X chromosome origin of a supernumerary-like segment in Blatella germanica.

PubMed

Ross, M H

1986-12-01

An extraneous heterochromatic segment was discovered in a strain selected for a large-body trait. Derivation from the X chromosome is indicated by its behavior at metaphase I and association with the X and nucleolus in early prophase I. The segment does not pair with the X. Association with a mid-length bivalent is attributed to fusion of heterochromatin. Centromeric activity of small fragments, independent of, but apparently derived from, the X, is also reported.

Cellular image segmentation using n-agent cooperative game theory

NASA Astrophysics Data System (ADS)

Dimock, Ian B.; Wan, Justin W. L.

2016-03-01

Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

An automatic multi-atlas prostate segmentation in MRI using a multiscale representation and a label fusion strategy

NASA Astrophysics Data System (ADS)

Álvarez, Charlens; Martínez, Fabio; Romero, Eduardo

2015-01-01

The pelvic magnetic Resonance images (MRI) are used in Prostate cancer radiotherapy (RT), a process which is part of the radiation planning. Modern protocols require a manual delineation, a tedious and variable activity that may take about 20 minutes per patient, even for trained experts. That considerable time is an important work ow burden in most radiological services. Automatic or semi-automatic methods might improve the efficiency by decreasing the measure times while conserving the required accuracy. This work presents a fully automatic atlas- based segmentation strategy that selects the more similar templates for a new MRI using a robust multi-scale SURF analysis. Then a new segmentation is achieved by a linear combination of the selected templates, which are previously non-rigidly registered towards the new image. The proposed method shows reliable segmentations, obtaining an average DICE Coefficient of 79%, when comparing with the expert manual segmentation, under a leave-one-out scheme with the training database.

Segmentation and determination of joint space width in foot radiographs

NASA Astrophysics Data System (ADS)

Schenk, O.; de Muinck Keizer, D. M.; Bernelot Moens, H. J.; Slump, C. H.

2016-03-01

Joint damage in rheumatoid arthritis is frequently assessed using radiographs of hands and feet. Evaluation includes measurements of the joint space width (JSW) and detection of erosions. Current visual scoring methods are timeconsuming and subject to inter- and intra-observer variability. Automated measurement methods avoid these limitations and have been fairly successful in hand radiographs. This contribution aims at foot radiographs. Starting from an earlier proposed automated segmentation method we have developed a novel model based image analysis algorithm for JSW measurements. This method uses active appearance and active shape models to identify individual bones. The model compiles ten submodels, each representing a specific bone of the foot (metatarsals 1-5, proximal phalanges 1-5). We have performed segmentation experiments using 24 foot radiographs, randomly selected from a large database from the rheumatology department of a local hospital: 10 for training and 14 for testing. Segmentation was considered successful if the joint locations are correctly determined. Segmentation was successful in only 14%. To improve results a step-by-step analysis will be performed. We performed JSW measurements on 14 randomly selected radiographs. JSW was successfully measured in 75%, mean and standard deviation are 2.30+/-0.36mm. This is a first step towards automated determination of progression of RA and therapy response in feet using radiographs.

Diagnostic accuracy of ovarian cyst segmentation in B-mode ultrasound images

NASA Astrophysics Data System (ADS)

Bibicu, Dorin; Moraru, Luminita; Stratulat (Visan), Mirela

2013-11-01

Cystic and polycystic ovary syndrome is an endocrine disorder affecting women in the fertile age. The Moore Neighbor Contour, Watershed Method, Active Contour Models, and a recent method based on Active Contour Model with Selective Binary and Gaussian Filtering Regularized Level Set (ACM&SBGFRLS) techniques were used in this paper to detect the border of the ovarian cyst from echography images. In order to analyze the efficiency of the segmentation an original computer aided software application developed in MATLAB was proposed. The results of the segmentation were compared and evaluated against the reference contour manually delineated by a sonography specialist. Both the accuracy and time complexity of the segmentation tasks are investigated. The Fréchet distance (FD) as a similarity measure between two curves and the area error rate (AER) parameter as the difference between the segmented areas are used as estimators of the segmentation accuracy. In this study, the most efficient methods for the segmentation of the ovarian were analyzed cyst. The research was carried out on a set of 34 ultrasound images of the ovarian cyst.

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

MRI Brain Tumor Segmentation and Necrosis Detection Using Adaptive Sobolev Snakes.

PubMed

Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

2014-03-21

Brain tumor segmentation in brain MRI volumes is used in neurosurgical planning and illness staging. It is important to explore the tumor shape and necrosis regions at different points of time to evaluate the disease progression. We propose an algorithm for semi-automatic tumor segmentation and necrosis detection. Our algorithm consists of three parts: conversion of MRI volume to a probability space based on the on-line learned model, tumor probability density estimation, and adaptive segmentation in the probability space. We use manually selected acceptance and rejection classes on a single MRI slice to learn the background and foreground statistical models. Then, we propagate this model to all MRI slices to compute the most probable regions of the tumor. Anisotropic 3D diffusion is used to estimate the probability density. Finally, the estimated density is segmented by the Sobolev active contour (snake) algorithm to select smoothed regions of the maximum tumor probability. The segmentation approach is robust to noise and not very sensitive to the manual initialization in the volumes tested. Also, it is appropriate for low contrast imagery. The irregular necrosis regions are detected by using the outliers of the probability distribution inside the segmented region. The necrosis regions of small width are removed due to a high probability of noisy measurements. The MRI volume segmentation results obtained by our algorithm are very similar to expert manual segmentation.

