal pigment epithelial cells were visible in regions without cones in patients with CLRN1 mutations. High-resolution measures of retinal structure demonstrate patterns of cone loss associated with CLRN1 mutations. Clinical Relevance These findings provide insight into the effect of CLRN1 mutations on macular cone structure, which has implications for the development of treatments for USH3. Trial Registration clinicaltrials.gov Identifier: NCT00254605 PMID:22964989

Slit-lamp photography and videography with high magnifications

PubMed Central

Yuan, Jin; Jiang, Hong; Mao, Xinjie; Ke, Bilian; Yan, Wentao; Liu, Che; Cintrón-Colón, Hector R; Perez, Victor L; Wang, Jianhua

2015-01-01

Purpose To demonstrate the use of the slit-lamp photography and videography with extremely high magnifications for visualizing structures of the anterior segment of the eye. Methods A Canon 60D digital camera with Movie Crop Function was adapted into a Nikon FS-2 slit-lamp to capture still images and video clips of the structures of the anterior segment of the eye. Images obtained using the slit-lamp were tested for spatial resolution. The cornea of human eyes was imaged with the slit-lamp and the structures were compared with the pictures captured using the ultra-high resolution optical coherence tomography (UHR-OCT). The central thickness of the corneal epithelium and total cornea was obtained using the slit-lamp and the results were compared with the thickness obtained using UHR-OCT. Results High-quality ocular images and higher spatial resolutions were obtained by using the slit-lamp with extremely high magnifications and Movie Crop Function, rather than the traditional slit-lamp. The structures and characteristics of the cornea, such as the normal epithelium, abnormal epithelium of corneal intraepithelial neoplasia, LASIK interface, and contact lenses, were clearly visualized using this device. These features were confirmed by comparing the obtained images with those acquired using UHR-OCT. Moreover, the tear film debris on the ocular surface and the corneal nerve in the anterior corneal stroma were also visualized. The thicknesses of the corneal epithelium and total cornea were similar to that measured using UHR-OCT (P < 0.05). Conclusions We demonstrated that the slit-lamp photography and videography with extremely high magnifications allows better visualization of the anterior segment structures of the eye, especially of the epithelium, when compared with the traditional slit-lamp. PMID:26020484

Virtual modeling of polycrystalline structures of materials using particle packing algorithms and Laguerre cells

NASA Astrophysics Data System (ADS)

Morfa, Carlos Recarey; Farias, Márcio Muniz de; Morales, Irvin Pablo Pérez; Navarra, Eugenio Oñate Ibañez de; Valera, Roberto Roselló

2018-04-01

The influence of the microstructural heterogeneities is an important topic in the study of materials. In the context of computational mechanics, it is therefore necessary to generate virtual materials that are statistically equivalent to the microstructure under study, and to connect that geometrical description to the different numerical methods. Herein, the authors present a procedure to model continuous solid polycrystalline materials, such as rocks and metals, preserving their representative statistical grain size distribution. The first phase of the procedure consists of segmenting an image of the material into adjacent polyhedral grains representing the individual crystals. This segmentation allows estimating the grain size distribution, which is used as the input for an advancing front sphere packing algorithm. Finally, Laguerre diagrams are calculated from the obtained sphere packings. The centers of the spheres give the centers of the Laguerre cells, and their radii determine the cells' weights. The cell sizes in the obtained Laguerre diagrams have a distribution similar to that of the grains obtained from the image segmentation. That is why those diagrams are a convenient model of the original crystalline structure. The above-outlined procedure has been used to model real polycrystalline metallic materials. The main difference with previously existing methods lies in the use of a better particle packing algorithm.

Model-based segmentation of abdominal aortic aneurysms in CTA images

NASA Astrophysics Data System (ADS)

de Bruijne, Marleen; van Ginneken, Bram; Niessen, Wiro J.; Loog, Marco; Viergever, Max A.

2003-05-01

Segmentation of thrombus in abdominal aortic aneurysms is complicated by regions of low boundary contrast and by the presence of many neighboring structures in close proximity to the aneurysm wall. We present an automated method that is similar to the well known Active Shape Models (ASM), combining a three-dimensional shape model with a one-dimensional boundary appearance model. Our contribution is twofold: we developed a non-parametric appearance modeling scheme that effectively deals with a highly varying background, and we propose a way of generalizing models of curvilinear structures from small training sets. In contrast with the conventional ASM approach, the new appearance model trains on both true and false examples of boundary profiles. The probability that a given image profile belongs to the boundary is obtained using k nearest neighbor (kNN) probability density estimation. The performance of this scheme is compared to that of original ASMs, which minimize the Mahalanobis distance to the average true profile in the training set. The generalizability of the shape model is improved by modeling the objects axis deformation independent of its cross-sectional deformation. A leave-one-out experiment was performed on 23 datasets. Segmentation using the kNN appearance model significantly outperformed the original ASM scheme; average volume errors were 5.9% and 46% respectively.

Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

PubMed

Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Hara, Takeshi; Fujita, Hiroshi

2017-10-01

We propose a single network trained by pixel-to-label deep learning to address the general issue of automatic multiple organ segmentation in three-dimensional (3D) computed tomography (CT) images. Our method can be described as a voxel-wise multiple-class classification scheme for automatically assigning labels to each pixel/voxel in a 2D/3D CT image. We simplify the segmentation algorithms of anatomical structures (including multiple organs) in a CT image (generally in 3D) to a majority voting scheme over the semantic segmentation of multiple 2D slices drawn from different viewpoints with redundancy. The proposed method inherits the spirit of fully convolutional networks (FCNs) that consist of "convolution" and "deconvolution" layers for 2D semantic image segmentation, and expands the core structure with 3D-2D-3D transformations to adapt to 3D CT image segmentation. All parameters in the proposed network are trained pixel-to-label from a small number of CT cases with human annotations as the ground truth. The proposed network naturally fulfills the requirements of multiple organ segmentations in CT cases of different sizes that cover arbitrary scan regions without any adjustment. The proposed network was trained and validated using the simultaneous segmentation of 19 anatomical structures in the human torso, including 17 major organs and two special regions (lumen and content inside of stomach). Some of these structures have never been reported in previous research on CT segmentation. A database consisting of 240 (95% for training and 5% for testing) 3D CT scans, together with their manually annotated ground-truth segmentations, was used in our experiments. The results show that the 19 structures of interest were segmented with acceptable accuracy (88.1% and 87.9% voxels in the training and testing datasets, respectively, were labeled correctly) against the ground truth. We propose a single network based on pixel-to-label deep learning to address the challenging issue of anatomical structure segmentation in 3D CT cases. The novelty of this work is the policy of deep learning of the different 2D sectional appearances of 3D anatomical structures for CT cases and the majority voting of the 3D segmentation results from multiple crossed 2D sections to achieve availability and reliability with better efficiency, generality, and flexibility than conventional segmentation methods, which must be guided by human expertise. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

A 3D Hermite-based multiscale local active contour method with elliptical shape constraints for segmentation of cardiac MR and CT volumes.

PubMed

Barba-J, Leiner; Escalante-Ramírez, Boris; Vallejo Venegas, Enrique; Arámbula Cosío, Fernando

2018-05-01

Analysis of cardiac images is a fundamental task to diagnose heart problems. Left ventricle (LV) is one of the most important heart structures used for cardiac evaluation. In this work, we propose a novel 3D hierarchical multiscale segmentation method based on a local active contour (AC) model and the Hermite transform (HT) for LV analysis in cardiac magnetic resonance (MR) and computed tomography (CT) volumes in short axis view. Features such as directional edges, texture, and intensities are analyzed using the multiscale HT space. A local AC model is configured using the HT coefficients and geometrical constraints. The endocardial and epicardial boundaries are used for evaluation. Segmentation of the endocardium is controlled using elliptical shape constraints. The final endocardial shape is used to define the geometrical constraints for segmentation of the epicardium. We follow the assumption that epicardial and endocardial shapes are similar in volumes with short axis view. An initialization scheme based on a fuzzy C-means algorithm and mathematical morphology was designed. The algorithm performance was evaluated using cardiac MR and CT volumes in short axis view demonstrating the feasibility of the proposed method.

Analytical Verifications in Cryogenic Testing of NGST Advanced Mirror System Demonstrators

NASA Technical Reports Server (NTRS)

Cummings, Ramona; Levine, Marie; VanBuren, Dave; Kegley, Jeff; Green, Joseph; Hadaway, James; Presson, Joan; Cline, Todd; Stahl, H. Philip (Technical Monitor)

2002-01-01

Ground based testing is a critical and costly part of component, assembly, and system verifications of large space telescopes. At such tests, however, with integral teamwork by planners, analysts, and test personnel, segments can be included to validate specific analytical parameters and algorithms at relatively low additional cost. This paper opens with strategy of analytical verification segments added to vacuum cryogenic testing of Advanced Mirror System Demonstrator (AMSD) assemblies. These AMSD assemblies incorporate material and architecture concepts being considered in the Next Generation Space Telescope (NGST) design. The test segments for workmanship testing, cold survivability, and cold operation optical throughput are supplemented by segments for analytical verifications of specific structural, thermal, and optical parameters. Utilizing integrated modeling and separate materials testing, the paper continues with support plan for analyses, data, and observation requirements during the AMSD testing, currently slated for late calendar year 2002 to mid calendar year 2003. The paper includes anomaly resolution as gleaned by authors from similar analytical verification support of a previous large space telescope, then closes with draft of plans for parameter extrapolations, to form a well-verified portion of the integrated modeling being done for NGST performance predictions.

Organization of complex networks

NASA Astrophysics Data System (ADS)

Kitsak, Maksim

Many large complex systems can be successfully analyzed using the language of graphs and networks. Interactions between the objects in a network are treated as links connecting nodes. This approach to understanding the structure of networks is an important step toward understanding the way corresponding complex systems function. Using the tools of statistical physics, we analyze the structure of networks as they are found in complex systems such as the Internet, the World Wide Web, and numerous industrial and social networks. In the first chapter we apply the concept of self-similarity to the study of transport properties in complex networks. Self-similar or fractal networks, unlike non-fractal networks, exhibit similarity on a range of scales. We find that these fractal networks have transport properties that differ from those of non-fractal networks. In non-fractal networks, transport flows primarily through the hubs. In fractal networks, the self-similar structure requires any transport to also flow through nodes that have only a few connections. We also study, in models and in real networks, the crossover from fractal to non-fractal networks that occurs when a small number of random interactions are added by means of scaling techniques. In the second chapter we use k-core techniques to study dynamic processes in networks. The k-core of a network is the network's largest component that, within itself, exhibits all nodes with at least k connections. We use this k-core analysis to estimate the relative leadership positions of firms in the Life Science (LS) and Information and Communication Technology (ICT) sectors of industry. We study the differences in the k-core structure between the LS and the ICT sectors. We find that the lead segment (highest k-core) of the LS sector, unlike that of the ICT sector, is remarkably stable over time: once a particular firm enters the lead segment, it is likely to remain there for many years. In the third chapter we study how epidemics spread though networks. Our results indicate that a virus is more likely to infect a large area of a network if it originates at a node contained within k-core of high index k.

Segmentation of humeral head from axial proton density weighted shoulder MR images

NASA Astrophysics Data System (ADS)

Sezer, Aysun; Sezer, Hasan Basri; Albayrak, Songul

2015-01-01

The purpose of this study is to determine the effectiveness of segmentation of axial MR proton density (PD) images of bony humeral head. PD sequence images which are included in standard shoulder MRI protocol are used instead of T1 MR images. Bony structures were reported to be successfully segmented in the literature from T1 MR images. T1 MR images give more sharp determination of bone and soft tissue border but cannot address the pathological process which takes place in the bone. In the clinical settings PD images of shoulder are used to investigate soft tissue alterations which can cause shoulder instability and are better in demonstrating edema and the pathology but have a higher noise ratio than other modalities. Moreover the alteration of humeral head intensity in patients and soft tissues in contact with the humeral head which have the very similar intensities with bone makes the humeral head segmentation a challenging problem in PD images. However segmentation of the bony humeral head is required initially to facilitate the segmentation of the soft tissues of shoulder. In this study shoulder MRI of 33 randomly selected patients were included. Speckle reducing anisotropic diffusion (SRAD) method was used to decrease noise and then Active Contour Without Edge (ACWE) and Signed Pressure Force (SPF) models were applied on our data set. Success of these methods is determined by comparing our results with manually segmented images by an expert. Applications of these methods on PD images provide highly successful results for segmentation of bony humeral head. This is the first study to determine bone contours in PD images in literature.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

PubMed

Cui, Shaoguo; Mao, Lei; Jiang, Jingfeng; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice.

An improved approach for the segmentation of starch granules in microscopic images

PubMed Central

2010-01-01

Background Starches are the main storage polysaccharides in plants and are distributed widely throughout plants including seeds, roots, tubers, leaves, stems and so on. Currently, microscopic observation is one of the most important ways to investigate and analyze the structure of starches. The position, shape, and size of the starch granules are the main measurements for quantitative analysis. In order to obtain these measurements, segmentation of starch granules from the background is very important. However, automatic segmentation of starch granules is still a challenging task because of the limitation of imaging condition and the complex scenarios of overlapping granules. Results We propose a novel method to segment starch granules in microscopic images. In the proposed method, we first separate starch granules from background using automatic thresholding and then roughly segment the image using watershed algorithm. In order to reduce the oversegmentation in watershed algorithm, we use the roundness of each segment, and analyze the gradient vector field to find the critical points so as to identify oversegments. After oversegments are found, we extract the features, such as the position and intensity of the oversegments, and use fuzzy c-means clustering to merge the oversegments to the objects with similar features. Experimental results demonstrate that the proposed method can alleviate oversegmentation of watershed segmentation algorithm successfully. Conclusions We present a new scheme for starch granules segmentation. The proposed scheme aims to alleviate the oversegmentation in watershed algorithm. We use the shape information and critical points of gradient vector flow (GVF) of starch granules to identify oversegments, and use fuzzy c-mean clustering based on prior knowledge to merge these oversegments to the objects. Experimental results on twenty microscopic starch images demonstrate the effectiveness of the proposed scheme. PMID:21047380

Rosoboroneksport: Arms Sales and the Structure of Russian Defense Industry

DTIC Science & Technology

2007-01-01

comparable with such segments of the global economy as energy and food . Competition here is 11 extremely strong.”26 Moreover, he also stated that...as energy and food . Competition here is extremely strong.”266 Similarly, as early as 2004, management changes at key defense industrial firms like...Military Realities,” Juergen Schwarz, Wilfred A. Herrmann, and Hanns-Frank Seller, eds., Maritime Strategies in Asia, Bangkok: White Lotus Press

Subcortical structure segmentation using probabilistic atlas priors

NASA Astrophysics Data System (ADS)

Gouttard, Sylvain; Styner, Martin; Joshi, Sarang; Smith, Rachel G.; Cody Hazlett, Heather; Gerig, Guido

2007-03-01

The segmentation of the subcortical structures of the brain is required for many forms of quantitative neuroanatomic analysis. The volumetric and shape parameters of structures such as lateral ventricles, putamen, caudate, hippocampus, pallidus and amygdala are employed to characterize a disease or its evolution. This paper presents a fully automatic segmentation of these structures via a non-rigid registration of a probabilistic atlas prior and alongside a comprehensive validation. Our approach is based on an unbiased diffeomorphic atlas with probabilistic spatial priors built from a training set of MR images with corresponding manual segmentations. The atlas building computes an average image along with transformation fields mapping each training case to the average image. These transformation fields are applied to the manually segmented structures of each case in order to obtain a probabilistic map on the atlas. When applying the atlas for automatic structural segmentation, an MR image is first intensity inhomogeneity corrected, skull stripped and intensity calibrated to the atlas. Then the atlas image is registered to the image using an affine followed by a deformable registration matching the gray level intensity. Finally, the registration transformation is applied to the probabilistic maps of each structures, which are then thresholded at 0.5 probability. Using manual segmentations for comparison, measures of volumetric differences show high correlation with our results. Furthermore, the dice coefficient, which quantifies the volumetric overlap, is higher than 62% for all structures and is close to 80% for basal ganglia. The intraclass correlation coefficient computed on these same datasets shows a good inter-method correlation of the volumetric measurements. Using a dataset of a single patient scanned 10 times on 5 different scanners, reliability is shown with a coefficient of variance of less than 2 percents over the whole dataset. Overall, these validation and reliability studies show that our method accurately and reliably segments almost all structures. Only the hippocampus and amygdala segmentations exhibit relative low correlation with the manual segmentation in at least one of the validation studies, whereas they still show appropriate dice overlap coefficients.

A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain

NASA Technical Reports Server (NTRS)

Hall, Lawrence O.; Bensaid, Amine M.; Clarke, Laurence P.; Velthuizen, Robert P.; Silbiger, Martin S.; Bezdek, James C.

1992-01-01

Magnetic resonance (MR) brain section images are segmented and then synthetically colored to give visual representations of the original data with three approaches: the literal and approximate fuzzy c-means unsupervised clustering algorithms and a supervised computational neural network, a dynamic multilayered perception trained with the cascade correlation learning algorithm. Initial clinical results are presented on both normal volunteers and selected patients with brain tumors surrounded by edema. Supervised and unsupervised segmentation techniques provide broadly similar results. Unsupervised fuzzy algorithms were visually observed to show better segmentation when compared with raw image data for volunteer studies. However, for a more complex segmentation problem with tumor/edema or cerebrospinal fluid boundary, where the tissues have similar MR relaxation behavior, inconsistency in rating among experts was observed.

Regional shape-based feature space for segmenting biomedical images using neural networks

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Gopal; Hoford, John D.; Hoffman, Eric A.

1993-07-01

In biomedical images, structure of interest, particularly the soft tissue structures, such as the heart, airways, bronchial and arterial trees often have grey-scale and textural characteristics similar to other structures in the image, making it difficult to segment them using only gray- scale and texture information. However, these objects can be visually recognized by their unique shapes and sizes. In this paper we discuss, what we believe to be, a novel, simple scheme for extracting features based on regional shapes. To test the effectiveness of these features for image segmentation (classification), we use an artificial neural network and a statistical cluster analysis technique. The proposed shape-based feature extraction algorithm computes regional shape vectors (RSVs) for all pixels that meet a certain threshold criteria. The distance from each such pixel to a boundary is computed in 8 directions (or in 26 directions for a 3-D image). Together, these 8 (or 26) values represent the pixel's (or voxel's) RSV. All RSVs from an image are used to train a multi-layered perceptron neural network which uses these features to 'learn' a suitable classification strategy. To clearly distinguish the desired object from other objects within an image, several examples from inside and outside the desired object are used for training. Several examples are presented to illustrate the strengths and weaknesses of our algorithm. Both synthetic and actual biomedical images are considered. Future extensions to this algorithm are also discussed.

Architecture of interstitial nodal spaces in the rodent renal inner medulla.

PubMed

Gilbert, Rebecca L; Pannabecker, Thomas L

2013-09-01

Every collecting duct (CD) of the rat inner medulla is uniformly surrounded by about four abutting ascending vasa recta (AVR) running parallel to it. One or two ascending thin limbs (ATLs) lie between and parallel to each abutting AVR pair, opposite the CD. These structures form boundaries of axially running interstitial compartments. Viewed in transverse sections, these compartments appear as four interstitial nodal spaces (INSs) positioned symmetrically around each CD. The axially running compartments are segmented by interstitial cells spaced at regular intervals. The pairing of ATLs and CDs bounded by an abundant supply of AVR carrying reabsorbed water, NaCl, and urea make a strong argument that the mixing of NaCl and urea within the INSs and countercurrent flows play a critical role in generating the inner medullary osmotic gradient. The results of this study fully support that hypothesis. We quantified interactions of all structures comprising INSs along the corticopapillary axis for two rodent species, the Munich-Wistar rat and the kangaroo rat. The results showed remarkable similarities in the configurations of INSs, suggesting that the structural arrangement of INSs is a highly conserved architecture that plays a fundamental role in renal function. The number density of INSs along the corticopapillary axis directly correlated with a loop population that declines exponentially with distance below the outer medullary-inner medullary boundary. The axial configurations were consistent with discrete association between near-bend loop segments and INSs and with upper loop segments lying distant from INSs.

Architecture of interstitial nodal spaces in the rodent renal inner medulla

PubMed Central

Gilbert, Rebecca L.

2013-01-01

Every collecting duct (CD) of the rat inner medulla is uniformly surrounded by about four abutting ascending vasa recta (AVR) running parallel to it. One or two ascending thin limbs (ATLs) lie between and parallel to each abutting AVR pair, opposite the CD. These structures form boundaries of axially running interstitial compartments. Viewed in transverse sections, these compartments appear as four interstitial nodal spaces (INSs) positioned symmetrically around each CD. The axially running compartments are segmented by interstitial cells spaced at regular intervals. The pairing of ATLs and CDs bounded by an abundant supply of AVR carrying reabsorbed water, NaCl, and urea make a strong argument that the mixing of NaCl and urea within the INSs and countercurrent flows play a critical role in generating the inner medullary osmotic gradient. The results of this study fully support that hypothesis. We quantified interactions of all structures comprising INSs along the corticopapillary axis for two rodent species, the Munich-Wistar rat and the kangaroo rat. The results showed remarkable similarities in the configurations of INSs, suggesting that the structural arrangement of INSs is a highly conserved architecture that plays a fundamental role in renal function. The number density of INSs along the corticopapillary axis directly correlated with a loop population that declines exponentially with distance below the outer medullary-inner medullary boundary. The axial configurations were consistent with discrete association between near-bend loop segments and INSs and with upper loop segments lying distant from INSs. PMID:23825077

Early photoreceptor outer segment loss and retinoschisis in Cohen syndrome.

PubMed

Uyhazi, Katherine E; Binenbaum, Gil; Carducci, Nicholas; Zackai, Elaine H; Aleman, Tomas S

2018-06-01

To describe early structural and functional retinal changes in a patient with Cohen syndrome. A 13-month-old Caucasian girl of Irish and Spanish ancestry was noted to have micrognathia and laryngomalacia at birth, which prompted a genetic evaluation that revealed biallelic deletions in COH1 (VPS13B) (a maternally inherited 60-kb deletion involving exons 26-32 and a paternally inherited 3.5-kb deletion within exon 17) consistent with Cohen syndrome. She underwent a complete ophthalmic examination, full-field flash electroretinography and retinal imaging with spectral domain optical coherence tomography. Central vision was central, steady, and maintained. There was bilateral myopic astigmatic refractive error. Fundus exam was notable for dark foveolar pigmentation, but no obvious abnormalities of either eye. Spectral domain optical coherence tomography cross sections through the fovea revealed a normal appearing photoreceptor outer nuclear layer but loss of the interdigitation signal between the photoreceptor outer segments and the apical retinal pigment epithelium. Retinoschisis involving the inner nuclear layer of both eyes and possible ganglion cell layer thinning were also noted. There was a detectable electroretinogram with similarly reduced amplitudes of rod- (white, 0.01 cd.s.m -2 ) and cone-mediated (3 cd.s.m -2 , 30 Hz) responses. Photoreceptor outer segment abnormalities and retinoschisis may represent the earliest structural retinal change detected by spectral domain optical coherence tomography in patients with Cohen syndrome, suggesting a complex pathophysiology with primary involvement of the photoreceptor cilium and disorganization of the structural integrity of the inner retina.

Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Tade, Funmilayo; Schuster, David M.; Nieh, Peter; Master, Viraj; Fei, Baowei

2017-02-01

Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.

Alzheimer's disease detection via automatic 3D caudate nucleus segmentation using coupled dictionary learning with level set formulation.

PubMed

Al-Shaikhli, Saif Dawood Salman; Yang, Michael Ying; Rosenhahn, Bodo

2016-12-01

This paper presents a novel method for Alzheimer's disease classification via an automatic 3D caudate nucleus segmentation. The proposed method consists of segmentation and classification steps. In the segmentation step, we propose a novel level set cost function. The proposed cost function is constrained by a sparse representation of local image features using a dictionary learning method. We present coupled dictionaries: a feature dictionary of a grayscale brain image and a label dictionary of a caudate nucleus label image. Using online dictionary learning, the coupled dictionaries are learned from the training data. The learned coupled dictionaries are embedded into a level set function. In the classification step, a region-based feature dictionary is built. The region-based feature dictionary is learned from shape features of the caudate nucleus in the training data. The classification is based on the measure of the similarity between the sparse representation of region-based shape features of the segmented caudate in the test image and the region-based feature dictionary. The experimental results demonstrate the superiority of our method over the state-of-the-art methods by achieving a high segmentation (91.5%) and classification (92.5%) accuracy. In this paper, we find that the study of the caudate nucleus atrophy gives an advantage over the study of whole brain structure atrophy to detect Alzheimer's disease. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Automatic segmentation of the facial nerve and chorda tympani in pediatric CT scans.

PubMed

Reda, Fitsum A; Noble, Jack H; Rivas, Alejandro; McRackan, Theodore R; Labadie, Robert F; Dawant, Benoit M

2011-10-01

Cochlear implant surgery is used to implant an electrode array in the cochlea to treat hearing loss. The authors recently introduced a minimally invasive image-guided technique termed percutaneous cochlear implantation. This approach achieves access to the cochlea by drilling a single linear channel from the outer skull into the cochlea via the facial recess, a region bounded by the facial nerve and chorda tympani. To exploit existing methods for computing automatically safe drilling trajectories, the facial nerve and chorda tympani need to be segmented. The goal of this work is to automatically segment the facial nerve and chorda tympani in pediatric CT scans. The authors have proposed an automatic technique to achieve the segmentation task in adult patients that relies on statistical models of the structures. These models contain intensity and shape information along the central axes of both structures. In this work, the authors attempted to use the same method to segment the structures in pediatric scans. However, the authors learned that substantial differences exist between the anatomy of children and that of adults, which led to poor segmentation results when an adult model is used to segment a pediatric volume. Therefore, the authors built a new model for pediatric cases and used it to segment pediatric scans. Once this new model was built, the authors employed the same segmentation method used for adults with algorithm parameters that were optimized for pediatric anatomy. A validation experiment was conducted on 10 CT scans in which manually segmented structures were compared to automatically segmented structures. The mean, standard deviation, median, and maximum segmentation errors were 0.23, 0.17, 0.18, and 1.27 mm, respectively. The results indicate that accurate segmentation of the facial nerve and chorda tympani in pediatric scans is achievable, thus suggesting that safe drilling trajectories can also be computed automatically.

Automated 3D renal segmentation based on image partitioning

NASA Astrophysics Data System (ADS)

Yeghiazaryan, Varduhi; Voiculescu, Irina D.

2016-03-01

Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.

Model-based segmentation of the facial nerve and chorda tympani in pediatric CT scans

NASA Astrophysics Data System (ADS)

Reda, Fitsum A.; Noble, Jack H.; Rivas, Alejandro; Labadie, Robert F.; Dawant, Benoit M.

2011-03-01

In image-guided cochlear implant surgery an electrode array is implanted in the cochlea to treat hearing loss. Access to the cochlea is achieved by drilling from the outer skull to the cochlea through the facial recess, a region bounded by the facial nerve and the chorda tympani. To exploit existing methods for computing automatically safe drilling trajectories, the facial nerve and chorda tympani need to be segmented. The effectiveness of traditional segmentation approaches to achieve this is severely limited because the facial nerve and chorda are small structures (~1 mm and ~0.3 mm in diameter, respectively) and exhibit poor image contrast. We have recently proposed a technique to achieve this task in adult patients, which relies on statistical models of the structures. These models contain intensity and shape information along the central axes of both structures. In this work we use the same method to segment pediatric scans. We show that substantial differences exist between the anatomy of children and the anatomy of adults, which lead to poor segmentation results when an adult model is used to segment a pediatric volume. We have built a new model for pediatric cases and we have applied it to ten scans. A leave-one-out validation experiment was conducted in which manually segmented structures were compared to automatically segmented structures. The maximum segmentation error was 1 mm. This result indicates that accurate segmentation of the facial nerve and chorda in pediatric scans is achievable, thus suggesting that safe drilling trajectories can also be computed automatically.

Deformable M-Reps for 3D Medical Image Segmentation.

PubMed

Pizer, Stephen M; Fletcher, P Thomas; Joshi, Sarang; Thall, Andrew; Chen, James Z; Fridman, Yonatan; Fritsch, Daniel S; Gash, Graham; Glotzer, John M; Jiroutek, Michael R; Lu, Conglin; Muller, Keith E; Tracton, Gregg; Yushkevich, Paul; Chaney, Edward L

2003-11-01

M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geometry. They are particularly well suited to model anatomic objects and in particular to capture prior geometric information effectively in deformable models segmentation approaches. The representation is based on figural models , which define objects at coarse scale by a hierarchy of figures - each figure generally a slab representing a solid region and its boundary simultaneously. This paper focuses on the use of single figure models to segment objects of relatively simple structure. A single figure is a sheet of medial atoms, which is interpolated from the model formed by a net, i.e., a mesh or chain, of medial atoms (hence the name m-reps ), each atom modeling a solid region via not only a position and a width but also a local figural frame giving figural directions and an object angle between opposing, corresponding positions on the boundary implied by the m-rep. The special capability of an m-rep is to provide spatial and orientational correspondence between an object in two different states of deformation. This ability is central to effective measurement of both geometric typicality and geometry to image match, the two terms of the objective function optimized in segmentation by deformable models. The other ability of m-reps central to effective segmentation is their ability to support segmentation at multiple levels of scale, with successively finer precision. Objects modeled by single figures are segmented first by a similarity transform augmented by object elongation, then by adjustment of each medial atom, and finally by displacing a dense sampling of the m-rep implied boundary. While these models and approaches also exist in 2D, we focus on 3D objects. The segmentation of the kidney from CT and the hippocampus from MRI serve as the major examples in this paper. The accuracy of segmentation as compared to manual, slice-by-slice segmentation is reported.

Deformable M-Reps for 3D Medical Image Segmentation

PubMed Central

Pizer, Stephen M.; Fletcher, P. Thomas; Joshi, Sarang; Thall, Andrew; Chen, James Z.; Fridman, Yonatan; Fritsch, Daniel S.; Gash, Graham; Glotzer, John M.; Jiroutek, Michael R.; Lu, Conglin; Muller, Keith E.; Tracton, Gregg; Yushkevich, Paul; Chaney, Edward L.

2013-01-01

M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geometry. They are particularly well suited to model anatomic objects and in particular to capture prior geometric information effectively in deformable models segmentation approaches. The representation is based on figural models, which define objects at coarse scale by a hierarchy of figures – each figure generally a slab representing a solid region and its boundary simultaneously. This paper focuses on the use of single figure models to segment objects of relatively simple structure. A single figure is a sheet of medial atoms, which is interpolated from the model formed by a net, i.e., a mesh or chain, of medial atoms (hence the name m-reps), each atom modeling a solid region via not only a position and a width but also a local figural frame giving figural directions and an object angle between opposing, corresponding positions on the boundary implied by the m-rep. The special capability of an m-rep is to provide spatial and orientational correspondence between an object in two different states of deformation. This ability is central to effective measurement of both geometric typicality and geometry to image match, the two terms of the objective function optimized in segmentation by deformable models. The other ability of m-reps central to effective segmentation is their ability to support segmentation at multiple levels of scale, with successively finer precision. Objects modeled by single figures are segmented first by a similarity transform augmented by object elongation, then by adjustment of each medial atom, and finally by displacing a dense sampling of the m-rep implied boundary. While these models and approaches also exist in 2D, we focus on 3D objects. The segmentation of the kidney from CT and the hippocampus from MRI serve as the major examples in this paper. The accuracy of segmentation as compared to manual, slice-by-slice segmentation is reported. PMID:23825898

Petrologic, tectonic, and metallogenic evolution of the southern segment of the ancestral Cascades magmatic arc, California and Nevada

USGS Publications Warehouse

du Bray, Edward A.; John, David A.; Cousens, Brian L.

2013-01-01

Although rocks in the two arc segments have similar metal abundances, they are metallogenically distinct. Small porphyry copper deposits are characteristic of the northern segment whereas significant epithermal precious metal deposits are most commonly associated with the southern segment. These metallogenic differences are also fundamentally linked to the tectonic settings and crustal regimes within which these two arc segments evolved.

RNA secondary structures of the bacteriophage phi6 packaging regions.

PubMed

Pirttimaa, M J; Bamford, D H

2000-06-01

Bacteriophage phi6 genome consists of three segments of double-stranded RNA. During maturation, single-stranded copies of these segments are packaged into preformed polymerase complex particles. Only phi6 RNA is packaged, and each particle contains only one copy of each segment. An in vitro packaging and replication assay has been developed for phi6, and the packaging signals (pac sites) have been mapped to the 5' ends of the RNA segments. In this study, we propose secondary structure models for the pac sites of phi6 single-stranded RNA segments. Our models accommodate data from structure-specific chemical modifications, free energy minimizations, and phylogenetic comparisons. Previously reported pac site deletion studies are also discussed. Each pac site possesses a unique architecture, that, however, contains common structural elements.

Rigid shape matching by segmentation averaging.

PubMed

Wang, Hongzhi; Oliensis, John

2010-04-01

We use segmentations to match images by shape. The new matching technique does not require point-to-point edge correspondence and is robust to small shape variations and spatial shifts. To address the unreliability of segmentations computed bottom-up, we give a closed form approximation to an average over all segmentations. Our method has many extensions, yielding new algorithms for tracking, object detection, segmentation, and edge-preserving smoothing. For segmentation, instead of a maximum a posteriori approach, we compute the "central" segmentation minimizing the average distance to all segmentations of an image. For smoothing, instead of smoothing images based on local structures, we smooth based on the global optimal image structures. Our methods for segmentation, smoothing, and object detection perform competitively, and we also show promising results in shape-based tracking.

Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery.

PubMed

Belgiu, Mariana; Dr Guţ, Lucian

2014-10-01

Although multiresolution segmentation (MRS) is a powerful technique for dealing with very high resolution imagery, some of the image objects that it generates do not match the geometries of the target objects, which reduces the classification accuracy. MRS can, however, be guided to produce results that approach the desired object geometry using either supervised or unsupervised approaches. Although some studies have suggested that a supervised approach is preferable, there has been no comparative evaluation of these two approaches. Therefore, in this study, we have compared supervised and unsupervised approaches to MRS. One supervised and two unsupervised segmentation methods were tested on three areas using QuickBird and WorldView-2 satellite imagery. The results were assessed using both segmentation evaluation methods and an accuracy assessment of the resulting building classifications. Thus, differences in the geometries of the image objects and in the potential to achieve satisfactory thematic accuracies were evaluated. The two approaches yielded remarkably similar classification results, with overall accuracies ranging from 82% to 86%. The performance of one of the unsupervised methods was unexpectedly similar to that of the supervised method; they identified almost identical scale parameters as being optimal for segmenting buildings, resulting in very similar geometries for the resulting image objects. The second unsupervised method produced very different image objects from the supervised method, but their classification accuracies were still very similar. The latter result was unexpected because, contrary to previously published findings, it suggests a high degree of independence between the segmentation results and classification accuracy. The results of this study have two important implications. The first is that object-based image analysis can be automated without sacrificing classification accuracy, and the second is that the previously accepted idea that classification is dependent on segmentation is challenged by our unexpected results, casting doubt on the value of pursuing 'optimal segmentation'. Our results rather suggest that as long as under-segmentation remains at acceptable levels, imperfections in segmentation can be ruled out, so that a high level of classification accuracy can still be achieved.

The primary structures of two yeast enolase genes. Homology between the 5' noncoding flanking regions of yeast enolase and glyceraldehyde-3-phosphate dehydrogenase genes.

PubMed

Holland, M J; Holland, J P; Thill, G P; Jackson, K A

1981-02-10

Segments of yeast genomic DNA containing two enolase structural genes have been isolated by subculture cloning procedures using a cDNA hybridization probe synthesized from purified yeast enolase mRNA. Based on restriction endonuclease and transcriptional maps of these two segments of yeast DNA, each hybrid plasmid contains a region of extensive nucleotide sequence homology which forms hybrids with the cDNA probe. The DNA sequences which flank this homologous region in the two hybrid plasmids are nonhomologous indicating that these sequences are nontandemly repeated in the yeast genome. The complete nucleotide sequence of the coding as well as the flanking noncoding regions of these genes has been determined. The amino acid sequence predicted from one reading frame of both structural genes is extremely similar to that determined for yeast enolase (Chin, C. C. Q., Brewer, J. M., Eckard, E., and Wold, F. (1981) J. Biol. Chem. 256, 1370-1376), confirming that these isolated structural genes encode yeast enolase. The nucleotide sequences of the coding regions of the genes are approximately 95% homologous, and neither gene contains an intervening sequence. Codon utilization in the enolase genes follows the same biased pattern previously described for two yeast glyceraldehyde-3-phosphate dehydrogenase structural genes (Holland, J. P., and Holland, M. J. (1980) J. Biol. Chem. 255, 2596-2605). DNA blotting analysis confirmed that the isolated segments of yeast DNA are colinear with yeast genomic DNA and that there are two nontandemly repeated enolase genes per haploid yeast genome. The noncoding portions of the two enolase genes adjacent to the initiation and termination codons are approximately 70% homologous and contain sequences thought to be involved in the synthesis and processing messenger RNA. Finally there are regions of extensive homology between the two enolase structural genes and two yeast glyceraldehyde-3-phosphate dehydrogenase structural genes within the 5- noncoding portions of these glycolytic genes.

3D segmentation of annulus fibrosus and nucleus pulposus from T2-weighted magnetic resonance images

NASA Astrophysics Data System (ADS)

Castro-Mateos, Isaac; Pozo, Jose M.; Eltes, Peter E.; Del Rio, Luis; Lazary, Aron; Frangi, Alejandro F.

2014-12-01

Computational medicine aims at employing personalised computational models in diagnosis and treatment planning. The use of such models to help physicians in finding the best treatment for low back pain (LBP) is becoming popular. One of the challenges of creating such models is to derive patient-specific anatomical and tissue models of the lumbar intervertebral discs (IVDs), as a prior step. This article presents a segmentation scheme that obtains accurate results irrespective of the degree of IVD degeneration, including pathological discs with protrusion or herniation. The segmentation algorithm, employing a novel feature selector, iteratively deforms an initial shape, which is projected into a statistical shape model space at first and then, into a B-Spline space to improve accuracy. The method was tested on a MR dataset of 59 patients suffering from LBP. The images follow a standard T2-weighted protocol in coronal and sagittal acquisitions. These two image volumes were fused in order to overcome large inter-slice spacing. The agreement between expert-delineated structures, used here as gold-standard, and our automatic segmentation was evaluated using Dice Similarity Index and surface-to-surface distances, obtaining a mean error of 0.68 mm in the annulus segmentation and 1.88 mm in the nucleus, which are the best results with respect to the image resolution in the current literature.

Segmentation of pelvic structures for planning CT using a geometrical shape model tuned by a multi-scale edge detector

PubMed Central

Martínez, Fabio; Romero, Eduardo; Dréan, Gaël; Simon, Antoine; Haigron, Pascal; De Crevoisier, Renaud; Acosta, Oscar

2014-01-01

Accurate segmentation of the prostate and organs at risk in computed tomography (CT) images is a crucial step for radiotherapy (RT) planning. Manual segmentation, as performed nowadays, is a time consuming process and prone to errors due to the a high intra- and inter-expert variability. This paper introduces a new automatic method for prostate, rectum and bladder segmentation in planning CT using a geometrical shape model under a Bayesian framework. A set of prior organ shapes are first built by applying Principal Component Analysis (PCA) to a population of manually delineated CT images. Then, for a given individual, the most similar shape is obtained by mapping a set of multi-scale edge observations to the space of organs with a customized likelihood function. Finally, the selected shape is locally deformed to adjust the edges of each organ. Experiments were performed with real data from a population of 116 patients treated for prostate cancer. The data set was split in training and test groups, with 30 and 86 patients, respectively. Results show that the method produces competitive segmentations w.r.t standard methods (Averaged Dice = 0.91 for prostate, 0.94 for bladder, 0.89 for Rectum) and outperforms the majority-vote multi-atlas approaches (using rigid registration, free-form deformation (FFD) and the demons algorithm) PMID:24594798

Organizational differences between cytoplasmic male sterile and male fertile Brassica mitochondrial genomes are confined to a single transposed locus.

PubMed Central

L'Homme, Y; Brown, G G

1993-01-01

Comparison of the physical maps of male fertile (cam) and male sterile (pol) mitochondrial genomes of Brassica napus indicates that structural differences between the two mtDNAs are confined to a region immediately upstream of the atp6 gene. Relative to cam mtDNA, pol mtDNA possesses a 4.5 kb segment at this locus that includes a chimeric gene that is cotranscribed with atp6 and lacks an approximately 1kb region located upstream of the cam atp6 gene. The 4.5 kb pol segment is present and similarly organized in the mitochondrial genome of the common nap B.napus cytoplasm; however, the nap and pol DNA regions flanking this segment are different and the nap sequences are not expressed. The 4.5 kb CMS-associated pol segment has thus apparently undergone transposition during the evolution of the nap and pol cytoplasms and has been lost in the cam genome subsequent to the pol-cam divergence. This 4.5 kb segment comprises the single DNA region that is expressed differently in fertile, pol CMS and fertility restored pol cytoplasm plants. The finding that this locus is part of the single mtDNA region organized differently in the fertile and male sterile mitochondrial genomes provides strong support for the view that it specifies the pol CMS trait. Images PMID:8388101

Development and applications of a flat triangular element for thin laminated shells

NASA Astrophysics Data System (ADS)

Mohan, P.

Finite element analysis of thin laminated shells using a three-noded flat triangular shell element is presented. The flat shell element is obtained by combining the Discrete Kirchhoff Theory (DKT) plate bending element and a membrane element similar to the Allman element, but derived from the Linear Strain Triangular (LST) element. The major drawback of the DKT plate bending element is that the transverse displacement is not explicitly defined within the interior of the element. In the present research, free vibration analysis is performed both by using a lumped mass matrix and a so called consistent mass matrix, obtained by borrowing shape functions from an existing element, in order to compare the performance of the two methods. Several numerical examples are solved to demonstrate the accuracy of the formulation for both small and large rotation analysis of laminated plates and shells. The results are compared with those available in the existing literature and those obtained using the commercial finite element package ABAQUS and are found to be in good agreement. The element is employed for two main applications involving large flexible structures. The first application is the control of thermal deformations of a spherical mirror segment, which is a segment of a multi-segmented primary mirror used in a space telescope. The feasibility of controlling the surface distortions of the mirror segment due to arbitrary thermal fields, using discrete and distributed actuators, is studied. The second application is the analysis of an inflatable structure, being considered by the US Army for housing vehicles and personnel. The updated Lagrangian formulation of the flat shell element has been developed primarily for the nonlinear analysis of the tent structure, since such a structure is expected to undergo large deformations and rotations under the action of environmental loads like the wind and snow loads. The follower effects of the pressure load have been included in the updated Lagrangian formulation of the flat shell element and have been validated using standard examples in the literature involving deformation-dependent pressure loads. The element can be used to obtain the nonlinear response of the tent structure under wind and snow loads. (Abstract shortened by UMI.)

Anatomical pulmonary magnetic resonance imaging segmentation for regional structure-function measurements of asthma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, F.; Graduate Program in Biomedical Engineering, University of Western Ontario, London, Ontario N6A 5B9; Svenningsen, S.

Purpose: Pulmonary magnetic-resonance-imaging (MRI) and x-ray computed-tomography have provided strong evidence of spatially and temporally persistent lung structure-function abnormalities in asthmatics. This has generated a shift in their understanding of lung disease and supports the use of imaging biomarkers as intermediate endpoints of asthma severity and control. In particular, pulmonary {sup 1}H MRI can be used to provide quantitative lung structure-function measurements longitudinally and in response to treatment. However, to translate such biomarkers of asthma, robust methods are required to segment the lung from pulmonary {sup 1}H MRI. Therefore, their objective was to develop a pulmonary {sup 1}H MRI segmentationmore » algorithm to provide regional measurements with the precision and speed required to support clinical studies. Methods: The authors developed a method to segment the left and right lung from {sup 1}H MRI acquired in 20 asthmatics including five well-controlled and 15 severe poorly controlled participants who provided written informed consent to a study protocol approved by Health Canada. Same-day spirometry and plethysmography measurements of lung function and volume were acquired as well as {sup 1}H MRI using a whole-body radiofrequency coil and fast spoiled gradient-recalled echo sequence at a fixed lung volume (functional residual capacity + 1 l). We incorporated the left-to-right lung volume proportion prior based on the Potts model and derived a volume-proportion preserved Potts model, which was approximated through convex relaxation and further represented by a dual volume-proportion preserved max-flow model. The max-flow model led to a linear problem with convex and linear equality constraints that implicitly encoded the proportion prior. To implement the algorithm, {sup 1}H MRI was resampled into ∼3 × 3 × 3 mm{sup 3} isotropic voxel space. Two observers placed seeds on each lung and on the background of 20 pulmonary {sup 1}H MR images in a randomized dataset, on five occasions, five consecutive days in a row. Segmentation accuracy was evaluated using the Dice-similarity-coefficient (DSC) of the segmented thoracic cavity with comparison to five-rounds of manual segmentation by an expert observer. The authors also evaluated the root-mean-squared-error (RMSE) of the Euclidean distance between lung surfaces, the absolute, and percent volume error. Reproducibility was measured using the coefficient of variation (CoV) and intraclass correlation coefficient (ICC) for two observers who repeated segmentation measurements five-times. Results: For five well-controlled asthmatics, forced expiratory volume in 1 s (FEV{sub 1})/forced vital capacity (FVC) was 83% ± 7% and FEV{sub 1} was 86 ± 9%{sub pred}. For 15 severe, poorly controlled asthmatics, FEV{sub 1}/FV C = 66% ± 17% and FEV{sub 1} = 72 ± 27%{sub pred}. The DSC for algorithm and manual segmentation was 91% ± 3%, 92% ± 2% and 91% ± 2% for the left, right, and whole lung, respectively. RMSE was 4.0 ± 1.0 mm for each of the left, right, and whole lung. The absolute (percent) volume errors were 0.1 l (∼6%) for each of right and left lung and ∼0.2 l (∼6%) for whole lung. Intra- and inter-CoV (ICC) were <0.5% (>0.91%) for DSC and <4.5% (>0.93%) for RMSE. While segmentation required 10 s including ∼6 s for user interaction, the smallest detectable difference was 0.24 l for algorithm measurements which was similar to manual measurements. Conclusions: This lung segmentation approach provided the necessary and sufficient precision and accuracy required for research and clinical studies.« less

Plasmon-enhanced versatile optical nonlinearities in a Au-Ag-Au multi-segmental hybrid structure.

PubMed

Yao, Lin-Hua; Zhang, Jun-Pei; Dai, Hong-Wei; Wang, Ming-Shan; Zhang, Lu-Man; Wang, Xia; Han, Jun-Bo

2018-06-27

A Au-Ag-Au multi-segmental hybrid structure has been synthesized by using an electrodeposition method based on an anodic aluminum oxide (AAO) membrane. The third-order optical nonlinearities, second harmonic generation (SHG) and photoluminescence (PL) properties containing ultrafast supercontinuum generation and plasmon mediated thermal emission have been investigated. Significant optical enhancements have been obtained near surface plasmon resonance wavelength in all the abovementioned nonlinear processes. Comparative studies between the Au-Ag-Au multi-segmental hybrid structure and the corresponding single-component Au and Ag hybrid structures demonstrate that the Au-Ag-Au multi-segmental hybrid structure has much larger optical nonlinearities than its counterparts. These results demonstrate that the Au-Ag-Au hybrid structure is a promising candidate for applications in plasmonic devices and enhancement substrates.

FragBag, an accurate representation of protein structure, retrieves structural neighbors from the entire PDB quickly and accurately.

PubMed

Budowski-Tal, Inbal; Nov, Yuval; Kolodny, Rachel

2010-02-23

Fast identification of protein structures that are similar to a specified query structure in the entire Protein Data Bank (PDB) is fundamental in structure and function prediction. We present FragBag: An ultrafast and accurate method for comparing protein structures. We describe a protein structure by the collection of its overlapping short contiguous backbone segments, and discretize this set using a library of fragments. Then, we succinctly represent the protein as a "bags-of-fragments"-a vector that counts the number of occurrences of each fragment-and measure the similarity between two structures by the similarity between their vectors. Our representation has two additional benefits: (i) it can be used to construct an inverted index, for implementing a fast structural search engine of the entire PDB, and (ii) one can specify a structure as a collection of substructures, without combining them into a single structure; this is valuable for structure prediction, when there are reliable predictions only of parts of the protein. We use receiver operating characteristic curve analysis to quantify the success of FragBag in identifying neighbor candidate sets in a dataset of over 2,900 structures. The gold standard is the set of neighbors found by six state of the art structural aligners. Our best FragBag library finds more accurate candidate sets than the three other filter methods: The SGM, PRIDE, and a method by Zotenko et al. More interestingly, FragBag performs on a par with the computationally expensive, yet highly trusted structural aligners STRUCTAL and CE.

Straight trajectory planning for keyhole neurosurgery in sheep with automatic brain structures segmentation

NASA Astrophysics Data System (ADS)

Favaro, Alberto; Lad, Akash; Formenti, Davide; Zani, Davide Danilo; De Momi, Elena

2017-03-01

In a translational neuroscience/neurosurgery perspective, sheep are considered good candidates to study because of the similarity between their brain and the human one. Automatic planning systems for safe keyhole neurosurgery maximize the probe/catheter distance from vessels and risky structures. This work consists in the development of a trajectories planner for straight catheters placement intended to be used for investigating the drug diffusivity mechanisms in sheep brain. Automatic brain segmentation of gray matter, white matter and cerebrospinal fluid is achieved using an online available sheep atlas. Ventricles, midbrain and cerebellum segmentation have been also carried out. The veterinary surgeon is asked to select a target point within the white matter to be reached by the probe and to define an entry area on the brain cortex. To mitigate the risk of hemorrhage during the insertion process, which can prevent the success of the insertion procedure, the trajectory planner performs a curvature analysis of the brain cortex and wipes out from the poll of possible entry points the sulci, as part of brain cortex where superficial blood vessels are naturally located. A limited set of trajectories is then computed and presented to the surgeon, satisfying an optimality criteria based on a cost function which considers the distance from critical brain areas and the whole trajectory length. The planner proved to be effective in defining rectilinear trajectories accounting for the safety constraints determined by the brain morphology. It also demonstrated a short computational time and good capability in segmenting gyri and sulci surfaces.

Mechanics of slip and fracture along small faults and simple strike-slip fault zones in granitic rock

NASA Astrophysics Data System (ADS)

Martel, Stephen J.; Pollard, David D.

1989-07-01

We exploit quasi-static fracture mechanics models for slip along pre-existing faults to account for the fracture structure observed along small exhumed faults and small segmented fault zones in the Mount Abbot quadrangle of California and to estimate stress drop and shear fracture energy from geological field measurements. Along small strike-slip faults, cracks that splay from the faults are common only near fault ends. In contrast, many cracks splay from the boundary faults at the edges of a simple fault zone. Except near segment ends, the cracks preferentially splay into a zone. We infer that shear displacement discontinuities (slip patches) along a small fault propagated to near the fault ends and caused fracturing there. Based on elastic stress analyses, we suggest that slip on one boundary fault triggered slip on the adjacent boundary fault, and that the subsequent interaction of the slip patches preferentially led to the generation of fractures that splayed into the zones away from segment ends and out of the zones near segment ends. We estimate the average stress drops for slip events along the fault zones as ˜1 MPa and the shear fracture energy release rate during slip as 5 × 102 - 2 × 104 J/m2. This estimate is similar to those obtained from shear fracture of laboratory samples, but orders of magnitude less than those for large fault zones. These results suggest that the shear fracture energy release rate increases as the structural complexity of fault zones increases.

Atlas-Guided Segmentation of Vervet Monkey Brain MRI

PubMed Central

Fedorov, Andriy; Li, Xiaoxing; Pohl, Kilian M; Bouix, Sylvain; Styner, Martin; Addicott, Merideth; Wyatt, Chris; Daunais, James B; Wells, William M; Kikinis, Ron

2011-01-01

The vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model. PMID:22253661

Multifaulting in a tectonic syntaxis revealed by InSAR: The case of the Ziarat earthquake sequence (Pakistan)

NASA Astrophysics Data System (ADS)

Pinel-Puysségur, B.; Grandin, R.; Bollinger, L.; Baudry, C.

2014-07-01

On 28-29 October 2008, within 12 h, two similar Mw = 6.4 strike-slip earthquakes struck Baluchistan (Pakistan), as part of a complex seismic sequence. Interferometric Synthetic Aperture Radar (InSAR) data reveal that the peak of surface displacement is near the Ziarat anticline, a large active fold affected by Quaternary strike-slip faulting. All coseismic interferograms integrate the deformation due to both earthquakes. As their causative faults ruptured close to each other, the individual signals cannot be separated. According to their focal mechanisms, each earthquake may have activated a NE-SW sinistral or a NW-SE dextral fault segment, which leads to four possible scenarios of fault orientations. A nonlinear inversion of the InSAR data set allows rejecting two scenarios. The best slip distributions on the two fault segments for the two remaining scenarios are determined by linear inversion. Stress-change modeling favors a scenario involving two abutting conjugate strike-slip faults. Two other fault segments accommodated left-lateral strike slip during the seismic sequence. The activated fault system includes multiple fault segments with different orientations and little surface expression. This may highlight, at a smaller scale, the distributed, possibly transient character of deformation within a broader right-lateral shear zone. It suggests that the activated faults delineate a small tectonic block extruding and subtly rotating within the shear zone. It occurs in the vicinity of the local tectonic syntaxis where orogenic structures sharply turn around a vertical axis. These mechanisms could participate in the long-term migration of active tectonic structures within this kinematically unstable tectonic syntaxis.

Random forest classification of large volume structures for visuo-haptic rendering in CT images

NASA Astrophysics Data System (ADS)

Mastmeyer, Andre; Fortmeier, Dirk; Handels, Heinz

2016-03-01

For patient-specific voxel-based visuo-haptic rendering of CT scans of the liver area, the fully automatic segmentation of large volume structures such as skin, soft tissue, lungs and intestine (risk structures) is important. Using a machine learning based approach, several existing segmentations from 10 segmented gold-standard patients are learned by random decision forests individually and collectively. The core of this paper is feature selection and the application of the learned classifiers to a new patient data set. In a leave-some-out cross-validation, the obtained full volume segmentations are compared to the gold-standard segmentations of the untrained patients. The proposed classifiers use a multi-dimensional feature space to estimate the hidden truth, instead of relying on clinical standard threshold and connectivity based methods. The result of our efficient whole-body section classification are multi-label maps with the considered tissues. For visuo-haptic simulation, other small volume structures would have to be segmented additionally. We also take a look into these structures (liver vessels). For an experimental leave-some-out study consisting of 10 patients, the proposed method performs much more efficiently compared to state of the art methods. In two variants of leave-some-out experiments we obtain best mean DICE ratios of 0.79, 0.97, 0.63 and 0.83 for skin, soft tissue, hard bone and risk structures. Liver structures are segmented with DICE 0.93 for the liver, 0.43 for blood vessels and 0.39 for bile vessels.

Patch-based automatic retinal vessel segmentation in global and local structural context.

PubMed

Cao, Shuoying; Bharath, Anil A; Parker, Kim H; Ng, Jeffrey

2012-01-01

In this paper, we extend our published work [1] and propose an automated system to segment retinal vessel bed in digital fundus images with enough adaptability to analyze images from fluorescein angiography. This approach takes into account both the global and local context and enables both vessel segmentation and microvascular centreline extraction. These tools should allow researchers and clinicians to estimate and assess vessel diameter, capillary blood volume and microvascular topology for early stage disease detection, monitoring and treatment. Global vessel bed segmentation is achieved by combining phase-invariant orientation fields with neighbourhood pixel intensities in a patch-based feature vector for supervised learning. This approach is evaluated against benchmarks on the DRIVE database [2]. Local microvascular centrelines within Regions-of-Interest (ROIs) are segmented by linking the phase-invariant orientation measures with phase-selective local structure features. Our global and local structural segmentation can be used to assess both pathological structural alterations and microemboli occurrence in non-invasive clinical settings in a longitudinal study.

Chain and mirophase-separated structures of ultrathin polyurethane films

NASA Astrophysics Data System (ADS)

Kojio, Ken; Uchiba, Yusuke; Yamamoto, Yasunori; Motokucho, Suguru; Furukawa, Mutsuhisa

2009-08-01

Measurements are presented how chain and microphase-separated structures of ultrathin polyurethane (PU) films are controlled by the thickness. The film thickness is varied by a solution concentration for spin coating. The systems are PUs prepared from commercial raw materials. Fourier-transform infrared spectroscopic measurement revealed that the degree of hydrogen bonding among hard segment chains decreased and increased with decreasing film thickness for strong and weak microphase separation systems, respectively. The microphase-separated structure, which is formed from hard segment domains and a surrounding soft segment matrix, were observed by atomic force microscopy. The size of hard segment domains decreased with decreasing film thickness, and possibility of specific orientation of the hard segment chains was exhibited for both systems. These results are due to decreasing space for the formation of the microphase-separated structure.

Method to planarize three-dimensional structures to enable conformal electrodes

DOEpatents

Nikolic, Rebecca J; Conway, Adam M; Graff, Robert T; Reinhardt, Catherine; Voss, Lars F; Shao, Qinghui

2012-11-20

Methods for fabricating three-dimensional PIN structures having conformal electrodes are provided, as well as the structures themselves. The structures include a first layer and an array of pillars with cavity regions between the pillars. A first end of each pillar is in contact with the first layer. A segment is formed on the second end of each pillar. The cavity regions are filled with a fill material, which may be a functional material such as a neutron sensitive material. The fill material covers each segment. A portion of the fill material is etched back to produce an exposed portion of the segment. A first electrode is deposited onto the fill material and each exposed segment, thereby forming a conductive layer that provides a common contact to each the exposed segment. A second electrode is deposited onto the first layer.

3D reconstruction of the porous microstructure of Al2O3-coatings based on sequentially revealed surface data

NASA Astrophysics Data System (ADS)

Loftfield, Nina; Kästner, Markus; Reithmeier, Eduard

2018-06-01

Local and global liquid transport properties correlate strongly with the morphology of porous materials. Therefore, by characterizing the porous network information is indirectly gained on the materials properties. Properties like the open-porosity are easily accessible with techniques like mercury porosimetry. However, the 3D image reconstruction, destructive or non-destructive, holds advantages like an accurate spatially resolved representation of the investigated material. Common 3D data acquisition is done by x-ray microtomography or a combination of focused ion beam based milling and scanning electron microscopy. In this work a reconstruction approach similar to the latter one is implemented. The porous network is reconstructed based on an alternating process of milling the surface by fly cutting and measuring the surface data with a confocal laser scanning microscope. This has the benefit of reconstructing the pore network on the basis of surface height data, measuring the structure boundaries directly. The stack of milled surface height data needs to be registered and the pore structure to be segmented. The segmented pore structure is connected throughout each height layer and afterwards meshed. The investigated materials are porous surface coatings of aluminum oxide for the usage in tribological pairings.

Structure of the MecI repressor from Staphylococcus aureus in complex with the cognate DNA operator of mec

DOE Office of Scientific and Technical Information (OSTI.GOV)

Safo, Martin K., E-mail: msafo@vcu.edu; Ko, Tzu-Ping; Musayev, Faik N.

The up-and-down binding of dimeric MecI to mecA dyad DNA may account for the cooperative effect of the repressor. The dimeric repressor MecI regulates the mecA gene that encodes the penicillin-binding protein PBP-2a in methicillin-resistant Staphylococcus aureus (MRSA). MecI is similar to BlaI, the repressor for the blaZ gene of β-lactamase. MecI and BlaI can bind to both operator DNA sequences. The crystal structure of MecI in complex with the 32 base-pair cognate DNA of mec was determined to 3.8 Å resolution. MecI is a homodimer and each monomer consists of a compact N-terminal winged-helix domain, which binds to DNA,more » and a loosely packed C-terminal helical domain, which intertwines with its counter-monomer. The crystal contains horizontal layers of virtual DNA double helices extending in three directions, which are separated by perpendicular DNA segments. Each DNA segment is bound to two MecI dimers. Similar to the BlaI–mec complex, but unlike the MecI–bla complex, the MecI repressors bind to both sides of the mec DNA dyad that contains four conserved sequences of TACA/TGTA. The results confirm the up-and-down binding to the mec operator, which may account for cooperative effect of the repressor.« less

Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

PubMed

Terunuma, Toshiyuki; Tokui, Aoi; Sakae, Takeji

2018-03-01

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tracking should be performed by controlling "importance recognition": the understanding that soft-tissue is an important tracking feature and bone structure is unimportant. We propose a new real-time tumor-contouring method that uses deep learning with importance recognition control. The novelty of the proposed method is the combination of the devised random overlay method and supervised deep learning to induce the recognition of structures in tumor contouring as important or unimportant. This method can be used for tumor contouring because it uses deep learning to perform image segmentation. Our results from a simulated fluoroscopy model showed accurate tracking of a low-visibility tumor with an error of approximately 1 mm, even if enhanced bone structure acted as an obstacle. A high similarity of approximately 0.95 on the Jaccard index was observed between the segmented and ground truth tumor regions. A short processing time of 25 ms was achieved. The results of this simulated fluoroscopy model support the feasibility of robust real-time tumor contouring with fluoroscopy. Further studies using clinical fluoroscopy are highly anticipated.

Propensities of peptides containing the Asn-Gly segment to form β-turn and β-hairpin structures.

PubMed

Kang, Young Kee; Yoo, In Kee

2016-09-01

The propensities of peptides that contain the Asn-Gly segment to form β-turn and β-hairpin structures were explored using the density functional methods and the implicit solvation model in CH2 Cl2 and water. The populations of preferred β-turn structures varied depending on the sequence and solvent polarity. In solution, β-hairpin structures with βI' turn motifs were most preferred for the heptapeptides containing the Asn-Gly segment regardless of the sequence of the strands. These preferences in solution are consistent with the corresponding X-ray structures. The sequence, H-bond strengths, solvent polarity, and conformational flexibility appeared to interact to determine the preferred β-hairpin structure of each heptapeptide, although the β-turn segments played a role in promoting the formation of β-hairpin structures and the β-hairpin propensity varied. In the heptapeptides containing the Asn-Gly segment, the β-hairpin formation was enthalpically favored and entropically disfavored at 25°C in water. The calculated results for β-turns and β-hairpins containing the Asn-Gly segment imply that these structural preferences may be useful for the design of bioactive macrocyclic peptides containing β-hairpin mimics and the design of binding epitopes for protein-protein and protein-nucleic acid recognitions. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 653-664, 2016. © 2016 Wiley Periodicals, Inc.

Segmentation of white matter hyperintensities using convolutional neural networks with global spatial information in routine clinical brain MRI with none or mild vascular pathology.

PubMed

Rachmadi, Muhammad Febrian; Valdés-Hernández, Maria Del C; Agan, Maria Leonora Fatimah; Di Perri, Carol; Komura, Taku

2018-06-01

We propose an adaptation of a convolutional neural network (CNN) scheme proposed for segmenting brain lesions with considerable mass-effect, to segment white matter hyperintensities (WMH) characteristic of brains with none or mild vascular pathology in routine clinical brain magnetic resonance images (MRI). This is a rather difficult segmentation problem because of the small area (i.e., volume) of the WMH and their similarity to non-pathological brain tissue. We investigate the effectiveness of the 2D CNN scheme by comparing its performance against those obtained from another deep learning approach: Deep Boltzmann Machine (DBM), two conventional machine learning approaches: Support Vector Machine (SVM) and Random Forest (RF), and a public toolbox: Lesion Segmentation Tool (LST), all reported to be useful for segmenting WMH in MRI. We also introduce a way to incorporate spatial information in convolution level of CNN for WMH segmentation named global spatial information (GSI). Analysis of covariance corroborated known associations between WMH progression, as assessed by all methods evaluated, and demographic and clinical data. Deep learning algorithms outperform conventional machine learning algorithms by excluding MRI artefacts and pathologies that appear similar to WMH. Our proposed approach of incorporating GSI also successfully helped CNN to achieve better automatic WMH segmentation regardless of network's settings tested. The mean Dice Similarity Coefficient (DSC) values for LST-LGA, SVM, RF, DBM, CNN and CNN-GSI were 0.2963, 0.1194, 0.1633, 0.3264, 0.5359 and 5389 respectively. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Boundary overlap for medical image segmentation evaluation

NASA Astrophysics Data System (ADS)

Yeghiazaryan, Varduhi; Voiculescu, Irina

2017-03-01

All medical image segmentation algorithms need to be validated and compared, and yet no evaluation framework is widely accepted within the imaging community. Collections of segmentation results often need to be compared and ranked by their effectiveness. Evaluation measures which are popular in the literature are based on region overlap or boundary distance. None of these are consistent in the way they rank segmentation results: they tend to be sensitive to one or another type of segmentation error (size, location, shape) but no single measure covers all error types. We introduce a new family of measures, with hybrid characteristics. These measures quantify similarity/difference of segmented regions by considering their overlap around the region boundaries. This family is more sensitive than other measures in the literature to combinations of segmentation error types. We compare measure performance on collections of segmentation results sourced from carefully compiled 2D synthetic data, and also on 3D medical image volumes. We show that our new measure: (1) penalises errors successfully, especially those around region boundaries; (2) gives a low similarity score when existing measures disagree, thus avoiding overly inflated scores; and (3) scores segmentation results over a wider range of values. We consider a representative measure from this family and the effect of its only free parameter on error sensitivity, typical value range, and running time.

Layout pattern analysis using the Voronoi diagram of line segments

NASA Astrophysics Data System (ADS)

Dey, Sandeep Kumar; Cheilaris, Panagiotis; Gabrani, Maria; Papadopoulou, Evanthia

2016-01-01

Early identification of problematic patterns in very large scale integration (VLSI) designs is of great value as the lithographic simulation tools face significant timing challenges. To reduce the processing time, such a tool selects only a fraction of possible patterns which have a probable area of failure, with the risk of missing some problematic patterns. We introduce a fast method to automatically extract patterns based on their structure and context, using the Voronoi diagram of line-segments as derived from the edges of VLSI design shapes. Designers put line segments around the problematic locations in patterns called "gauges," along which the critical distance is measured. The gauge center is the midpoint of a gauge. We first use the Voronoi diagram of VLSI shapes to identify possible problematic locations, represented as gauge centers. Then we use the derived locations to extract windows containing the problematic patterns from the design layout. The problematic locations are prioritized by the shape and proximity information of the design polygons. We perform experiments for pattern selection in a portion of a 22-nm random logic design layout. The design layout had 38,584 design polygons (consisting of 199,946 line segments) on layer Mx, and 7079 markers generated by an optical rule checker (ORC) tool. The optical rules specify requirements for printing circuits with minimum dimension. Markers are the locations of some optical rule violations in the layout. We verify our approach by comparing the coverage of our extracted patterns to the ORC-generated markers. We further derive a similarity measure between patterns and between layouts. The similarity measure helps to identify a set of representative gauges that reduces the number of patterns for analysis.

Along strike variation of active fault arrays and their effect on landscape morphology of the northwestern Himalaya

NASA Astrophysics Data System (ADS)

Nennewitz, Markus; Thiede, Rasmus; Bookhagen, Bodo

2017-04-01

The location and magnitude of the active deformation of the Himalaya has been debated for decades, but several aspects remain unknown. For instance, the spatial distribution of the deformation and the shortening that ultimately sustains Himalayan topography and the activity of major fault zones are not well constrained neither for the present day and nor for Holocene and Quarternary timescales. Because of these weakly constrained factors, many previous studies have assumed that the structural setting and the fault geometry of the Himalaya is continuous along strike and similar to fault geometries of central Nepal. Thus, the sub-surface structural information from central Nepal have been projected along strike, but have not been verified at other locations. In this study we use digital topographic analysis of the NW Himalaya. We obtained catchment-averaged, normalized steepness indexes of longitudinal river profiles with drainage basins ranging between 5 and 250km2 and analyzed the relative change in their spatial distribution both along and across strike. More specific, we analyzed the relative changes of basins located in the footwall and in the hanging wall of major fault zones. Under the assumption that along strike changes in the normalized steepness index are primarily controlled by the activity of thrust segments, we revealed new insights in the tectonic deformation and uplift pattern. Our results show three different segments along the northwest Himalaya, which are located, from east to west, in Garwhal, Chamba and Kashmir Himalaya. These have formed independent orogenic segments characterized by significant changes in their structural architecture and fault geometry. Moreover, their topographic changes indicate strong variations on fault displacement rates across first-order fault zones. With the help of along- and across-strike profiles, we were able to identify fault segments of pronounced fault activity across MFT, MBT, and the PT2 and identify the location of along strike changes which are interpreted as their segment boundaries. In addition to the steepness indices we use the accumulation of elevation data as a proxy for the strain that has been accumulated over a specific distance. Thus, despite the changes in topography, structural setting, and kinematics along the NW Himalaya we observe that the topography of the orogen is in good agreement with recently measured convergence rates obtained from GPS campaigns. These data suggest reduced crustal shortening towards the northwest. Deformation in the Central Himalaya has been explained either by in-sequence thrusting along the MFT that localize the entire Holocene shortening or a combination of this with out-of-sequence thrusting in the vicinity of the PT2. In contrast to these conceptual models, we propose that the segmented NW Himalaya is a product of the synchronous activity of different fault segments, accommodating the crustal shortening along three independently deforming organic segments. The lateral discontinuity of these segments is responsible for the accommodation of the variation in the deformation and the maintenance of the topography of the Himalaya in NW India.

Origami-based earthworm-like locomotion robots.

PubMed

Fang, Hongbin; Zhang, Yetong; Wang, K W

2017-10-16

Inspired by the morphology characteristics of the earthworms and the excellent deformability of origami structures, this research creates a novel earthworm-like locomotion robot through exploiting the origami techniques. In this innovation, appropriate actuation mechanisms are incorporated with origami ball structures into the earthworm-like robot 'body', and the earthworm's locomotion mechanism is mimicked to develop a gait generator as the robot 'centralized controller'. The origami ball, which is a periodic repetition of waterbomb units, could output significant bidirectional (axial and radial) deformations in an antagonistic way similar to the earthworm's body segment. Such bidirectional deformability can be strategically programmed by designing the number of constituent units. Experiments also indicate that the origami ball possesses two outstanding mechanical properties that are beneficial to robot development: one is the structural multistability in the axil direction that could contribute to the robot control implementation; and the other is the structural compliance in the radial direction that would increase the robot robustness and applicability. To validate the origami-based innovation, this research designs and constructs three robot segments based on different axial actuators: DC-motor, shape-memory-alloy springs, and pneumatic balloon. Performance evaluations reveal their merits and limitations, and to prove the concept, the DC-motor actuation is selected for building a six-segment robot prototype. Learning from earthworms' fundamental locomotion mechanism-retrograde peristalsis wave, seven gaits are automatically generated; controlled by which, the robot could achieve effective locomotion with qualitatively different modes and a wide range of average speeds. The outcomes of this research could lead to the development of origami locomotion robots with low fabrication costs, high customizability, light weight, good scalability, and excellent re-configurability.

Interplay of Structure and Sediment Supply May Influence Subduction Zone Rupture Patches and Propagation

NASA Astrophysics Data System (ADS)

Goldfinger, C.; Wang, K.; Witter, R.; Baptista, A.; Zhang, Y.; Priest, G.; Nelson, H.; Morey, A.; Johnson, J.

2007-12-01

The question of whether there are universal controls on the genesis and maintenance of large slip and moment patches along strike on subduction megathrusts has proved remarkably elusive, in part due to the short temporal records we have of these great events around the globe. Many events this century are poorly constrained, and many subduction zones only have one or a few events available for comparison. Long historical records and good structural constraints have made Nankai a leading case for basin centered asperities, yet the recent Sumatra Mw 9.2 rupture models show that slip and moment for the most part avoided basins and was centered under structural highs. In Cascadia, both deformation and tsunami models clearly fit the respective subsidence and runup data better if slip in past events was centered under or did not avoid these highs as opposed to basin centered model. Onshore and offshore paleoseismic evidence from 38 Cascadia earthquakes strongly suggest that structural segmentation plays a role only along the southernmost margin. These data do not provide information on moment or slip distribution, but do effectively constrain rupture lengths. Rupture lengths constrained by the paleoseismic data show that there is no Holocene segmentation for the northern margin, and that southern segments may be controlled by some of the obvious structural boundaries such as the Blanco Fracture zone, and outer arc uplifts and forearc basins. Where resolution is adequate, these data also suggest that ruptures die out into the basins and are linked multi-segment ruptures of structural uplifts, similar to that observed in the 2004 and 2005 earthquakes from Sumatra where outer arc uplifts may mark segment boundaries, high slip patches and initiation points for great earthquakes. The difference between the rupture modes observed for Nankai and Sumatra, and suggested here for Cascadia may be linked to the sediment supply for these systems. Cascadia and Sumatra are both systems where massive submarine fans are accreting to the margin in their northern regions, with incoming sections of 3-4 km thickness that taper southward. These thick sections promote high fluid pressure, but also tend to smooth the plate interface with respect to structures in both the downgoing and upper plates. A smooth plate interface has long been thought to promote long ruptures and high moment release, and so we suspect that northern Cascadia and northern Sumatra may be prone to large ruptures due to the masking of other structures by large influxes of sediment on the subducting plate. By comparison, the relatively thin sediment supply at Nankai may allow these structural boundaries to play a greater role in rupture propagation and moment release. The smaller southern Cascadia ruptures are also consistent with this model, with structural control taking precedence as the sediment supply thins southward.

Automated segmentation of the atrial region and fossa ovalis towards computer-aided planning of inter-atrial wall interventions.

PubMed

Morais, Pedro; Vilaça, João L; Queirós, Sandro; Marchi, Alberto; Bourier, Felix; Deisenhofer, Isabel; D'hooge, Jan; Tavares, João Manuel R S

2018-07-01

Image-fusion strategies have been applied to improve inter-atrial septal (IAS) wall minimally-invasive interventions. Hereto, several landmarks are initially identified on richly-detailed datasets throughout the planning stage and then combined with intra-operative images, enhancing the relevant structures and easing the procedure. Nevertheless, such planning is still performed manually, which is time-consuming and not necessarily reproducible, hampering its regular application. In this article, we present a novel automatic strategy to segment the atrial region (left/right atrium and aortic tract) and the fossa ovalis (FO). The method starts by initializing multiple 3D contours based on an atlas-based approach with global transforms only and refining them to the desired anatomy using a competitive segmentation strategy. The obtained contours are then applied to estimate the FO by evaluating both IAS wall thickness and the expected FO spatial location. The proposed method was evaluated in 41 computed tomography datasets, by comparing the atrial region segmentation and FO estimation results against manually delineated contours. The automatic segmentation method presented a performance similar to the state-of-the-art techniques and a high feasibility, failing only in the segmentation of one aortic tract and of one right atrium. The FO estimation method presented an acceptable result in all the patients with a performance comparable to the inter-observer variability. Moreover, it was faster and fully user-interaction free. Hence, the proposed method proved to be feasible to automatically segment the anatomical models for the planning of IAS wall interventions, making it exceptionally attractive for use in the clinical practice. Copyright © 2018 Elsevier B.V. All rights reserved.

Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-Weighted MRI.

PubMed

Xie, Long; Wisse, Laura E M; Das, Sandhitsu R; Wang, Hongzhi; Wolk, David A; Manjón, Jose V; Yushkevich, Paul A

2016-10-01

Quantification of medial temporal lobe (MTL) cortices, including entorhinal cortex (ERC) and perirhinal cortex (PRC), from in vivo MRI is desirable for studying the human memory system as well as in early diagnosis and monitoring of Alzheimer's disease. However, ERC and PRC are commonly over-segmented in T1-weighted (T1w) MRI because of the adjacent meninges that have similar intensity to gray matter in T1 contrast. This introduces errors in the quantification and could potentially confound imaging studies of ERC/PRC. In this paper, we propose to segment MTL cortices along with the adjacent meninges in T1w MRI using an established multi-atlas segmentation framework together with super-resolution technique. Experimental results comparing the proposed pipeline with existing pipelines support the notion that a large portion of meninges is segmented as gray matter by existing algorithms but not by our algorithm. Cross-validation experiments demonstrate promising segmentation accuracy. Further, agreement between the volume and thickness measures from the proposed pipeline and those from the manual segmentations increase dramatically as a result of accounting for the confound of meninges. Evaluated in the context of group discrimination between patients with amnestic mild cognitive impairment and normal controls, the proposed pipeline generates more biologically plausible results and improves the statistical power in discriminating groups in absolute terms comparing to other techniques using T1w MRI. Although the performance of the proposed pipeline is inferior to that using T2-weighted MRI, which is optimized to image MTL sub-structures, the proposed pipeline could still provide important utilities in analyzing many existing large datasets that only have T1w MRI available.