MRI brain tumor segmentation and necrosis detection using adaptive Sobolev snakes

NASA Astrophysics Data System (ADS)

Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

2014-03-01

Brain tumor segmentation in brain MRI volumes is used in neurosurgical planning and illness staging. It is important to explore the tumor shape and necrosis regions at di erent points of time to evaluate the disease progression. We propose an algorithm for semi-automatic tumor segmentation and necrosis detection. Our algorithm consists of three parts: conversion of MRI volume to a probability space based on the on-line learned model, tumor probability density estimation, and adaptive segmentation in the probability space. We use manually selected acceptance and rejection classes on a single MRI slice to learn the background and foreground statistical models. Then, we propagate this model to all MRI slices to compute the most probable regions of the tumor. Anisotropic 3D di usion is used to estimate the probability density. Finally, the estimated density is segmented by the Sobolev active contour (snake) algorithm to select smoothed regions of the maximum tumor probability. The segmentation approach is robust to noise and not very sensitive to the manual initialization in the volumes tested. Also, it is appropriate for low contrast imagery. The irregular necrosis regions are detected by using the outliers of the probability distribution inside the segmented region. The necrosis regions of small width are removed due to a high probability of noisy measurements. The MRI volume segmentation results obtained by our algorithm are very similar to expert manual segmentation.

Guiding automated left ventricular chamber segmentation in cardiac imaging using the concept of conserved myocardial volume.

PubMed

Garson, Christopher D; Li, Bing; Acton, Scott T; Hossack, John A

2008-06-01

The active surface technique using gradient vector flow allows semi-automated segmentation of ventricular borders. The accuracy of the algorithm depends on the optimal selection of several key parameters. We investigated the use of conservation of myocardial volume for quantitative assessment of each of these parameters using synthetic and in vivo data. We predicted that for a given set of model parameters, strong conservation of volume would correlate with accurate segmentation. The metric was most useful when applied to the gradient vector field weighting and temporal step-size parameters, but less effective in guiding an optimal choice of the active surface tension and rigidity parameters.

Automated segmentation of ultrasonic breast lesions using statistical texture classification and active contour based on probability distance.

PubMed

Liu, Bo; Cheng, H D; Huang, Jianhua; Tian, Jiawei; Liu, Jiafeng; Tang, Xianglong

2009-08-01

Because of its complicated structure, low signal/noise ratio, low contrast and blurry boundaries, fully automated segmentation of a breast ultrasound (BUS) image is a difficult task. In this paper, a novel segmentation method for BUS images without human intervention is proposed. Unlike most published approaches, the proposed method handles the segmentation problem by using a two-step strategy: ROI generation and ROI segmentation. First, a well-trained texture classifier categorizes the tissues into different classes, and the background knowledge rules are used for selecting the regions of interest (ROIs) from them. Second, a novel probability distance-based active contour model is applied for segmenting the ROIs and finding the accurate positions of the breast tumors. The active contour model combines both global statistical information and local edge information, using a level set approach. The proposed segmentation method was performed on 103 BUS images (48 benign and 55 malignant). To validate the performance, the results were compared with the corresponding tumor regions marked by an experienced radiologist. Three error metrics, true-positive ratio (TP), false-negative ratio (FN) and false-positive ratio (FP) were used for measuring the performance of the proposed method. The final results (TP = 91.31%, FN = 8.69% and FP = 7.26%) demonstrate that the proposed method can segment BUS images efficiently, quickly and automatically.

Robust Indoor Human Activity Recognition Using Wireless Signals.

PubMed

Wang, Yi; Jiang, Xinli; Cao, Rongyu; Wang, Xiyang

2015-07-15

Wireless signals-based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI) of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP) and access points (AP). First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions' CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO) signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM) based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.

[Cardiac rhythm variability as an index of vegetative heart regulation in a situation of psychoemotional tension].

PubMed

Revina, N E

2006-01-01

Differentiated role of segmental and suprasegmental levels of cardiac rhythm variability regulation in dynamics of motivational human conflict was studied for the first time. The author used an original method allowing simultaneous analysis of psychological and physiological parameters of human activity. The study demonstrates that will and anxiety, as components of motivational activity spectrum, form the "energetic" basis of voluntary-constructive and involuntary-affective behavioral strategies, selectively uniting various levels of suprasegmental and segmental control of human heart functioning in a conflict situation.

Parietal Epithelial Cells Participate in the Formation of Sclerotic Lesions in Focal Segmental Glomerulosclerosis

PubMed Central

Smeets, Bart; Kuppe, Christoph; Sicking, Eva-Maria; Fuss, Astrid; Jirak, Peggy; van Kuppevelt, Toin H.; Endlich, Karlhans; Wetzels, Jack F.M.; Gröne, Hermann-Josef; Floege, Jürgen

2011-01-01

The pathogenesis of the development of sclerotic lesions in focal segmental glomerulosclerosis (FSGS) remains unknown. Here, we selectively tagged podocytes or parietal epithelial cells (PECs) to determine whether PECs contribute to sclerosis. In three distinct models of FSGS (5/6-nephrectomy + DOCA-salt; the murine transgenic chronic Thy1.1 model; or the MWF rat) and in human biopsies, the primary injury to induce FSGS associated with focal activation of PECs and the formation of cellular adhesions to the capillary tuft. From this entry site, activated PECs invaded the affected segment of the glomerular tuft and deposited extracellular matrix. Within the affected segment, podocytes were lost and mesangial sclerosis developed within the endocapillary compartment. In conclusion, these results demonstrate that PECs contribute to the development and progression of the sclerotic lesions that define FSGS, but this pathogenesis may be relevant to all etiologies of glomerulosclerosis. PMID:21719782

Automated segmentation of the actively stained mouse brain using multi-spectral MR microscopy.

PubMed

Sharief, Anjum A; Badea, Alexandra; Dale, Anders M; Johnson, G Allan

2008-01-01

Magnetic resonance microscopy (MRM) has created new approaches for high-throughput morphological phenotyping of mouse models of diseases. Transgenic and knockout mice serve as a test bed for validating hypotheses that link genotype to the phenotype of diseases, as well as developing and tracking treatments. We describe here a Markov random fields based segmentation of the actively stained mouse brain, as a prerequisite for morphological phenotyping. Active staining achieves higher signal to noise ratio (SNR) thereby enabling higher resolution imaging per unit time than obtained in previous formalin-fixed mouse brain studies. The segmentation algorithm was trained on isotropic 43-mum T1- and T2-weighted MRM images. The mouse brain was segmented into 33 structures, including the hippocampus, amygdala, hypothalamus, thalamus, as well as fiber tracts and ventricles. Probabilistic information used in the segmentation consisted of (a) intensity distributions in the T1- and T2-weighted data, (b) location, and (c) contextual priors for incorporating spatial information. Validation using standard morphometric indices showed excellent consistency between automatically and manually segmented data. The algorithm has been tested on the widely used C57BL/6J strain, as well as on a selection of six recombinant inbred BXD strains, chosen especially for their largely variant hippocampus.