Shortest-path constraints for 3D multiobject semiautomatic segmentation via clustering and Graph Cut.

PubMed

Kéchichian, Razmig; Valette, Sébastien; Desvignes, Michel; Prost, Rémy

2013-11-01

We derive shortest-path constraints from graph models of structure adjacency relations and introduce them in a joint centroidal Voronoi image clustering and Graph Cut multiobject semiautomatic segmentation framework. The vicinity prior model thus defined is a piecewise-constant model incurring multiple levels of penalization capturing the spatial configuration of structures in multiobject segmentation. Qualitative and quantitative analyses and comparison with a Potts prior-based approach and our previous contribution on synthetic, simulated, and real medical images show that the vicinity prior allows for the correct segmentation of distinct structures having identical intensity profiles and improves the precision of segmentation boundary placement while being fairly robust to clustering resolution. The clustering approach we take to simplify images prior to segmentation strikes a good balance between boundary adaptivity and cluster compactness criteria furthermore allowing to control the trade-off. Compared with a direct application of segmentation on voxels, the clustering step improves the overall runtime and memory footprint of the segmentation process up to an order of magnitude without compromising the quality of the result.

Electromigration resistance in a short three-contact interconnect tree

NASA Astrophysics Data System (ADS)

Chang, C. W.; Choi, Z.-S.; Thompson, C. V.; Gan, C. L.; Pey, K. L.; Choi, W. K.; Hwang, N.

2006-05-01

Electromigration has been characterized in via-terminated interconnect lines with additional vias in the middle, creating two adjacent segments that can be stressed independently. The mortality of a segment was found to depend on the direction and magnitude of the current in the adjacent segment, confirming that there is not a fixed value of the product of the current density and segment length, jL, that defines immortality in individual segments that are part of a multisegment interconnect tree. Instead, it is found that the probability of failure of a multisegment tree increases with the increasing value of an effective jL product defined in earlier work. However, contrary to expectations, the failures were still observed when (jL)eff was less than the critical jL product for which lines were found to be immortal in single-segment test structures. It is argued that this is due to reservoir effects associated with unstressed segments or due to liner failure at the central via. Multisegment test structures are therefore shown to reveal more types of failure mechanisms and mortality conditions that are not found in tests with single-segment structures.

Line segment extraction for large scale unorganized point clouds

NASA Astrophysics Data System (ADS)

Lin, Yangbin; Wang, Cheng; Cheng, Jun; Chen, Bili; Jia, Fukai; Chen, Zhonggui; Li, Jonathan

2015-04-01

Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction.

Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

PubMed

Zuluaga, Maria A; Rodionov, Roman; Nowell, Mark; Achhala, Sufyan; Zombori, Gergely; Mendelson, Alex F; Cardoso, M Jorge; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sébastien

2015-08-01

Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying significantly associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer-assisted planning systems that can optimise the safety profile of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Twelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89 ± 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ± 0.03). Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

Demountable externally anchored low-stress magnet system and related method

DOEpatents

Powell, James; Hsieh, Shih-Yung; Lehner, John R.

1981-01-01

Toroidal field coils are interlaced with other toroidal structures and are operated under supercooled conditions. To facilitate demounting the toroidal field coils, which are supercooled, they are made in the form of connected segments constituting coils of polygonal form. The segments may be rectilinear in form, but some may also be U-shaped or L-shaped. The segments are detachable from one another and are supported in load relieving manner. Power devices are used to displace the segments to facilitate removal of the coils from the aforesaid toroidal structures and to provide for the accommodation of dimensional changes and stresses due to thermal and magnetic conditions. The segments are formed of spaced parallel conductive slabs with the slabs of one segment being interdigitated with the slabs of the adjacent segment. The interdigitated slabs may be soldered together or slidingly engaged. The slabs are shaped to accommodate superconductors and to provide passages for a cooling medium. The slabs are moreover separated by insulator slabs with which they form a coil structure which is jacketed.

Brain blood vessel segmentation using line-shaped profiles

NASA Astrophysics Data System (ADS)

Babin, Danilo; Pižurica, Aleksandra; De Vylder, Jonas; Vansteenkiste, Ewout; Philips, Wilfried

2013-11-01

Segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, especially for embolization of cerebral aneurysms and arteriovenous malformations (AVMs). In order to perform embolization of the AVM, the structural and geometric information of blood vessels from 3D images is of utmost importance. For this reason, the in-depth segmentation of cerebral blood vessels is usually done as a fusion of different segmentation techniques, often requiring extensive user interaction. In this paper we introduce the idea of line-shaped profiling with an application to brain blood vessel and AVM segmentation, efficient both in terms of resolving details and in terms of computation time. Our method takes into account both local proximate and wider neighbourhood of the processed pixel, which makes it efficient for segmenting large blood vessel tree structures, as well as fine structures of the AVMs. Another advantage of our method is that it requires selection of only one parameter to perform segmentation, yielding very little user interaction.

Deep structure of Pyrenees range (SW Europe) imaged by joint inversion of gravity and teleseismic delay time

NASA Astrophysics Data System (ADS)

Dufréchou, G.; Tiberi, C.; Martin, R.; Bonvalot, S.; Chevrot, S.; Seoane, L.

2018-04-01

We present a new model of the lithosphere and asthenosphere structure down to 300 km depth beneath the Pyrenees from the joint inversion of recent gravity and teleseismic data. Unlike previous studies, crustal correction were not applied on teleseismic data in order (i) to preserve the consistency between gravity data, which are mainly sensitive to the density structure of the crust.lithosphere, and travel time data, and (ii) to avoid the introduction of biases resulting from crustal reductions. The density model down to 100 km depth is preferentially used here to discuss the lithospheric structure of the Pyrenees, whereas the asthenospheric structure from 100 km to 300 km depth is discussed from our velocity model. The absence of a high density anomaly in our model between 30-100 km depth (except the Labourd density anomaly) in the northern part of the Pyrenees seems to preclude eclogitization of the subducted Iberian crust at the scale of the entire Pyrenean range. Local eclogitization of the deep Pyrenean crust beneath the western part of the Axial Zone (West of Andorra) associated with the positive Central density anomaly is proposed. The Pyrenean lithosphere in density and velocity models appears segmented from East to West. No clear relation between the along-strike segmentation and mapped major faults is visible in our models. The Pyrenees' lithosphere segments are associated to different seismicity pattern in the Pyrenees suggesting a possible relation between the deep structure of the Pyrenees and its seismicity in the upper crust. The concentration of earthquakes localized just straight up the Central density anomaly can result of the subsidence and/or delamination of an eclogitized Pyrenean deep root. The velocity model in the asthenosphere is similar to previous studies. The absence of a high-velocity anomaly in the upper mantle and transition zone (i.e. 125 to 225 km depth) seems to preclude the presence of a detached oceanic lithosphere beneath the European lithosphere.

Scalable Joint Segmentation and Registration Framework for Infant Brain Images.

PubMed

Dong, Pei; Wang, Li; Lin, Weili; Shen, Dinggang; Wu, Guorong

2017-03-15

The first year of life is the most dynamic and perhaps the most critical phase of postnatal brain development. The ability to accurately measure structure changes is critical in early brain development study, which highly relies on the performances of image segmentation and registration techniques. However, either infant image segmentation or registration, if deployed independently, encounters much more challenges than segmentation/registration of adult brains due to dynamic appearance change with rapid brain development. In fact, image segmentation and registration of infant images can assists each other to overcome the above challenges by using the growth trajectories (i.e., temporal correspondences) learned from a large set of training subjects with complete longitudinal data. Specifically, a one-year-old image with ground-truth tissue segmentation can be first set as the reference domain. Then, to register the infant image of a new subject at earlier age, we can estimate its tissue probability maps, i.e., with sparse patch-based multi-atlas label fusion technique, where only the training images at the respective age are considered as atlases since they have similar image appearance. Next, these probability maps can be fused as a good initialization to guide the level set segmentation. Thus, image registration between the new infant image and the reference image is free of difficulty of appearance changes, by establishing correspondences upon the reasonably segmented images. Importantly, the segmentation of new infant image can be further enhanced by propagating the much more reliable label fusion heuristics at the reference domain to the corresponding location of the new infant image via the learned growth trajectories, which brings image segmentation and registration to assist each other. It is worth noting that our joint segmentation and registration framework is also flexible to handle the registration of any two infant images even with significant age gap in the first year of life, by linking their joint segmentation and registration through the reference domain. Thus, our proposed joint segmentation and registration method is scalable to various registration tasks in early brain development studies. Promising segmentation and registration results have been achieved for infant brain MR images aged from 2-week-old to 1-year-old, indicating the applicability of our method in early brain development study.

Atomic structures of corkscrew-forming segments of SOD1 reveal varied oligomer conformations.

PubMed

Sangwan, Smriti; Sawaya, Michael R; Murray, Kevin A; Hughes, Michael P; Eisenberg, David S

2018-02-17

The aggregation cascade of disease-related amyloidogenic proteins, terminating in insoluble amyloid fibrils, involves intermediate oligomeric states. The structural and biochemical details of these oligomers have been largely unknown. Here we report crystal structures of variants of the cytotoxic oligomer-forming segment residues 28-38 of the ALS-linked protein, SOD1. The crystal structures reveal three different architectures: corkscrew oligomeric structure, nontwisting curved sheet structure and a steric zipper proto-filament structure. Our work highlights the polymorphism of the segment 28-38 of SOD1 and identifies the molecular features of amyloidogenic entities. © 2018 The Protein Society.

Research on a pulmonary nodule segmentation method combining fast self-adaptive FCM and classification.

PubMed

Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai

2015-01-01

The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms.

A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain.

PubMed

Hall, L O; Bensaid, A M; Clarke, L P; Velthuizen, R P; Silbiger, M S; Bezdek, J C

1992-01-01

Magnetic resonance (MR) brain section images are segmented and then synthetically colored to give visual representations of the original data with three approaches: the literal and approximate fuzzy c-means unsupervised clustering algorithms, and a supervised computational neural network. Initial clinical results are presented on normal volunteers and selected patients with brain tumors surrounded by edema. Supervised and unsupervised segmentation techniques provide broadly similar results. Unsupervised fuzzy algorithms were visually observed to show better segmentation when compared with raw image data for volunteer studies. For a more complex segmentation problem with tumor/edema or cerebrospinal fluid boundary, where the tissues have similar MR relaxation behavior, inconsistency in rating among experts was observed, with fuzz-c-means approaches being slightly preferred over feedforward cascade correlation results. Various facets of both approaches, such as supervised versus unsupervised learning, time complexity, and utility for the diagnostic process, are compared.

MS lesion segmentation using a multi-channel patch-based approach with spatial consistency

NASA Astrophysics Data System (ADS)

Mechrez, Roey; Goldberger, Jacob; Greenspan, Hayit

2015-03-01

This paper presents an automatic method for segmentation of Multiple Sclerosis (MS) in Magnetic Resonance Images (MRI) of the brain. The approach is based on similarities between multi-channel patches (T1, T2 and FLAIR). An MS lesion patch database is built using training images for which the label maps are known. For each patch in the testing image, k similar patches are retrieved from the database. The matching labels for these k patches are then combined to produce an initial segmentation map for the test case. Finally a novel iterative patch-based label refinement process based on the initial segmentation map is performed to ensure spatial consistency of the detected lesions. A leave-one-out evaluation is done for each testing image in the MS lesion segmentation challenge of MICCAI 2008. Results are shown to compete with the state-of-the-art methods on the MICCAI 2008 challenge.

Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches.

PubMed

Ogier, Augustin; Sdika, Michael; Foure, Alexandre; Le Troter, Arnaud; Bendahan, David

2017-07-01

Manual and automated segmentation of individual muscles in magnetic resonance images have been recognized as challenging given the high variability of shapes between muscles and subjects and the discontinuity or lack of visible boundaries between muscles. In the present study, we proposed an original algorithm allowing a semi-automatic transversal propagation of manually-drawn masks. Our strategy was based on several ascending and descending non-linear registration approaches which is similar to the estimation of a Lagrangian trajectory applied to manual masks. Using several manually-segmented slices, we have evaluated our algorithm on the four muscles of the quadriceps femoris group. We mainly showed that our 3D propagated segmentation was very accurate with an averaged Dice similarity coefficient value higher than 0.91 for the minimal manual input of only two manually-segmented slices.

Task-oriented lossy compression of magnetic resonance images

NASA Astrophysics Data System (ADS)

Anderson, Mark C.; Atkins, M. Stella; Vaisey, Jacques

1996-04-01

A new task-oriented image quality metric is used to quantify the effects of distortion introduced into magnetic resonance images by lossy compression. This metric measures the similarity between a radiologist's manual segmentation of pathological features in the original images and the automated segmentations performed on the original and compressed images. The images are compressed using a general wavelet-based lossy image compression technique, embedded zerotree coding, and segmented using a three-dimensional stochastic model-based tissue segmentation algorithm. The performance of the compression system is then enhanced by compressing different regions of the image volume at different bit rates, guided by prior knowledge about the location of important anatomical regions in the image. Application of the new system to magnetic resonance images is shown to produce compression results superior to the conventional methods, both subjectively and with respect to the segmentation similarity metric.

Vessel segmentation in 3D spectral OCT scans of the retina

NASA Astrophysics Data System (ADS)

Niemeijer, Meindert; Garvin, Mona K.; van Ginneken, Bram; Sonka, Milan; Abràmoff, Michael D.

2008-03-01

The latest generation of spectral optical coherence tomography (OCT) scanners is able to image 3D cross-sectional volumes of the retina at a high resolution and high speed. These scans offer a detailed view of the structure of the retina. Automated segmentation of the vessels in these volumes may lead to more objective diagnosis of retinal vascular disease including hypertensive retinopathy, retinopathy of prematurity. Additionally, vessel segmentation can allow color fundus images to be registered to these 3D volumes, possibly leading to a better understanding of the structure and localization of retinal structures and lesions. In this paper we present a method for automatically segmenting the vessels in a 3D OCT volume. First, the retina is automatically segmented into multiple layers, using simultaneous segmentation of their boundary surfaces in 3D. Next, a 2D projection of the vessels is produced by only using information from certain segmented layers. Finally, a supervised, pixel classification based vessel segmentation approach is applied to the projection image. We compared the influence of two methods for the projection on the performance of the vessel segmentation on 10 optic nerve head centered 3D OCT scans. The method was trained on 5 independent scans. Using ROC analysis, our proposed vessel segmentation system obtains an area under the curve of 0.970 when compared with the segmentation of a human observer.

Pancreas segmentation from 3D abdominal CT images using patient-specific weighted subspatial probabilistic atlases

NASA Astrophysics Data System (ADS)

Karasawa, Kenichi; Oda, Masahiro; Hayashi, Yuichiro; Nimura, Yukitaka; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Rueckert, Daniel; Mori, Kensaku

2015-03-01

Abdominal organ segmentations from CT volumes are now widely used in the computer-aided diagnosis and surgery assistance systems. Among abdominal organs, the pancreas is especially difficult to segment because of its large individual differences of the shape and position. In this paper, we propose a new pancreas segmentation method from 3D abdominal CT volumes using patient-specific weighted-subspatial probabilistic atlases. First of all, we perform normalization of organ shapes in training volumes and an input volume. We extract the Volume Of Interest (VOI) of the pancreas from the training volumes and an input volume. We divide each training VOI and input VOI into some cubic regions. We use a nonrigid registration method to register these cubic regions of the training VOI to corresponding regions of the input VOI. Based on the registration results, we calculate similarities between each cubic region of the training VOI and corresponding region of the input VOI. We select cubic regions of training volumes having the top N similarities in each cubic region. We subspatially construct probabilistic atlases weighted by the similarities in each cubic region. After integrating these probabilistic atlases in cubic regions into one, we perform a rough-to-precise segmentation of the pancreas using the atlas. The results of the experiments showed that utilization of the training volumes having the top N similarities in each cubic region led good results of the pancreas segmentation. The Jaccard Index and the average surface distance of the result were 58.9% and 2.04mm on average, respectively.

Volcanic Eruptions of the EPR and Ridge Axis Segmentation: An Interdisciplinary View

NASA Astrophysics Data System (ADS)

White, S.; Soule, S. A.; Tolstoy, M.; Waldhauser, F.; Rubin, K.

2008-12-01

The eruption of the EPR in 2005-06 provides an ideal window into the relationship between fine-scale segmentation of the ridge axis and individual eruptive episodes. Lava flow mapping of the eruption by visual and acoustic images, precise dates on multiple eruptive units, stress information from seismicity, long-term records of hydrothermal activity, and well known segment boundaries illustrate the relationships between eruptions and segmentation of mid-ocean ridges. Lava flows emerged from several sections of the axial summit trough (AST) during the eruption, presumably from en echelon fissures between 9 45'N and 9 57'N. Each en echelon fissure is a 4th order segment, and the overall area matches the 3rd Order segment between ~9 45'N and ~9 58'N. Within the eruption, the primary eruptive fissure jumped east by 600 m at 9 53'N, and ran along an inward facing fault scarp, although limited lava effusion also extended northward along the axial fissure. A zone of high seismicity connects the normal fault bounding the eastern fissure eruption with the main locus of eruption on the ridge axis to the south, suggesting that the offset eruption may have occurred in response to stress buildup on this fault. Radiometric ages indicate that the entire along-axis extent of the eruptive fissures activated initially, but that volcanic activity focused to a single fourth-order segment within 1-3 months. Previously indentified breaks in the AST and its overall outline were largely unchanged by the eruption. These observations support the hypothesis that fourth-order segments are offsets controlled by the mechanics of dike emplacement, whereas third-order segments represent discrete volcanic systems. Dike segmentation may be controlled by variations in underlying ridge structure or the magma reservoir. Hydrothermal systems disrupted as far south as 9 37'N may be responding to cracking due to stress interaction or share a common deeper magmatic source. Comparisons between the 1991 EPR eruption at the same site, and several mapped southern EPR eruptions, the 10 45'N EPR eruption in ca. 2003 all show similar relationships to segmentation

The Structure of Lombricine Kinase

PubMed Central

Bush, D. Jeffrey; Kirillova, Olga; Clark, Shawn A.; Davulcu, Omar; Fabiola, Felcy; Xie, Qing; Somasundaram, Thayumanasamy; Ellington, W. Ross; Chapman, Michael S.

2011-01-01

Lombricine kinase is a member of the phosphagen kinase family and a homolog of creatine and arginine kinases, enzymes responsible for buffering cellular ATP levels. Structures of lombricine kinase from the marine worm Urechis caupo were determined by x-ray crystallography. One form was crystallized as a nucleotide complex, and the other was substrate-free. The two structures are similar to each other and more similar to the substrate-free forms of homologs than to the substrate-bound forms of the other phosphagen kinases. Active site specificity loop 309–317, which is disordered in substrate-free structures of homologs and is known from the NMR of arginine kinase to be inherently dynamic, is resolved in both lombricine kinase structures, providing an improved basis for understanding the loop dynamics. Phosphagen kinases undergo a segmented closing on substrate binding, but the lombricine kinase ADP complex is in the open form more typical of substrate-free homologs. Through a comparison with prior complexes of intermediate structure, a correlation was revealed between the overall enzyme conformation and the substrate interactions of His178. Comparative modeling provides a rationale for the more relaxed specificity of these kinases, of which the natural substrates are among the largest of the phosphagen substrates. PMID:21212263

TALC: a new deployable concept for a 20m far-infrared space telescope

NASA Astrophysics Data System (ADS)

Durand, Gilles; Sauvage, Marc; Bonnet, Aymeric; Rodriguez, Louis; Ronayette, Samuel; Chanial, Pierre; Scola, Loris; Révéret, Vincent; Aussel, Hervé; Carty, Michael; Durand, Matthis; Durand, Lancelot; Tremblin, Pascal; Pantin, Eric; Berthe, Michel; Martignac, Jérôme; Motte, Frédérique; Talvard, Michel; Minier, Vincent; Bultel, Pascal

2014-08-01

TALC, Thin Aperture Light Collector is a 20 m space observatory project exploring some unconventional optical solutions (between the single dish and the interferometer) allowing the resolving power of a classical 27 m telescope. With TALC, the principle is to remove the central part of the prime mirror dish, cut the remaining ring into 24 sectors and store them on top of one-another. The aim of this far infrared telescope is to explore the 600 μm to 100 μm region. With this approach we have shown that we can store a ring-telescope of outer diameter 20m and ring thickness of 3m inside the fairing of Ariane 5 or Ariane 6. The general structure is the one of a bicycle wheel, whereas the inner sides of the segments are in compression to each other and play the rule of a rim. The segments are linked to each other using a pantograph scissor system that let the segments extend from a pile of dishes to a parabolic ring keeping high stiffness at all time during the deployment. The inner corners of the segments are linked to a central axis using spokes as in a bicycle wheel. The secondary mirror and the instrument box are built as a solid unit fixed at the extremity of the main axis. The tensegrity analysis of this structure shows a very high stiffness to mass ratio, resulting into 3 Hz Eigen frequency. The segments will consist of two composite skins and honeycomb CFRP structure build by replica process. Solid segments will be compared to deformable segments using the controlled shear of the rear surface. The adjustment of the length of the spikes and the relative position of the side of neighbor segments let control the phasing of the entire primary mirror. The telescope is cooled by natural radiation. It is protected from sun radiation by a large inflatable solar screen, loosely linked to the telescope. The orientation is performed by inertia-wheels. This telescope carries a wide field bolometer camera using cryocooler at 0.3K as one of the main instruments. This telescope may be launched with an Ariane 6 rocket up to 800 km altitude, and use a plasma stage to reach the Lagrange 2 point within 18 month. The plasma propulsion stage is a serial unit also used in commercial telecommunication satellites. When the plasma launch is completed, the solar panels will be used to provide the power for communication, orientation and power the cryo-coolers for the instruments. The guide-line for development of this telescope is to use similar techniques and serial subsystems developed for the satellite industry. This is the only way to design and manufacture a large telescope at a reasonable cost.

Multiscale simulations on conformational dynamics and membrane interactions of the non-structural 2 (NS2) transmembrane domain.

PubMed

Hung, Huynh Minh; Hang, Tran Dieu; Nguyen, Minh Tho

2016-09-09

Hepatitis C virus (HCV) is one of the most crucial global health issues, in which the HCV non-structural protein 2 (NS2), particularly its three transmembrane segments, plays a crucial role in HCV assembly. In this context, multiscale MD simulations have been applied to investigate the preferred orientation of transmembrane domain of NS2 protein (TNS2) in a POPC bilayer, structural stability and characteristic of intramembrane protein-lipid and protein-protein interaction. Our study indicates that NS2 protein adopts three trans-membrane segments with highly stable α-helix structure in a POPC bilayer and a short helical luminal segment. While the first and second TM segment involved in continuous helical domain, the third TM segment is however cleaved into two sub-segments with different tilt angles via a kink at L87G88. Salt bridges K81-E45, R32-PO4 and R43-PO4 are determined as the key factor to stabilize the structure of TM2 and TM3 which consist of charged residues located in the hydrophobic region of the membrane. Copyright © 2016 Elsevier Inc. All rights reserved.

Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.

PubMed

Babin, D; Pižurica, A; Bellens, R; De Bock, J; Shang, Y; Goossens, B; Vansteenkiste, E; Philips, W

2012-07-01

Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure. Copyright © 2012 Elsevier B.V. All rights reserved.

Aging and the segmentation of narrative film.

PubMed

Kurby, Christopher A; Asiala, Lillian K E; Mills, Steven R

2014-01-01

The perception of event structure in continuous activity is important for everyday comprehension. Although the segmentation of experience into events is a normal concomitant of perceptual processing, previous research has shown age differences in the ability to perceive structure in naturalistic activity, such as a movie of someone washing a car. However, past research has also shown that older adults have a preserved ability to comprehend events in narrative text, which suggests that narrative may improve the event processing of older adults. This study tested whether there are age differences in event segmentation at the intersection of continuous activity and narrative: narrative film. Younger and older adults watched and segmented a narrative film, The Red Balloon, into coarse and fine events. Changes in situational features, such as changes in characters, goals, and objects predicted segmentation. Analyses revealed little age-difference in segmentation behavior. This suggests the possibility that narrative structure supports event understanding for older adults.

Along-axis steps in Ethiopian rift Bouguer gravity anomalies: Implications for crustal thinning and melt emplacement prior to breakup

NASA Astrophysics Data System (ADS)

Ebinger, C. J.; Tiberi, C.; Fowler, M. R.; Hunegnaw, A.

2001-12-01

The southern Afar depression, Africa, is virtually the only area worldwide where the transition from continental rifting to seafloor spreading is exposed onshore. During mid-Miocene to Pleistocene time the rift valley was segmented along its length by long normal faults; since Pleistocene time, faulting and magmatism have jumped to a narrow ca. 60 km-long volcanic mound marked by small faults. These magmatic segments are structurally similar to slow-spreading mid-ocean ridges, yet the rift is floored by continental crust. As part of the Ethiopia Afar Geoscientific Lithospheric Experiment (EAGLE), we examine new and existing Bouguer gravity anomaly data from the rift to study the modification of the lithosphere by extensional and magmatic processes. New and existing Bouguer gravity anomaly data also show an along-axis segmentation of elongate relative positive anomalies that coincide with the magmatic segments. These anomalies are superposed on a regionally eastward increasing field as one approaches true seafloor spreading in the Gulf of Aden, and crustal thickness decreases. Quite remarkably, the magmatic segment boundaries, where data coverage is good, are marked by 15-25 mGal steps. The amplitude of the along-axis steps, as well as their across-axis characteristics, indicate that magmatic intrusion and ca. 2 km relief at the crust-mantle interface contribute to the steps. We use inverse and forward models of gravity data constrained by existing seismic and petrological data to evaluate models for the along-axis steps. EAGLE seismic data will be acquired across and along the magmatic segments to improve our understanding of breakup processes.

Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features.

PubMed

Zheng, Yefeng; Barbu, Adrian; Georgescu, Bogdan; Scheuering, Michael; Comaniciu, Dorin

2008-11-01

We propose an automatic four-chamber heart segmentation system for the quantitative functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics are discussed: heart modeling and automatic model fitting to an unseen volume. Heart modeling is a nontrivial task since the heart is a complex nonrigid organ. The model must be anatomically accurate, allow manual editing, and provide sufficient information to guide automatic detection and segmentation. Unlike previous work, we explicitly represent important landmarks (such as the valves and the ventricular septum cusps) among the control points of the model. The control points can be detected reliably to guide the automatic model fitting process. Using this model, we develop an efficient and robust approach for automatic heart chamber segmentation in 3-D CT volumes. We formulate the segmentation as a two-step learning problem: anatomical structure localization and boundary delineation. In both steps, we exploit the recent advances in learning discriminative models. A novel algorithm, marginal space learning (MSL), is introduced to solve the 9-D similarity transformation search problem for localizing the heart chambers. After determining the pose of the heart chambers, we estimate the 3-D shape through learning-based boundary delineation. The proposed method has been extensively tested on the largest dataset (with 323 volumes from 137 patients) ever reported in the literature. To the best of our knowledge, our system is the fastest with a speed of 4.0 s per volume (on a dual-core 3.2-GHz processor) for the automatic segmentation of all four chambers.

An earthworm-like robot using origami-ball structures

NASA Astrophysics Data System (ADS)

Fang, Hongbin; Zhang, Yetong; Wang, K. W.

2017-04-01

Earthworms possess extraordinary on-ground and underground mobility, which inspired researchers to mimic their morphology characteristics and locomotion mechanisms to develop crawling robots. One of the bottlenecks that constrain the development and wide-spread application of earthworm-like robots is the process of design, fabrication and assembly of the robot frameworks. Here we present a new earthworm-like robot design and prototype by exploring and utilizing origami ball structures. The origami ball is able to antagonistically output both axial and radial deformations, similar as an earthworm's body segment. The origami folding techniques also introduce many advantages to the robot development, including precise and low cost fabrication and high customizability. Starting from a flat polymer film, we adopt laser machining technique to engrave the crease pattern and manually fold the patterned flat film into an origami ball. Coupling the ball with a servomotor-driven linkage yields a robot segment. Connecting six segments in series, we obtain an earthworm-like origami robot prototype. The prototype is tested in a tube to evaluate its locomotion performance. It shows that the robot could crawl effectively in the tube, manifesting the feasibility of the origami-based design. In addition, test results indicate that the robot's locomotion could be tailored by employing different peristalsis-wave based gaits. The robot design and prototype reported in this paper could foster a new breed of crawling robots with simply design, fabrication, and assemble processes, and improved locomotion performance.

Mutagenesis of the La Crosse Virus glycoprotein supports a role for Gc (1066-1087) as the fusion peptide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plassmeyer, Matthew L.; Graduate Group Molecular and Cell Biology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104-6058; Soldan, Samantha S.

The La Crosse Virus (LACV) M segment encodes two glycoproteins (Gn and Gc), and plays a critical role in the neuropathogenesis of LACV infection as the primary determinant of neuroinvasion. A recent study from our group demonstrated that the region comprising the membrane proximal two-thirds of Gc, amino acids 860-1442, is critical in mediating LACV fusion and entry. Furthermore, computational analysis identified structural similarities between a portion of this region, amino acids 970-1350, and the E1 fusion protein of two alphaviruses: Sindbis virus and Semliki Forrest virus (SFV). Within the region 970-1350, a 22-amino-acid hydrophobic segment (1066-1087) is predicted tomore » correlate structurally with the fusion peptides of class II fusion proteins. We performed site-directed mutagenesis of key amino acids in this 22-amino acid segment and determined the functional consequences of these mutations on fusion and entry. Several mutations within this hydrophobic domain affected glycoprotein expression to some extent, but all mutations either shifted the pH threshold of fusion below that of the wild-type protein, reduced fusion efficiency, or abrogated cell-to-cell fusion and pseudotype entry altogether. These results, coupled with the aforementioned computational modeling, suggest that the LACV Gc functions as a class II fusion protein and support a role for the region Gc 1066-1087 as a fusion peptide.« less

Segmentation of brain structures in presence of a space-occupying lesion.

PubMed

Pollo, Claudio; Cuadra, Meritxell Bach; Cuisenaire, Olivier; Villemure, Jean-Guy; Thiran, Jean-Philippe

2005-02-15

Brain deformations induced by space-occupying lesions may result in unpredictable position and shape of functionally important brain structures. The aim of this study is to propose a method for segmentation of brain structures by deformation of a segmented brain atlas in presence of a space-occupying lesion. Our approach is based on an a priori model of lesion growth (MLG) that assumes radial expansion from a seeding point and involves three steps: first, an affine registration bringing the atlas and the patient into global correspondence; then, the seeding of a synthetic tumor into the brain atlas providing a template for the lesion; finally, the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. The method was applied on two meningiomas inducing a pure displacement of the underlying brain structures, and segmentation accuracy of ventricles and basal ganglia was assessed. Results show that the segmented structures were consistent with the patient's anatomy and that the deformation accuracy of surrounding brain structures was highly dependent on the accurate placement of the tumor seeding point. Further improvements of the method will optimize the segmentation accuracy. Visualization of brain structures provides useful information for therapeutic consideration of space-occupying lesions, including surgical, radiosurgical, and radiotherapeutic planning, in order to increase treatment efficiency and prevent neurological damage.

Influence of the segmentation on the characterization of cerebral networks of structural damage for patients with disorders of consciousness

NASA Astrophysics Data System (ADS)

Martínez, Darwin; Mahalingam, Jamuna J.; Soddu, Andrea; Franco, Hugo; Lepore, Natasha; Laureys, Steven; Gómez, Francisco

2015-01-01

Disorders of consciousness (DOC) are a consequence of a variety of severe brain injuries. DOC commonly results in anatomical brain modifications, which can affect cortical and sub-cortical brain structures. Postmortem studies suggest that severity of brain damage correlates with level of impairment in DOC. In-vivo studies in neuroimaging mainly focus in alterations on single structures. Recent evidence suggests that rather than one, multiple brain regions can be simultaneously affected by this condition. In other words, DOC may be linked to an underlying cerebral network of structural damage. Recently, geometrical spatial relationships among key sub-cortical brain regions, such as left and right thalamus and brain stem, have been used for the characterization of this network. This approach is strongly supported on automatic segmentation processes, which aim to extract regions of interests without human intervention. Nevertheless, patients with DOC usually present massive structural brain changes. Therefore, segmentation methods may highly influence the characterization of the underlying cerebral network structure. In this work, we evaluate the level of characterization obtained by using the spatial relationships as descriptor of a sub-cortical cerebral network (left and right thalamus) in patients with DOC, when different segmentation approaches are used (FSL, Free-surfer and manual segmentation). Our results suggest that segmentation process may play a critical role for the construction of robust and reliable structural characterization of DOC conditions.

Atlas selection for hippocampus segmentation: Relevance evaluation of three meta-information parameters.

PubMed

Dill, Vanderson; Klein, Pedro Costa; Franco, Alexandre Rosa; Pinho, Márcio Sarroglia

2018-04-01

Current state-of-the-art methods for whole and subfield hippocampus segmentation use pre-segmented templates, also known as atlases, in the pre-processing stages. Typically, the input image is registered to the template, which provides prior information for the segmentation process. Using a single standard atlas increases the difficulty in dealing with individuals who have a brain anatomy that is morphologically different from the atlas, especially in older brains. To increase the segmentation precision in these cases, without any manual intervention, multiple atlases can be used. However, registration to many templates leads to a high computational cost. Researchers have proposed to use an atlas pre-selection technique based on meta-information followed by the selection of an atlas based on image similarity. Unfortunately, this method also presents a high computational cost due to the image-similarity process. Thus, it is desirable to pre-select a smaller number of atlases as long as this does not impact on the segmentation quality. To pick out an atlas that provides the best registration, we evaluate the use of three meta-information parameters (medical condition, age range, and gender) to choose the atlas. In this work, 24 atlases were defined and each is based on the combination of the three meta-information parameters. These atlases were used to segment 352 vol from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Hippocampus segmentation with each of these atlases was evaluated and compared to reference segmentations of the hippocampus, which are available from ADNI. The use of atlas selection by meta-information led to a significant gain in the Dice similarity coefficient, which reached 0.68 ± 0.11, compared to 0.62 ± 0.12 when using only the standard MNI152 atlas. Statistical analysis showed that the three meta-information parameters provided a significant improvement in the segmentation accuracy. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Analysis of fragments of intergenome spacers of human body observed in chromosomes containing no nuclear organization].

PubMed

Kupriyanova, N S; Nechvolodov, K K; Korsunenko, A V

2014-01-01

Tandem repetitions of rDNA provide so-called nuclear organizations (NOR). On the other hand, rDNA-structures are observed in some NOR chromosomes. It was demonstrated that, in addition to ribosome biogenesis, nucleoli provided a number of functions: cell cycle regulation, stress-induced response, transcription regulation, which often induced cell cascades. The mechanisms of the induction of rDNA segments in NOR chromosomes are obscure and require further research. About 1/3 repetitions are associated with nucleoli and SINE/Alu repetitions, homogeneous repetition, and tandem repetition. Perhaps, relative position of nucleoli and chromosomes may facilitate/prevent interaction of chromosomes with rDNA clusters. The variability of two larger repetitions in the central part of rMGS, LR1, and LR2 similar by -90% and separated by several hundred pairs of bases from each other was studied in our previous works. This work was devoted to the search for the LR1-LR2 segments in other chromosomes, characterization of their terminal tips at rupture points and genome areas of incorporation of the LR1-LR2 segments.

Inducing and assessing differentiated emotion-feeling states in the laboratory.

PubMed

Philippot, P

1993-03-01

Two questions are addressed. The first question pertains to the capacity of film segments to induce emotional states that are: (a) as comparable as possible to naturally occurring emotions; (b) similar across individuals; and (c) clearly differentiated across the intended emotions. The second question concerns the discriminant capacity of self-report questionnaires of emotion-feeling states differing in their theoretical assumptions. Subjects viewed six short film segments and rated the strength of their responses on one of three kinds of questionnaires. The questionnaires were: (1) the Differential Emotions Scale that postulates category-based distinctions between emotions; (2) the Semantic Differential that postulates that emotions are distinguished along bipolar dimensions; and (3) free labelling of their feelings by the subjects (control condition with no theoretical a priori). Overall, results indicate that film segments can elicit a diversity of predictable emotions, in the same way, in a majority of individuals. In the present procedure, the Differential Emotions Scale yielded a better discrimination between emotional states than the Semantic Differential. Implications for emotion research and theories of the cognitive structure of emotion are discussed.

Pineal organs of deep-sea fish: photopigments and structure.

PubMed

Bowmaker, James K; Wagner, Hans-Joachim

2004-06-01

We have examined the morphology and photopigments of the pineal organs from a number of mesopelagic fish, including representatives of the hatchet fish (Sternoptychidae), scaly dragon-fish (Chauliodontidae) and bristlemouths (Gonostomidae). Although these fish were caught at depths of between 500 and 1000 m, the morphological organisation of their pineal organs is remarkably similar to that of surface-dwelling fish. Photoreceptor inner and outer segments protrude into the lumen of the pineal vesicle, and the outer segment is composed of a stack of up to 20 curved disks that form a cap-like cover over the inner segment. In all species, the pineal photopigment was spectrally distinct from the retinal rod pigment, with lambdamax displaced to longer wavelengths, between approximately 485 and 503 nm. We also investigated the pineal organ of the deep demersal eel, Synaphobranchus kaupi, caught at depths below 2000 m, which possesses a rod visual pigment with lambdamax at 478 nm, but the pineal pigment has lambdamax at approximately 515 nm. In one species of hatchet fish, Argyropelecus affinis, two spectral classes of pinealocyte were identified, both spectrally distinct from the retinal rod photopigment.

Semiautomated hybrid algorithm for estimation of three-dimensional liver surface in CT using dynamic cellular automata and level-sets

PubMed Central

Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla

2015-01-01

Abstract. Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as w, Δt, z, α, μ, α1, and α2, play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method. PMID:26158101

An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.

PubMed

Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong

2016-01-01

Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels.

[Building an effective nonlinear three-dimensional finite-element model of human thoracolumbar spine].

PubMed

Zeng, Zhi-Li; Cheng, Li-Ming; Zhu, Rui; Wang, Jian-Jie; Yu, Yan

2011-08-23

To build an effective nonlinear three-dimensional finite-element (FE) model of T(11)-L(3) segments for a further biomechanical study of thoracolumbar spine. The CT (computed tomography) scan images of healthy adult T(11)-L(3) segments were imported into software Simpleware 2.0 to generate a triangular mesh model. Using software Geomagic 8 for model repair and optimization, a solid model was generated into the finite element software Abaqus 6.9. The reasonable element C3D8 was selected for bone structures. Created between bony endplates, the intervertebral disc was subdivided into nucleus pulposus and annulus fibrosus (44% nucleus, 56% annulus). The nucleus was filled with 5 layers of 8-node solid elements and annulus reinforced by 8 crisscross collagenous fiber layers. The nucleus and annulus were meshed by C3D8RH while the collagen fibers meshed by two node-truss elements. The anterior (ALL) and posterior (PLL) longitudinal ligaments, flavum (FL), supraspinous (SSL), interspinous (ISL) and intertransverse (ITL) ligaments were modeled with S4R shell elements while capsular ligament (CL) was modeled with 3-node shell element. All surrounding ligaments were represented by envelope of 1 mm uniform thickness. The discs and bone structures were modeled with hyper-elastic and elasto-plastic material laws respectively while the ligaments governed by visco-elastic material law. The nonlinear three-dimensional finite-element model of T(11)-L(3) segments was generated and its efficacy verified through validating the geometric similarity and disc load-displacement and stress distribution under the impact of violence. Using ABAQUS/ EXPLICIT 6.9 the explicit dynamic finite element solver, the impact test was simulated in vitro. In this study, a 3-dimensional, nonlinear FE model including 5 vertebrae, 4 intervertebral discs and 7 ligaments consisted of 78 887 elements and 71 939 nodes. The model had good geometric similarity under the same conditions. The results of FEM intervertebral disc load-displacement curve were similar to those of in vitro test. The stress distribution results of vertebral cortical bone, posterior complex and cancellous bone were similar to those of other static experiments in a dynamic impact test under the observation of stress cloud. With the advantages of high geometric and mechanical similarity and complete thoracolumbar, hexahedral meshes, nonlinear finite element model may facilitate the impact loading test for a further dynamic analysis of injury mechanism for thoracolumbar burst fracture.

Segmenting root systems in xray computed tomography images using level sets

USDA-ARS?s Scientific Manuscript database

The segmentation of plant roots from soil and other growing mediums in xray computed tomography images is needed to effectively study the shapes of roots without excavation. However, segmentation is a challenging problem in this context because the root and non-root regions share similar features. ...

The Crystallographic Structure of Panicum Mosaic Virus (PMV)

PubMed Central

Makino, Debora L.; Larson, Steven B.; McPherson, Alexander

2012-01-01

The structure of Panicum Mosaic Virus (PMV) was determined by X-ray diffraction analysis to 2.9 Å resolution. The crystals were of pseudo symmetry F23; the true crystallographic unit cell was of space group P21 with a=411.7 Å, b=403.9 Å and c=412.5 Å, with β=89.7°. The asymmetric unit was two entire T=3 virus particles, or 360 protein subunits. The structure was solved by conventional molecular replacement from two distant homologues, Cocksfoot Mottle Virus (CfMV) and Tobacco Necrosis Virus (TNV), of ~20% sequence identity followed by phase extension. The model was initially refined with exact icosahedral constraints and then with icosahedral restraints. The virus has Ca++ ions octahedrally coordinated by six aspartic acid residues on quasi threefold axes, which is completely different than for either CfMV or TNV. Amino terminal residues 1–53, 1–49 and 1-21 of the A, B and C subunits, respectively, and the four C-terminal residues (239-242) are not visible in electron density maps. The additional ordered residues of the C chain form a prominent “arm” that intertwines with symmetry equivalent “arms” at icosahedral threefold axes, as was seen in both CfMV and TNV. A 17 nucleotide hairpin segment of genomic RNA is icosahedrally ordered and bound at 60 equivalent sites at quasi twofold A–B subunit interfaces at the interior surface of the capsid. This segment of RNA may serve as a conformational switch for coat protein subunits, as has been proposed for similar RNA segments in other viruses. PMID:23123270

Analysis of the Junction of the East African Rift and the Cretaceous-Paleogene Rifts in Northern Kenya and Southern Ethiopia

NASA Astrophysics Data System (ADS)

Mariita, N. O.; Tadesse, K.; Keller, G. R.

2003-12-01

The East African rift (EAR) is a Tertiary-Miocene system that extends from the Middle East, through East Africa, to Mozambique in southern Africa. Much of the present information is from the Ethiopian and Kenyan parts of the rift. Several characteristics of the EAR such as rift-related volcanism, faulting and topographic relief being exposed make it attractive for studying continental rift processes. Structural complexities reflected in the geometries of grabens and half-grabens, the existence of transverse fault zones and accommodation zones, and the influence of pre-existing geologic structures have been documented. In particular, the EAR traverses the Anza graben and related structures near the Kenya/Ethiopian border. The Anza graben is one in a series of Cretaceous-Paleogene failed rifts that trend across Central Africa from Nigeria through Chad to Sudan and Kenya with an overall northwest-southeast trend. In spite of a number of recent studies, we do not understand the interaction of these two rift systems. In both Ethiopia and Kenya, the rift segments share some broad similarities in timing and are related in a geographic sense. For example, volcanism appears to have generally preceded or in some cases have been contemporaneous with major rift faulting. Although, these segments are distinct entities, each with its own tectonic and magmatic evolution, and they do connect in the region crossed by the Anza graben and related structures. In our present study, we are using a combination of recently collected seismic, gravity and remote sensing data to increase our understanding of these two segments of the EAR. We hope that by analysing the satellite data, the variety and differences in the volume of magmatic products extruded along in southern Ethiopia and northern Kenya will be identified. The geometry of structures (in particular, those causing the gravity axial high) will be modelled to study the impact of the older Anza graben structural trends with the younger EAR. For example there is significant crustal thinning in the Lake Turkana area of the northern Kenya segment of the EAR system. In regard to the recent EAGLE experiment in Ethiopia, we are ivestigating if the transition from relatively thick crust (~40 km) to thinned, rifted crust is as abrupt in Ethiopia as it is in Kenya.

Is the Central America forearc sliver part of the North America plate?

NASA Astrophysics Data System (ADS)

Guzman-Speziale, M.

2012-04-01

The Central America Forearc sliver is located between the Central America volcanic arc and the Middle America trench. Several authors have suggested that the forearc is being displaced to the northwest with respect to the Caribbean plate; they point to right-lateral, normal-faulting earthquakes along the Central America volcanic arc as prime evidence of this displacement. Apparently, the forearc continues to the northwest into southeastern Mexico, although this portion of the forearc is not being displaced. I present evidence that suggests that the forearc indeed continues into southeastern Mexico and that it belongs to the North America plate. Physiographically, there is a continuity of the forearc into the Coastal plains of southeastern (Chiapas) Mexico, across the Motagua and Polochic faults. Offshore, cross-sections of the Middle America trench are similar along the mexican (Chiapas) segment, and the Central American segment. Furthermore, at the northwestern end of the coastal plain there are no compressive structures, which suggests that the coastal plain is not being displaced to the northwest. As a matter of fact, fault-plane solutions for shallow earthquakes show extension rather than compression. Shallow, interplate earthquakes along the trench show similar parameters along both segments. P-axes and earthquake slip vectors have consistent azimuths, which relate better with Cocos-North America convergence than with Cocos-Caribbean. Azimuth of T-axes for normal-faulting earthquakes also agree well with Cocos-North America convergence. Similarity in several parameters is thus found across both segments, the Chiapas coastal plain and the Central America forearc sliver proper. This suggests that both segments are continuous and probably one and the same, and belonging to the North America plate. Perhaps more properly, the forearc sliver extends into southeastern Mexico and is part of the zone of deformation associated to the Cocos-North America-Caribbean plates triple junction. Right-lateral, strike-slip faulting along the volcanic arc, and GPS results for the forearc sliver indicate that the the forearc sliver is moving with respect to the Caribbean plate. In the model presented here, I propose that it is the Chortis block (the northwestern corner of the Caribbean plate) is the one moving with respect to the forearc. In fact, I have presented evidence elsewhere attesting to this.

An Automatic Method for Geometric Segmentation of Masonry Arch Bridges for Structural Engineering Purposes

NASA Astrophysics Data System (ADS)

Riveiro, B.; DeJong, M.; Conde, B.

2016-06-01

Despite the tremendous advantages of the laser scanning technology for the geometric characterization of built constructions, there are important limitations preventing more widespread implementation in the structural engineering domain. Even though the technology provides extensive and accurate information to perform structural assessment and health monitoring, many people are resistant to the technology due to the processing times involved. Thus, new methods that can automatically process LiDAR data and subsequently provide an automatic and organized interpretation are required. This paper presents a new method for fully automated point cloud segmentation of masonry arch bridges. The method efficiently creates segmented, spatially related and organized point clouds, which each contain the relevant geometric data for a particular component (pier, arch, spandrel wall, etc.) of the structure. The segmentation procedure comprises a heuristic approach for the separation of different vertical walls, and later image processing tools adapted to voxel structures allows the efficient segmentation of the main structural elements of the bridge. The proposed methodology provides the essential processed data required for structural assessment of masonry arch bridges based on geometric anomalies. The method is validated using a representative sample of masonry arch bridges in Spain.

Atlas-based segmentation in breast cancer radiotherapy: Evaluation of specific and generic-purpose atlases.

PubMed

Ciardo, Delia; Gerardi, Marianna Alessandra; Vigorito, Sabrina; Morra, Anna; Dell'acqua, Veronica; Diaz, Federico Javier; Cattani, Federica; Zaffino, Paolo; Ricotti, Rosalinda; Spadea, Maria Francesca; Riboldi, Marco; Orecchia, Roberto; Baroni, Guido; Leonardi, Maria Cristina; Jereczek-Fossa, Barbara Alicja

2017-04-01

Atlas-based automatic segmentation (ABAS) addresses the challenges of accuracy and reliability in manual segmentation. We aim to evaluate the contribution of specific-purpose in ABAS of breast cancer (BC) patients with respect to generic-purpose libraries. One generic-purpose and 9 specific-purpose libraries, stratified according to type of surgery and size of thorax circumference, were obtained from the computed tomography of 200 BC patients. Keywords about contralateral breast volume and presence of breast expander/prostheses were recorded. ABAS was validated on 47 independent patients, considering manual segmentation from scratch as reference. Five ABAS datasets were obtained, testing single-ABAS and multi-ABAS with simultaneous truth and performance level estimation (STAPLE). Center of mass distance (CMD), average Hausdorff distance (AHD) and Dice similarity coefficient (DSC) between corresponding ABAS and manual structures were evaluated and statistically significant differences between different surgeries, structures and ABAS strategies were investigated. Statistically significant differences between patients who underwent different surgery were found, with superior results for conservative-surgery group, and between different structures were observed: ABAS of heart, lungs, kidneys and liver was satisfactory (median values: CMD<2 mm, DSC≥0.80, AHD<1.5 mm), whereas chest wall, breast and spinal cord obtained moderate performance (median values: 2 mm ≤ CMD<5 mm, 0.60 ≤ DSC<0.80, 1.5 mm ≤ AHD<4 mm) and esophagus, stomach, brachial plexus and supraclavicular nodes obtained poor performance (median CMD≥5 mm, DSC<0.60, AHD≥4 mm). The application of STAPLE algorithm generally yields higher performance and the use of keywords improves results for breast ABAS. The homogeneity in the selection of atlases based on multiple anatomical and clinical features and the use of specific-purpose libraries can improve ABAS performance with respect to generic-purpose libraries. Copyright © 2016 Elsevier Ltd. All rights reserved.

High Tech High School Interns Develop a Mid-Ocean Ridge Database for Research and Education

NASA Astrophysics Data System (ADS)

Staudigel, D.; Delaney, R.; Staudigel, H.; Koppers, A. A.; Miller, S. P.

2004-12-01

Mid-ocean ridges (MOR) represent one of the most important geographical and geological features on planet Earth. MORs are the locations where plates spread apart, they are the locations of the majority of the Earths' volcanoes that harbor some of the most extreme life forms. These concepts attract much research, but mid-ocean ridges are still effectively underrepresented in the Earth science class rooms. As two High Tech High School students, we began an internship at Scripps to develop a database for mid-ocean ridges as a resource for science and education. This Ridge Catalog will be accessible via http://earthref.org/databases/RC/ and applies a similar structure, design and data archival principle as the Seamount Catalog under EarthRef.org. Major research goals of this project include the development of (1) an archival structure for multibeam and sidescan data, standard bathymetric maps (including ODP-DSDP drill site and dredge locations) or any other arbitrary digital objects relating to MORs, and (2) to compile a global data set for some of the most defining characteristics of every ridge segment including ridge segment length, depth and azimuth and half spreading rates. One of the challenges included the need of making MOR data useful to the scientist as well as the teacher in the class room. Since the basic structure follows the design of the Seamount Catalog closely, we could move our attention to the basic data population of the database. We have pulled together multibeam data for the MOR segments from various public archives (SIOExplorer, SIO-GDC, NGDC, Lamont), and pre-processed it for public use. In particular, we have created individual bathymetric maps for each ridge segment, while merging the multibeam data with global satellite bathymetry data from Smith & Sandwell (1997). The global scale of this database will give it the ability to be used for any number of applications, from cruise planning to data

Segmental duplications: evolution and impact among the current Lepidoptera genomes.

PubMed

Zhao, Qian; Ma, Dongna; Vasseur, Liette; You, Minsheng

2017-07-06

Structural variation among genomes is now viewed to be as important as single nucleoid polymorphisms in influencing the phenotype and evolution of a species. Segmental duplication (SD) is defined as segments of DNA with homologous sequence. Here, we performed a systematic analysis of segmental duplications (SDs) among five lepidopteran reference genomes (Plutella xylostella, Danaus plexippus, Bombyx mori, Manduca sexta and Heliconius melpomene) to understand their potential impact on the evolution of these species. We find that the SDs content differed substantially among species, ranging from 1.2% of the genome in B. mori to 15.2% in H. melpomene. Most SDs formed very high identity (similarity higher than 90%) blocks but had very few large blocks. Comparative analysis showed that most of the SDs arose after the divergence of each linage and we found that P. xylostella and H. melpomene showed more duplications than other species, suggesting they might be able to tolerate extensive levels of variation in their genomes. Conserved ancestral and species specific SD events were assessed, revealing multiple examples of the gain, loss or maintenance of SDs over time. SDs content analysis showed that most of the genes embedded in SDs regions belonged to species-specific SDs ("Unique" SDs). Functional analysis of these genes suggested their potential roles in the lineage-specific evolution. SDs and flanking regions often contained transposable elements (TEs) and this association suggested some involvement in SDs formation. Further studies on comparison of gene expression level between SDs and non-SDs showed that the expression level of genes embedded in SDs was significantly lower, suggesting that structure changes in the genomes are involved in gene expression differences in species. The results showed that most of the SDs were "unique SDs", which originated after species formation. Functional analysis suggested that SDs might play different roles in different species. Our results provide a valuable resource beyond the genetic mutation to explore the genome structure for future Lepidoptera research.

A functional Kv1.2-hERG chimaeric channel expressed in Pichia pastoris

PubMed Central

Dhillon, Mandeep S.; Cockcroft, Christopher J.; Munsey, Tim; Smith, Kathrine J.; Powell, Andrew J.; Carter, Paul; Wrighton, David C.; Rong, Hong-lin; Yusaf, Shahnaz P.; Sivaprasadarao, Asipu

2014-01-01

Members of the six-transmembrane segment family of ion channels share a common structural design. However, there are sequence differences between the members that confer distinct biophysical properties on individual channels. Currently, we do not have 3D structures for all members of the family to help explain the molecular basis for the differences in their biophysical properties and pharmacology. This is due to low-level expression of many members in native or heterologous systems. One exception is rat Kv1.2 which has been overexpressed in Pichia pastoris and crystallised. Here, we tested chimaeras of rat Kv1.2 with the hERG channel for function in Xenopus oocytes and for overexpression in Pichia. Chimaera containing the S1–S6 transmembrane region of HERG showed functional and pharmacological properties similar to hERG and could be overexpressed and purified from Pichia. Our results demonstrate that rat Kv1.2 could serve as a surrogate to express difficult-to-overexpress members of the six-transmembrane segment channel family. PMID:24569544

Sequence-independent construction of ordered combinatorial libraries with predefined crossover points.

PubMed

Jézéquel, Laetitia; Loeper, Jacqueline; Pompon, Denis

2008-11-01

Combinatorial libraries coding for mosaic enzymes with predefined crossover points constitute useful tools to address and model structure-function relationships and for functional optimization of enzymes based on multivariate statistics. The presented method, called sequence-independent generation of a chimera-ordered library (SIGNAL), allows easy shuffling of any predefined amino acid segment between two or more proteins. This method is particularly well adapted to the exchange of protein structural modules. The procedure could also be well suited to generate ordered combinatorial libraries independent of sequence similarities in a robotized manner. Sequence segments to be recombined are first extracted by PCR from a single-stranded template coding for an enzyme of interest using a biotin-avidin-based method. This technique allows the reduction of parental template contamination in the final library. Specific PCR primers allow amplification of two complementary mosaic DNA fragments, overlapping in the region to be exchanged. Fragments are finally reassembled using a fusion PCR. The process is illustrated via the construction of a set of mosaic CYP2B enzymes using this highly modular approach.

High-resolution, anthropomorphic, computational breast phantom: fusion of rule-based structures with patient-based anatomy

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Gong, Xiaolin; Graff, Christian G.; Santana, Maira; Sturgeon, Gregory M.; Sauer, Thomas J.; Zeng, Rongping; Glick, Stephen J.; Lo, Joseph Y.

2017-03-01

While patient-based breast phantoms are realistic, they are limited by low resolution due to the image acquisition and segmentation process. The purpose of this study is to restore the high frequency components for the patient-based phantoms by adding power law noise (PLN) and breast structures generated based on mathematical models. First, 3D radial symmetric PLN with β=3 was added at the boundary between adipose and glandular tissue to connect broken tissue and create a high frequency contour of the glandular tissue. Next, selected high-frequency features from the FDA rule-based computational phantom (Cooper's ligaments, ductal network, and blood vessels) were fused into the phantom. The effects of enhancement in this study were demonstrated by 2D mammography projections and digital breast tomosynthesis (DBT) reconstruction volumes. The addition of PLN and rule-based models leads to a continuous decrease in β. The new β is 2.76, which is similar to what typically found for reconstructed DBT volumes. The new combined breast phantoms retain the realism from segmentation and gain higher resolution after restoration.

Application of the 3D slicer chest imaging platform segmentation algorithm for large lung nodule delineation

PubMed Central

Parmar, Chintan; Blezek, Daniel; Estepar, Raul San Jose; Pieper, Steve; Kim, John; Aerts, Hugo J. W. L.

2017-01-01

Purpose Accurate segmentation of lung nodules is crucial in the development of imaging biomarkers for predicting malignancy of the nodules. Manual segmentation is time consuming and affected by inter-observer variability. We evaluated the robustness and accuracy of a publically available semiautomatic segmentation algorithm that is implemented in the 3D Slicer Chest Imaging Platform (CIP) and compared it with the performance of manual segmentation. Methods CT images of 354 manually segmented nodules were downloaded from the LIDC database. Four radiologists performed the manual segmentation and assessed various nodule characteristics. The semiautomatic CIP segmentation was initialized using the centroid of the manual segmentations, thereby generating four contours for each nodule. The robustness of both segmentation methods was assessed using the region of uncertainty (δ) and Dice similarity index (DSI). The robustness of the segmentation methods was compared using the Wilcoxon-signed rank test (pWilcoxon<0.05). The Dice similarity index (DSIAgree) between the manual and CIP segmentations was computed to estimate the accuracy of the semiautomatic contours. Results The median computational time of the CIP segmentation was 10 s. The median CIP and manually segmented volumes were 477 ml and 309 ml, respectively. CIP segmentations were significantly more robust than manual segmentations (median δCIP = 14ml, median dsiCIP = 99% vs. median δmanual = 222ml, median dsimanual = 82%) with pWilcoxon~10−16. The agreement between CIP and manual segmentations had a median DSIAgree of 60%. While 13% (47/354) of the nodules did not require any manual adjustment, minor to substantial manual adjustments were needed for 87% (305/354) of the nodules. CIP segmentations were observed to perform poorly (median DSIAgree≈50%) for non-/sub-solid nodules with subtle appearances and poorly defined boundaries. Conclusion Semi-automatic CIP segmentation can potentially reduce the physician workload for 13% of nodules owing to its computational efficiency and superior stability compared to manual segmentation. Although manual adjustment is needed for many cases, CIP segmentation provides a preliminary contour for physicians as a starting point. PMID:28594880

Volcanism on the fossil Galapagos Rise spreading centre, SE Pacific

NASA Astrophysics Data System (ADS)

Haase, K. M.; Stroncik, N. A.

2002-12-01

A part of the fossil spreading centre of the Galapagos Rise at 10° S, 95° W in the SE Pacific Ocean was mapped and sampled. This spreading centre was active for about 12 Ma and was abandoned about 6.5 Ma ago when the spreading rate of the East Pacific Rise (EPR) increased. The aim of this study is to understand the tectonic and petrological implications of the ridge jump for the spreading centre and to gain insights into the processes in its melting column. Bathymetric swath mapping of a part of the Galapagos Rise revealed an elongated structure with a NNE-SSW strike direction which is bounded by a large fracture zone in the north. The mapped area can be divided into three segments, each of about 50 km length. The northernmost segment consists of an ~4400 m deep rift which shows similarities to a slow-spreading centre, e.g. the Mid-Atlantic Ridge. The southern two segments are volcanic ridges with numerous volcanic flank cones which reach water depths up to 490 m. This volcanic ridge is interpreted as the continuation of the fossil spreading axis. While the northernmost segment is magmatically starved, the volcanic ridges of the southern two segments apparently formed after cessation of spreading. The rock samples from the rift flanks in the north are incompatible element-depleted (K/Ti 0.08-0.28) and plagioclase-phyric basalts resembling typical mid-ocean ridge basalts (MORB). In contrast, the lavas from the two volcanic ridge segments in the south are highly vesicular incompatible element-enriched alkali basalts with K/Ti of 0.65-1.4. The depleted rift basalts have Sr isotope ratios below 0.7027 while the alkali basalts from the ridge range between 0.7029 and 0.7031. The rift basalts have significantly lower sodium contents than the alkali basalts and thus the southern lavas are probably derived by smaller degrees of partial melting. The relatively low Si contents of the alkali basalts also indicates formation deeper in the melting column than the northern MORB-like samples. The mantle source of the alkali basalts is similar to the enriched source of off-axis seamounts along the EPR. Our preliminary data suggest that the northernmost segment formed by tectonic processes during a final slow-spreading phase of the Galapagos Rise while the southern two segments erupted alkaline lavas probably after spreading stopped.

Scale-space for empty catheter segmentation in PCI fluoroscopic images.

PubMed

Bacchuwar, Ketan; Cousty, Jean; Vaillant, Régis; Najman, Laurent

2017-07-01

In this article, we present a method for empty guiding catheter segmentation in fluoroscopic X-ray images. The guiding catheter, being a commonly visible landmark, its segmentation is an important and a difficult brick for Percutaneous Coronary Intervention (PCI) procedure modeling. In number of clinical situations, the catheter is empty and appears as a low contrasted structure with two parallel and partially disconnected edges. To segment it, we work on the level-set scale-space of image, the min tree, to extract curve blobs. We then propose a novel structural scale-space, a hierarchy built on these curve blobs. The deep connected component, i.e. the cluster of curve blobs on this hierarchy, that maximizes the likelihood to be an empty catheter is retained as final segmentation. We evaluate the performance of the algorithm on a database of 1250 fluoroscopic images from 6 patients. As a result, we obtain very good qualitative and quantitative segmentation performance, with mean precision and recall of 80.48 and 63.04% respectively. We develop a novel structural scale-space to segment a structured object, the empty catheter, in challenging situations where the information content is very sparse in the images. Fully-automatic empty catheter segmentation in X-ray fluoroscopic images is an important and preliminary step in PCI procedure modeling, as it aids in tagging the arrival and removal location of other interventional tools.

Glioblastoma Segmentation: Comparison of Three Different Software Packages.

PubMed

Fyllingen, Even Hovig; Stensjøen, Anne Line; Berntsen, Erik Magnus; Solheim, Ole; Reinertsen, Ingerid

2016-01-01

To facilitate a more widespread use of volumetric tumor segmentation in clinical studies, there is an urgent need for reliable, user-friendly segmentation software. The aim of this study was therefore to compare three different software packages for semi-automatic brain tumor segmentation of glioblastoma; namely BrainVoyagerTM QX, ITK-Snap and 3D Slicer, and to make data available for future reference. Pre-operative, contrast enhanced T1-weighted 1.5 or 3 Tesla Magnetic Resonance Imaging (MRI) scans were obtained in 20 consecutive patients who underwent surgery for glioblastoma. MRI scans were segmented twice in each software package by two investigators. Intra-rater, inter-rater and between-software agreement was compared by using differences of means with 95% limits of agreement (LoA), Dice's similarity coefficients (DSC) and Hausdorff distance (HD). Time expenditure of segmentations was measured using a stopwatch. Eighteen tumors were included in the analyses. Inter-rater agreement was highest for BrainVoyager with difference of means of 0.19 mL and 95% LoA from -2.42 mL to 2.81 mL. Between-software agreement and 95% LoA were very similar for the different software packages. Intra-rater, inter-rater and between-software DSC were ≥ 0.93 in all analyses. Time expenditure was approximately 41 min per segmentation in BrainVoyager, and 18 min per segmentation in both 3D Slicer and ITK-Snap. Our main findings were that there is a high agreement within and between the software packages in terms of small intra-rater, inter-rater and between-software differences of means and high Dice's similarity coefficients. Time expenditure was highest for BrainVoyager, but all software packages were relatively time-consuming, which may limit usability in an everyday clinical setting.

Simulation of nutrient and sediment concentrations and loads in the Delaware inland bays watershed: Extension of the hydrologic and water-quality model to ungaged segments

USGS Publications Warehouse

Gutierrez-Magness, Angelica L.

2006-01-01

Rapid population increases, agriculture, and industrial practices have been identified as important sources of excessive nutrients and sediments in the Delaware Inland Bays watershed. The amount and effect of excessive nutrients and sediments in the Inland Bays watershed have been well documented by the Delaware Geological Survey, the Delaware Department of Natural Resources and Environmental Control, the U.S. Environmental Protection Agency's National Estuary Program, the Delaware Center for Inland Bays, the University of Delaware, and other agencies. This documentation and data previously were used to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed to simulate nutrients and sediment concentrations and loads, and to calibrate the model by comparing concentrations and streamflow data at six stations in the watershed over a limited period of time (October 1998 through April 2000). Although the model predictions of nutrient and sediment concentrations for the calibrated segments were fairly accurate, the predictions for the 28 ungaged segments located near tidal areas, where stream data were not available, were above the range of values measured in the area. The cooperative study established in 2000 by the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was extended to evaluate the model predictions in ungaged segments and to ensure that the model, developed as a planning and management tool, could accurately predict nutrient and sediment concentrations within the measured range of values in the area. The evaluation of the predictions was limited to the period of calibration (1999) of the 2003 model. To develop estimates on ungaged watersheds, parameter values from calibrated segments are transferred to the ungaged segments; however, accurate predictions are unlikely where parameter transference is subject to error. The unexpected nutrient and sediment concentrations simulated with the 2003 model were likely the result of inappropriate criteria for the transference of parameter values. From a model-simulation perspective, it is a common practice to transfer parameter values based on the similarity of soils or the similarity of land-use proportions between segments. For the Inland Bays model, the similarity of soils between segments was used as the basis to transfer parameter values. An alternative approach, which is documented in this report, is based on the similarity of the spatial distribution of the land use between segments and the similarity of land-use proportions, as these can be important factors for the transference of parameter values in lumped models. Previous work determined that the difference in the variation of runoff due to various spatial distributions of land use within a watershed can cause substantialloss of accuracy in the model predictions. The incorporation of the spatial distribution of land use to transfer parameter values from calibrated to uncalibrated segments provided more consistent and rational predictions of flow, especially during the summer, and consequently, predictions of lower nutrient concentrations during the same period. For the segments where the similarity of spatial distribution of land use was not clearly established with a calibrated segment, the similarity of the location of the most impervious areas was also used as a criterion for the transference of parameter values. The model predictions from the 28 ungaged segments were verified through comparison with measured in-stream concentrations from local and nearby streams provided by the Delaware Department of Natural Resources and Environmental Control. Model results indicated that the predicted edge-of-stream total suspended solids loads in the Inland Bays watershed were low in comparison to loads reported for the Eastern Shore of Maryland from the Chesapeake Bay watershed model. The flatness of the ter

Advances in Geophysical Methods at Parkfield, California

NASA Astrophysics Data System (ADS)

Bennington, Ninfa

The Parkfield segment of the San Andreas fault (SAF) is one of the most highly monitored fault sites in the world. I carry out two studies, taking advantage of the dense set of geophysical observations obtained for this segment of the fault. In the first study, I use geodetic data to had a model of coseismic slip for the 2004 Parkfield earthquake with the constraint that the edges of coseismic slip patches preferentially align with aftershocks. Application of the aftershock distribution constraint on coseismic slip yields a model that agrees in location and amplitude with features observed in previous geodetic studies and the majority of strong motion studies. The curvature-constrained solution shows slip primarily between aftershock "streaks" with the continuation of moderate levels of slip towards the 2004 Parkfield earthquake hypocenter. The observed continuation of coseismic slip towards the hypocenter is in good agreement with strong motion studies but is not observed in the majority of published geodetic slip models, which I attribute to resolution limitations. In the second study, I develop tomoDDMT, a joint inversion code that simultaneously inverts for resistivity and seismic velocity models under the cross- gradient constraint. This constraint uses a weighted penalty function to encourage areas where the two models are changing to be structurally similar. I present jointly inverted models of P-wave velocity (Vp) and resistivity for a cross-section centered on the San Andreas Fault Observatory at Depth (SAFOD). The joint inversion scheme achieves structurally similar Vp and resistivity images that adequately fit the seismic and MT data without forcing model similarity where none exists. Using tomoDDMT, I obtain models or resistivity and Vp that yield increased insight into the geologic structure at Parkfield. I address key issues including: the location of the Franciscan formation at depth, the spatial extent of the Upper Great Valley sequence, the validity of the eastern wall as a fluid pathway, the distribution of the eastern conductor, and the distribution of the Salinian block at depth.

Automatic liver segmentation on Computed Tomography using random walkers for treatment planning

PubMed Central

Moghbel, Mehrdad; Mashohor, Syamsiah; Mahmud, Rozi; Saripan, M. Iqbal Bin

2016-01-01

Segmentation of the liver from Computed Tomography (CT) volumes plays an important role during the choice of treatment strategies for liver diseases. Despite lots of attention, liver segmentation remains a challenging task due to the lack of visible edges on most boundaries of the liver coupled with high variability of both intensity patterns and anatomical appearances with all these difficulties becoming more prominent in pathological livers. To achieve a more accurate segmentation, a random walker based framework is proposed that can segment contrast-enhanced livers CT images with great accuracy and speed. Based on the location of the right lung lobe, the liver dome is automatically detected thus eliminating the need for manual initialization. The computational requirements are further minimized utilizing rib-caged area segmentation, the liver is then extracted by utilizing random walker method. The proposed method was able to achieve one of the highest accuracies reported in the literature against a mixed healthy and pathological liver dataset compared to other segmentation methods with an overlap error of 4.47 % and dice similarity coefficient of 0.94 while it showed exceptional accuracy on segmenting the pathological livers with an overlap error of 5.95 % and dice similarity coefficient of 0.91. PMID:28096782

Semiautomatic tumor segmentation with multimodal images in a conditional random field framework.

PubMed

Hu, Yu-Chi; Grossberg, Michael; Mageras, Gikas

2016-04-01

Volumetric medical images of a single subject can be acquired using different imaging modalities, such as computed tomography, magnetic resonance imaging (MRI), and positron emission tomography. In this work, we present a semiautomatic segmentation algorithm that can leverage the synergies between different image modalities while integrating interactive human guidance. The algorithm provides a statistical segmentation framework partly automating the segmentation task while still maintaining critical human oversight. The statistical models presented are trained interactively using simple brush strokes to indicate tumor and nontumor tissues and using intermediate results within a patient's image study. To accomplish the segmentation, we construct the energy function in the conditional random field (CRF) framework. For each slice, the energy function is set using the estimated probabilities from both user brush stroke data and prior approved segmented slices within a patient study. The progressive segmentation is obtained using a graph-cut-based minimization. Although no similar semiautomated algorithm is currently available, we evaluated our method with an MRI data set from Medical Image Computing and Computer Assisted Intervention Society multimodal brain segmentation challenge (BRATS 2012 and 2013) against a similar fully automatic method based on CRF and a semiautomatic method based on grow-cut, and our method shows superior performance.

Imaging hydrothermal roots along the Endeavour segment of the Juan de Fuca ridge using elastic full waveform inversion.

NASA Astrophysics Data System (ADS)

Arnulf, A. F.; Harding, A. J.; Kent, G. M.

2016-12-01

The Endeavour segment is a 90 km-long, medium-spreading-rate, oceanic spreading center located on the northern Juan de Fuca ridge (JDFR). The central part of this segment forms a 25-km-long volcanic high that hosts five of the most hydrothermally active vent fields on the MOR system, namely (from north to south): Sasquatch, Salty Dawg, High Rise, Main Endeavour and Mothra. Mass, heat and chemical fluxes associated to vigorous hydrothermal venting are large, however the geometry of the fluid circulation system through the oceanic crust remains almost completely undefined. To produce high-resolution velocity/reflectivity structures along the axis of the Endeavour segment, here, we combined a synthetic ocean bottom experiment (SOBE), 2-D traveltime tomography, 2D elastic full waveform and reverse time migration (RTM). We present velocity and reflectivity sections along Endeavour segment at unprecedented spatial resolutions. We clearly image a set of independent, geometrically complex, elongated low-velocity regions linking the top of the magma chamber at depth to the hydrothermal vent fields on the seafloor. We interpret these narrow pipe-like units as focused regions of hydrothermal fluid up-flow, where acidic and corrosive fluids form pipe-like alteration zones as previously observed in Cyprus ophiolites. Furthermore, the amplitude of these low-velocity channels is shown to be highly variable, with the strongest velocity drops observed at Main Endeavour, Mothra and Salty Dawg hydrothermal vent fields, possibly suggesting more mature hydrothermal cells. Interestingly, the near-seafloor structure beneath those three sites is very similar and highlights a sharp lateral transition in velocity (north to south). On the other hand, the High-Rise hydrothermal vent field is characterized by several lower amplitudes up-flow zones and relatively slow near-surface velocities. Last, Sasquatch vent field is located in an area of high near-surface velocities and is not characterized by an obvious low-velocity up-flow region, in good agreement with an extinct vent field.

Correcting for the effects of pupil discontinuities with the ACAD method

NASA Astrophysics Data System (ADS)

Mazoyer, Johan; Pueyo, Laurent; N'Diaye, Mamadou; Mawet, Dimitri; Soummer, Rémi; Norman, Colin

2016-07-01

The current generation of ground-based coronagraphic instruments uses deformable mirrors to correct for phase errors and to improve contrast levels at small angular separations. Improving these techniques, several space and ground based instruments are currently developed using two deformable mirrors to correct for both phase and amplitude errors. However, as wavefront control techniques improve, more complex telescope pupil geometries (support structures, segmentation) will soon be a limiting factor for these next generation coronagraphic instruments. The technique presented in this proceeding, the Active Correction of Aperture Discontinuities method, is taking advantage of the fact that most future coronagraphic instruments will include two deformable mirrors, and is proposing to find the shapes and actuator movements to correct for the effect introduced by these complex pupil geometries. For any coronagraph previously designed for continuous apertures, this technique allow to obtain similar performance in contrast with a complex aperture (with segmented and secondary mirror support structures), with high throughput and flexibility to adapt to changing pupil geometry (e.g. in case of segment failure or maintenance of the segments). We here present the results of the parametric analysis realized on the WFIRST pupil for which we obtained high contrast levels with several deformable mirror setups (size, separation between them), coronagraphs (Vortex charge 2, vortex charge 4, APLC) and spectral bandwidths. However, because contrast levels and separation are not the only metrics to maximize the scientific return of an instrument, we also included in this study the influence of these deformable mirror shapes on the throughput of the instrument and sensitivity to pointing jitters. Finally, we present results obtained on another potential space based telescope segmented aperture. The main result of this proceeding is that we now obtain comparable performance than the coronagraphs previously designed for WFIRST. First result from the parametric analysis strongly suggest that the 2 deformable mirror set up (size and distance between them) have a important impact on the performance in contrast and throughput of the final instrument.

Segmentation of High Angular Resolution Diffusion MRI using Sparse Riemannian Manifold Clustering

PubMed Central

Wright, Margaret J.; Thompson, Paul M.; Vidal, René

2015-01-01

We address the problem of segmenting high angular resolution diffusion imaging (HARDI) data into multiple regions (or fiber tracts) with distinct diffusion properties. We use the orientation distribution function (ODF) to represent HARDI data and cast the problem as a clustering problem in the space of ODFs. Our approach integrates tools from sparse representation theory and Riemannian geometry into a graph theoretic segmentation framework. By exploiting the Riemannian properties of the space of ODFs, we learn a sparse representation for each ODF and infer the segmentation by applying spectral clustering to a similarity matrix built from these representations. In cases where regions with similar (resp. distinct) diffusion properties belong to different (resp. same) fiber tracts, we obtain the segmentation by incorporating spatial and user-specified pairwise relationships into the formulation. Experiments on synthetic data evaluate the sensitivity of our method to image noise and the presence of complex fiber configurations, and show its superior performance compared to alternative segmentation methods. Experiments on phantom and real data demonstrate the accuracy of the proposed method in segmenting simulated fibers, as well as white matter fiber tracts of clinical importance in the human brain. PMID:24108748

Evolutionarily conserved TCR binding sites, identification of T cells in primary lymphoid tissues, and surprising trans-rearrangements in nurse shark.