Segmenting the thoracic, abdominal and pelvic musculature on CT scans combining atlas-based model and active contour model

NASA Astrophysics Data System (ADS)

Zhang, Weidong; Liu, Jiamin; Yao, Jianhua; Summers, Ronald M.

2013-03-01

Segmentation of the musculature is very important for accurate organ segmentation, analysis of body composition, and localization of tumors in the muscle. In research fields of computer assisted surgery and computer-aided diagnosis (CAD), muscle segmentation in CT images is a necessary pre-processing step. This task is particularly challenging due to the large variability in muscle structure and the overlap in intensity between muscle and internal organs. This problem has not been solved completely, especially for all of thoracic, abdominal and pelvic regions. We propose an automated system to segment the musculature on CT scans. The method combines an atlas-based model, an active contour model and prior segmentation of fat and bones. First, body contour, fat and bones are segmented using existing methods. Second, atlas-based models are pre-defined using anatomic knowledge at multiple key positions in the body to handle the large variability in muscle shape. Third, the atlas model is refined using active contour models (ACM) that are constrained using the pre-segmented bone and fat. Before refining using ACM, the initialized atlas model of next slice is updated using previous atlas. The muscle is segmented using threshold and smoothed in 3D volume space. Thoracic, abdominal and pelvic CT scans were used to evaluate our method, and five key position slices for each case were selected and manually labeled as the reference. Compared with the reference ground truth, the overlap ratio of true positives is 91.1%+/-3.5%, and that of false positives is 5.5%+/-4.2%.

Heart-Rate Variability During Deep Sleep in World-Class Alpine Skiers: A Time-Efficient Alternative to Morning Supine Measurements.

PubMed

Herzig, David; Testorelli, Moreno; Olstad, Daniela Schäfer; Erlacher, Daniel; Achermann, Peter; Eser, Prisca; Wilhelm, Matthias

2017-05-01

It is increasingly popular to use heart-rate variability (HRV) to tailor training for athletes. A time-efficient method is HRV assessment during deep sleep. To validate the selection of deep-sleep segments identified by RR intervals with simultaneous electroencephalography (EEG) recordings and to compare HRV parameters of these segments with those of standard morning supine measurements. In 11 world-class alpine skiers, RR intervals were monitored during 10 nights, and simultaneous EEGs were recorded during 2-4 nights. Deep sleep was determined from the HRV signal and verified by delta power from the EEG recordings. Four further segments were chosen for HRV determination, namely, a 4-h segment from midnight to 4 AM and three 5-min segments: 1 just before awakening, 1 after waking in supine position, and 1 in standing after orthostatic challenge. Training load was recorded every day. A total of 80 night and 68 morning measurements of 9 athletes were analyzed. Good correspondence between the phases selected by RR intervals vs those selected by EEG was found. Concerning root-mean-squared difference of successive RR intervals (RMSSD), a marker for parasympathetic activity, the best relationship with the morning supine measurement was found in deep sleep. HRV is a simple tool for approximating deep-sleep phases, and HRV measurement during deep sleep could provide a time-efficient alternative to HRV in supine position.

40 CFR 761.247 - Sample site selection for pipe segment removal.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe Samples § 761.247 Sample site selection for pipe segment removal. (a) General. (1) Select the pipe... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sample site selection for pipe segment...

40 CFR 761.247 - Sample site selection for pipe segment removal.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 31 2011-07-01 2011-07-01 false Sample site selection for pipe segment... Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe Samples § 761.247 Sample site selection for pipe segment removal. (a) General. (1) Select the pipe...

A parameter for the assessment of the segmentation of TEM tomography reconstructed volumes based on mutual information.

PubMed

Okariz, Ana; Guraya, Teresa; Iturrondobeitia, Maider; Ibarretxe, Julen

2017-12-01

A method is proposed and verified for selecting the optimum segmentation of a TEM reconstruction among the results of several segmentation algorithms. The selection criterion is the accuracy of the segmentation. To do this selection, a parameter for the comparison of the accuracies of the different segmentations has been defined. It consists of the mutual information value between the acquired TEM images of the sample and the Radon projections of the segmented volumes. In this work, it has been proved that this new mutual information parameter and the Jaccard coefficient between the segmented volume and the ideal one are correlated. In addition, the results of the new parameter are compared to the results obtained from another validated method to select the optimum segmentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

SU-E-J-132: Automated Segmentation with Post-Registration Atlas Selection Based On Mutual Information

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

Ren, X; Gao, H; Sharp, G

2015-06-15

Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to eachmore » chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

NASA Astrophysics Data System (ADS)

Barat, Christian; Phlypo, Ronald

2010-12-01

We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.

Fluid mechanical consequences of pendular activity, segmentation and pyloric outflow in the proximal duodenum of the rat and the guinea pig

PubMed Central

de Loubens, Clément; Lentle, Roger G.; Love, Richard J.; Hulls, Corrin; Janssen, Patrick W. M.