PubMed

Criscitiello, Michael F; Ohta, Yuko; Saltis, Mark; McKinney, E Churchill; Flajnik, Martin F

2010-06-15

Cartilaginous fish are the oldest animals that generate RAG-based Ag receptor diversity. We have analyzed the genes and expressed transcripts of the four TCR chains for the first time in a cartilaginous fish, the nurse shark (Ginglymostoma cirratum). Northern blotting found TCR mRNA expression predominantly in lymphoid and mucosal tissues. Southern blotting suggested translocon-type loci encoding all four chains. Based on diversity of V and J segments, the expressed combinatorial diversity for gamma is similar to that of human, alpha and beta may be slightly lower, and delta diversity is the highest of any organism studied to date. Nurse shark TCRdelta have long CDR3 loops compared with the other three chains, creating binding site topologies comparable to those of mammalian TCR in basic paratope structure; additionally, nurse shark TCRdelta CDR3 are more similar to IgH CDR3 in length and heterogeneity than to other TCR chains. Most interestingly, several cDNAs were isolated that contained IgM or IgW V segments rearranged to other gene segments of TCRdelta and alpha. Finally, in situ hybridization experiments demonstrate a conservation of both alpha/beta and gamma/delta T cell localization in the thymus across 450 million years of vertebrate evolution, with gamma/delta TCR expression especially high in the subcapsular region. Collectively, these data make the first cellular identification of TCR-expressing lymphocytes in a cartilaginous fish.

Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification.

PubMed

Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V; Robles, Montserrat; Aparici, F; Martí-Bonmatí, L; García-Gómez, Juan M

2015-01-01

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation.

[The accuracy of rapid equilibrium assumption in steady-state enzyme kinetics is the function of equilibrium segment structure and properties].

PubMed

Vrzheshch, P V

2015-01-01

Quantitative evaluation of the accuracy of the rapid equilibrium assumption in the steady-state enzyme kinetics was obtained for an arbitrary mechanism of an enzyme-catalyzed reaction. This evaluation depends only on the structure and properties of the equilibrium segment, but doesn't depend on the structure and properties of the rest (stationary part) of the kinetic scheme. The smaller the values of the edges leaving equilibrium segment in relation to values of the edges within the equilibrium segment, the higher the accuracy of determination of intermediate concentrations and reaction velocity in a case of the rapid equilibrium assumption.

Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters.

PubMed

Schneider, Matthias; Hirsch, Sven; Weber, Bruno; Székely, Gábor; Menze, Bjoern H

2015-01-01

We propose a novel framework for joint 3-D vessel segmentation and centerline extraction. The approach is based on multivariate Hough voting and oblique random forests (RFs) that we learn from noisy annotations. It relies on steerable filters for the efficient computation of local image features at different scales and orientations. We validate both the segmentation performance and the centerline accuracy of our approach both on synthetic vascular data and four 3-D imaging datasets of the rat visual cortex at 700 nm resolution. First, we evaluate the most important structural components of our approach: (1) Orthogonal subspace filtering in comparison to steerable filters that show, qualitatively, similarities to the eigenspace filters learned from local image patches. (2) Standard RF against oblique RF. Second, we compare the overall approach to different state-of-the-art methods for (1) vessel segmentation based on optimally oriented flux (OOF) and the eigenstructure of the Hessian, and (2) centerline extraction based on homotopic skeletonization and geodesic path tracing. Our experiments reveal the benefit of steerable over eigenspace filters as well as the advantage of oblique split directions over univariate orthogonal splits. We further show that the learning-based approach outperforms different state-of-the-art methods and proves highly accurate and robust with regard to both vessel segmentation and centerline extraction in spite of the high level of label noise in the training data. Copyright © 2014 Elsevier B.V. All rights reserved.

MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection

PubMed Central

Ou, Yangming; Resnick, Susan M.; Gur, Ruben C.; Gur, Raquel E.; Satterthwaite, Theodore D.; Furth, Susan; Davatzikos, Christos

2016-01-01

Atlas-based automated anatomical labeling is a fundamental tool in medical image segmentation, as it defines regions of interest for subsequent analysis of structural and functional image data. The extensive investigation of multi-atlas warping and fusion techniques over the past 5 or more years has clearly demonstrated the advantages of consensus-based segmentation. However, the common approach is to use multiple atlases with a single registration method and parameter set, which is not necessarily optimal for every individual scan, anatomical region, and problem/data-type. Different registration criteria and parameter sets yield different solutions, each providing complementary information. Herein, we present a consensus labeling framework that generates a broad ensemble of labeled atlases in target image space via the use of several warping algorithms, regularization parameters, and atlases. The label fusion integrates two complementary sources of information: a local similarity ranking to select locally optimal atlases and a boundary modulation term to refine the segmentation consistently with the target image's intensity profile. The ensemble approach consistently outperforms segmentations using individual warping methods alone, achieving high accuracy on several benchmark datasets. The MUSE methodology has been used for processing thousands of scans from various datasets, producing robust and consistent results. MUSE is publicly available both as a downloadable software package, and as an application that can be run on the CBICA Image Processing Portal (https://ipp.cbica.upenn.edu), a web based platform for remote processing of medical images. PMID:26679328

Unsupervised segmentation of MRI knees using image partition forests

NASA Astrophysics Data System (ADS)

Marčan, Marija; Voiculescu, Irina

2016-03-01

Nowadays many people are affected by arthritis, a condition of the joints with limited prevention measures, but with various options of treatment the most radical of which is surgical. In order for surgery to be successful, it can make use of careful analysis of patient-based models generated from medical images, usually by manual segmentation. In this work we show how to automate the segmentation of a crucial and complex joint -- the knee. To achieve this goal we rely on our novel way of representing a 3D voxel volume as a hierarchical structure of partitions which we have named Image Partition Forest (IPF). The IPF contains several partition layers of increasing coarseness, with partitions nested across layers in the form of adjacency graphs. On the basis of a set of properties (size, mean intensity, coordinates) of each node in the IPF we classify nodes into different features. Values indicating whether or not any particular node belongs to the femur or tibia are assigned through node filtering and node-based region growing. So far we have evaluated our method on 15 MRI knee images. Our unsupervised segmentation compared against a hand-segmented gold standard has achieved an average Dice similarity coefficient of 0.95 for femur and 0.93 for tibia, and an average symmetric surface distance of 0.98 mm for femur and 0.73 mm for tibia. The paper also discusses ways to introduce stricter morphological and spatial conditioning in the bone labelling process.

Re-entry vehicle shape for enhanced performance

NASA Technical Reports Server (NTRS)

Brown, James L. (Inventor); Garcia, Joseph A. (Inventor); Prabhu, Dinesh K. (Inventor)

2008-01-01

A convex shell structure for enhanced aerodynamic performance and/or reduced heat transfer requirements for a space vehicle that re-enters an atmosphere. The structure has a fore-body, an aft-body, a longitudinal axis and a transverse cross sectional shape, projected on a plane containing the longitudinal axis, that includes: first and second linear segments, smoothly joined at a first end of each the first and second linear segments to an end of a third linear segment by respective first and second curvilinear segments; and a fourth linear segment, joined to a second end of each of the first and second segments by curvilinear segments, including first and second ellipses having unequal ellipse parameters. The cross sectional shape is non-symmetric about the longitudinal axis. The fourth linear segment can be replaced by a sum of one or more polynomials, trigonometric functions or other functions satisfying certain constraints.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

PubMed Central

Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai

2015-01-01

The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120

A Longitudinal Study of the Six Degrees of Freedom Cervical Spine Range of Motion During Dynamic Flexion/Extension and Rotation After Single-Level Anterior Arthrodesis

PubMed Central

Anderst, William J.; West, Tyler; Donaldson, William F; Lee, Joon Y.; Kang, James D.

2016-01-01

Study Design A longitudinal study using biplane radiography to measure in vivo intervertebral range of motion (ROM) during dynamic flexion/extension and rotation. Objective To longitudinally compare intervertebral maximal ROM and midrange motion in asymptomatic control subjects and single-level arthrodesis patients. Summary of Background Data In vitro studies consistently report that adjacent segment maximal ROM increases superior and inferior to cervical arthrodesis. Previous in vivo results have been conflicting, indicating that maximal ROM may or may not increase superior and/or inferior to the arthrodesis. There are no previous reports of midrange motion in arthrodesis patients and similar-aged controls. Methods Eight single-level (C5/C6) anterior arthrodesis patients (tested 7±1 months and 28±6 months post-surgery) and six asymptomatic control subjects (tested twice, 58±6 months apart) performed dynamic full ROM flexion/extension and axial rotation while biplane radiographs were collected at 30 images/s. A previously validated tracking process determined three-dimensional vertebral position from each pair of radiographs with sub-millimeter accuracy. The intervertebral maximal ROM and midrange motion in flexion/extension, rotation, lateral bending, and anterior-posterior translation were compared between test dates and between groups. Results Adjacent segment maximal ROM did not increase over time during flexion/extension or rotation movements. Adjacent segment maximal rotational ROM was not significantly greater in arthrodesis patients than in corresponding motion segments of similar-aged controls. C4/C5 adjacent segment rotation during the midrange of head motion and maximal anterior-posterior translation were significantly greater in arthrodesis patients than in the corresponding motion segment in controls on the second test date. Conclusions C5/C6 arthrodesis appears to significantly affect midrange, but not end-range, adjacent segment motions. The effects of arthrodesis on adjacent segment motion may be best evaluated by longitudinal studies that compare maximal and midrange adjacent segment motion to corresponding motion segments of similar-aged controls to determine if the adjacent segment motion is truly excessive. PMID:27831986

Longitudinal Study of the Six Degrees of Freedom Cervical Spine Range of Motion During Dynamic Flexion, Extension, and Rotation After Single-level Anterior Arthrodesis.

PubMed

Anderst, William J; West, Tyler; Donaldson, William F; Lee, Joon Y; Kang, James D

2016-11-15

A longitudinal study using biplane radiography to measure in vivo intervertebral range of motion (ROM) during dynamic flexion/extension, and rotation. To longitudinally compare intervertebral maximal ROM and midrange motion in asymptomatic control subjects and single-level arthrodesis patients. In vitro studies consistently report that adjacent segment maximal ROM increases superior and inferior to cervical arthrodesis. Previous in vivo results have been conflicting, indicating that maximal ROM may or may not increase superior and/or inferior to the arthrodesis. There are no previous reports of midrange motion in arthrodesis patients and similar-aged controls. Eight single-level (C5/C6) anterior arthrodesis patients (tested 7 ± 1 months and 28 ± 6 months postsurgery) and six asymptomatic control subjects (tested twice, 58 ± 6 months apart) performed dynamic full ROM flexion/extension and axial rotation whereas biplane radiographs were collected at 30 images per second. A previously validated tracking process determined three-dimensional vertebral position from each pair of radiographs with submillimeter accuracy. The intervertebral maximal ROM and midrange motion in flexion/extension, rotation, lateral bending, and anterior-posterior translation were compared between test dates and between groups. Adjacent segment maximal ROM did not increase over time during flexion/extension, or rotation movements. Adjacent segment maximal rotational ROM was not significantly greater in arthrodesis patients than in corresponding motion segments of similar-aged controls. C4/C5 adjacent segment rotation during the midrange of head motion and maximal anterior-posterior translation were significantly greater in arthrodesis patients than in the corresponding motion segment in controls on the second test date. C5/C6 arthrodesis appears to significantly affect midrange, but not end-range, adjacent segment motions. The effects of arthrodesis on adjacent segment motion may be best evaluated by longitudinal studies that compare maximal and midrange adjacent segment motion to corresponding motion segments of similar-aged controls to determine if the adjacent segment motion is truly excessive. 3.

Unsupervised motion-based object segmentation refined by color

NASA Astrophysics Data System (ADS)

Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

2003-06-01

For various applications, such as data compression, structure from motion, medical imaging and video enhancement, there is a need for an algorithm that divides video sequences into independently moving objects. Because our focus is on video enhancement and structure from motion for consumer electronics, we strive for a low complexity solution. For still images, several approaches exist based on colour, but these lack in both speed and segmentation quality. For instance, colour-based watershed algorithms produce a so-called oversegmentation with many segments covering each single physical object. Other colour segmentation approaches exist which somehow limit the number of segments to reduce this oversegmentation problem. However, this often results in inaccurate edges or even missed objects. Most likely, colour is an inherently insufficient cue for real world object segmentation, because real world objects can display complex combinations of colours. For video sequences, however, an additional cue is available, namely the motion of objects. When different objects in a scene have different motion, the motion cue alone is often enough to reliably distinguish objects from one another and the background. However, because of the lack of sufficient resolution of efficient motion estimators, like the 3DRS block matcher, the resulting segmentation is not at pixel resolution, but at block resolution. Existing pixel resolution motion estimators are more sensitive to noise, suffer more from aperture problems or have less correspondence to the true motion of objects when compared to block-based approaches or are too computationally expensive. From its tendency to oversegmentation it is apparent that colour segmentation is particularly effective near edges of homogeneously coloured areas. On the other hand, block-based true motion estimation is particularly effective in heterogeneous areas, because heterogeneous areas improve the chance a block is unique and thus decrease the chance of the wrong position producing a good match. Consequently, a number of methods exist which combine motion and colour segmentation. These methods use colour segmentation as a base for the motion segmentation and estimation or perform an independent colour segmentation in parallel which is in some way combined with the motion segmentation. The presented method uses both techniques to complement each other by first segmenting on motion cues and then refining the segmentation with colour. To our knowledge few methods exist which adopt this approach. One example is te{meshrefine}. This method uses an irregular mesh, which hinders its efficient implementation in consumer electronics devices. Furthermore, the method produces a foreground/background segmentation, while our applications call for the segmentation of multiple objects. NEW METHOD As mentioned above we start with motion segmentation and refine the edges of this segmentation with a pixel resolution colour segmentation method afterwards. There are several reasons for this approach: + Motion segmentation does not produce the oversegmentation which colour segmentation methods normally produce, because objects are more likely to have colour discontinuities than motion discontinuities. In this way, the colour segmentation only has to be done at the edges of segments, confining the colour segmentation to a smaller part of the image. In such a part, it is more likely that the colour of an object is homogeneous. + This approach restricts the computationally expensive pixel resolution colour segmentation to a subset of the image. Together with the very efficient 3DRS motion estimation algorithm, this helps to reduce the computational complexity. + The motion cue alone is often enough to reliably distinguish objects from one another and the background. To obtain the motion vector fields, a variant of the 3DRS block-based motion estimator which analyses three frames of input was used. The 3DRS motion estimator is known for its ability to estimate motion vectors which closely resemble the true motion. BLOCK-BASED MOTION SEGMENTATION As mentioned above we start with a block-resolution segmentation based on motion vectors. The presented method is inspired by the well-known K-means segmentation method te{K-means}. Several other methods (e.g. te{kmeansc}) adapt K-means for connectedness by adding a weighted shape-error. This adds the additional difficulty of finding the correct weights for the shape-parameters. Also, these methods often bias one particular pre-defined shape. The presented method, which we call K-regions, encourages connectedness because only blocks at the edges of segments may be assigned to another segment. This constrains the segmentation method to such a degree that it allows the method to use least squares for the robust fitting of affine motion models for each segment. Contrary to te{parmkm}, the segmentation step still operates on vectors instead of model parameters. To make sure the segmentation is temporally consistent, the segmentation of the previous frame will be used as initialisation for every new frame. We also present a scheme which makes the algorithm independent of the initially chosen amount of segments. COLOUR-BASED INTRA-BLOCK SEGMENTATION The block resolution motion-based segmentation forms the starting point for the pixel resolution segmentation. The pixel resolution segmentation is obtained from the block resolution segmentation by reclassifying pixels only at the edges of clusters. We assume that an edge between two objects can be found in either one of two neighbouring blocks that belong to different clusters. This assumption allows us to do the pixel resolution segmentation on each pair of such neighbouring blocks separately. Because of the local nature of the segmentation, it largely avoids problems with heterogeneously coloured areas. Because no new segments are introduced in this step, it also does not suffer from oversegmentation problems. The presented method has no problems with bifurcations. For the pixel resolution segmentation itself we reclassify pixels such that we optimize an error norm which favour similarly coloured regions and straight edges. SEGMENTATION MEASURE To assist in the evaluation of the proposed algorithm we developed a quality metric. Because the problem does not have an exact specification, we decided to define a ground truth output which we find desirable for a given input. We define the measure for the segmentation quality as being how different the segmentation is from the ground truth. Our measure enables us to evaluate oversegmentation and undersegmentation seperately. Also, it allows us to evaluate which parts of a frame suffer from oversegmentation or undersegmentation. The proposed algorithm has been tested on several typical sequences. CONCLUSIONS In this abstract we presented a new video segmentation method which performs well in the segmentation of multiple independently moving foreground objects from each other and the background. It combines the strong points of both colour and motion segmentation in the way we expected. One of the weak points is that the segmentation method suffers from undersegmentation when adjacent objects display similar motion. In sequences with detailed backgrounds the segmentation will sometimes display noisy edges. Apart from these results, we think that some of the techniques, and in particular the K-regions technique, may be useful for other two-dimensional data segmentation problems.

Semi-automated stand delineation in Mediterranean Pinus sylvestris plantations through segmentation of LiDAR data: The influence of pulse density

NASA Astrophysics Data System (ADS)

Varo-Martínez, Mª Ángeles; Navarro-Cerrillo, Rafael M.; Hernández-Clemente, Rocío; Duque-Lazo, Joaquín

2017-04-01

Traditionally, forest-stand delineation has been assessed based on orthophotography. The application of LiDAR has improved forest management by providing high-spatial-resolution data on the vertical structure of the forest. The aim of this study was to develop and test a semi-automated algorithm for stands delineation in a plantation of Pinus sylvestris L. using LiDAR data. Three specific objectives were evaluated, i) to assess two complementary LiDAR metrics, Assmann dominant height and basal area, for the characterization of the structure of P. sylvestris Mediterranean forests based on object-oriented segmentation, ii) to evaluate the influence of the LiDAR pulse density on forest-stand delineation accuracy, and iii) to investigate the algorithmś effectiveness in the delineation of P. sylvestris stands for map prediction of Assmann dominant height and basal area. Our results show that it is possible to generate accurate P. sylvestris forest-stand segmentations using multiresolution or mean shift segmentation methods, even with low-pulse-density LiDAR - which is an important economic advantage for forest management. However, eCognition multiresolution methods provided better results than the OTB (Orfeo Tool Box) for stand delineation based on dominant height and basal area estimations. Furthermore, the influence of pulse density on the results was not statistically significant in the basal area calculations. However, there was a significant effect of pulse density on Assmann dominant height [F2,9595 = 5.69, p = 0.003].for low pulse density. We propose that the approach shown here should be considered for stand delineation in other large Pinus plantations in Mediterranean regions with similar characteristics.

Proline residues in transmembrane segment IV are critical for activity, expression and targeting of the Na+/H+ exchanger isoform 1.

PubMed Central

Slepkov, Emily R; Chow, Signy; Lemieux, M Joanne; Fliegel, Larry

2004-01-01

NHE1 (Na+/H+ exchanger isoform 1) is a ubiquitously expressed integral membrane protein that regulates intracellular pH in mammalian cells. Proline residues within transmembrane segments have unusual properties, acting as helix breakers and increasing flexibility of membrane segments, since they lack an amide hydrogen. We examined the importance of three conserved proline residues in TM IV (transmembrane segment IV) of NHE1. Pro167 and Pro168 were mutated to Gly, Ala or Cys, and Pro178 was mutated to Ala. Pro168 and Pro178 mutant proteins were expressed at levels similar to wild-type NHE1 and were targeted to the plasma membrane. However, the mutants P167G (Pro167-->Gly), P167A and P167C were expressed at lower levels compared with wild-type NHE1, and a significant portion of P167G and P167C were retained intracellularly, possibly indicating induced changes in the structure of TM IV. P167G, P167C, P168A and P168C mutations abolished NHE activity, and P167A and P168G mutations caused markedly decreased activity. In contrast, the activity of the P178A mutant was not significantly different from that of wild-type NHE1. The results indicate that both Pro167 and Pro168 in TM IV of NHE1 are required for normal NHE activity. In addition, mutation of Pro167 affects the expression and membrane targeting of the exchanger. Thus both Pro167 and Pro168 are strictly required for NHE function and may play critical roles in the structure of TM IV of the NHE. PMID:14680478

Exploring the Dynamics of Dyadic Interactions via Hierarchical Segmentation

ERIC Educational Resources Information Center

Hsieh, Fushing; Ferrer, Emilio; Chen, Shu-Chun; Chow, Sy-Miin

2010-01-01

In this article we present an exploratory tool for extracting systematic patterns from multivariate data. The technique, hierarchical segmentation (HS), can be used to group multivariate time series into segments with similar discrete-state recurrence patterns and it is not restricted by the stationarity assumption. We use a simulation study to…

Unsupervised object segmentation with a hybrid graph model (HGM).

PubMed

Liu, Guangcan; Lin, Zhouchen; Yu, Yong; Tang, Xiaoou

2010-05-01

In this work, we address the problem of performing class-specific unsupervised object segmentation, i.e., automatic segmentation without annotated training images. Object segmentation can be regarded as a special data clustering problem where both class-specific information and local texture/color similarities have to be considered. To this end, we propose a hybrid graph model (HGM) that can make effective use of both symmetric and asymmetric relationship among samples. The vertices of a hybrid graph represent the samples and are connected by directed edges and/or undirected ones, which represent the asymmetric and/or symmetric relationship between them, respectively. When applied to object segmentation, vertices are superpixels, the asymmetric relationship is the conditional dependence of occurrence, and the symmetric relationship is the color/texture similarity. By combining the Markov chain formed by the directed subgraph and the minimal cut of the undirected subgraph, the object boundaries can be determined for each image. Using the HGM, we can conveniently achieve simultaneous segmentation and recognition by integrating both top-down and bottom-up information into a unified process. Experiments on 42 object classes (9,415 images in total) show promising results.

Automatic layer segmentation of H&E microscopic images of mice skin

NASA Astrophysics Data System (ADS)

Hussein, Saif; Selway, Joanne; Jassim, Sabah; Al-Assam, Hisham

2016-05-01

Mammalian skin is a complex organ composed of a variety of cells and tissue types. The automatic detection and quantification of changes in skin structures has a wide range of applications for biological research. To accurately segment and quantify nuclei, sebaceous gland, hair follicles, and other skin structures, there is a need for a reliable segmentation of different skin layers. This paper presents an efficient segmentation algorithm to segment the three main layers of mice skin, namely epidermis, dermis, and subcutaneous layers. It also segments the epidermis layer into two sub layers, basal and cornified layers. The proposed algorithm uses adaptive colour deconvolution technique on H&E stain images to separate different tissue structures, inter-modes and Otsu thresholding techniques were effectively combined to segment the layers. It then uses a set of morphological and logical operations on each layer to removing unwanted objects. A dataset of 7000 H&E microscopic images of mutant and wild type mice were used to evaluate the effectiveness of the algorithm. Experimental results examined by domain experts have confirmed the viability of the proposed algorithms.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network

PubMed Central

Mao, Lei; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice. PMID:29755716

Evolution of Fseg/Cseg dimorphism in region III of the Plasmodium falciparum eba-175 gene.

PubMed

Yasukochi, Yoshiki; Naka, Izumi; Patarapotikul, Jintana; Hananantachai, Hathairad; Ohashi, Jun

2017-04-01

The 175-kDa erythrocyte binding antigen (EBA-175) of the malaria parasite Plasmodium falciparum is important for its invasion into human erythrocytes. The primary structure of eba-175 is divided into seven regions, namely I to VII. Region III contains highly divergent dimorphic segments, termed Fseg and Cseg. The allele frequencies of segmental dimorphism within a P. falciparum population have been extensively examined; however, the molecular evolution of segmental dimorphism is not well understood. A comprehensive comparison of nucleotide sequences among 32 P. falciparum eba-175 alleles identified in our previous study, two Plasmodium reichenowi, and one P. gaboni orthologous alleles obtained from the GenBank database was conducted to uncover the origin and evolutionary processes of segmental dimorphism in P. falciparum eba-175. In the eba-175 nucleotide sequence derived from a P. reichenowi CDC strain, both Fseg and Cseg were found in region III, which implies that the original eba-175 gene had both segments, and deletions of F- and C-segments generated Cseg and Fseg alleles, respectively. We also confirmed the presence of allele with Fseg and Cseg in another P. reichenowi strain (SY57), by re-mapping short reads obtained from the GenBank database. On the other hand, the segmental sequence of eba-175 ortholog in P. gaboni was quite diverged from those of the other species, suggesting that the original eba-175 dimorphism of P. falciparum can be traced back to the stem linage of P. falciparum and P. reichenowi. Our findings suggest that Fseg and Cseg alleles are derived from a single eba-175 allele containing both segments in the ancestral population of P. falciparum and P. reichenowi, and that the allelic dimorphism of eba-175 was shaped by the independent emergence of similar dimorphic lineage in different species that has never been observed in any evolutionary mode of allelic dimorphism at other loci in malaria genomes. Copyright © 2017 Elsevier B.V. All rights reserved.

Localized-atlas-based segmentation of breast MRI in a decision-making framework.

PubMed

Fooladivanda, Aida; Shokouhi, Shahriar B; Ahmadinejad, Nasrin

2017-03-01

Breast-region segmentation is an important step for density estimation and Computer-Aided Diagnosis (CAD) systems in Magnetic Resonance Imaging (MRI). Detection of breast-chest wall boundary is often a difficult task due to similarity between gray-level values of fibroglandular tissue and pectoral muscle. This paper proposes a robust breast-region segmentation method which is applicable for both complex cases with fibroglandular tissue connected to the pectoral muscle, and simple cases with high contrast boundaries. We present a decision-making framework based on geometric features and support vector machine (SVM) to classify breasts in two main groups, complex and simple. For complex cases, breast segmentation is done using a combination of intensity-based and atlas-based techniques; however, only intensity-based operation is employed for simple cases. A novel atlas-based method, that is called localized-atlas, accomplishes the processes of atlas construction and registration based on the region of interest (ROI). Atlas-based segmentation is performed by relying on the chest wall template. Our approach is validated using a dataset of 210 cases. Based on similarity between automatic and manual segmentation results, the proposed method achieves Dice similarity coefficient, Jaccard coefficient, total overlap, false negative, and false positive values of 96.3, 92.9, 97.4, 2.61 and 4.77%, respectively. The localization error of the breast-chest wall boundary is 1.97 mm, in terms of averaged deviation distance. The achieved results prove that the suggested framework performs the breast segmentation with negligible errors and efficient computational time for different breasts from the viewpoints of size, shape, and density pattern.

TU-H-CAMPUS-JeP2-05: Can Automatic Delineation of Cardiac Substructures On Noncontrast CT Be Used for Cardiac Toxicity Analysis?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Y; Liao, Z; Jiang, W

Purpose: To evaluate the feasibility of using an automatic segmentation tool to delineate cardiac substructures from computed tomography (CT) images for cardiac toxicity analysis for non-small cell lung cancer (NSCLC) patients after radiotherapy. Methods: A multi-atlas segmentation tool developed in-house was used to delineate eleven cardiac substructures including the whole heart, four heart chambers, and six greater vessels automatically from the averaged 4DCT planning images for 49 NSCLC patients. The automatic segmented contours were edited appropriately by two experienced radiation oncologists. The modified contours were compared with the auto-segmented contours using Dice similarity coefficient (DSC) and mean surface distance (MSD)more » to evaluate how much modification was needed. In addition, the dose volume histogram (DVH) of the modified contours were compared with that of the auto-segmented contours to evaluate the dosimetric difference between modified and auto-segmented contours. Results: Of the eleven structures, the averaged DSC values ranged from 0.73 ± 0.08 to 0.95 ± 0.04 and the averaged MSD values ranged from 1.3 ± 0.6 mm to 2.9 ± 5.1mm for the 49 patients. Overall, the modification is small. The pulmonary vein (PV) and the inferior vena cava required the most modifications. The V30 (volume receiving 30 Gy or above) for the whole heart and the mean dose to the whole heart and four heart chambers did not show statistically significant difference between modified and auto-segmented contours. The maximum dose to the greater vessels did not show statistically significant difference except for the PV. Conclusion: The automatic segmentation of the cardiac substructures did not require substantial modification. The dosimetric evaluation showed no statistically significant difference between auto-segmented and modified contours except for the PV, which suggests that auto-segmented contours for the cardiac dose response study are feasible in the clinical practice with a minor modification to the PV vessel.« less

Spatial Statistics for Segmenting Histological Structures in H&E Stained Tissue Images.

PubMed

Nguyen, Luong; Tosun, Akif Burak; Fine, Jeffrey L; Lee, Adrian V; Taylor, D Lansing; Chennubhotla, S Chakra

2017-07-01

Segmenting a broad class of histological structures in transmitted light and/or fluorescence-based images is a prerequisite for determining the pathological basis of cancer, elucidating spatial interactions between histological structures in tumor microenvironments (e.g., tumor infiltrating lymphocytes), facilitating precision medicine studies with deep molecular profiling, and providing an exploratory tool for pathologists. This paper focuses on segmenting histological structures in hematoxylin- and eosin-stained images of breast tissues, e.g., invasive carcinoma, carcinoma in situ, atypical and normal ducts, adipose tissue, and lymphocytes. We propose two graph-theoretic segmentation methods based on local spatial color and nuclei neighborhood statistics. For benchmarking, we curated a data set of 232 high-power field breast tissue images together with expertly annotated ground truth. To accurately model the preference for histological structures (ducts, vessels, tumor nets, adipose, etc.) over the remaining connective tissue and non-tissue areas in ground truth annotations, we propose a new region-based score for evaluating segmentation algorithms. We demonstrate the improvement of our proposed methods over the state-of-the-art algorithms in both region- and boundary-based performance measures.

A spatiotemporal-based scheme for efficient registration-based segmentation of thoracic 4-D MRI.

PubMed

Yang, Y; Van Reeth, E; Poh, C L; Tan, C H; Tham, I W K

2014-05-01

Dynamic three-dimensional (3-D) (four-dimensional, 4-D) magnetic resonance (MR) imaging is gaining importance in the study of pulmonary motion for respiratory diseases and pulmonary tumor motion for radiotherapy. To perform quantitative analysis using 4-D MR images, segmentation of anatomical structures such as the lung and pulmonary tumor is required. Manual segmentation of entire thoracic 4-D MRI data that typically contains many 3-D volumes acquired over several breathing cycles is extremely tedious, time consuming, and suffers high user variability. This requires the development of new automated segmentation schemes for 4-D MRI data segmentation. Registration-based segmentation technique that uses automatic registration methods for segmentation has been shown to be an accurate method to segment structures for 4-D data series. However, directly applying registration-based segmentation to segment 4-D MRI series lacks efficiency. Here we propose an automated 4-D registration-based segmentation scheme that is based on spatiotemporal information for the segmentation of thoracic 4-D MR lung images. The proposed scheme saved up to 95% of computation amount while achieving comparable accurate segmentations compared to directly applying registration-based segmentation to 4-D dataset. The scheme facilitates rapid 3-D/4-D visualization of the lung and tumor motion and potentially the tracking of tumor during radiation delivery.

Joint multi-object registration and segmentation of left and right cardiac ventricles in 4D cine MRI

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Kepp, Timo; Schmidt-Richberg, Alexander; Handels, Heinz

2014-03-01

The diagnosis of cardiac function based on cine MRI requires the segmentation of cardiac structures in the images, but the problem of automatic cardiac segmentation is still open, due to the imaging characteristics of cardiac MR images and the anatomical variability of the heart. In this paper, we present a variational framework for joint segmentation and registration of multiple structures of the heart. To enable the simultaneous segmentation and registration of multiple objects, a shape prior term is introduced into a region competition approach for multi-object level set segmentation. The proposed algorithm is applied for simultaneous segmentation of the myocardium as well as the left and right ventricular blood pool in short axis cine MRI images. Two experiments are performed: first, intra-patient 4D segmentation with a given initial segmentation for one time-point in a 4D sequence, and second, a multi-atlas segmentation strategy is applied to unseen patient data. Evaluation of segmentation accuracy is done by overlap coefficients and surface distances. An evaluation based on clinical 4D cine MRI images of 25 patients shows the benefit of the combined approach compared to sole registration and sole segmentation.

What is a segment?

PubMed

Hannibal, Roberta L; Patel, Nipam H

2013-12-17

Animals have been described as segmented for more than 2,000 years, yet a precise definition of segmentation remains elusive. Here we give the history of the definition of segmentation, followed by a discussion on current controversies in defining a segment. While there is a general consensus that segmentation involves the repetition of units along the anterior-posterior (a-p) axis, long-running debates exist over whether a segment can be composed of only one tissue layer, whether the most anterior region of the arthropod head is considered segmented, and whether and how the vertebrate head is segmented. Additionally, we discuss whether a segment can be composed of a single cell in a column of cells, or a single row of cells within a grid of cells. We suggest that 'segmentation' be used in its more general sense, the repetition of units with a-p polarity along the a-p axis, to prevent artificial classification of animals. We further suggest that this general definition be combined with an exact description of what is being studied, as well as a clearly stated hypothesis concerning the specific nature of the potential homology of structures. These suggestions should facilitate dialogue among scientists who study vastly differing segmental structures.

Brain tissue segmentation based on DTI data

PubMed Central

Liu, Tianming; Li, Hai; Wong, Kelvin; Tarokh, Ashley; Guo, Lei; Wong, Stephen T.C.

2008-01-01

We present a method for automated brain tissue segmentation based on the multi-channel fusion of diffusion tensor imaging (DTI) data. The method is motivated by the evidence that independent tissue segmentation based on DTI parametric images provides complementary information of tissue contrast to the tissue segmentation based on structural MRI data. This has important applications in defining accurate tissue maps when fusing structural data with diffusion data. In the absence of structural data, tissue segmentation based on DTI data provides an alternative means to obtain brain tissue segmentation. Our approach to the tissue segmentation based on DTI data is to classify the brain into two compartments by utilizing the tissue contrast existing in a single channel. Specifically, because the apparent diffusion coefficient (ADC) values in the cerebrospinal fluid (CSF) are more than twice that of gray matter (GM) and white matter (WM), we use ADC images to distinguish CSF and non-CSF tissues. Additionally, fractional anisotropy (FA) images are used to separate WM from non-WM tissues, as highly directional white matter structures have much larger fractional anisotropy values. Moreover, other channels to separate tissue are explored, such as eigenvalues of the tensor, relative anisotropy (RA), and volume ratio (VR). We developed an approach based on the Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm that combines these two-class maps to obtain a complete tissue segmentation map of CSF, GM, and WM. Evaluations are provided to demonstrate the performance of our approach. Experimental results of applying this approach to brain tissue segmentation and deformable registration of DTI data and spoiled gradient-echo (SPGR) data are also provided. PMID:17804258

A Segment-Based Trajectory Similarity Measure in the Urban Transportation Systems.

PubMed

Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang

2017-03-06

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

Pre-operative segmentation of neck CT datasets for the planning of neck dissections

NASA Astrophysics Data System (ADS)

Cordes, Jeanette; Dornheim, Jana; Preim, Bernhard; Hertel, Ilka; Strauss, Gero

2006-03-01

For the pre-operative segmentation of CT neck datasets, we developed the software assistant NeckVision. The relevant anatomical structures for neck dissection planning can be segmented and the resulting patient-specific 3D-models are visualized afterwards in another software system for intervention planning. As a first step, we examined the appropriateness of elementary segmentation techniques based on gray values and contour information to extract the structures in the neck region from CT data. Region growing, interactive watershed transformation and live-wire are employed for segmentation of different target structures. It is also examined, which of the segmentation tasks can be automated. Based on this analysis, the software assistant NeckVision was developed to optimally support the workflow of image analysis for clinicians. The usability of NeckVision was tested within a first evaluation with four otorhinolaryngologists from the university hospital of Leipzig, four computer scientists from the university of Magdeburg and two laymen in both fields.

A New Model for Root Growth in Soil with Macropores

NASA Astrophysics Data System (ADS)

Landl, M.; Huber, K.; Schnepf, A.; Vanderborght, J.; Javaux, M.; Bengough, G.; Vereecken, H.

2016-12-01

In order to study soil-root interaction processes, dynamic root architecture models which are linked to models that simulate water flow and nutrient transport in the soil-root system are needed. Such models can be used to predict the impact of soil structural features, e.g. the presence of macropores in dense subsoil, on water and nutrient uptake by plants. In dynamic root architecture models, root growth is represented by moving root tips whose growth trajectory results in the creation of linear root segments. Typically, the direction of each new root segment is calculated as the vector sum of various direction-affecting components. The use of these established methods to simulate root growth in soil containing macropores, however, failed to reproduce experimentally observed root growth patterns. We therefore developed an alternative modelling approach where we distinguish between, firstly, the driving force for root growth which is determined by the orientation of the previous root segment as well as the influence of gravitropism and, secondly, soil mechanical resistance to root growth. The latter is expressed by root conductance which represents the inverse of soil penetration resistance and is treated similarly to hydraulic conductivity in Darcy's law. At the presence of macropores, root conductance is anisotropic which leads to a difference between the direction of the driving force and the direction of the root tip movement. The model was tested using data from the literature, at pot scale, at macropore scale, and in a series of simulations where sensitivity to gravity and macropore orientation was evaluated. The model simulated root growth trajectories in structured soil at both single root and whole root-system scales, generating root systems that were similar to images from experiments. Its implementation in the three dimensional soil and root water uptake model R-SWMS enables the use of the model in the future to evaluate the effect of macropores on crop access to water and nutrients.

Structure-based inhibitors of tau aggregation

NASA Astrophysics Data System (ADS)

Seidler, P. M.; Boyer, D. R.; Rodriguez, J. A.; Sawaya, M. R.; Cascio, D.; Murray, K.; Gonen, T.; Eisenberg, D. S.

2018-02-01

Aggregated tau protein is associated with over 20 neurological disorders, which include Alzheimer's disease. Previous work has shown that tau's sequence segments VQIINK and VQIVYK drive its aggregation, but inhibitors based on the structure of the VQIVYK segment only partially inhibit full-length tau aggregation and are ineffective at inhibiting seeding by full-length fibrils. Here we show that the VQIINK segment is the more powerful driver of tau aggregation. Two structures of this segment determined by the cryo-electron microscopy method micro-electron diffraction explain its dominant influence on tau aggregation. Of practical significance, the structures lead to the design of inhibitors that not only inhibit tau aggregation but also inhibit the ability of exogenous full-length tau fibrils to seed intracellular tau in HEK293 biosensor cells into amyloid. We also raise the possibility that the two VQIINK structures represent amyloid polymorphs of tau that may account for a subset of prion-like strains of tau.

Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

NASA Astrophysics Data System (ADS)

Xiao, P.; Kelly, M.; Guo, Q.

2014-12-01

This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree from multispectral image and Lidar data: recall, precision and F-score. This work explores the tradeoff between the expensive Lidar data and inexpensive multispectral image. The conclusion will guide the optimal data selection in different density canopy areas for individual tree segmentation, and contribute to the field of forest remote sensing.

Review methods for image segmentation from computed tomography images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik

Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affectmore » the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan.« less

Structures associated with strike-slip faults that bound landslide elements

USGS Publications Warehouse

Fleming, R.W.; Johnson, A.M.

1989-01-01

Large landslides are bounded on their flanks and on elements within the landslides by structures analogous to strike-slip faults. We observed the formation of thwse strike-slip faults and associated structures at two large landslides in central Utah during 1983-1985. The strike-slip faults in landslides are nearly vertical but locally may dip a few degrees toward or away from the moving ground. Fault surfaces are slickensided, and striations are subparallel to the ground surface. Displacement along strike-slip faults commonly produces scarps; scarps occur where local relief of the failure surface or ground surface is displaced and becomes adjacent to higher or lower ground, or where the landslide is thickening or thinning as a result of internal deformation. Several types of structures are formed at the ground surface as a strike-slip fault, which is fully developed at some depth below the ground surface, propagates upward in response to displacement. The simplest structure is a tension crack oriented at 45?? clockwise or counterclockwise from the trend of an underlying right- or left-lateral strike-slip fault, respectively. The tension cracks are typically arranged en echelon with the row of cracks parallel to the trace of the underlying strike-slip fault. Another common structure that forms above a developing strike-slip fault is a fault segment. Fault segments are discontinuous strike-slip faults that contain the same sense of slip but are turned clockwise or counterclockwise from a few to perhaps 20?? from the underlying strike-slip fault. The fault segments are slickensided and striated a few centimeters below the ground surface; continued displacement of the landslide causes the fault segments to open and a short tension crack propagates out of one or both ends of the fault segments. These structures, open fault segments containing a short tension crack, are termed compound cracks; and the short tension crack that propagates from the tip of the fault segment is typically oriented 45?? to the trend of the underlying fault. Fault segments are also typically arranged en echelon above the upward-propagating strike-slip fault. Continued displacement of the landslide causes the ground to buckle between the tension crack portions of the compound cracks. Still more displacement produces a thrust fault on one or both limbs of the buckle fold. These compressional structures form at right angles to the short tension cracks at the tips of the fault segments. Thus, the compressional structures are bounded on their ends by one face of a tension crack and detached from underlying material by thrusting or buckling. The tension cracks, fault segments, compound cracks, folds, and thrusts are ephemeral; they are created and destroyed with continuing displacement of the landslide. Ultimately, the structures are replaced by a throughgoing strike-slip fault. At one landslide, we observed the creation and destruction of the ephemeral structures as the landslide enlarged. Displacement of a few centimeters to about a decimeter was sufficient to produce scattered tension cracks and fault segments. Sets of compound cracks with associated folds and thrusts were produced by displacements of up to 1 m, and 1 to 2 m of displacement was required to produce a throughgoing strike-slip fault. The type of first-formed structure above an upward-propagating strike-slip fault is apparently controlled by the rheology of the material. Brittle material such as dry topsoil or the compact surface of a gravel road produces echelon tension cracks and sets of tension cracks and compressional structures, wherein the cracks and compressional structures are normal to each other and 45?? to the strike-slip fault at depth. First-formed structures in more ductile material such as moist cohesive soil are fault segments. In very ductile material such as soft clay and very wet soil in swampy areas, the first-formed structure is a throughgoing strike-slip fault. There are othe

RNA structural constraints in the evolution of the influenza A virus genome NP segment

PubMed Central

Gultyaev, Alexander P; Tsyganov-Bodounov, Anton; Spronken, Monique IJ; van der Kooij, Sander; Fouchier, Ron AM; Olsthoorn, René CL

2014-01-01

Conserved RNA secondary structures were predicted in the nucleoprotein (NP) segment of the influenza A virus genome using comparative sequence and structure analysis. A number of structural elements exhibiting nucleotide covariations were identified over the whole segment length, including protein-coding regions. Calculations of mutual information values at the paired nucleotide positions demonstrate that these structures impose considerable constraints on the virus genome evolution. Functional importance of a pseudoknot structure, predicted in the NP packaging signal region, was confirmed by plaque assays of the mutant viruses with disrupted structure and those with restored folding using compensatory substitutions. Possible functions of the conserved RNA folding patterns in the influenza A virus genome are discussed. PMID:25180940

Histomolecular interpretation of pleomorphic adenomas of the salivary gland by matrix-assisted laser desorption ionization imaging and spatial segmentation.

PubMed

Ernst, Günther; Guntinas-Lichius, Orlando; Hauberg-Lotte, Lena; Trede, Dennis; Becker, Michael; Alexandrov, Theodore; von Eggeling, Ferdinand

2015-07-01

Despite efforts in localization of key proteins using immunohistochemistry, the complex proteomic composition of pleomorphic adenomas has not yet been characterized. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI imaging) allows label-free and spatially resolved detection of hundreds of proteins directly from tissue sections and of histomorphological regions by finding colocalized molecular signals. Spatial segmentation of MALDI imaging data is an algorithmic method for finding regions of similar proteomic composition as functionally similar regions. We investigated 2 pleomorphic adenomas by applying spatial segmentation to the MALDI imaging data of tissue sections. The spatial segmentation subdivided the tissue in a good accordance with the tissue histology. Numerous molecular signals colocalized with histologically defined tissue regions were found. Our study highlights the cellular transdifferentiation within the pleomorphic adenoma. It could be shown that spatial segmentation of MALDI imaging data is a promising approach in the emerging field of digital histological analysis and characterization of tumors. © 2014 Wiley Periodicals, Inc.

Decreasing transmembrane segment length greatly decreases perfringolysin O pore size

DOE PAGES

Lin, Qingqing; Li, Huilin; Wang, Tong; ...

2015-04-08

Perfringolysin O (PFO) is a transmembrane (TM) β-barrel protein that inserts into mammalian cell membranes. Once inserted into membranes, PFO assembles into pore-forming oligomers containing 30–50 PFO monomers. These form a pore of up to 300 Å, far exceeding the size of most other proteinaceous pores. In this study, we found that altering PFO TM segment length can alter the size of PFO pores. A PFO mutant with lengthened TM segments oligomerized to a similar extent as wild-type PFO, and exhibited pore-forming activity and a pore size very similar to wild-type PFO as measured by electron microscopy and a leakagemore » assay. In contrast, PFO with shortened TM segments exhibited a large reduction in pore-forming activity and pore size. This suggests that the interaction between TM segments can greatly affect the size of pores formed by TM β-barrel proteins. PFO may be a promising candidate for engineering pore size for various applications.« less

Repeating Something Familiar: Using Reoccurring, Television-Inspired Segments to Promote Students' Recall of Learning Events and Course Content

ERIC Educational Resources Information Center

Bemis, Rhyannon H.

2018-01-01

Segments are a structured presentation style that is commonly used on late-night talk and variety television shows. Research has shown that shows that contain segments with both entertaining and informative content (e.g., "The Daily Show") have increased students' political knowledge. This study investigated how the structure of segments…

Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

PubMed Central

Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V.; Robles, Montserrat; Aparici, F.; Martí-Bonmatí, L.; García-Gómez, Juan M.

2015-01-01

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation. PMID:25978453

Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

PubMed

Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

2014-01-01

The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

Reproducible segmentation of white matter hyperintensities using a new statistical definition.

PubMed

Damangir, Soheil; Westman, Eric; Simmons, Andrew; Vrenken, Hugo; Wahlund, Lars-Olof; Spulber, Gabriela

2017-06-01

We present a method based on a proposed statistical definition of white matter hyperintensities (WMH), which can work with any combination of conventional magnetic resonance (MR) sequences without depending on manually delineated samples. T1-weighted, T2-weighted, FLAIR, and PD sequences acquired at 1.5 Tesla from 119 subjects from the Kings Health Partners-Dementia Case Register (healthy controls, mild cognitive impairment, Alzheimer's disease) were used. The segmentation was performed using a proposed definition for WMH based on the one-tailed Kolmogorov-Smirnov test. The presented method was verified, given all possible combinations of input sequences, against manual segmentations and a high similarity (Dice 0.85-0.91) was observed. Comparing segmentations with different input sequences to one another also yielded a high similarity (Dice 0.83-0.94) that exceeded intra-rater similarity (Dice 0.75-0.91). We compared the results with those of other available methods and showed that the segmentation based on the proposed definition has better accuracy and reproducibility in the test dataset used. Overall, the presented definition is shown to produce accurate results with higher reproducibility than manual delineation. This approach can be an alternative to other manual or automatic methods not only because of its accuracy, but also due to its good reproducibility.

Mandibular reconstruction using fibula free flap harvested using a customised cutting guide: how we do it.

PubMed

Tarsitano, A; Ciocca, L; Cipriani, R; Scotti, R; Marchetti, C

2015-06-01

Free fibula flap is routinely used for mandibular reconstructions. For contouring the flap, multiple osteotomies should be shaped to reproduce the native mandibular contour. The bone segments should be fixed using a reconstructive plate. This plate is usually manually bent by the surgeon during surgery. This method is efficient, but during reconstruction it is complicated to reproduce the complex 3D conformation of the mandible and recreate a normal morphology with a mandibular profile as similar as possible to the original; any aberration in its structural alignment may lead to aesthetic and function alterations due to malocclusion or temporomandibular disorders. In order to achieve better morphological and functional outcomes, we have performed a customised flap harvest using cutting guides. This study demonstrates how we have performed customised mandibular reconstruction using CAD-CAM fibular cutting guides in 20 patients undergoing oncological segmental resection.

An immunocytochemical, histochemical and ultrastructural study of the nervous system of the tapeworm Cyathocephalus truncatus (Cestoda, Spathebothriidea).

PubMed

Terenina, Nadezhda B; Poddubnaya, Larisa G; Tolstenkov, Oleg O; Gustafsson, Margaretha K S

2009-01-01

This study is the first detailed study of the organisation of the neuromuscular system of Cyathocephalus truncatus (Cestoda, Spathebothriidea). Five techniques have been used: (1) immunocytochemistry, (2) staining with TRITC-conjugated phalloidin, (3) NADPHdiaphorase histochemistry, (4) confocal scanning laser microscopy and (5) transmission electron microscopy. The patterns of nerves immunoreactive (IR) to antibodies towards serotonin (5-HT) and the invertebrate neuropeptide FMRFamide are described in relation to the musculature. The patterns of NADPHdiaphorase positive nerves and 5-HT-IR nerves are compared. The fine structure of the nervous system (NS) is described. The organisation of NS in the non-segmented, polyzoic C. truncatus differs clearly from that in the non-segmented, monozoic Caryophyllaeus laticeps and shows distinct similarities with the NS in pseudophyllidean cestodes. This supports the hypothesis that taxon Caryophyllidea and Spatheobothriidea form independent lineages within Eucestoda.

Deciphering the fine-structure of tribal admixture in the Bedouin population using genomic data

PubMed Central

Markus, B; Alshafee, I; Birk, O S

2014-01-01

The Bedouin Israeli population is highly inbred and structured with a very high prevalence of recessive diseases. Many studies in the past two decades focused on linkage analysis in large, multiple consanguineous pedigrees of this population. The advent of high-throughput technologies motivated researchers to search for rare variants shared between smaller pedigrees, integrating data from clinically similar yet seemingly non-related sporadic cases. However, such analyses are challenging because, without pedigree data, there is no prior knowledge regarding possible relatedness between the sporadic cases. Here, we describe models and techniques for the study of relationships between pedigrees and use them for the inference of tribal co-ancestry, delineating the complex social interactions between different tribes in the Negev Bedouins of southern Israel. Through our analysis, we differentiate between tribes that share many yet small genomic segments because of co-ancestry versus tribes that share larger segments because of recent admixture. The emergent pattern is well correlated with the prevalence of rare mutations in the different tribes. Tribes that do not intermarry, mostly because of social restrictions, hold private mutations, whereas tribes that do intermarry demonstrate a genetic flow of mutations between them. Thus, social structure within an inbred community can be delineated through genomic data, with implications to genetic counseling and genetic mapping. PMID:24084643

Deciphering the fine-structure of tribal admixture in the Bedouin population using genomic data.

PubMed

Markus, B; Alshafee, I; Birk, O S

2014-02-01

The Bedouin Israeli population is highly inbred and structured with a very high prevalence of recessive diseases. Many studies in the past two decades focused on linkage analysis in large, multiple consanguineous pedigrees of this population. The advent of high-throughput technologies motivated researchers to search for rare variants shared between smaller pedigrees, integrating data from clinically similar yet seemingly non-related sporadic cases. However, such analyses are challenging because, without pedigree data, there is no prior knowledge regarding possible relatedness between the sporadic cases. Here, we describe models and techniques for the study of relationships between pedigrees and use them for the inference of tribal co-ancestry, delineating the complex social interactions between different tribes in the Negev Bedouins of southern Israel. Through our analysis, we differentiate between tribes that share many yet small genomic segments because of co-ancestry versus tribes that share larger segments because of recent admixture. The emergent pattern is well correlated with the prevalence of rare mutations in the different tribes. Tribes that do not intermarry, mostly because of social restrictions, hold private mutations, whereas tribes that do intermarry demonstrate a genetic flow of mutations between them. Thus, social structure within an inbred community can be delineated through genomic data, with implications to genetic counseling and genetic mapping.

Segmentation editing improves efficiency while reducing inter-expert variation and maintaining accuracy for normal brain tissues in the presence of space-occupying lesions

PubMed Central

Deeley, MA; Chen, A; Datteri, R; Noble, J; Cmelak, A; Donnelly, EF; Malcolm, A; Moretti, L; Jaboin, J; Niermann, K; Yang, Eddy S; Yu, David S; Dawant, BM

2013-01-01

Image segmentation has become a vital and often rate limiting step in modern radiotherapy treatment planning. In recent years the pace and scope of algorithm development, and even introduction into the clinic, have far exceeded evaluative studies. In this work we build upon our previous evaluation of a registration driven segmentation algorithm in the context of 8 expert raters and 20 patients who underwent radiotherapy for large space-occupying tumors in the brain. In this work we tested four hypotheses concerning the impact of manual segmentation editing in a randomized single-blinded study. We tested these hypotheses on the normal structures of the brainstem, optic chiasm, eyes and optic nerves using the Dice similarity coefficient, volume, and signed Euclidean distance error to evaluate the impact of editing on inter-rater variance and accuracy. Accuracy analyses relied on two simulated ground truth estimation methods: STAPLE and a novel implementation of probability maps. The experts were presented with automatic, their own, and their peers’ segmentations from our previous study to edit. We found, independent of source, editing reduced inter-rater variance while maintaining or improving accuracy and improving efficiency with at least 60% reduction in contouring time. In areas where raters performed poorly contouring from scratch, editing of the automatic segmentations reduced the prevalence of total anatomical miss from approximately 16% to 8% of the total slices contained within the ground truth estimations. These findings suggest that contour editing could be useful for consensus building such as in developing delineation standards, and that both automated methods and even perhaps less sophisticated atlases could improve efficiency, inter-rater variance, and accuracy. PMID:23685866

Segmentation of megathrust rupture zones from fore-arc deformation patterns over hundreds to millions of years, Arauco peninsula, Chile

NASA Astrophysics Data System (ADS)

Melnick, Daniel; Bookhagen, Bodo; Strecker, Manfred R.; Echtler, Helmut P.

2009-01-01

This work explores the control of fore-arc structure on segmentation of megathrust earthquake ruptures using coastal geomorphic markers. The Arauco-Nahuelbuta region at the south-central Chile margin constitutes an anomalous fore-arc sector in terms of topography, geology, and exhumation, located within the overlap between the Concepción and Valdivia megathrust segments. This boundary, however, is only based on ˜500 years of historical records. We integrate deformed marine terraces dated by cosmogenic nuclides, syntectonic sediments, published fission track data, seismic reflection profiles, and microseismicity to analyze this earthquake boundary over 102-106 years. Rapid exhumation of Nahuelbuta's dome-like core started at 4 ± 1.2 Ma, coeval with inversion of the adjacent Arauco basin resulting in emergence of the Arauco peninsula. Here, similarities between topography, spatiotemporal trends in fission track ages, Pliocene-Pleistocene growth strata, and folded marine terraces suggest that margin-parallel shortening has dominated since Pliocene time. This shortening likely results from translation of a fore-arc sliver or microplate, decoupled from South America by an intra-arc strike-slip fault. Microplate collision against a buttress leads to localized uplift at Arauco accrued by deep-seated reverse faults, as well as incipient oroclinal bending. The extent of the Valdivia segment, which ruptured last in 1960 with an Mw 9.5 event, equals the inferred microplate. We propose that mechanical homogeneity of the fore-arc microplate delimits the Valdivia segment and that a marked discontinuity in the continental basement at Arauco acts as an inhomogeneous barrier controlling nucleation and propagation of 1960-type ruptures. As microplate-related deformation occurs since the Pliocene, we propose that this earthquake boundary and the extent of the Valdivia segment are spatially stable seismotectonic features at million year scale.

Automated synovium segmentation in doppler ultrasound images for rheumatoid arthritis assessment

NASA Astrophysics Data System (ADS)

Yeung, Pak-Hei; Tan, York-Kiat; Xu, Shuoyu

2018-02-01

We need better clinical tools to improve monitoring of synovitis, synovial inflammation in the joints, in rheumatoid arthritis (RA) assessment. Given its economical, safe and fast characteristics, ultrasound (US) especially Doppler ultrasound is frequently used. However, manual scoring of synovitis in US images is subjective and prone to observer variations. In this study, we propose a new and robust method for automated synovium segmentation in the commonly affected joints, i.e. metacarpophalangeal (MCP) and metatarsophalangeal (MTP) joints, which would facilitate automation in quantitative RA assessment. The bone contour in the US image is firstly detected based on a modified dynamic programming method, incorporating angular information for detecting curved bone surface and using image fuzzification to identify missing bone structure. K-means clustering is then performed to initialize potential synovium areas by utilizing the identified bone contour as boundary reference. After excluding invalid candidate regions, the final segmented synovium is identified by reconnecting remaining candidate regions using level set evolution. 15 MCP and 15 MTP US images were analyzed in this study. For each image, segmentations by our proposed method as well as two sets of annotations performed by an experienced clinician at different time-points were acquired. Dice's coefficient is 0.77+/-0.12 between the two sets of annotations. Similar Dice's coefficients are achieved between automated segmentation and either the first set of annotations (0.76+/-0.12) or the second set of annotations (0.75+/-0.11), with no significant difference (P = 0.77). These results verify that the accuracy of segmentation by our proposed method and by clinician is comparable. Therefore, reliable synovium identification can be made by our proposed method.

THE STRUCTURE AND CONCENTRATION OF SOLIDS IN PHOTORECEPTOR CELLS STUDIED BY REFRACTOMETRY AND INTERFERENCE MICROSCOPY

PubMed Central

Sidman, Richard L.

1957-01-01

Fragments of freshly obtained retinas of several vertebrate species were studied by refractometry, with reference to the structure of the rods and cones. The findings allowed a reassessment of previous descriptions based mainly on fixed material. The refractometric method was used also to measure the refractice indices and to calculate the concentrations of solids and water in the various cell segments. The main quantitative data were confirmed by interference microscopy. When examined by the method of refractometry the outer segments of freshly prepared retinal rods appear homogeneous. Within a few minutes a single eccentric longitudinal fiber appears, and transverse striations may develop. These changes are attributed to imbibition of water and swelling in structures normally too small for detection by light microscopy. The central "core" of outer segments and the chromophobic disc between outer and inner segments appear to be artifacts resulting from shrinkage during dehydration. The fresh outer segments of cones, and the inner segments of rods and cones also are described and illustrated. The volumes, refractive indices, concentrations of solids, and wet and dry weights of various segments of the photoreceptor cells were tabulated. Rod outer segments of the different species vary more than 100-fold in volume and mass but all have concentrations of solids of 40 to 43 per cent. Cone outer segments contain only about 30 per cent solids. The myoids, paraboloids, and ellipsoids of the inner segments likewise have characteristic refractive indices and concentrations of solids. Some of the limitations and particular virtues of refractometry as a method for quantitative analysis of living cells are discussed in comparison with more conventional biochemical techniques. Also the shapes and refractive indices of the various segments of photoreceptor cells are considered in relation to the absorption and transmission of light. The Stiles-Crawford effect can be accounted for on the basis of the structure of cone cells. PMID:13416308

Machine learning in a graph framework for subcortical segmentation

NASA Astrophysics Data System (ADS)

Guo, Zhihui; Kashyap, Satyananda; Sonka, Milan; Oguz, Ipek

2017-02-01

Automated and reliable segmentation of subcortical structures from human brain magnetic resonance images is of great importance for volumetric and shape analyses in quantitative neuroimaging studies. However, poor boundary contrast and variable shape of these structures make the automated segmentation a tough task. We propose a 3D graph-based machine learning method, called LOGISMOS-RF, to segment the caudate and the putamen from brain MRI scans in a robust and accurate way. An atlas-based tissue classification and bias-field correction method is applied to the images to generate an initial segmentation for each structure. Then a 3D graph framework is utilized to construct a geometric graph for each initial segmentation. A locally trained random forest classifier is used to assign a cost to each graph node. The max-flow algorithm is applied to solve the segmentation problem. Evaluation was performed on a dataset of T1-weighted MRI's of 62 subjects, with 42 images used for training and 20 images for testing. For comparison, FreeSurfer, FSL and BRAINSCut approaches were also evaluated using the same dataset. Dice overlap coefficients and surface-to-surfaces distances between the automated segmentation and expert manual segmentations indicate the results of our method are statistically significantly more accurate than the three other methods, for both the caudate (Dice: 0.89 +/- 0.03) and the putamen (0.89 +/- 0.03).

What is a segment?

PubMed Central

2013-01-01

Animals have been described as segmented for more than 2,000 years, yet a precise definition of segmentation remains elusive. Here we give the history of the definition of segmentation, followed by a discussion on current controversies in defining a segment. While there is a general consensus that segmentation involves the repetition of units along the anterior-posterior (a-p) axis, long-running debates exist over whether a segment can be composed of only one tissue layer, whether the most anterior region of the arthropod head is considered segmented, and whether and how the vertebrate head is segmented. Additionally, we discuss whether a segment can be composed of a single cell in a column of cells, or a single row of cells within a grid of cells. We suggest that ‘segmentation’ be used in its more general sense, the repetition of units with a-p polarity along the a-p axis, to prevent artificial classification of animals. We further suggest that this general definition be combined with an exact description of what is being studied, as well as a clearly stated hypothesis concerning the specific nature of the potential homology of structures. These suggestions should facilitate dialogue among scientists who study vastly differing segmental structures. PMID:24345042

Automatic aortic root segmentation in CTA whole-body dataset

NASA Astrophysics Data System (ADS)

Gao, Xinpei; Kitslaar, Pieter H.; Scholte, Arthur J. H. A.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke; Reiber, Johan H. C.

2016-03-01

Trans-catheter aortic valve replacement (TAVR) is an evolving technique for patients with serious aortic stenosis disease. Typically, in this application a CTA data set is obtained of the patient's arterial system from the subclavian artery to the femoral arteries, to evaluate the quality of the vascular access route and analyze the aortic root to determine if and which prosthesis should be used. In this paper, we concentrate on the automated segmentation of the aortic root. The purpose of this study was to automatically segment the aortic root in computed tomography angiography (CTA) datasets to support TAVR procedures. The method in this study includes 4 major steps. First, the patient's cardiac CTA image was resampled to reduce the computation time. Next, the cardiac CTA image was segmented using an atlas-based approach. The most similar atlas was selected from a total of 8 atlases based on its image similarity to the input CTA image. Third, the aortic root segmentation from the previous step was transferred to the patient's whole-body CTA image by affine registration and refined in the fourth step using a deformable subdivision surface model fitting procedure based on image intensity. The pipeline was applied to 20 patients. The ground truth was created by an analyst who semi-automatically corrected the contours of the automatic method, where necessary. The average Dice similarity index between the segmentations of the automatic method and the ground truth was found to be 0.965±0.024. In conclusion, the current results are very promising.

BBSome function is required for both the morphogenesis and maintenance of the photoreceptor outer segment

PubMed Central

Hsu, Ying; Kim, Gunhee; Zhang, Qihong; Datta, Poppy; Seo, Seongjin

2017-01-01

Genetic mutations disrupting the structure and function of primary cilia cause various inherited retinal diseases in humans. Bardet-Biedl syndrome (BBS) is a genetically heterogeneous, pleiotropic ciliopathy characterized by retinal degeneration, obesity, postaxial polydactyly, intellectual disability, and genital and renal abnormalities. To gain insight into the mechanisms of retinal degeneration in BBS, we developed a congenital knockout mouse of Bbs8, as well as conditional mouse models in which function of the BBSome (a protein complex that mediates ciliary trafficking) can be temporally inactivated or restored. We demonstrate that BBS mutant mice have defects in retinal outer segment morphogenesis. We further demonstrate that removal of Bbs8 in adult mice affects photoreceptor function and disrupts the structural integrity of the outer segment. Notably, using a mouse model in which a gene trap inhibiting Bbs8 gene expression can be removed by an inducible FLP recombinase, we show that when BBS8 is restored in immature retinas with malformed outer segments, outer segment extension can resume normally and malformed outer segment discs are displaced distally by normal outer segment structures. Over time, the retinas of the rescued mice become morphologically and functionally normal, indicating that there is a window of plasticity when initial retinal outer segment morphogenesis defects can be ameliorated. PMID:29049287

- and Graph-Based Point Cloud Segmentation of 3d Scenes Using Perceptual Grouping Laws

NASA Astrophysics Data System (ADS)

Xu, Y.; Hoegner, L.; Tuttas, S.; Stilla, U.

2017-05-01

Segmentation is the fundamental step for recognizing and extracting objects from point clouds of 3D scene. In this paper, we present a strategy for point cloud segmentation using voxel structure and graph-based clustering with perceptual grouping laws, which allows a learning-free and completely automatic but parametric solution for segmenting 3D point cloud. To speak precisely, two segmentation methods utilizing voxel and supervoxel structures are reported and tested. The voxel-based data structure can increase efficiency and robustness of the segmentation process, suppressing the negative effect of noise, outliers, and uneven points densities. The clustering of voxels and supervoxel is carried out using graph theory on the basis of the local contextual information, which commonly conducted utilizing merely pairwise information in conventional clustering algorithms. By the use of perceptual laws, our method conducts the segmentation in a pure geometric way avoiding the use of RGB color and intensity information, so that it can be applied to more general applications. Experiments using different datasets have demonstrated that our proposed methods can achieve good results, especially for complex scenes and nonplanar surfaces of objects. Quantitative comparisons between our methods and other representative segmentation methods also confirms the effectiveness and efficiency of our proposals.

A combined learning algorithm for prostate segmentation on 3D CT images.

PubMed

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Schuster, David M; Fei, Baowei

2017-11-01

Segmentation of the prostate on CT images has many applications in the diagnosis and treatment of prostate cancer. Because of the low soft-tissue contrast on CT images, prostate segmentation is a challenging task. A learning-based segmentation method is proposed for the prostate on three-dimensional (3D) CT images. We combine population-based and patient-based learning methods for segmenting the prostate on CT images. Population data can provide useful information to guide the segmentation processing. Because of inter-patient variations, patient-specific information is particularly useful to improve the segmentation accuracy for an individual patient. In this study, we combine a population learning method and a patient-specific learning method to improve the robustness of prostate segmentation on CT images. We train a population model based on the data from a group of prostate patients. We also train a patient-specific model based on the data of the individual patient and incorporate the information as marked by the user interaction into the segmentation processing. We calculate the similarity between the two models to obtain applicable population and patient-specific knowledge to compute the likelihood of a pixel belonging to the prostate tissue. A new adaptive threshold method is developed to convert the likelihood image into a binary image of the prostate, and thus complete the segmentation of the gland on CT images. The proposed learning-based segmentation algorithm was validated using 3D CT volumes of 92 patients. All of the CT image volumes were manually segmented independently three times by two, clinically experienced radiologists and the manual segmentation results served as the gold standard for evaluation. The experimental results show that the segmentation method achieved a Dice similarity coefficient of 87.18 ± 2.99%, compared to the manual segmentation. By combining the population learning and patient-specific learning methods, the proposed method is effective for segmenting the prostate on 3D CT images. The prostate CT segmentation method can be used in various applications including volume measurement and treatment planning of the prostate. © 2017 American Association of Physicists in Medicine.

Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features.

PubMed

Kushibar, Kaisar; Valverde, Sergi; González-Villà, Sandra; Bernal, Jose; Cabezas, Mariano; Oliver, Arnau; Lladó, Xavier

2018-06-15

Sub-cortical brain structure segmentation in Magnetic Resonance Images (MRI) has attracted the interest of the research community for a long time as morphological changes in these structures are related to different neurodegenerative disorders. However, manual segmentation of these structures can be tedious and prone to variability, highlighting the need for robust automated segmentation methods. In this paper, we present a novel convolutional neural network based approach for accurate segmentation of the sub-cortical brain structures that combines both convolutional and prior spatial features for improving the segmentation accuracy. In order to increase the accuracy of the automated segmentation, we propose to train the network using a restricted sample selection to force the network to learn the most difficult parts of the structures. We evaluate the accuracy of the proposed method on the public MICCAI 2012 challenge and IBSR 18 datasets, comparing it with different traditional and deep learning state-of-the-art methods. On the MICCAI 2012 dataset, our method shows an excellent performance comparable to the best participant strategy on the challenge, while performing significantly better than state-of-the-art techniques such as FreeSurfer and FIRST. On the IBSR 18 dataset, our method also exhibits a significant increase in the performance with respect to not only FreeSurfer and FIRST, but also comparable or better results than other recent deep learning approaches. Moreover, our experiments show that both the addition of the spatial priors and the restricted sampling strategy have a significant effect on the accuracy of the proposed method. In order to encourage the reproducibility and the use of the proposed method, a public version of our approach is available to download for the neuroimaging community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Ultrasound imaging of the anterior section of the eye of five different snake species.

PubMed

Lauridsen, Henrik; Da Silva, Mari-Ann O; Hansen, Kasper; Jensen, Heidi M; Warming, Mads; Wang, Tobias; Pedersen, Michael

2014-12-30

Nineteen clinically normal snakes: six ball pythons (Python regius), six Burmese pythons (Python bivittatus), one Children's python (Antaresia childreni), four Amazon tree boas (Corallus hortulanus), and two Malagasy ground boas (Acrantophis madagascariensis) were subjected to ultrasound imaging with 21 MHz (ball python) and 50 MHz (ball python, Burmese python, Children's python, Amazon tree boa, Malagasy ground boa) transducers in order to measure the different structures of the anterior segment in clinically normal snake eyes with the aim to review baseline values for clinically important ophthalmic structures. The ultrasonographic measurements included horizontal spectacle diameter, spectacle thickness, depth of sub-spectacular space and corneal thickness. For comparative purposes, a formalin-fixed head of a Burmese python was subjected to micro computed tomography. In all snakes, the spectacle was thinner than the cornea. There was significant difference in spectacle diameter, and spectacle and corneal thickness between the Amazon tree boa and the Burmese and ball pythons. There was no difference in the depth of the sub-spectacular space. The results obtained in the Burmese python with the 50 MHz transducer were similar to the results obtained with micro computed tomography. Images acquired with the 21 MHz transducer included artifacts which may be misinterpreted as ocular structures. Our measurements of the structures in the anterior segment of the eye can serve as orientative values for snakes examined for ocular diseases. In addition, we demonstrated that using a high frequency transducer minimizes the risk of misinterpreting artifacts as ocular structures.

SEGMENTATION OF MITOCHONDRIA IN ELECTRON MICROSCOPY IMAGES USING ALGEBRAIC CURVES.

PubMed

Seyedhosseini, Mojtaba; Ellisman, Mark H; Tasdizen, Tolga

2013-01-01

High-resolution microscopy techniques have been used to generate large volumes of data with enough details for understanding the complex structure of the nervous system. However, automatic techniques are required to segment cells and intracellular structures in these multi-terabyte datasets and make anatomical analysis possible on a large scale. We propose a fully automated method that exploits both shape information and regional statistics to segment irregularly shaped intracellular structures such as mitochondria in electron microscopy (EM) images. The main idea is to use algebraic curves to extract shape features together with texture features from image patches. Then, these powerful features are used to learn a random forest classifier, which can predict mitochondria locations precisely. Finally, the algebraic curves together with regional information are used to segment the mitochondria at the predicted locations. We demonstrate that our method outperforms the state-of-the-art algorithms in segmentation of mitochondria in EM images.

Segmentation of White Blood Cells From Microscopic Images Using a Novel Combination of K-Means Clustering and Modified Watershed Algorithm.

PubMed

Ghane, Narjes; Vard, Alireza; Talebi, Ardeshir; Nematollahy, Pardis

2017-01-01

Recognition of white blood cells (WBCs) is the first step to diagnose some particular diseases such as acquired immune deficiency syndrome, leukemia, and other blood-related diseases that are usually done by pathologists using an optical microscope. This process is time-consuming, extremely tedious, and expensive and needs experienced experts in this field. Thus, a computer-aided diagnosis system that assists pathologists in the diagnostic process can be so effective. Segmentation of WBCs is usually a first step in developing a computer-aided diagnosis system. The main purpose of this paper is to segment WBCs from microscopic images. For this purpose, we present a novel combination of thresholding, k-means clustering, and modified watershed algorithms in three stages including (1) segmentation of WBCs from a microscopic image, (2) extraction of nuclei from cell's image, and (3) separation of overlapping cells and nuclei. The evaluation results of the proposed method show that similarity measures, precision, and sensitivity respectively were 92.07, 96.07, and 94.30% for nucleus segmentation and 92.93, 97.41, and 93.78% for cell segmentation. In addition, statistical analysis presents high similarity between manual segmentation and the results obtained by the proposed method.

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

PubMed

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lavenne, Franck; Le Bars, Didier; Costes, Nicolas

2013-08-15

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures. Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data. Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of atlases used. When all four atlases were used for the MAXPROB creation, the accuracy of morphometric segmentation approached that of the PROPAG method. PET measures extracted either via automatic methods or via the manually defined regions were strongly correlated, with no significant regional differences between methods. Intra-class correlation coefficients for test-retest data were over 0.87. Compared to single atlas extractions, multi-atlas methods improve the accuracy of region definition. They also perform comparably to manually defined regions for PET quantification. Multiple atlases of Macaca fascicularis brains are now available and allow reproducible and simplified analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

Neural markers reveal a one-segmented head in tardigrades (water bears).

PubMed

Mayer, Georg; Kauschke, Susann; Rüdiger, Jan; Stevenson, Paul A

2013-01-01

While recent neuroanatomical and gene expression studies have clarified the alignment of cephalic segments in arthropods and onychophorans, the identity of head segments in tardigrades remains controversial. In particular, it is unclear whether the tardigrade head and its enclosed brain comprises one, or several segments, or a non-segmental structure. To clarify this, we applied a variety of histochemical and immunocytochemical markers to specimens of the tardigrade Macrobiotus cf. harmsworthi and the onychophoran Euperipatoides rowelli. Our immunolabelling against serotonin, FMRFamide and α-tubulin reveals that the tardigrade brain is a dorsal, bilaterally symmetric structure that resembles the brain of onychophorans and arthropods rather than a circumoesophageal ring typical of cycloneuralians (nematodes and allies). A suboesophageal ganglion is clearly lacking. Our data further reveal a hitherto unknown, unpaired stomatogastric ganglion in Macrobiotus cf. harmsworthi, which innervates the ectodermal oesophagus and the endodermal midgut and is associated with the second leg-bearing segment. In contrast, the oesophagus of the onychophoran E. rowelli possesses no immunoreactive neurons, whereas scattered bipolar, serotonin-like immunoreactive cell bodies are found in the midgut wall. Furthermore, our results show that the onychophoran pharynx is innervated by a medullary loop nerve accompanied by monopolar, serotonin-like immunoreactive cell bodies. A comparison of the nervous system innervating the foregut and midgut structures in tardigrades and onychophorans to that of arthropods indicates that the stomatogastric ganglion is a potential synapomorphy of Tardigrada and Arthropoda. Its association with the second leg-bearing segment in tardigrades suggests that the second trunk ganglion is a homologue of the arthropod tritocerebrum, whereas the first ganglion corresponds to the deutocerebrum. We therefore conclude that the tardigrade brain consists of a single segmental region corresponding to the arthropod protocerebrum and, accordingly, that the tardigrade head is a non-composite, one-segmented structure.