2013-01-01

We conducted numerical experiments to study the influence of non-propagating longitudinal and circular contractions, i.e. pendular activity and segmentation, respectively, on flow and mixing in the proximal duodenum. A lattice-Boltzmann numerical method was developed to simulate the fluid mechanical consequences for each of 22 randomly selected sequences of high-definition video of real longitudinal and radial contractile activity in the isolated proximal duodenum of the rat and guinea pig. During pendular activity in the rat duodenum, the flow was characterized by regions of high shear rate. Mixing was so governed by shearing deformation of the fluid that increased the interface between adjacent domains and accelerated their inter-diffusion (for diffusion coefficients approx. less than 10−8 m² s−1). When pendular activity was associated with a slow gastric outflow characteristic of post-prandial period, the dispersion was also improved, especially near the walls. Mixing was not promoted by isolated segmentative contractions in the guinea pig duodenum and not notably influenced by pylorus outflow. We concluded that pendular activity generates mixing of viscous fluids ‘in situ’ and accelerates the diffusive mass transfer, whereas segmentation may be more important in mixing particulate suspensions with high solid volume ratios. PMID:23536539

Fluid mechanical consequences of pendular activity, segmentation and pyloric outflow in the proximal duodenum of the rat and the guinea pig.

PubMed

de Loubens, Clément; Lentle, Roger G; Love, Richard J; Hulls, Corrin; Janssen, Patrick W M

2013-06-06

We conducted numerical experiments to study the influence of non-propagating longitudinal and circular contractions, i.e. pendular activity and segmentation, respectively, on flow and mixing in the proximal duodenum. A lattice-Boltzmann numerical method was developed to simulate the fluid mechanical consequences for each of 22 randomly selected sequences of high-definition video of real longitudinal and radial contractile activity in the isolated proximal duodenum of the rat and guinea pig. During pendular activity in the rat duodenum, the flow was characterized by regions of high shear rate. Mixing was so governed by shearing deformation of the fluid that increased the interface between adjacent domains and accelerated their inter-diffusion (for diffusion coefficients approx. less than 10(-8) m² s(-1)). When pendular activity was associated with a slow gastric outflow characteristic of post-prandial period, the dispersion was also improved, especially near the walls. Mixing was not promoted by isolated segmentative contractions in the guinea pig duodenum and not notably influenced by pylorus outflow. We concluded that pendular activity generates mixing of viscous fluids 'in situ' and accelerates the diffusive mass transfer, whereas segmentation may be more important in mixing particulate suspensions with high solid volume ratios.

Chimeras of human complement C9 reveal the site recognized by complement regulatory protein CD59.

PubMed

Hüsler, T; Lockert, D H; Kaufman, K M; Sodetz, J M; Sims, P J

1995-02-24

CD59 antigen is a membrane glycoprotein that inhibits the activity of the C9 component of the C5b-9 membrane attack complex, thereby protecting human cells from lysis by human complement. The complement-inhibitory activity of CD59 is species-selective and is most effective toward C9 derived from human or other primate plasma. By contrast, rabbit C9, which can substitute for human C9 in the membrane attack complex, mediates unrestricted lysis of human cells. To identify the peptide segment of human C9 that is recognized by CD59, rabbit C9 cDNA clones were isolated, characterized, and used to construct hybrid cDNAs for expression of full-length human/rabbit C9 chimeras in COS-7 cells. All resulting chimeras were hemolytically active, when tested against chicken erythrocytes bearing C5b-8 complexes. Assays performed in the presence or absence of CD59 revealed that this inhibitor reduced the hemolytic activity of those chimeras containing human C9 sequence between residues 334-415, irrespective of whether the remainder of the protein contained human or rabbit sequence. By contrast, when this segment of C9 contained rabbit sequence, lytic activity was unaffected by CD59. These data establish that human C9 residues 334-415 contain the site recognized by CD59, and they suggest that sequence variability within this segment of C9 is responsible for the observed species-selective inhibitory activity of CD59.

A two-stage method for microcalcification cluster segmentation in mammography by deformable models

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

Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.

Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods aremore » applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST{sub cluster}, average of minimum distance—AMINDIST{sub cluster}) and the area overlap measure (AOM{sub cluster}). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross-validation methodology. A previously developed B-spline active rays segmentation method was also considered for comparison purposes. Results: Interobserver and intraobserver segmentation agreements (median and [25%, 75%] quartile range) were substantial with respect to the distance metrics HDIST{sub cluster} (2.3 [1.8, 2.9] and 2.5 [2.1, 3.2] pixels) and AMINDIST{sub cluster} (0.8 [0.6, 1.0] and 1.0 [0.8, 1.2] pixels), while moderate with respect to AOM{sub cluster} (0.64 [0.55, 0.71] and 0.59 [0.52, 0.66]). The proposed segmentation method outperformed (0.80 ± 0.04) statistically significantly (Mann-Whitney U-test, p < 0.05) the B-spline active rays segmentation method (0.69 ± 0.04), suggesting the significance of the proposed semiautomated method. Conclusions: Results indicate a reliable semiautomated segmentation method for MC clusters offered by deformable models, which could be utilized in MC cluster quantitative image analysis.« less

Continuous EEG signal analysis for asynchronous BCI application.

PubMed

Hsu, Wei-Yen

2011-08-01

In this study, we propose a two-stage recognition system for continuous analysis of electroencephalogram (EEG) signals. An independent component analysis (ICA) and correlation coefficient are used to automatically eliminate the electrooculography (EOG) artifacts. Based on the continuous wavelet transform (CWT) and Student's two-sample t-statistics, active segment selection then detects the location of active segment in the time-frequency domain. Next, multiresolution fractal feature vectors (MFFVs) are extracted with the proposed modified fractal dimension from wavelet data. Finally, the support vector machine (SVM) is adopted for the robust classification of MFFVs. The EEG signals are continuously analyzed in 1-s segments, and every 0.5 second moves forward to simulate asynchronous BCI works in the two-stage recognition architecture. The segment is first recognized as lifted or not in the first stage, and then is classified as left or right finger lifting at stage two if the segment is recognized as lifting in the first stage. Several statistical analyses are used to evaluate the performance of the proposed system. The results indicate that it is a promising system in the applications of asynchronous BCI work.

Enteric Micromotor Can Selectively Position and Spontaneously Propel in the Gastrointestinal Tract.

PubMed

Li, Jinxing; Thamphiwatana, Soracha; Liu, Wenjuan; Esteban-Fernández de Ávila, Berta; Angsantikul, Pavimol; Sandraz, Elodie; Wang, Jianxing; Xu, Tailin; Soto, Fernando; Ramez, Valentin; Wang, Xiaolei; Gao, Weiwei; Zhang, Liangfang; Wang, Joseph

2016-09-22

The gastrointestinal (GI) tract, which hosts hundreds of bacteria species, becomes the most exciting organ for the emerging microbiome research. Some of these GI microbes are hostile and cause a variety of diseases. These bacteria colonize in different segments of the GI tract dependent on the local physicochemical and biological factors. Therefore, selectively locating therapeutic or imaging agents to specific GI segments is of significant importance for studying gut microbiome and treating various GI-related diseases. Herein, we demonstrate an enteric micromotor system capable of precise positioning and controllable retention in desired segments of the GI tract. These motors, consisting of magnesium-based tubular micromotors coated with an enteric polymer layer, act as a robust nanobiotechnology tool for site-specific GI delivery. The micromotors can deliver payload to a particular location via dissolution of their enteric coating to activate their propulsion at the target site toward localized tissue penetration and retention.

Locally excitatory, globally inhibitory oscillator networks: theory and application to scene segmentation

NASA Astrophysics Data System (ADS)

Wang, DeLiang; Terman, David

1995-01-01

A novel class of locally excitatory, globally inhibitory oscillator networks (LEGION) is proposed and investigated analytically and by computer simulation. The model of each oscillator corresponds to a standard relaxation oscillator with two time scales. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing other oscillators from jumping up. We show analytically that with the selective gating mechanism the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate LEGION's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding, and may provide an effective computational framework for scene segmentation and figure/ground segregation.

Breast tumor segmentation in DCE-MRI using fully convolutional networks with an application in radiogenomics

NASA Astrophysics Data System (ADS)

Zhang, Jun; Saha, Ashirbani; Zhu, Zhe; Mazurowski, Maciej A.

2018-02-01

Breast tumor segmentation based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) remains an active as well as a challenging problem. Previous studies often rely on manual annotation for tumor regions, which is not only time-consuming but also error-prone. Recent studies have shown high promise of deep learning-based methods in various segmentation problems. However, these methods are usually faced with the challenge of limited number (e.g., tens or hundreds) of medical images for training, leading to sub-optimal segmentation performance. Also, previous methods cannot efficiently deal with prevalent class-imbalance problems in tumor segmentation, where the number of voxels in tumor regions is much lower than that in the background area. To address these issues, in this study, we propose a mask-guided hierarchical learning (MHL) framework for breast tumor segmentation via fully convolutional networks (FCN). Our strategy is first decomposing the original difficult problem into several sub-problems and then solving these relatively simpler sub-problems in a hierarchical manner. To precisely identify locations of tumors that underwent a biopsy, we further propose an FCN model to detect two landmarks defined on nipples. Finally, based on both segmentation probability maps and our identified landmarks, we proposed to select biopsied tumors from all detected tumors via a tumor selection strategy using the pathology location. We validate our MHL method using data for 272 patients, and achieve a mean Dice similarity coefficient (DSC) of 0.72 in breast tumor segmentation. Finally, in a radiogenomic analysis, we show that a previously developed image features show a comparable performance for identifying luminal A subtype when applied to the automatic segmentation and a semi-manual segmentation demonstrating a high promise for fully automated radiogenomic analysis in breast cancer.

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.

Three-dimensional lung tumor segmentation from x-ray computed tomography using sparse field active models.

PubMed

Awad, Joseph; Owrangi, Amir; Villemaire, Lauren; O'Riordan, Elaine; Parraga, Grace; Fenster, Aaron

2012-02-01

Manual segmentation of lung tumors is observer dependent and time-consuming but an important component of radiology and radiation oncology workflow. The objective of this study was to generate an automated lung tumor measurement tool for segmentation of pulmonary metastatic tumors from x-ray computed tomography (CT) images to improve reproducibility and decrease the time required to segment tumor boundaries. The authors developed an automated lung tumor segmentation algorithm for volumetric image analysis of chest CT images using shape constrained Otsu multithresholding (SCOMT) and sparse field active surface (SFAS) algorithms. The observer was required to select the tumor center and the SCOMT algorithm subsequently created an initial surface that was deformed using level set SFAS to minimize the total energy consisting of mean separation, edge, partial volume, rolling, distribution, background, shape, volume, smoothness, and curvature energies. The proposed segmentation algorithm was compared to manual segmentation whereby 21 tumors were evaluated using one-dimensional (1D) response evaluation criteria in solid tumors (RECIST), two-dimensional (2D) World Health Organization (WHO), and 3D volume measurements. Linear regression goodness-of-fit measures (r(2) = 0.63, p < 0.0001; r(2) = 0.87, p < 0.0001; and r(2) = 0.96, p < 0.0001), and Pearson correlation coefficients (r = 0.79, p < 0.0001; r = 0.93, p < 0.0001; and r = 0.98, p < 0.0001) for 1D, 2D, and 3D measurements, respectively, showed significant correlations between manual and algorithm results. Intra-observer intraclass correlation coefficients (ICC) demonstrated high reproducibility for algorithm (0.989-0.995, 0.996-0.997, and 0.999-0.999) and manual measurements (0.975-0.993, 0.985-0.993, and 0.980-0.992) for 1D, 2D, and 3D measurements, respectively. The intra-observer coefficient of variation (CV%) was low for algorithm (3.09%-4.67%, 4.85%-5.84%, and 5.65%-5.88%) and manual observers (4.20%-6.61%, 8.14%-9.57%, and 14.57%-21.61%) for 1D, 2D, and 3D measurements, respectively. The authors developed an automated segmentation algorithm requiring only that the operator select the tumor to measure pulmonary metastatic tumors in 1D, 2D, and 3D. Algorithm and manual measurements were significantly correlated. Since the algorithm segmentation involves selection of a single seed point, it resulted in reduced intra-observer variability and decreased time, for making the measurements.