Emergence of Functional Hierarchy in a Multiple Timescale Neural Network Model: A Humanoid Robot Experiment

PubMed Central

Yamashita, Yuichi; Tani, Jun

2008-01-01

It is generally thought that skilled behavior in human beings results from a functional hierarchy of the motor control system, within which reusable motor primitives are flexibly integrated into various sensori-motor sequence patterns. The underlying neural mechanisms governing the way in which continuous sensori-motor flows are segmented into primitives and the way in which series of primitives are integrated into various behavior sequences have, however, not yet been clarified. In earlier studies, this functional hierarchy has been realized through the use of explicit hierarchical structure, with local modules representing motor primitives in the lower level and a higher module representing sequences of primitives switched via additional mechanisms such as gate-selecting. When sequences contain similarities and overlap, however, a conflict arises in such earlier models between generalization and segmentation, induced by this separated modular structure. To address this issue, we propose a different type of neural network model. The current model neither makes use of separate local modules to represent primitives nor introduces explicit hierarchical structure. Rather than forcing architectural hierarchy onto the system, functional hierarchy emerges through a form of self-organization that is based on two distinct types of neurons, each with different time properties (“multiple timescales”). Through the introduction of multiple timescales, continuous sequences of behavior are segmented into reusable primitives, and the primitives, in turn, are flexibly integrated into novel sequences. In experiments, the proposed network model, coordinating the physical body of a humanoid robot through high-dimensional sensori-motor control, also successfully situated itself within a physical environment. Our results suggest that it is not only the spatial connections between neurons but also the timescales of neural activity that act as important mechanisms leading to functional hierarchy in neural systems. PMID:18989398

Identification of a Novel TGF-β-Binding Site in the Zona Pellucida C-terminal (ZP-C) Domain of TGF-β-Receptor-3 (TGFR-3)

PubMed Central

Diestel, Uschi; Resch, Marcus; Meinhardt, Kathrin; Weiler, Sigrid; Hellmann, Tina V.; Mueller, Thomas D.; Nickel, Joachim; Eichler, Jutta; Muller, Yves A.

2013-01-01

The zona pellucida (ZP) domain is present in extracellular proteins such as the zona pellucida proteins and tectorins and participates in the formation of polymeric protein networks. However, the ZP domain also occurs in the cytokine signaling co-receptor transforming growth factor β (TGF-β) receptor type 3 (TGFR-3, also known as betaglycan) where it contributes to cytokine ligand recognition. Currently it is unclear how the ZP domain architecture enables this dual functionality. Here, we identify a novel major TGF-β-binding site in the FG loop of the C-terminal subdomain of the murine TGFR-3 ZP domain (ZP-C) using protein crystallography, limited proteolysis experiments, surface plasmon resonance measurements and synthetic peptides. In the murine 2.7 Å crystal structure that we are presenting here, the FG-loop is disordered, however, well-ordered in a recently reported homologous rat ZP-C structure. Surprisingly, the adjacent external hydrophobic patch (EHP) segment is registered differently in the rat and murine structures suggesting that this segment only loosely associates with the remaining ZP-C fold. Such a flexible and temporarily-modulated association of the EHP segment with the ZP domain has been proposed to control the polymerization of ZP domain-containing proteins. Our findings suggest that this flexibility also extends to the ZP domain of TGFR-3 and might facilitate co-receptor ligand interaction and presentation via the adjacent FG-loop. This hints that a similar C-terminal region of the ZP domain architecture possibly regulates both the polymerization of extracellular matrix proteins and cytokine ligand recognition of TGFR-3. PMID:23826237

Untangleing the effects of chain rigidity on the structure and dynamics of strongly adsorbed polymer melts

DOE PAGES

Carrillo, Jan-Michael Y.; Cheng, Shiwang; Kumar, Rajeev; ...

2015-06-11

Here, we present a detailed analysis of coarse-grained molecular dynamics simulations of semiflexible polymer melts in contact with a strongly adsorbing substrate. We have characterized the segments in the interfacial layer by counting the number of trains, loops, tails and unadsorbed segments. For more rigid chains, a tail and an adsorbed segment (a train) dominate while loops are more prevalent in more flexible chains. The tails exhibit a non-uniformly stretched conformation akin to the polydispersed pseudobrush envisioned by Guiselin. To probe the dynamics of the segments we computed the layer z-resolved intermediate coherent collective dynamics structure factor, S(q, t, z),more » mean-square displacement of segments, and the 2nd Legendre polynomial of the time-autocorrelation of unit bond vectors, 2[n i(t,z)•n i(0,z)]>. Our results show that segmental dynamics is slower for stiffer chains and there is a strong correlation between the structure and dynamics in the interfacial layer. There is no glassy layer, and the slowing down in dynamics of stiffer chains in the adsorbed region can be attributed to the densification and the more persistent layering of segments.« less

Distribution of Mitral Annular and Aortic Valve Calcium as Assessed by Unenhanced Multidetector Computed Tomography.

PubMed

Koshkelashvili, Nikoloz; Codolosa, Jose N; Goykhman, Igor; Romero-Corral, Abel; Pressman, Gregg S

2015-12-15

Aging is associated with calcium deposits in various cardiovascular structures, but patterns of calcium deposition, if any, are unknown. In search of such patterns, we performed quantitative assessment of mitral annular calcium (MAC) and aortic valve calcium (AVC) in a broad clinical sample. Templates were created from gated computed tomography (CT) scans depicting the aortic valve cusps and mitral annular segments in relation to surrounding structures. These were then applied to CT reconstructions from ungated, clinically indicated CT scans of 318 subjects, aged ≥65 years. Calcium location was assigned using the templates and quantified by the Agatston method. Mean age was 76 ± 7.3 years; 48% were men and 58% were white. Whites had higher prevalence (p = 0.03) and density of AVC than blacks (p = 0.02), and a trend toward increased MAC (p = 0.06). Prevalence of AVC was similar between men and women, but AVC scores were higher in men (p = 0.008); this difference was entirely accounted for by whites. Within the aortic valve, the left cusp was more frequently calcified than the others. MAC was most common in the posterior mitral annulus, especially its middle (P2) segment. For the anterior mitral annulus, the medial (A3) segment calcified most often. In conclusion, AVC is more common in whites than blacks, and more intense in men, but only in whites. Furthermore, calcium deposits in the mitral annulus and aortic valve favor certain locations. Copyright © 2015 Elsevier Inc. All rights reserved.

Semiautomated hybrid algorithm for estimation of three-dimensional liver surface in CT using dynamic cellular automata and level-sets.

PubMed

Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla

2015-04-01

Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method.

A possible transoceanic tsunami directed toward the U.S. west coast from the Semidi segment, Alaska convergent margin

USGS Publications Warehouse

von Huene, Roland E.; Miller, John J.; Dartnell, Peter

2016-01-01

The Semidi segment of the Alaska convergent margin appears capable of generating a giant tsunami like the one produced along the nearby Unimak segment in 1946. Reprocessed legacy seismic reflection data and a compilation of multibeam bathymetric surveys reveal structures that could generate such a tsunami. A 200 km long ridge or escarpment with crests >1 km high is the surface expression of an active out-of-sequence fault zone, recently referred to as a splay fault. Such faults are potentially tsunamigenic. This type of fault zone separates the relatively rigid rock of the margin framework from the anelastic accreted sediment prism. Seafloor relief of the ridge exceeds that of similar age accretionary prism ridges indicating preferential slip along the splay fault zone. The greater slip may derive from Quaternary subduction of the Patton Murray hot spot ridge that extends 200 km toward the east across the north Pacific. Estimates of tsunami repeat times from paleotsunami studies indicate that the Semidi segment could be near the end of its current inter-seismic cycle. GPS records from Chirikof Island at the shelf edge indicate 90% locking of plate interface faults. An earthquake in the shallow Semidi subduction zone could generate a tsunami that will inundate the US west coast more than the 1946 and 1964 earthquakes because the Semidi continental slope azimuth directs a tsunami southeastward.

A long-lived Late Cretaceous-early Eocene extensional province in Anatolia? Structural evidence from the Ivriz Detachment, southern central Turkey

NASA Astrophysics Data System (ADS)

Gürer, Derya; Plunder, Alexis; Kirst, Frederik; Corfu, Fernando; Schmid, Stefan M.; van Hinsbergen, Douwe J. J.

2018-01-01

Central Anatolia exposes previously buried and metamorphosed, continent-derived rocks - the Kırşehir and Afyon zones - now covering an area of ∼300 × 400 km. So far, the exhumation history of these rocks has been poorly constrained. We show for the first time that the major, >120 km long, top-NE 'Ivriz' Detachment controlled the exhumation of the HP/LT metamorphic Afyon Zone in southern Central Anatolia. We date its activity at between the latest Cretaceous and early Eocene times. Combined with previously documented isolated extensional detachments found in the Kırşehir Block, our results suggest that a major province governed by extensional exhumation was active throughout Central Anatolia between ∼80 and ∼48 Ma. Although similar in dimension to the Aegean extensional province to the east, the Central Anatolian extensional province is considerably older and was controlled by a different extension direction. From this, we infer that the African slab(s) that subducted below Anatolia must have rolled back relative to the Aegean slab since at least the latest Cretaceous, suggesting that these regions were underlain by a segmented slab. Whether or not these early segments already corresponded to the modern Aegean, Antalya, and Cyprus slab segments remains open for debate, but slab segmentation must have occurred much earlier than previously thought.

The Structure of Lombricine Kinase: Implications for Phosphagen Conformational Changes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bush, D. Jeffrey; Kirillova, Olga; Clark, Shawn A.

2012-05-29

Lombricine kinase is a member of the phosphagen kinase family and a homolog of creatine and arginine kinases, enzymes responsible for buffering cellular ATP levels. Structures of lombricine kinase from the marine worm Urechis caupo were determined by x-ray crystallography. One form was crystallized as a nucleotide complex, and the other was substrate-free. The two structures are similar to each other and more similar to the substrate-free forms of homologs than to the substrate-bound forms of the other phosphagen kinases. Active site specificity loop 309-317, which is disordered in substrate-free structures of homologs and is known from the NMR ofmore » arginine kinase to be inherently dynamic, is resolved in both lombricine kinase structures, providing an improved basis for understanding the loop dynamics. Phosphagen kinases undergo a segmented closing on substrate binding, but the lombricine kinase ADP complex is in the open form more typical of substrate-free homologs. Through a comparison with prior complexes of intermediate structure, a correlation was revealed between the overall enzyme conformation and the substrate interactions of His{sup 178}. Comparative modeling provides a rationale for the more relaxed specificity of these kinases, of which the natural substrates are among the largest of the phosphagen substrates.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

N. Seth Carpenter; Suzette J. Payne; Annette L. Schafer

We recognize a discrepancy in magnitudes estimated for several Basin and Range, U.S.A. faults. For example, magnitudes predicted for the Wasatch (Utah), Lost River (Idaho), and Lemhi (Idaho) faults from fault segment lengths (L{sub seg}) where lengths are defined between geometrical, structural, and/or behavioral discontinuities assumed to persistently arrest rupture, are consistently less than magnitudes calculated from displacements (D) along these same segments. For self-similarity, empirical relationships (e.g. Wells and Coppersmith, 1994) should predict consistent magnitudes (M) using diverse fault dimension values for a given fault (i.e. M {approx} L{sub seg}, should equal M {approx} D). Typically, the empirical relationshipsmore » are derived from historical earthquake data and parameter values used as input into these relationships are determined from field investigations of paleoearthquakes. A commonly used assumption - grounded in the characteristic-earthquake model of Schwartz and Coppersmith (1984) - is equating L{sub seg} with surface rupture length (SRL). Many large historical events yielded secondary and/or sympathetic faulting (e.g. 1983 Borah Peak, Idaho earthquake) which are included in the measurement of SRL and used to derive empirical relationships. Therefore, calculating magnitude from the M {approx} SRL relationship using L{sub seg} as SRL leads to an underestimation of magnitude and the M {approx} L{sub seg} and M {approx} D discrepancy. Here, we propose an alternative approach to earthquake magnitude estimation involving a relationship between moment magnitude (Mw) and length, where length is L{sub seg} instead of SRL. We analyze seven historical, surface-rupturing, strike-slip and normal faulting earthquakes for which segmentation of the causative fault and displacement data are available and whose rupture included at least one entire fault segment, but not two or more. The preliminary Mw {approx} L{sub seg} results are strikingly consistent with Mw {approx} D calculations using paleoearthquake data for the Wasatch, Lost River, and Lemhi faults, demonstrating self-similarity and implying that the Mw {approx} L{sub seg} relationship should supplant M {approx} SRL relationships currently employed in seismic hazard analyses. The relationship will permit reliable use of L{sub seg} data from field investigations and proper use and weighting of multiple-segment-rupture scenarios in seismic hazard analyses, and eliminate the need to reconcile the Mw {approx} SRL and Mw {approx} D differences in a multiple-parameter relationship for segmented faults.« less

Magnetic resonance brain tissue segmentation based on sparse representations

NASA Astrophysics Data System (ADS)

Rueda, Andrea

2015-12-01

Segmentation or delineation of specific organs and structures in medical images is an important task in the clinical diagnosis and treatment, since it allows to characterize pathologies through imaging measures (biomarkers). In brain imaging, segmentation of main tissues or specific structures is challenging, due to the anatomic variability and complexity, and the presence of image artifacts (noise, intensity inhomogeneities, partial volume effect). In this paper, an automatic segmentation strategy is proposed, based on sparse representations and coupled dictionaries. Image intensity patterns are singly related to tissue labels at the level of small patches, gathering this information in coupled intensity/segmentation dictionaries. This dictionaries are used within a sparse representation framework to find the projection of a new intensity image onto the intensity dictionary, and the same projection can be used with the segmentation dictionary to estimate the corresponding segmentation. Preliminary results obtained with two publicly available datasets suggest that the proposal is capable of estimating adequate segmentations for gray matter (GM) and white matter (WM) tissues, with an average overlapping of 0:79 for GM and 0:71 for WM (with respect to original segmentations).

Microplitis demolitor bracovirus genome segments vary in abundance and are individually packaged in virions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beck, Markus H.; Inman, Ross B.; Strand, Michael R.

2007-03-01

Polydnaviruses (PDVs) are distinguished by their unique association with parasitoid wasps and their segmented, double-stranded (ds) DNA genomes that are non-equimolar in abundance. Relatively little is actually known, however, about genome packaging or segment abundance of these viruses. Here, we conducted electron microscopy (EM) and real-time polymerase chain reaction (PCR) studies to characterize packaging and segment abundance of Microplitis demolitor bracovirus (MdBV). Like other PDVs, MdBV replicates in the ovaries of females where virions accumulate to form a suspension called calyx fluid. Wasps then inject a quantity of calyx fluid when ovipositing into hosts. The MdBV genome consists of 15more » segments that range from 3.6 (segment A) to 34.3 kb (segment O). EM analysis indicated that MdBV virions contain a single nucleocapsid that encapsidates one circular DNA of variable size. We developed a semi-quantitative real-time PCR assay using SYBR Green I. This assay indicated that five (J, O, H, N and B) segments of the MdBV genome accounted for more than 60% of the viral DNAs in calyx fluid. Estimates of relative segment abundance using our real-time PCR assay were also very similar to DNA size distributions determined from micrographs. Analysis of parasitized Pseudoplusia includens larvae indicated that copy number of MdBV segments C, B and J varied between hosts but their relative abundance within a host was virtually identical to their abundance in calyx fluid. Among-tissue assays indicated that each viral segment was most abundant in hemocytes and least abundant in salivary glands. However, the relative abundance of each segment to one another was similar in all tissues. We also found no clear relationship between MdBV segment and transcript abundance in hemocytes and fat body.« less

Segmentation of anterior cruciate ligament in knee MR images using graph cuts with patient-specific shape constraints and label refinement.

PubMed

Lee, Hansang; Hong, Helen; Kim, Junmo

2014-12-01

We propose a graph-cut-based segmentation method for the anterior cruciate ligament (ACL) in knee MRI with a novel shape prior and label refinement. As the initial seeds for graph cuts, candidates for the ACL and the background are extracted from knee MRI roughly by means of adaptive thresholding with Gaussian mixture model fitting. The extracted ACL candidate is segmented iteratively by graph cuts with patient-specific shape constraints. Two shape constraints termed fence and neighbor costs are suggested such that the graph cuts prevent any leakage into adjacent regions with similar intensity. The segmented ACL label is refined by means of superpixel classification. Superpixel classification makes the segmented label propagate into missing inhomogeneous regions inside the ACL. In the experiments, the proposed method segmented the ACL with Dice similarity coefficient of 66.47±7.97%, average surface distance of 2.247±0.869, and root mean squared error of 3.538±1.633, which increased the accuracy by 14.8%, 40.3%, and 37.6% from the Boykov model, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Oman Ophiolite Structural Constraints Complement Models of Crustal Accretion at the EAST Pacific RISE

NASA Astrophysics Data System (ADS)

Nicolas, A. A.; Jousselin, D.; Boudier, F. I.

2014-12-01

This review documents significant similarities between East Pacific Rise (EPR), especially EPR at 9°-10°N and the Oman ophiolites. Both share comparable fast spreading rates, size and their dominant source of information that is mainly geophysical in EPR and structural in Oman. In these respects, they are remarkably complementary. Mantle upwelling zones at the EPR and mantle diapirs in Oman have a similar size and spacing. They punctually introduce basaltic melt and heat in the accreting crust, thus controlling elementary segments structure and activity. A tent-shaped magma chamber fits onto the diapir head, the top of which is a Mantle Transition Zone (MTZ) that stores, modifies, and injects the modified melt into the upper Axial Melt Lens (AML) beneath the lid. This MTZ-AML connection is central in crustal accretion, as documented in Oman. Heat from the diapir is captured above the Moho by the magma chamber and escapes through its walls, into a thin thermal boundary layer that bounds the chamber. Beyond, seawater at lower temperatures feeds smokers on the seafloor.

Temporal Organization of Sound Information in Auditory Memory.

PubMed

Song, Kun; Luo, Huan

2017-01-01

Memory is a constructive and organizational process. Instead of being stored with all the fine details, external information is reorganized and structured at certain spatiotemporal scales. It is well acknowledged that time plays a central role in audition by segmenting sound inputs into temporal chunks of appropriate length. However, it remains largely unknown whether critical temporal structures exist to mediate sound representation in auditory memory. To address the issue, here we designed an auditory memory transferring study, by combining a previously developed unsupervised white noise memory paradigm with a reversed sound manipulation method. Specifically, we systematically measured the memory transferring from a random white noise sound to its locally temporal reversed version on various temporal scales in seven experiments. We demonstrate a U-shape memory-transferring pattern with the minimum value around temporal scale of 200 ms. Furthermore, neither auditory perceptual similarity nor physical similarity as a function of the manipulating temporal scale can account for the memory-transferring results. Our results suggest that sounds are not stored with all the fine spectrotemporal details but are organized and structured at discrete temporal chunks in long-term auditory memory representation.

In Vivo Imaging of Human Cone Photoreceptor Inner Segments

PubMed Central

Scoles, Drew; Sulai, Yusufu N.; Langlo, Christopher S.; Fishman, Gerald A.; Curcio, Christine A.; Carroll, Joseph; Dubra, Alfredo

2014-01-01

Purpose. An often overlooked prerequisite to cone photoreceptor gene therapy development is residual photoreceptor structure that can be rescued. While advances in adaptive optics (AO) retinal imaging have recently enabled direct visualization of individual cone and rod photoreceptors in the living human retina, these techniques largely detect strongly directionally-backscattered (waveguided) light from normal intact photoreceptors. This represents a major limitation in using existing AO imaging to quantify structure of remnant cones in degenerating retina. Methods. Photoreceptor inner segment structure was assessed with a novel AO scanning light ophthalmoscopy (AOSLO) differential phase technique, that we termed nonconfocal split-detector, in two healthy subjects and four subjects with achromatopsia. Ex vivo preparations of five healthy donor eyes were analyzed for comparison of inner segment diameter to that measured in vivo with split-detector AOSLO. Results. Nonconfocal split-detector AOSLO reveals the photoreceptor inner segment with or without the presence of a waveguiding outer segment. The diameter of inner segments measured in vivo is in good agreement with histology. A substantial number of foveal and parafoveal cone photoreceptors with apparently intact inner segments were identified in patients with the inherited disease achromatopsia. Conclusions. The application of nonconfocal split-detector to emerging human gene therapy trials will improve the potential of therapeutic success, by identifying patients with sufficient retained photoreceptor structure to benefit the most from intervention. Additionally, split-detector imaging may be useful for studies of other retinal degenerations such as AMD, retinitis pigmentosa, and choroideremia where the outer segment is lost before the remainder of the photoreceptor cell. PMID:24906859

Incorporating priors on expert performance parameters for segmentation validation and label fusion: a maximum a posteriori STAPLE

PubMed Central

Commowick, Olivier; Warfield, Simon K

2010-01-01

In order to evaluate the quality of segmentations of an image and assess intra- and inter-expert variability in segmentation performance, an Expectation Maximization (EM) algorithm for Simultaneous Truth And Performance Level Estimation (STAPLE) was recently developed. This algorithm, originally presented for segmentation validation, has since been used for many applications, such as atlas construction and decision fusion. However, the manual delineation of structures of interest is a very time consuming and burdensome task. Further, as the time required and burden of manual delineation increase, the accuracy of the delineation is decreased. Therefore, it may be desirable to ask the experts to delineate only a reduced number of structures or the segmentation of all structures by all experts may simply not be achieved. Fusion from data with some structures not segmented by each expert should be carried out in a manner that accounts for the missing information. In other applications, locally inconsistent segmentations may drive the STAPLE algorithm into an undesirable local optimum, leading to misclassifications or misleading experts performance parameters. We present a new algorithm that allows fusion with partial delineation and which can avoid convergence to undesirable local optima in the presence of strongly inconsistent segmentations. The algorithm extends STAPLE by incorporating prior probabilities for the expert performance parameters. This is achieved through a Maximum A Posteriori formulation, where the prior probabilities for the performance parameters are modeled by a beta distribution. We demonstrate that this new algorithm enables dramatically improved fusion from data with partial delineation by each expert in comparison to fusion with STAPLE. PMID:20879379

Incorporating priors on expert performance parameters for segmentation validation and label fusion: a maximum a posteriori STAPLE.

PubMed

Commowick, Olivier; Warfield, Simon K

2010-01-01

In order to evaluate the quality of segmentations of an image and assess intra- and inter-expert variability in segmentation performance, an Expectation Maximization (EM) algorithm for Simultaneous Truth And Performance Level Estimation (STAPLE) was recently developed. This algorithm, originally presented for segmentation validation, has since been used for many applications, such as atlas construction and decision fusion. However, the manual delineation of structures of interest is a very time consuming and burdensome task. Further, as the time required and burden of manual delineation increase, the accuracy of the delineation is decreased. Therefore, it may be desirable to ask the experts to delineate only a reduced number of structures or the segmentation of all structures by all experts may simply not be achieved. Fusion from data with some structures not segmented by each expert should be carried out in a manner that accounts for the missing information. In other applications, locally inconsistent segmentations may drive the STAPLE algorithm into an undesirable local optimum, leading to misclassifications or misleading experts performance parameters. We present a new algorithm that allows fusion with partial delineation and which can avoid convergence to undesirable local optima in the presence of strongly inconsistent segmentations. The algorithm extends STAPLE by incorporating prior probabilities for the expert performance parameters. This is achieved through a Maximum A Posteriori formulation, where the prior probabilities for the performance parameters are modeled by a beta distribution. We demonstrate that this new algorithm enables dramatically improved fusion from data with partial delineation by each expert in comparison to fusion with STAPLE.

Automated method for structural segmentation of nasal airways based on cone beam computed tomography

NASA Astrophysics Data System (ADS)

Tymkovych, Maksym Yu.; Avrunin, Oleg G.; Paliy, Victor G.; Filzow, Maksim; Gryshkov, Oleksandr; Glasmacher, Birgit; Omiotek, Zbigniew; DzierŻak, RóŻa; Smailova, Saule; Kozbekova, Ainur

2017-08-01

The work is dedicated to the segmentation problem of human nasal airways using Cone Beam Computed Tomography. During research, we propose a specialized approach of structured segmentation of nasal airways. That approach use spatial information, symmetrisation of the structures. The proposed stages can be used for construction a virtual three dimensional model of nasal airways and for production full-scale personalized atlases. During research we build the virtual model of nasal airways, which can be used for construction specialized medical atlases and aerodynamics researches.

What limits the achievable areal densities of large aperture space telescopes?

NASA Astrophysics Data System (ADS)

Peterson, Lee D.; Hinkle, Jason D.

2005-08-01

This paper examines requirements trades involving areal density for large space telescope mirrors. A segmented mirror architecture is used to define a quantitative example that leads to relevant insight about the trades. In this architecture, the mirror consists of segments of non-structural optical elements held in place by a structural truss that rests behind the segments. An analysis is presented of the driving design requirements for typical on-orbit loads and ground-test loads. It is shown that the driving on-orbit load would be the resonance of the lowest mode of the mirror by a reaction wheel static unbalance. The driving ground-test load would be dynamics due to ground-induced random vibration. Two general conclusions are derived from these results. First, the areal density that can be allocated to the segments depends on the depth allocated to the structure. More depth in the structure allows the allocation of more mass to the segments. This, however, leads to large structural depth that might be a significant development challenge. Second, the requirement for ground-test-ability results in an order of magnitude or more depth in the structure than is required by the on-orbit loads. This leads to the proposition that avoiding ground test as a driving requirement should be a fundamental technology on par with the provision of deployable depth. Both are important structural challenges for these future systems.

Structural controls on the spatial distribution and geochemical composition of volcanism in a continental rift zone; an example from Owens Valley, eastern California

NASA Astrophysics Data System (ADS)

Haproff, P. J.; Yin, A.

2014-12-01

Bimodal volcanism is common in continental rift zones. Structural controls to the emplacement and compositions of magmas, however, are not well understood. To address this issue, we examine the location, age, and geochemistry of active volcanic centers, and geometry and kinematics of rift-related faults across the active transtensional Owens Valley rift zone. Building on existing studies, we postulate that the spatial distribution and geochemical composition of volcanism are controlled by motion along rift-bounding fault systems. Along-strike variation in fault geometry and characteristics of active volcanism allow us to divide Owens Valley into three segments: southern, northern, and central. The southern segment of Owens Valley is a simple shear, asymmetric rift bounded to the west by the east-dipping Sierra Nevada frontal fault (SNFF). Active vents of Coso volcanic field are distributed along the eastern rift shoulder and characterized by the eruption of bimodal lavas. The SNFF within this segment is low-angle and penetrates through the lithosphere and into the ductile asthenosphere, allowing for mantle-derived magma to migrate across the weakest part of the fault zone beneath the eastern rift shoulder. Magma thermally weakens wall rocks and eventually stalls in the crust where the melt develops a greater felsic component prior to eruption. The northern segment of Owens Valley displays similar structural geometry, as the west-dipping White Mountains fault (WMF) is listric at depth and offsets the crust and mantle lithosphere, allowing for vertical transport of magma and reservoir emplacement within the crust. Bimodal lavas periodically erupted in the Long Valley Caldera region along the western rift shoulder. The central segment of Owens Valley is a pure shear, symmetric graben generated by motion along the SNFF and WMF. The subvertical, right-slip Owens Valley fault (OVF) strikes along the axis of the valley and penetrates through the lithosphere into the asthenosphere. Volcanic centers of Big Pine volcanic field are located along the trace of the OVF and characterized by mafic eruptions. The OVF is interpreted to provide a subvertical conduit for asthenospheric magma to migrate across the LAB and Moho and erupt on the rift surface without significant contamination with felsic crust.

Synthesis of hollow spherical calcium phosphate nanoparticles using polymeric nanotemplates

NASA Astrophysics Data System (ADS)

Tjandra, Wiliana; Ravi, Palaniswamy; Yao, Jia; Tam, Kam C.

2006-12-01

Poly(methylmethacrylate)-block-poly(methacrylic acid) (PMMA-b-PMAA) copolymer was synthesized by an atom transfer radical polymerization (ATRP) technique. The block copolymer was employed as a template for the controlled precipitation of calcium phosphate from aqueous solution at different pH values. A Ca2+ ion selective electrode was used to study the interactions between Ca2+ ions and the polymer, which indicated a possible weak interaction between Ca2+ and un-ionized MAA segments at pH~4.0 in addition to electrostatic interaction between Ca2+ and ionized MAA segments at higher pH. An interesting structure representing that of a superstructure consisting of hybrid nano-filaments was observed by the transmission electron microscope at pH~4.0. The filaments originated from a core of similar size to primary polymer aggregates, suggesting that cooperative interactions at a local level between dissolving calcium phosphate clusters and disassembling polymer segments are responsible for the secondary growth process. A hollow spherical morphology was obtained at pH~7.0 and 9.0. Such calcium phosphate/polymer monohybrids with complex morphologies are interesting and might be useful as novel drug delivery carriers, ceramics precursors, reinforcing fillers or biomedical implants.

Tissue classification and segmentation of pressure injuries using convolutional neural networks.

PubMed

Zahia, Sofia; Sierra-Sosa, Daniel; Garcia-Zapirain, Begonya; Elmaghraby, Adel

2018-06-01

This paper presents a new approach for automatic tissue classification in pressure injuries. These wounds are localized skin damages which need frequent diagnosis and treatment. Therefore, a reliable and accurate systems for segmentation and tissue type identification are needed in order to achieve better treatment results. Our proposed system is based on a Convolutional Neural Network (CNN) devoted to performing optimized segmentation of the different tissue types present in pressure injuries (granulation, slough, and necrotic tissues). A preprocessing step removes the flash light and creates a set of 5x5 sub-images which are used as input for the CNN network. The network output will classify every sub-image of the validation set into one of the three classes studied. The metrics used to evaluate our approach show an overall average classification accuracy of 92.01%, an average total weighted Dice Similarity Coefficient of 91.38%, and an average precision per class of 97.31% for granulation tissue, 96.59% for necrotic tissue, and 77.90% for slough tissue. Our system has been proven to make recognition of complicated structures in biomedical images feasible. Copyright © 2018 Elsevier B.V. All rights reserved.

Delineation of major geologic structures in Turkey using SIR-B data

NASA Technical Reports Server (NTRS)

Toksoz, M. N.; Pettengill, G. H.; Ford, P.; Gulen, L.

1984-01-01

Shuttle Imaging Radar-B (SIR-B) images of well mapped segments of major faults, such as the North Anatolian Fault (NAF) and East Anatolian Fault (EAF) will be studied to identify the prominent signatures that characterize the fault zones for those specific regions. The information will be used to delineate the unmapped fault zones in areas with similar geological and geomorphological properties. The data obtained from SIR-B images will be compared and correlated with the LANDSAT thematic mapper and seismicity alignments based on well constrained earthquake epicenters.

A Three-Dimensional Atlas of the Honeybee Neck

PubMed Central

Berry, Richard P.; Ibbotson, Michael R.

2010-01-01

Three-dimensional digital atlases are rapidly becoming indispensible in modern biology. We used serial sectioning combined with manual registration and segmentation of images to develop a comprehensive and detailed three-dimensional atlas of the honeybee head-neck system. This interactive atlas includes skeletal structures of the head and prothorax, the neck musculature, and the nervous system. The scope and resolution of the model exceeds atlases previously developed on similar sized animals, and the interactive nature of the model provides a far more accessible means of interpreting and comprehending insect anatomy and neuroanatomy. PMID:20520729

Stress Analysis of Bolted, Segmented Cylindrical Shells Exhibiting Flange Mating-Surface Waviness

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Phillips, Dawn R.; Raju, Ivatury S.

2009-01-01

Bolted, segmented cylindrical shells are a common structural component in many engineering systems especially for aerospace launch vehicles. Segmented shells are often needed due to limitations of manufacturing capabilities or transportation issues related to very long, large-diameter cylindrical shells. These cylindrical shells typically have a flange or ring welded to opposite ends so that shell segments can be mated together and bolted to form a larger structural system. As the diameter of these shells increases, maintaining strict fabrication tolerances for the flanges to be flat and parallel on a welded structure is an extreme challenge. Local fit-up stresses develop in the structure due to flange mating-surface mismatch (flange waviness). These local stresses need to be considered when predicting a critical initial flaw size. Flange waviness is one contributor to the fit-up stress state. The present paper describes the modeling and analysis effort to simulate fit-up stresses due to flange waviness in a typical bolted, segmented cylindrical shell. Results from parametric studies are presented for various flange mating-surface waviness distributions and amplitudes.

A volumetric pulmonary CT segmentation method with applications in emphysema assessment

NASA Astrophysics Data System (ADS)

Silva, José Silvestre; Silva, Augusto; Santos, Beatriz S.

2006-03-01

A segmentation method is a mandatory pre-processing step in many automated or semi-automated analysis tasks such as region identification and densitometric analysis, or even for 3D visualization purposes. In this work we present a fully automated volumetric pulmonary segmentation algorithm based on intensity discrimination and morphologic procedures. Our method first identifies the trachea as well as primary bronchi and then the pulmonary region is identified by applying a threshold and morphologic operations. When both lungs are in contact, additional procedures are performed to obtain two separated lung volumes. To evaluate the performance of the method, we compared contours extracted from 3D lung surfaces with reference contours, using several figures of merit. Results show that the worst case generally occurs at the middle sections of high resolution CT exams, due the presence of aerial and vascular structures. Nevertheless, the average error is inferior to the average error associated with radiologist inter-observer variability, which suggests that our method produces lung contours similar to those drawn by radiologists. The information created by our segmentation algorithm is used by an identification and representation method in pulmonary emphysema that also classifies emphysema according to its severity degree. Two clinically proved thresholds are applied which identify regions with severe emphysema, and with highly severe emphysema. Based on this thresholding strategy, an application for volumetric emphysema assessment was developed offering new display paradigms concerning the visualization of classification results. This framework is easily extendable to accommodate other classifiers namely those related with texture based segmentation as it is often the case with interstitial diseases.

Semi-automated segmentation of solid and GGO nodules in lung CT images using vessel-likelihood derived from local foreground structure

NASA Astrophysics Data System (ADS)

Yaguchi, Atsushi; Okazaki, Tomoya; Takeguchi, Tomoyuki; Matsumoto, Sumiaki; Ohno, Yoshiharu; Aoyagi, Kota; Yamagata, Hitoshi

2015-03-01

Reflecting global interest in lung cancer screening, considerable attention has been paid to automatic segmentation and volumetric measurement of lung nodules on CT. Ground glass opacity (GGO) nodules deserve special consideration in this context, since it has been reported that they are more likely to be malignant than solid nodules. However, due to relatively low contrast and indistinct boundaries of GGO nodules, segmentation is more difficult for GGO nodules compared with solid nodules. To overcome this difficulty, we propose a method for accurately segmenting not only solid nodules but also GGO nodules without prior information about nodule types. First, the histogram of CT values in pre-extracted lung regions is modeled by a Gaussian mixture model and a threshold value for including high-attenuation regions is computed. Second, after setting up a region of interest around the nodule seed point, foreground regions are extracted by using the threshold and quick-shift-based mode seeking. Finally, for separating vessels from the nodule, a vessel-likelihood map derived from elongatedness of foreground regions is computed, and a region growing scheme starting from the seed point is applied to the map with the aid of fast marching method. Experimental results using an anthropomorphic chest phantom showed that our method yielded generally lower volumetric measurement errors for both solid and GGO nodules compared with other methods reported in preceding studies conducted using similar technical settings. Also, our method allowed reasonable segmentation of GGO nodules in low-dose images and could be applied to clinical CT images including part-solid nodules.

Evaluation and optimization of the parameters used in multiple-atlas-based segmentation of prostate cancers in radiation therapy.

PubMed

Wong, Wicger K H; Leung, Lucullus H T; Kwong, Dora L W

2016-01-01

To evaluate and optimize the parameters used in multiple-atlas-based segmentation of prostate cancers in radiation therapy. A retrospective study was conducted, and the accuracy of the multiple-atlas-based segmentation was tested on 30 patients. The effect of library size (LS), number of atlases used for contour averaging and the contour averaging strategy were also studied. The autogenerated contours were compared with the manually drawn contours. Dice similarity coefficient (DSC) and Hausdorff distance were used to evaluate the segmentation agreement. Mixed results were found between simultaneous truth and performance level estimation (STAPLE) and majority vote (MV) strategies. Multiple-atlas approaches were relatively insensitive to LS. A LS of ten was adequate, and further increase in the LS only showed insignificant gain. Multiple atlas performed better than single atlas for most of the time. Using more atlases did not guarantee better performance, with five atlases performing better than ten atlases. With our recommended setting, the median DSC for the bladder, rectum, prostate, seminal vesicle and femurs was 0.90, 0.77, 0.84, 0.56 and 0.95, respectively. Our study shows that multiple-atlas-based strategies have better accuracy than single-atlas approach. STAPLE is preferred, and a LS of ten is adequate for prostate cases. Using five atlases for contour averaging is recommended. The contouring accuracy of seminal vesicle still needs improvement, and manual editing is still required for the other structures. This article provides a better understanding of the influence of the parameters used in multiple-atlas-based segmentation of prostate cancers.

Segmental Isotopic Labeling of Proteins for Nuclear Magnetic Resonance

PubMed Central

Dongsheng, Liu; Xu, Rong; Cowburn, David

2009-01-01

Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as one of the principle techniques of structural biology. It is not only a powerful method for elucidating the 3D structures under near physiological conditions, but also a convenient method for studying protein-ligand interactions and protein dynamics. A major drawback of macromolecular NMR is its size limitation caused by slower tumbling rates and greater complexity of the spectra as size increases. Segmental isotopic labeling allows specific segment(s) within a protein to be selectively examined by NMR thus significantly reducing the spectral complexity for large proteins and allowing a variety of solution-based NMR strategies to be applied. Two related approaches are generally used in the segmental isotopic labeling of proteins: expressed protein ligation and protein trans-splicing. Here we describe the methodology and recent application of expressed protein ligation and protein trans-splicing for NMR structural studies of proteins and protein complexes. We also describe the protocol used in our lab for the segmental isotopic labeling of a 50 kDa protein Csk (C-terminal Src Kinase) using expressed protein ligation methods. PMID:19632474

Deep convolutional neural network for prostate MR segmentation

NASA Astrophysics Data System (ADS)

Tian, Zhiqiang; Liu, Lizhi; Fei, Baowei

2017-03-01

Automatic segmentation of the prostate in magnetic resonance imaging (MRI) has many applications in prostate cancer diagnosis and therapy. We propose a deep fully convolutional neural network (CNN) to segment the prostate automatically. Our deep CNN model is trained end-to-end in a single learning stage based on prostate MR images and the corresponding ground truths, and learns to make inference for pixel-wise segmentation. Experiments were performed on our in-house data set, which contains prostate MR images of 20 patients. The proposed CNN model obtained a mean Dice similarity coefficient of 85.3%+/-3.2% as compared to the manual segmentation. Experimental results show that our deep CNN model could yield satisfactory segmentation of the prostate.