Neighborhood sampling: how many streets must an auditor walk?

PubMed

McMillan, Tracy E; Cubbin, Catherine; Parmenter, Barbara; Medina, Ashley V; Lee, Rebecca E

2010-03-12

This study tested the representativeness of four street segment sampling protocols using the Pedestrian Environment Data Scan (PEDS) in eleven neighborhoods surrounding public housing developments in Houston, TX. The following four street segment sampling protocols were used (1) all segments, both residential and arterial, contained within the 400 meter radius buffer from the center point of the housing development (the core) were compared with all segments contained between the 400 meter radius buffer and the 800 meter radius buffer (the ring); all residential segments in the core were compared with (2) 75% (3) 50% and (4) 25% samples of randomly selected residential street segments in the core. Analyses were conducted on five key variables: sidewalk presence; ratings of attractiveness and safety for walking; connectivity; and number of traffic lanes. Some differences were found when comparing all street segments, both residential and arterial, in the core to the ring. Findings suggested that sampling 25% of residential street segments within the 400 m radius of a residence sufficiently represents the pedestrian built environment. Conclusions support more cost effective environmental data collection for physical activity research.

Neighborhood sampling: how many streets must an auditor walk?

PubMed Central

2010-01-01

This study tested the representativeness of four street segment sampling protocols using the Pedestrian Environment Data Scan (PEDS) in eleven neighborhoods surrounding public housing developments in Houston, TX. The following four street segment sampling protocols were used (1) all segments, both residential and arterial, contained within the 400 meter radius buffer from the center point of the housing development (the core) were compared with all segments contained between the 400 meter radius buffer and the 800 meter radius buffer (the ring); all residential segments in the core were compared with (2) 75% (3) 50% and (4) 25% samples of randomly selected residential street segments in the core. Analyses were conducted on five key variables: sidewalk presence; ratings of attractiveness and safety for walking; connectivity; and number of traffic lanes. Some differences were found when comparing all street segments, both residential and arterial, in the core to the ring. Findings suggested that sampling 25% of residential street segments within the 400 m radius of a residence sufficiently represents the pedestrian built environment. Conclusions support more cost effective environmental data collection for physical activity research. PMID:20226052

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

PubMed

Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

2017-07-01

Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiclass feature selection for improved pediatric brain tumor segmentation

NASA Astrophysics Data System (ADS)

Ahmed, Shaheen; Iftekharuddin, Khan M.

2012-03-01

In our previous work, we showed that fractal-based texture features are effective in detection, segmentation and classification of posterior-fossa (PF) pediatric brain tumor in multimodality MRI. We exploited an information theoretic approach such as Kullback-Leibler Divergence (KLD) for feature selection and ranking different texture features. We further incorporated the feature selection technique with segmentation method such as Expectation Maximization (EM) for segmentation of tumor T and non tumor (NT) tissues. In this work, we extend the two class KLD technique to multiclass for effectively selecting the best features for brain tumor (T), cyst (C) and non tumor (NT). We further obtain segmentation robustness for each tissue types by computing Bay's posterior probabilities and corresponding number of pixels for each tissue segments in MRI patient images. We evaluate improved tumor segmentation robustness using different similarity metric for 5 patients in T1, T2 and FLAIR modalities.

Autonomous initiation and propagation of action potentials in neurons of the subthalamic nucleus.

PubMed

Atherton, Jeremy F; Wokosin, David L; Ramanathan, Sankari; Bevan, Mark D

2008-12-01

The activity of the subthalamic nucleus (STN) is intimately related to movement and is generated, in part, by voltage-dependent Na(+) (Na(v)) channels that drive autonomous firing. In order to determine the principles underlying the initiation and propagation of action potentials in STN neurons, 2-photon laser scanning microscopy was used to guide tight-seal whole-cell somatic and loose-seal cell-attached axonal/dendritic patch-clamp recordings and compartment-selective ion channel manipulation in rat brain slices. Action potentials were first detected in a region that corresponded most closely to the unmyelinated axon initial segment, as defined by Golgi and ankyrin G labelling. Following initiation, action potentials propagated reliably into axonal and somatodendritic compartments with conduction velocities of approximately 5 m s(-1) and approximately 0.7 m s(-1), respectively. Action potentials generated by neurons with axons truncated within or beyond the axon initial segment were not significantly different. However, axon initial segment and somatic but not dendritic or more distal axonal application of low [Na(+)] ACSF or the selective Na(v) channel blocker tetrodotoxin consistently depolarized action potential threshold. Finally, somatodendritic but not axonal application of GABA evoked large, rapid inhibitory currents in concordance with electron microscopic analyses, which revealed that the somatodendritic compartment was the principal target of putative inhibitory inputs. Together the data are consistent with the conclusions that in STN neurons the axon initial segment and soma express an excess of Na(v) channels for the generation of autonomous activity, while synaptic activation of somatodendritic GABA(A) receptors regulates the axonal initiation of action potentials.

Autonomous initiation and propagation of action potentials in neurons of the subthalamic nucleus

PubMed Central

Atherton, Jeremy F; Wokosin, David L; Ramanathan, Sankari; Bevan, Mark D

2008-01-01

The activity of the subthalamic nucleus (STN) is intimately related to movement and is generated, in part, by voltage-dependent Na+ (Nav) channels that drive autonomous firing. In order to determine the principles underlying the initiation and propagation of action potentials in STN neurons, 2-photon laser scanning microscopy was used to guide tight-seal whole-cell somatic and loose-seal cell-attached axonal/dendritic patch-clamp recordings and compartment-selective ion channel manipulation in rat brain slices. Action potentials were first detected in a region that corresponded most closely to the unmyelinated axon initial segment, as defined by Golgi and ankyrin G labelling. Following initiation, action potentials propagated reliably into axonal and somatodendritic compartments with conduction velocities of ∼5 m s−1 and ∼0.7 m s−1, respectively. Action potentials generated by neurons with axons truncated within or beyond the axon initial segment were not significantly different. However, axon initial segment and somatic but not dendritic or more distal axonal application of low [Na+] ACSF or the selective Nav channel blocker tetrodotoxin consistently depolarized action potential threshold. Finally, somatodendritic but not axonal application of GABA evoked large, rapid inhibitory currents in concordance with electron microscopic analyses, which revealed that the somatodendritic compartment was the principal target of putative inhibitory inputs. Together the data are consistent with the conclusions that in STN neurons the axon initial segment and soma express an excess of Nav channels for the generation of autonomous activity, while synaptic activation of somatodendritic GABAA receptors regulates the axonal initiation of action potentials. PMID:18832425