Study on the bearing capacity of embedded chute on shield tunnel segment

NASA Astrophysics Data System (ADS)

Fanzhen, Zhang; Jie, Bu; Zhibo, Su; Qigao, Hu

2018-05-01

The method of perforation and steel implantation is often used to fix and install pipeline, cables and other facilities in the shield tunnel, which would inevitably do damage to the precast segments. In order to reduce the damage and the resulting safety and durability problems, embedded chute was set at the equipment installation in one shield tunnel. Finite element models of segment concrete and steel are established in this paper. When water-soil pressure calculated separately and calculated together, the mechanical property of segment is studied. The bearing capacity and deformation of segment are analysed before and after embedding the chute. Research results provide a reference for similar shield tunnel segment engineering.

Enhanced Mantle Upwelling/Melting Caused Segment Propagation, Oceanic Core Complex Die Off, and the Death of a Transform Fault: The Mid-Atlantic Ridge at 21.5°N

NASA Astrophysics Data System (ADS)

Dannowski, A.; Morgan, J. P.; Grevemeyer, I.; Ranero, C. R.

2018-02-01

Crustal structure provides the key to understand the interplay of magmatism and tectonism, while oceanic crust is constructed at Mid-Ocean Ridges (MORs). At slow spreading rates, magmatic processes dominate central areas of MOR segments, whereas segment ends are highly tectonized. The TAMMAR segment at the Mid-Atlantic Ridge (MAR) between 21°25'N and 22°N is a magmatically active segment. At 4.5 Ma this segment started to propagate south, causing the termination of the transform fault at 21°40'N. This stopped long-lived detachment faulting and caused the migration of the ridge offset to the south. Here a segment center with a high magmatic budget has replaced a transform fault region with limited magma supply. We present results from seismic refraction profiles that mapped the crustal structure across the ridge crest of the TAMMAR segment. Seismic data yield crustal structure changes at the segment center as a function of melt supply. Seismic Layer 3 underwent profound changes in thickness and became rapidly thicker 5 Ma. This correlates with the observed "Bull's Eye" gravimetric anomaly in that region. Our observations support a temporal change from thick lithosphere with oceanic core complex formation and transform faulting to thin lithosphere with focused mantle upwelling and segment growth. Temporal changes in crustal construction are connected to variations in the underlying mantle. We propose that there is a link between the neighboring segments at a larger scale within the asthenosphere, to form a long, highly magmatically active macrosegment, here called the TAMMAR-Kane Macrosegment.

Vertical stratification of forest canopy for segmentation of understory trees within small-footprint airborne LiDAR point clouds

NASA Astrophysics Data System (ADS)

Hamraz, Hamid; Contreras, Marco A.; Zhang, Jun

2017-08-01

Airborne LiDAR point cloud representing a forest contains 3D data, from which vertical stand structure even of understory layers can be derived. This paper presents a tree segmentation approach for multi-story stands that stratifies the point cloud to canopy layers and segments individual tree crowns within each layer using a digital surface model based tree segmentation method. The novelty of the approach is the stratification procedure that separates the point cloud to an overstory and multiple understory tree canopy layers by analyzing vertical distributions of LiDAR points within overlapping locales. The procedure does not make a priori assumptions about the shape and size of the tree crowns and can, independent of the tree segmentation method, be utilized to vertically stratify tree crowns of forest canopies. We applied the proposed approach to the University of Kentucky Robinson Forest - a natural deciduous forest with complex and highly variable terrain and vegetation structure. The segmentation results showed that using the stratification procedure strongly improved detecting understory trees (from 46% to 68%) at the cost of introducing a fair number of over-segmented understory trees (increased from 1% to 16%), while barely affecting the overall segmentation quality of overstory trees. Results of vertical stratification of the canopy showed that the point density of understory canopy layers were suboptimal for performing a reasonable tree segmentation, suggesting that acquiring denser LiDAR point clouds would allow more improvements in segmenting understory trees. As shown by inspecting correlations of the results with forest structure, the segmentation approach is applicable to a variety of forest types.

Safety impacts of Design Exceptions in Utah

DOT National Transportation Integrated Search

2012-06-01

The objective of this research was to compare safety, measured by expected crash frequency and severity, on road segments where design exceptions were approved and constructed to similar road segments where no design exceptions were approved or const...

Safety Impacts of Design Exceptions in Utah

DOT National Transportation Integrated Search

2012-08-01

The objective of this research was to compare safety, measured by expected crash frequency and severity, on road segments where design exceptions were approved and constructed to similar road segments where no design exceptions were approved or const...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Qingqing; Li, Huilin; Wang, Tong

Perfringolysin O (PFO) is a transmembrane (TM) β-barrel protein that inserts into mammalian cell membranes. Once inserted into membranes, PFO assembles into pore-forming oligomers containing 30–50 PFO monomers. These form a pore of up to 300 Å, far exceeding the size of most other proteinaceous pores. In this study, we found that altering PFO TM segment length can alter the size of PFO pores. A PFO mutant with lengthened TM segments oligomerized to a similar extent as wild-type PFO, and exhibited pore-forming activity and a pore size very similar to wild-type PFO as measured by electron microscopy and a leakagemore » assay. In contrast, PFO with shortened TM segments exhibited a large reduction in pore-forming activity and pore size. This suggests that the interaction between TM segments can greatly affect the size of pores formed by TM β-barrel proteins. PFO may be a promising candidate for engineering pore size for various applications.« less

Joint volumetric extraction and enhancement of vasculature from low-SNR 3-D fluorescence microscopy images.

PubMed

Almasi, Sepideh; Ben-Zvi, Ayal; Lacoste, Baptiste; Gu, Chenghua; Miller, Eric L; Xu, Xiaoyin

2017-03-01

To simultaneously overcome the challenges imposed by the nature of optical imaging characterized by a range of artifacts including space-varying signal to noise ratio (SNR), scattered light, and non-uniform illumination, we developed a novel method that segments the 3-D vasculature directly from original fluorescence microscopy images eliminating the need for employing pre- and post-processing steps such as noise removal and segmentation refinement as used with the majority of segmentation techniques. Our method comprises two initialization and constrained recovery and enhancement stages. The initialization approach is fully automated using features derived from bi-scale statistical measures and produces seed points robust to non-uniform illumination, low SNR, and local structural variations. This algorithm achieves the goal of segmentation via design of an iterative approach that extracts the structure through voting of feature vectors formed by distance, local intensity gradient, and median measures. Qualitative and quantitative analysis of the experimental results obtained from synthetic and real data prove the effcacy of this method in comparison to the state-of-the-art enhancing-segmenting methods. The algorithmic simplicity, freedom from having a priori probabilistic information about the noise, and structural definition gives this algorithm a wide potential range of applications where i.e. structural complexity significantly complicates the segmentation problem.

Structural Segmentation of Toru Takemitsu's Piece, Itinerant, by Advanced Level Music Graduate Students.

PubMed

Ordoñana, Jose A; Laucirica, Ana

2017-01-01

This work attempts to study the way higher music graduate students segment a contemporary music work, Itinerant, and to understand the influence of musical feature on segmentation. It attempts to test the theory stating that saliences contribute to organising the music surface. The 42 students listened to the work several times and, in real time, they were requested to indicate the places on the score where they perceived structural boundaries. This work is characterised by its linearity, which could hinder identification of saliences and thereby, the establishment of structural boundaries. The participants show stability in the points of segmentation chosen. The results show significant coincidences among the participants in strategic places of the work, which leads us to conclude, in line with other researches, although in a work with different characteristics, that listeners can find a structural organisation in contemporary music that could allow them to understand it.

Concepts and analysis for precision segmented reflector and feed support structures

NASA Technical Reports Server (NTRS)

Miller, Richard K.; Thomson, Mark W.; Hedgepeth, John M.

1990-01-01

Several issues surrounding the design of a large (20-meter diameter) Precision Segmented Reflector are investigated. The concerns include development of a reflector support truss geometry that will permit deployment into the required doubly-curved shape without significant member strains. For deployable and erectable reflector support trusses, the reduction of structural redundancy was analyzed to achieve reduced weight and complexity for the designs. The stiffness and accuracy of such reduced member trusses, however, were found to be affected to a degree that is unexpected. The Precision Segmented Reflector designs were developed with performance requirements that represent the Reflector application. A novel deployable sunshade concept was developed, and a detailed parametric study of various feed support structural concepts was performed. The results of the detailed study reveal what may be the most desirable feed support structure geometry for Precision Segmented Reflector/Large Deployable Reflector applications.

SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Y; Olsen, J.; Parikh, P.

2014-06-01

Purpose: Evaluate commonly used segmentation algorithms on a commercially available real-time MR image guided radiotherapy (MR-IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy. Methods: MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on-board MR imaging system and an imaging protocol used during MR-IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE),more » along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground-truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison. Results: In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD-LSE cannot consistently segment a liver tumor and the duodenum. Conclusion: The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR-IGRT. Future studies include a selection of conformal segmentation methods based on image/organ-specific information, different filtering methods and their influences on the segmentation results. Parag Parikh receives research grant from ViewRay. Sasa Mutic has consulting and research agreements with ViewRay. Yanle Hu receives travel reimbursement from ViewRay. Iwan Kawrakow and James Dempsey are ViewRay employees.« less

Structures of the transmembrane helices of the G-protein coupled receptor, rhodopsin.

PubMed

Katragadda, M; Chopra, A; Bennett, M; Alderfer, J L; Yeagle, P L; Albert, A D

2001-07-01

An hypothesis is tested that individual peptides corresponding to the transmembrane helices of the membrane protein, rhodopsin, would form helices in solution similar to those in the native protein. Peptides containing the sequences of helices 1, 4 and 5 of rhodopsin were synthesized. Two peptides, with overlapping sequences at their termini, were synthesized to cover each of the helices. The peptides from helix 1 and helix 4 were helical throughout most of their length. The N- and C-termini of all the peptides were disordered and proline caused opening of the helical structure in both helix 1 and helix 4. The peptides from helix 5 were helical in the middle segment of each peptide, with larger disordered regions in the N- and C-termini than for helices 1 and 4. These observations show that there is a strong helical propensity in the amino acid sequences corresponding to the transmembrane domain of this G-protein coupled receptor. In the case of the peptides from helix 4, it was possible to superimpose the structures of the overlapping sequences to produce a construct covering the whole of the sequence of helix 4 of rhodopsin. As similar superposition for the peptides from helix 1 also produced a construct, but somewhat less successfully because of the disordering in the region of sequence overlap. This latter problem was more severe for helix 5 and therefore a single peptide was synthesized for the entire sequence of this helix, and its structure determined. It proved to be helical throughout. Comparison of all these structures with the recent crystal structure of rhodopsin revealed that the peptide structures mimicked the structures seen in the whole protein. Thus similar studies of peptides may provide useful information on the secondary structure of other transmembrane proteins built around helical bundles.

Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring

PubMed Central

Moghbel, Mehrdad; Mashohor, Syamsiah; Mahmud, Rozi; Saripan, M. Iqbal Bin

2016-01-01

Segmentation of liver tumors from Computed Tomography (CT) and tumor burden analysis play an important role in the choice of therapeutic strategies for liver diseases and treatment monitoring. In this paper, a new segmentation method for liver tumors from contrast-enhanced CT imaging is proposed. As manual segmentation of tumors for liver treatment planning is both labor intensive and time-consuming, a highly accurate automatic tumor segmentation is desired. The proposed framework is fully automatic requiring no user interaction. The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. The accuracy of the proposed method was validated using a clinical liver dataset containing one of the highest numbers of tumors utilized for liver tumor segmentation containing 127 tumors in total with further validation of the results by a consultant radiologist. The proposed method was able to achieve one of the highest accuracies reported in the literature for liver tumor segmentation compared to other segmentation methods with a mean overlap error of 22.78 % and dice similarity coefficient of 0.75 in 3Dircadb dataset and a mean overlap error of 15.61 % and dice similarity coefficient of 0.81 in MIDAS dataset. The proposed method was able to outperform most other tumor segmentation methods reported in the literature while representing an overlap error improvement of 6 % compared to one of the best performing automatic methods in the literature. The proposed framework was able to provide consistently accurate results considering the number of tumors and the variations in tumor contrast enhancements and tumor appearances while the tumor burden was estimated with a mean error of 0.84 % in 3Dircadb dataset. PMID:27540353

Segmental expression of Pax3/7 and engrailed homologs in tardigrade development.

PubMed

Gabriel, Willow N; Goldstein, Bob

2007-06-01

How morphological diversity arises through evolution of gene sequence is a major question in biology. In Drosophila, the genetic basis for body patterning and morphological segmentation has been studied intensively. It is clear that some of the genes in the Drosophila segmentation program are functioning similarly in certain other taxa, although many questions remain about when these gene functions arose and which taxa use these genes similarly to establish diverse body plans. Tardigrades are an outgroup to arthropods in the Ecdysozoa and, as such, can provide insight into how gene functions have evolved among the arthropods and their close relatives. We developed immunostaining methods for tardigrade embryos, and we used cross-reactive antibodies to investigate the expression of homologs of the pair-rule gene paired (Pax3/7) and the segment polarity gene engrailed in the tardigrade Hypsibius dujardini. We find that in H. dujardini embryos, Pax3/7 protein localizes not in a pair-rule pattern but in a segmentally iterated pattern, after the segments are established, in regions of the embryo where neurons later arise. Engrailed protein localizes in the posterior ectoderm of each segment before ectodermal segmentation is apparent. Together with previous results from others, our data support the conclusions that the pair-rule function of Pax3/7 is specific to the arthropods, that some of the ancient functions of Pax3/7 and Engrailed in ancestral bilaterians may have been in neurogenesis, and that Engrailed may have a function in establishing morphological boundaries between segments that is conserved at least among the Panarthropoda.

Iterative cross section sequence graph for handwritten character segmentation.

PubMed

Dawoud, Amer

2007-08-01

The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.

Short segment search method for phylogenetic analysis using nested sliding windows

NASA Astrophysics Data System (ADS)

Iskandar, A. A.; Bustamam, A.; Trimarsanto, H.

2017-10-01

To analyze phylogenetics in Bioinformatics, coding DNA sequences (CDS) segment is needed for maximal accuracy. However, analysis by CDS cost a lot of time and money, so a short representative segment by CDS, which is envelope protein segment or non-structural 3 (NS3) segment is necessary. After sliding window is implemented, a better short segment than envelope protein segment and NS3 is found. This paper will discuss a mathematical method to analyze sequences using nested sliding window to find a short segment which is representative for the whole genome. The result shows that our method can find a short segment which more representative about 6.57% in topological view to CDS segment than an Envelope segment or NS3 segment.

A Multi-Anatomical Retinal Structure Segmentation System for Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding

PubMed Central

Elleithy, Khaled; Elleithy, Abdelrahman

2018-01-01

Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue for detecting a variety of hidden health issues including pre-diabetes and diabetes. Through the process of clinical diagnosis and prognosis; ophthalmologists rely heavily on the binary segmented version of retina fundus image; where the accuracy of segmented vessels, optic disc, and abnormal lesions extremely affects the diagnosis accuracy which in turn affect the subsequent clinical treatment steps. This paper proposes an automated retinal fundus image segmentation system composed of three segmentation subsystems follow same core segmentation algorithm. Despite of broad difference in features and characteristics; retinal vessels, optic disc, and exudate lesions are extracted by each subsystem without the need for texture analysis or synthesis. For sake of compact diagnosis and complete clinical insight, our proposed system can detect these anatomical structures in one session with high accuracy even in pathological retina images. The proposed system uses a robust hybrid segmentation algorithm combines adaptive fuzzy thresholding and mathematical morphology. The proposed system is validated using four benchmark datasets: DRIVE and STARE (vessels), DRISHTI-GS (optic disc), and DIARETDB1 (exudates lesions). Competitive segmentation performance is achieved, outperforming a variety of up-to-date systems and demonstrating the capacity to deal with other heterogeneous anatomical structures. PMID:29888146

Cerebral vessels segmentation for light-sheet microscopy image using convolutional neural networks

NASA Astrophysics Data System (ADS)

Hu, Chaoen; Hui, Hui; Wang, Shuo; Dong, Di; Liu, Xia; Yang, Xin; Tian, Jie

2017-03-01

Cerebral vessel segmentation is an important step in image analysis for brain function and brain disease studies. To extract all the cerebrovascular patterns, including arteries and capillaries, some filter-based methods are used to segment vessels. However, the design of accurate and robust vessel segmentation algorithms is still challenging, due to the variety and complexity of images, especially in cerebral blood vessel segmentation. In this work, we addressed a problem of automatic and robust segmentation of cerebral micro-vessels structures in cerebrovascular images acquired by light-sheet microscope for mouse. To segment micro-vessels in large-scale image data, we proposed a convolutional neural networks (CNNs) architecture trained by 1.58 million pixels with manual label. Three convolutional layers and one fully connected layer were used in the CNNs model. We extracted a patch of size 32x32 pixels in each acquired brain vessel image as training data set to feed into CNNs for classification. This network was trained to output the probability that the center pixel of input patch belongs to vessel structures. To build the CNNs architecture, a series of mouse brain vascular images acquired from a commercial light sheet fluorescence microscopy (LSFM) system were used for training the model. The experimental results demonstrated that our approach is a promising method for effectively segmenting micro-vessels structures in cerebrovascular images with vessel-dense, nonuniform gray-level and long-scale contrast regions.

Structural insights into the functions of the FANCM-FAAP24 complex in DNA repair

PubMed Central

Yang, Hui; Zhang, Tianlong; Tao, Ye; Wang, Fang; Tong, Liang; Ding, Jianping

2013-01-01

Fanconi anemia (FA) is a genetically heterogeneous disorder associated with deficiencies in the FA complementation group network. FA complementation group M (FANCM) and FA-associated protein 24 kDa (FAAP24) form a stable complex to anchor the FA core complex to chromatin in repairing DNA interstrand crosslinks. Here, we report the first crystal structure of the C-terminal segment of FANCM in complex with FAAP24. The C-terminal segment of FANCM and FAAP24 both consist of a nuclease domain at the N-terminus and a tandem helix-hairpin-helix (HhH)2 domain at the C-terminus. The FANCM-FAAP24 complex exhibits a similar architecture as that of ApXPF. However, the variations of several key residues and the electrostatic property at the active-site region render a catalytically inactive nuclease domain of FANCM, accounting for the lack of nuclease activity. We also show that the first HhH motif of FAAP24 is a potential binding site for DNA, which plays a critical role in targeting FANCM-FAAP24 to chromatin. These results reveal the mechanistic insights into the functions of FANCM-FAAP24 in DNA repair. PMID:24003026

Segmented and "equivalent" representation of the cable equation.

PubMed

Andrietti, F; Bernardini, G

1984-11-01

The linear cable theory has been applied to a modular structure consisting of n repeating units each composed of two subunits with different values of resistance and capacitance. For n going to infinity, i.e., for infinite cables, we have derived analytically the Laplace transform of the solution by making use of a difference method and we have inverted it by means of a numerical procedure. The results have been compared with those obtained by the direct application of the cable equation to a simplified nonmodular model with "equivalent" electrical parameters. The implication of our work in the analysis of the time and space course of the potential of real fibers has been discussed. In particular, we have shown that the simplified ("equivalent") model is a very good representation of the segmented model for the nodal regions of myelinated fibers in a steady situation and in every condition for muscle fibers. An approximate solution for the steady potential of myelinated fibers has been derived for both nodal and internodal regions. The applications of our work to other cases dealing with repeating structures, such as earthworm giant fibers, have been discussed and our results have been compared with other attempts to solve similar problems.

SU-D-BRD-06: Automated Population-Based Planning for Whole Brain Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schreibmann, E; Fox, T; Crocker, I

2014-06-01

Purpose: Treatment planning for whole brain radiation treatment is technically a simple process but in practice it takes valuable clinical time of repetitive and tedious tasks. This report presents a method that automatically segments the relevant target and normal tissues and creates a treatment plan in only a few minutes after patient simulation. Methods: Segmentation is performed automatically through morphological operations on the soft tissue. The treatment plan is generated by searching a database of previous cases for patients with similar anatomy. In this search, each database case is ranked in terms of similarity using a customized metric designed formore » sensitivity by including only geometrical changes that affect the dose distribution. The database case with the best match is automatically modified to replace relevant patient info and isocenter position while maintaining original beam and MLC settings. Results: Fifteen patients were used to validate the method. In each of these cases the anatomy was accurately segmented to mean Dice coefficients of 0.970 ± 0.008 for the brain, 0.846 ± 0.009 for the eyes and 0.672 ± 0.111 for the lens as compared to clinical segmentations. Each case was then subsequently matched against a database of 70 validated treatment plans and the best matching plan (termed auto-planned), was compared retrospectively with the clinical plans in terms of brain coverage and maximum doses to critical structures. Maximum doses were reduced by a maximum of 20.809 Gy for the left eye (mean 3.533), by 13.352 (1.311) for the right eye, and by 27.471 (4.856), 25.218 (6.315) for the left and right lens. Time from simulation to auto-plan was 3-4 minutes. Conclusion: Automated database- based matching is an alternative to classical treatment planning that improves quality while providing a cost—effective solution to planning through modifying previous validated plans to match a current patient's anatomy.« less

Myomesin is a molecular spring with adaptable elasticity.

PubMed

Schoenauer, Roman; Bertoncini, Patricia; Machaidze, Gia; Aebi, Ueli; Perriard, Jean-Claude; Hegner, Martin; Agarkova, Irina

2005-06-03

The M-band is a transverse structure in the center of the sarcomere, which is thought to stabilize the thick filament lattice. It was shown recently that the constitutive vertebrate M-band component myomesin can form antiparallel dimers, which might cross-link the neighboring thick filaments. Myomesin consists mainly of immunoglobulin-like (Ig) and fibronectin type III (Fn) domains, while several muscle types express the EH-myomesin splice isoform, generated by the inclusion of the unique EH-segment of about 100 amino acid residues (aa) in the center of the molecule. Here we use atomic force microscopy (AFM), transmission electron microscopy (TEM) and circular dichroism (CD) spectroscopy for the biophysical characterization of myomesin. The AFM identifies the "mechanical fingerprints" of the modules constituting the myomesin molecule. Stretching of homomeric polyproteins, constructed of Ig and Fn domains of human myomesin, produces a typical saw-tooth pattern in the force-extension curve. The domains readily refold after relaxation. In contrast, stretching of a heterogeneous polyprotein, containing several repeats of the My6-EH fragment reveals a long initial plateau corresponding to the sum of EH-segment contour lengths, followed by several My6 unfolding peaks. According to this, the EH-segment is characterized as an entropic chain with a persistence length of about 0.3nm. In TEM pictures, the EH-domain appears as a gap in the molecule, indicating a random coil conformation similar to the PEVK region of titin. CD spectroscopy measurements support this result, demonstrating a mostly non-folded conformation for the EH-segment. We suggest that similarly to titin, myomesin is a molecular spring, whose elasticity is modulated by alternative splicing. The Ig and Fn domains might function as reversible "shock absorbers" by sequential unfolding in the case of extremely high or long sustained stretching forces. These complex visco-elastic properties of myomesin might be crucial for the stability of the sarcomere.

Morphometric Atlas Selection for Automatic Brachial Plexus Segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van de Velde, Joris, E-mail: joris.vandevelde@ugent.be; Department of Radiotherapy, Ghent University, Ghent; Wouters, Johan

Purpose: The purpose of this study was to determine the effects of atlas selection based on different morphometric parameters, on the accuracy of automatic brachial plexus (BP) segmentation for radiation therapy planning. The segmentation accuracy was measured by comparing all of the generated automatic segmentations with anatomically validated gold standard atlases developed using cadavers. Methods and Materials: Twelve cadaver computed tomography (CT) atlases (3 males, 9 females; mean age: 73 years) were included in the study. One atlas was selected to serve as a patient, and the other 11 atlases were registered separately onto this “patient” using deformable image registration. Thismore » procedure was repeated for every atlas as a patient. Next, the Dice and Jaccard similarity indices and inclusion index were calculated for every registered BP with the original gold standard BP. In parallel, differences in several morphometric parameters that may influence the BP segmentation accuracy were measured for the different atlases. Specific brachial plexus-related CT-visible bony points were used to define the morphometric parameters. Subsequently, correlations between the similarity indices and morphometric parameters were calculated. Results: A clear negative correlation between difference in protraction-retraction distance and the similarity indices was observed (mean Pearson correlation coefficient = −0.546). All of the other investigated Pearson correlation coefficients were weak. Conclusions: Differences in the shoulder protraction-retraction position between the atlas and the patient during planning CT influence the BP autosegmentation accuracy. A greater difference in the protraction-retraction distance between the atlas and the patient reduces the accuracy of the BP automatic segmentation result.« less

Automatic multiscale enhancement and segmentation of pulmonary vessels in CT pulmonary angiography images for CAD applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou Chuan; Chan, H.-P.; Sahiner, Berkman

2007-12-15

The authors are developing a computerized pulmonary vessel segmentation method for a computer-aided pulmonary embolism (PE) detection system on computed tomographic pulmonary angiography (CTPA) images. Because PE only occurs inside pulmonary arteries, an automatic and accurate segmentation of the pulmonary vessels in 3D CTPA images is an essential step for the PE CAD system. To segment the pulmonary vessels within the lung, the lung regions are first extracted using expectation-maximization (EM) analysis and morphological operations. The authors developed a 3D multiscale filtering technique to enhance the pulmonary vascular structures based on the analysis of eigenvalues of the Hessian matrix atmore » multiple scales. A new response function of the filter was designed to enhance all vascular structures including the vessel bifurcations and suppress nonvessel structures such as the lymphoid tissues surrounding the vessels. An EM estimation is then used to segment the vascular structures by extracting the high response voxels at each scale. The vessel tree is finally reconstructed by integrating the segmented vessels at all scales based on a 'connected component' analysis. Two CTPA cases containing PEs were used to evaluate the performance of the system. One of these two cases also contained pleural effusion disease. Two experienced thoracic radiologists provided the gold standard of pulmonary vessels including both arteries and veins by manually tracking the arterial tree and marking the center of the vessels using a computer graphical user interface. The accuracy of vessel tree segmentation was evaluated by the percentage of the 'gold standard' vessel center points overlapping with the segmented vessels. The results show that 96.2% (2398/2494) and 96.3% (1910/1984) of the manually marked center points in the arteries overlapped with segmented vessels for the case without and with other lung diseases. For the manually marked center points in all vessels including arteries and veins, the segmentation accuracy are 97.0% (4546/4689) and 93.8% (4439/4732) for the cases without and with other lung diseases, respectively. Because of the lack of ground truth for the vessels, in addition to quantitative evaluation of the vessel segmentation performance, visual inspection was conducted to evaluate the segmentation. The results demonstrate that vessel segmentation using our method can extract the pulmonary vessels accurately and is not degraded by PE occlusion to the vessels in these test cases.« less

Presence of cardiovascular structural changes in essential hypertensive patients with coronary microvascular disease and effects of long-term treatment.

PubMed

Virdis, A; Ghiadoni, L; Lucarini, A; Di Legge, V; Taddei, S; Salvetti, A

1996-04-01

In asymptomatic essential hypertensive patients with angiographically normal coronary arteries and without left ventricular hypertrophy, dipyridamole-induced ischemic-like ST segment depression may be a marker of coronary microvascular disease. In this study we evaluated, first, whether this cardiac abnormality is linked to structural or functional vascular abnormalities, and second, the effect of antihypertensive treatment by 12-month administration of the angiotensin converting enzyme (ACE) inhibitor captopril (50 mg twice a day orally). In essential hypertensives with dipypridamole echocardiography stress test (DET) (DET+, n = 8) and without (DET-, n = 8) ST segment depression greater than 0.1 mV during intravenous dipyridamole infusion (0.84 mg/kg over 10 min), we studied the forearm blood flow (FBF, venous plethysmography, mL/100) modifications induced by intrabrachial acetylcholine (Ach) (0.15, 0.45, 1.5, 4.5, 15 micrograms/100 mL/min x 5 min each), an endothelium-dependent vasodilator, and by sodium nitroprusside (SNP) (1, 2, 4 micrograms/100 mL/min x 5 min each), a smooth muscle cell relaxant compound. Minimal forearm vascular resistances (MFVR), an index of arteriolar structural changes, were also calculated. Both Ach and SNP caused greater vasodilation in DET- as compared to DET+ while MFVRs were lower in DET- compared to DET+. After treatment, both DET+ and DET- patients showed a significant and similar reduction in blood pressure and left ventricular mass index, while vasodilation to acetylcholine and sodium nitroprusside was increased only in the DET+ group. In addition, forearm minimal vascular resistances were significantly reduced only in DET+ patients, who showed disappearance of dipyridamole-induced ischemic-like ST segment depression. In conclusion, these data confirm that essential hypertensive patients with microvascular coronary disease are characterized by the presence of structural changes in the forearm vascular bed. Our results also indicate that both cardiac and forearm vascular abnormalities can be reversed by antihypertensive treatment with an ACE inhibitor.

Multi-atlas segmentation of the cartilage in knee MR images with sequential volume- and bone-mask-based registrations

NASA Astrophysics Data System (ADS)

Lee, Han Sang; Kim, Hyeun A.; Kim, Hyeonjin; Hong, Helen; Yoon, Young Cheol; Kim, Junmo

2016-03-01

In spite of its clinical importance in diagnosis of osteoarthritis, segmentation of cartilage in knee MRI remains a challenging task due to its shape variability and low contrast with surrounding soft tissues and synovial fluid. In this paper, we propose a multi-atlas segmentation of cartilage in knee MRI with sequential atlas registrations and locallyweighted voting (LWV). First, bone is segmented by sequential volume- and object-based registrations and LWV. Second, to overcome the shape variability of cartilage, cartilage is segmented by bone-mask-based registration and LWV. In experiments, the proposed method improved the bone segmentation by reducing misclassified bone region, and enhanced the cartilage segmentation by preventing cartilage leakage into surrounding similar intensity region, with the help of sequential registrations and LWV.

Effects on Ridge Segmentation, Magmatic Plumbing and Eruption Style Caused by Weak Hot-spot to Ridge Interaction: the Central Indian Ridge and Rodrigues Hot-spot Couplet.

NASA Astrophysics Data System (ADS)

Murton, B. J.; Parson, L. M.; Sauter, D.

2001-12-01

The intermediate spreading, Central Indian Ridge (CIR) forms a couplet with a weak hot-spot of which the Rodrigues archipelago is an expression. Recently collected bathymetry shows that despite having little in the way of a significant topographic swell, the hot-spot is associated with a change in offset sense across adjacent transforms of the CIR causing the ridge to draw nearer to the Rodrigues island system. The most proximal ridge segment of the CIR is over 20km long and comprises three non-transform bounded sub-segments. The most northerly sub-segment has a shallow (<3000m), narrow (<5km) and featureless flat rift valley. TOBI sidescan sonar imagery shows that the segment is host to a 15km-long, 5km-wide single sheet flow. Elsewhere in the segment the valley floor is characterised by long (>5km), narrow (<1km) ridges that often terminate in conical seamounts. These ridges are the loci of some of the acoustically freshest volcanic facies in the rift valley. Samples recovered from these ridges have similar petrology along strike. With increasing distance south along the CIR, the ridge segments are typically 500m deeper than to the north. Here they are about 75km long and bounded by transform offsets that are 50 km long. However, even in the deepest parts of these segments, where the axial floor is over 4000m deep at the ridge-transform-intersections, there is fresh lava and other evidence for abundant volcanic activity. Within these segments, the rift valley comprises mainly seamounts and hummocky volcanic features. We believe the westward stepping trend of the CIR towards the Rodrigues islands is a function of the hot spot. The elevated temperature and volatile content to the west reduces mantle viscosity which, combined with thinner and hence weaker lithosphere, influencec the loci of initial oceanic rifting and the relative position of the ridge axis. The unusually great length of the northern segment has a similar origin with the presence of thin and weak lithosphere and less viscous mantle reducing the tectonic ``memory" of the ridge system. Despite being farther from the hot-spot, the southern segments have a similarly robust melt supply to the northern segment. The main difference is melt delivery, with the northern segments supplied via long dikes that also erupt as fissure ridges, while to the south the supply is more disseminated. The massive lava sheet and robust and narrow axial valley in the northernmost sub-segment coincides with the tip of a southward propagating system. This system appears to herald the onset of more productive melting a may represent a relocation of the hot-spot-ridge interaction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Lin; Liu, Cong; Leibly, David

Amyloid protein aggregates are associated with dozens of devastating diseases including Alzheimer’s, Parkinson’s, ALS, and diabetes type 2. While structure-based discovery of compounds has been effective in combating numerous infectious and metabolic diseases, ignorance of amyloid structure has hindered similar approaches to amyloid disease. Here we show that knowledge of the atomic structure of one of the adhesive, steric-zipper segments of the amyloid-beta (Aβ) protein of Alzheimer’s disease, when coupled with computational methods, identifies eight diverse but mainly flat compounds and three compound derivatives that reduce Aβ cytotoxicity against mammalian cells by up to 90%. Although these compounds bind tomore » Aβ fibers, they do not reduce fiber formation of Aβ. Structure-activity relationship studies of the fiber-binding compounds and their derivatives suggest that compound binding increases fiber stability and decreases fiber toxicity, perhaps by shifting the equilibrium of Aβ from oligomers to fibers.« less

A Regions of Confidence Based Approach to Enhance Segmentation with Shape Priors.

PubMed

Appia, Vikram V; Ganapathy, Balaji; Abufadel, Amer; Yezzi, Anthony; Faber, Tracy

2010-01-18

We propose an improved region based segmentation model with shape priors that uses labels of confidence/interest to exclude the influence of certain regions in the image that may not provide useful information for segmentation. These could be regions in the image which are expected to have weak, missing or corrupt edges or they could be regions in the image which the user is not interested in segmenting, but are part of the object being segmented. In the training datasets, along with the manual segmentations we also generate an auxiliary map indicating these regions of low confidence/interest. Since, all the training images are acquired under similar conditions, we can train our algorithm to estimate these regions as well. Based on this training we will generate a map which indicates the regions in the image that are likely to contain no useful information for segmentation. We then use a parametric model to represent the segmenting curve as a combination of shape priors obtained by representing the training data as a collection of signed distance functions. We evolve an objective energy functional to evolve the global parameters that are used to represent the curve. We vary the influence each pixel has on the evolution of these parameters based on the confidence/interest label. When we use these labels to indicate the regions with low confidence; the regions containing accurate edges will have a dominant role in the evolution of the curve and the segmentation in the low confidence regions will be approximated based on the training data. Since our model evolves global parameters, it improves the segmentation even in the regions with accurate edges. This is because we eliminate the influence of the low confidence regions which may mislead the final segmentation. Similarly when we use the labels to indicate the regions which are not of importance, we will get a better segmentation of the object in the regions we are interested in.

Role of female sex hormones in neuronal nitric oxide release and metabolism in rat mesenteric arteries.

PubMed

Minoves, Nuria; Balfagón, Gloria; Ferrer, Mercedes

2002-09-01

This study examines the effects of female sex hormones on the vasoconstrictor response to electrical field stimulation (EFS), as well as the modulation of this response by neuronal NO. For this purpose, segments of denuded superior mesenteric artery from ovariectomized (OvX) female Sprague-Dawley rats and from control rats (in oestrus phase) were used. EFS induced frequency-dependent contractions, which were greater in segments from OvX rats than in those from control rats. The NO synthase inhibitor N(G)-nitro-l-arginine methyl ester strengthened EFS-elicited contractions to a greater extent in arteries from OvX rats than in those from control rats. Similar results were observed with the preferential neuronal NO synthase inhibitor 7-nitroindazole. The sensorial neurotoxin capsaicin did not modify EFS-induced contractions in segments from either group. In noradrenaline-precontracted segments, sodium nitroprusside (SNP) induced concentration-dependent relaxation, which was greater in segments from control rats than in those from OvX rats. 8-Bromo-cGMP induced similar concentration-dependent relaxation in noradrenaline-precontracted segments from both OvX and control rats. Diethyldithiocarbamate, a superoxide dismutase (SOD) inhibitor, reduced the relaxation induced by SNP in segments from both groups of rats. SOD, a superoxide anion scavenger, enhanced the relaxation induced by SNP in segments from OvX rats, but did not modify it in segments from control rats. EFS induced NO(-)(2) formation, which was greater in segments from OvX than in those from control rats, and pretreatment with tetrodotoxin, a blocker of nerve impulse propagation, abolished release in both cases. These results suggest that EFS induces greater neuronal NO release in mesenteric segments from OvX rats than in those from control rats and, although NO metabolism is also higher, the contribution of net neuronal NO in the vasomotor response to EFS is greater in segments from OvX rats than in those from control rats.

Segmentation and supercycles: A catalog of earthquake cycle complexities from the Sumatran Sunda Megathrust and other well-studied faults worldwide

NASA Astrophysics Data System (ADS)

Philibosian, B.; Meltzner, A. J.; Sieh, K.

2017-12-01

Understanding earthquake cycle processes is key to both seismic hazard and fault mechanics. A concept that has come into focus recently is that rupture segmentation and cyclicity can be complex, and that simple models of periodically repeating similar earthquakes are inadequate. The term "supercycle" has been used to describe repeating longer periods of strain accumulation that involve multiple fault ruptures. However, this term has become broadly applied, lumping together several distinct phenomena that likely have disparate underlying causes. Earthquake recurrence patterns have often been described as "clustered," but this term is also imprecise. It is necessary to develop a terminology framework that consistently and meaningfully describes all types of behavior that are observed. We divide earthquake cycle patterns into four major classes, each having different implications for seismic hazard and fault mechanics: 1) quasi-periodic similar ruptures, 2) temporally clustered similar ruptures, 3) temporally clustered complementary ruptures, also known as rupture cascades, in which neighboring fault patches fail sequentially, and 4) superimposed cycles in which neighboring fault patches have cycles with different recurrence intervals, but may occasionally rupture together. Rupture segmentation is classified as persistent, frequent, or transient depending on how reliably ruptures terminate in a given area. We discuss the paleoseismic and historical evidence currently available for each of these types of behavior on subduction zone megathrust faults worldwide. Due to the unique level of paleoseismic and paleogeodetic detail provided by the coral microatoll technique, the Sumatran Sunda megathrust provides one of the most complete records over multiple seismic cycles. Most subduction zones with sufficient data exhibit examples of persistent and frequent segmentation, with cycle patterns 1, 3, and 4 on different segments. Pattern 2 is generally confined to overlap zones between segments. This catalog of seismic cycle observations provides a basis for exploring and modeling root causes of rupture segmentation and cycle behavior. Researchers should expect to discover similar behavior styles on other megathrust faults and perhaps major crustal faults around the world.