Differential fMRI Activation Patterns to Noxious Heat and Tactile Stimuli in the Primate Spinal Cord

PubMed Central

Yang, Pai-Feng; Wang, Feng

2015-01-01

Mesoscale local functional organizations of the primate spinal cord are largely unknown. Using high-resolution fMRI at 9.4 T, we identified distinct interhorn and intersegment fMRI activation patterns to tactile versus nociceptive heat stimulation of digits in lightly anesthetized monkeys. Within a spinal segment, 8 Hz vibrotactile stimuli elicited predominantly fMRI activations in the middle part of ipsilateral dorsal horn (iDH), along with significantly weaker activations in ipsilateral (iVH) and contralateral (cVH) ventral horns. In contrast, nociceptive heat stimuli evoked widespread strong activations in the superficial part of iDH, as well as in iVH and contralateral dorsal (cDH) horns. As controls, only weak signal fluctuations were detected in the white matter. The iDH responded most strongly to both tactile and heat stimuli, whereas the cVH and cDH responded selectively to tactile versus nociceptive heat, respectively. Across spinal segments, iDH activations were detected in three consecutive segments in both tactile and heat conditions. Heat responses, however, were more extensive along the cord, with strong activations in iVH and cDH in two consecutive segments. Subsequent subunit B of cholera toxin tracer histology confirmed that the spinal segments showing fMRI activations indeed received afferent inputs from the stimulated digits. Comparisons of the fMRI signal time courses in early somatosensory area 3b and iDH revealed very similar hemodynamic stimulus–response functions. In summary, we identified with fMRI distinct segmental networks for the processing of tactile and nociceptive heat stimuli in the cervical spinal cord of nonhuman primates. SIGNIFICANCE STATEMENT This is the first fMRI demonstration of distinct intrasegmental and intersegmental nociceptive heat and touch processing circuits in the spinal cord of nonhuman primates. This study provides novel insights into the local functional organizations of the primate spinal cord for pain and touch, information that will be valuable for designing and optimizing therapeutic interventions for chronic pain management. PMID:26203144

Implantation of active fixation leads in coronary veins for left ventricular stimulation: report of five cases.

PubMed

Hansky, Bert; Vogt, Juergen; Gueldner, Holger; Schulte-Eistrup, Sebastian; Lamp, Barbara; Heintze, Johannes; Horstkotte, Dieter; Koerfer, Reiner

2007-01-01

Securing transvenous left ventricular (LV) pacing leads without an active fixation mechanism in proximal coronary vein (CV) segments is usually challenging and frequently impossible. We investigated how active fixation leads can be safely implanted in this location, how to avoid perforating the free wall of the CV, and how to recognize and respond to perforations. In five patients with no alternative to LV pacing from proximal CV segments, 4 Fr SelectSecure (Medtronic, Minneapolis, MN, USA) leads, which have a fixed helix, were implanted through a modified 6 Fr guide catheter with a pre-shaped tip (Launcher, Medtronic). Active fixation leads were successfully implanted in proximal CVs in five patients. There were no complications. Acute and chronic pacing thresholds were comparable to those of conventional CV leads. The pre-shaped guide catheter tip remains in close proximity to the myocardial aspect of the CV, directing the lead helix toward a safe implantation site. If only proximal CV pacing sites are available, 4 Fr SelectSecure leads can be safely implanted through a modified Launcher guide catheter, avoiding more invasive implantation techniques. Other than venous stenting or implantation of leads with retractable tines, SelectSecure leads are expected to remain extractable.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

PubMed Central

Wang, Yuliang; Zhang, Zaicheng; Wang, Huimin; Bi, Shusheng

2015-01-01

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells. PMID:26066315

Segmentation of lung fields using Chan-Vese active contour model in chest radiographs

NASA Astrophysics Data System (ADS)

Sohn, Kiwon

2011-03-01

A CAD tool for chest radiographs consists of several procedures and the very first step is segmentation of lung fields. We develop a novel methodology for segmentation of lung fields in chest radiographs that can satisfy the following two requirements. First, we aim to develop a segmentation method that does not need a training stage with manual estimation of anatomical features in a large training dataset of images. Secondly, for the ease of implementation, it is desirable to apply a well established model that is widely used for various image-partitioning practices. The Chan-Vese active contour model, which is based on Mumford-Shah functional in the level set framework, is applied for segmentation of lung fields. With the use of this model, segmentation of lung fields can be carried out without detailed prior knowledge on the radiographic anatomy of the chest, yet in some chest radiographs, the trachea regions are unfavorably segmented out in addition to the lung field contours. To eliminate artifacts from the trachea, we locate the upper end of the trachea, find a vertical center line of the trachea and delineate it, and then brighten the trachea region to make it less distinctive. The segmentation process is finalized by subsequent morphological operations. We randomly select 30 images from the Japanese Society of Radiological Technology image database to test the proposed methodology and the results are shown. We hope our segmentation technique can help to promote of CAD tools, especially for emerging chest radiographic imaging techniques such as dual energy radiography and chest tomosynthesis.

Suitability of cholinesterase of polychaete Diopatra neapolitana as biomarker of exposure to pesticides: In vitro characterization.

PubMed

Mennillo, Elvira; Casu, Valentina; Tardelli, Federica; De Marchi, Lucia; Freitas, Rosa; Pretti, Carlo

2017-01-01

Cholinesterases of Diopatra neapolitana were characterized for their activity in whole body and different body segments (apical, intermediate, posterior), substrate affinity (acetyl-, butyryl-, propionylthiocholine), kinetic parameters (K m and V max ) and in vitro response to model inhibitors (eserine hemisulfate, isoOMPA, BW284C51) and carbamates (carbofuran, methomyl, aldicarb and carbaryl). Results showed that the rate of hydrolysis for acetyl- and propionylthiocholine was higher in the posterior segment than the apical/intermediate segments and whole body. Cholinesterases of D. neapolitana showed a substrate preference for acetylthiocholine followed by propionylthiocholine; butyrylthioline was poorly hydrolyzed indicating, together with the absence of inhibition by the specific inhibitor and the absence of reactive bands in native electrophoresis, a lack of an active butyrylcholinesterase, differently than that observed in other Annelida species. The degree of inhibition by selected carbamates of cholinesterase activity with propionylthiocholine as substrate was higher than that observed with ATChI-ChE activity; aldicarb showed the highest inhibitory effect. Copyright © 2016 Elsevier Inc. All rights reserved.

Capacitance-level/density monitor for fluidized-bed combustor

DOEpatents

Fasching, George E.; Utt, Carroll E.

1982-01-01

A multiple segment three-terminal type capacitance probe with segment selection, capacitance detection and compensation circuitry and read-out control for level/density measurements in a fluidized-bed vessel is provided. The probe is driven at a high excitation frequency of up to 50 kHz to sense quadrature (capacitive) current related to probe/vessel capacitance while being relatively insensitive to the resistance current component. Compensation circuitry is provided for generating a negative current of equal magnitude to cancel out only the resistive component current. Clock-operated control circuitry separately selects the probe segments in a predetermined order for detecting and storing this capacitance measurement. The selected segment acts as a guarded electrode and is connected to the read-out circuitry while all unselected segments are connected to the probe body, which together form the probe guard electrode. The selected probe segment capacitance component signal is directed to a corresponding segment channel sample and hold circuit dedicated to that segment to store the signal derived from that segment. This provides parallel outputs for display, computer input, etc., for the detected capacitance values. The rate of segment sampling may be varied to either monitor the dynamic density profile of the bed (high sampling rate) or monitor average bed characteristics (slower sampling rate).

An investigation of the use of temporal decomposition in space mission scheduling

NASA Technical Reports Server (NTRS)

Bullington, Stanley E.; Narayanan, Venkat

1994-01-01

This research involves an examination of techniques for solving scheduling problems in long-duration space missions. The mission timeline is broken up into several time segments, which are then scheduled incrementally. Three methods are presented for identifying the activities that are to be attempted within these segments. The first method is a mathematical model, which is presented primarily to illustrate the structure of the temporal decomposition problem. Since the mathematical model is bound to be computationally prohibitive for realistic problems, two heuristic assignment procedures are also presented. The first heuristic method is based on dispatching rules for activity selection, and the second heuristic assigns performances of a model evenly over timeline segments. These heuristics are tested using a sample Space Station mission and a Spacelab mission. The results are compared with those obtained by scheduling the missions without any problem decomposition. The applicability of this approach to large-scale mission scheduling problems is also discussed.

Molecular determinants of Guanylate Cyclase Activating Protein subcellular distribution in photoreceptor cells of the retina.

PubMed

López-Begines, Santiago; Plana-Bonamaisó, Anna; Méndez, Ana

2018-02-13

Retinal guanylate cyclase (RetGC) and guanylate cyclase activating proteins (GCAPs) play an important role during the light response in photoreceptor cells. Mutations in these proteins are linked to distinct forms of blindness. RetGC and GCAPs exert their role at the ciliary outer segment where phototransduction takes place. We investigated the mechanisms governing GCAP1 and GCAP2 distribution to rod outer segments by expressing selected GCAP1 and GCAP2 mutants as transient transgenes in the rods of GCAP1/2 double knockout mice. We show that precluding GCAP1 direct binding to RetGC (K23D/GCAP1) prevented its distribution to rod outer segments, while preventing GCAP1 activation of RetGC post-binding (W94A/GCAP1) did not. We infer that GCAP1 translocation to the outer segment strongly depends on GCAP1 binding affinity for RetGC, which points to GCAP1 requirement to bind to RetGC to be transported. We gain further insight into the distinctive regulatory steps of GCAP2 distribution, by showing that a phosphomimic at position 201 is sufficient to retain GCAP2 at proximal compartments; and that the bovine equivalent to blindness-causative mutation G157R/GCAP2 results in enhanced phosphorylation in vitro and significant retention at the inner segment in vivo, as likely contributing factors to the pathophysiology.

A Multiatlas Segmentation Using Graph Cuts with Applications to Liver Segmentation in CT Scans

PubMed Central

2014-01-01

An atlas-based segmentation approach is presented that combines low-level operations, an affine probabilistic atlas, and a multiatlas-based segmentation. The proposed combination provides highly accurate segmentation due to registrations and atlas selections based on the regions of interest (ROIs) and coarse segmentations. Our approach shares the following common elements between the probabilistic atlas and multiatlas segmentation: (a) the spatial normalisation and (b) the segmentation method, which is based on minimising a discrete energy function using graph cuts. The method is evaluated for the segmentation of the liver in computed tomography (CT) images. Low-level operations define a ROI around the liver from an abdominal CT. We generate a probabilistic atlas using an affine registration based on geometry moments from manually labelled data. Next, a coarse segmentation of the liver is obtained from the probabilistic atlas with low computational effort. Then, a multiatlas segmentation approach improves the accuracy of the segmentation. Both the atlas selections and the nonrigid registrations of the multiatlas approach use a binary mask defined by coarse segmentation. We experimentally demonstrate that this approach performs better than atlas selections and nonrigid registrations in the entire ROI. The segmentation results are comparable to those obtained by human experts and to other recently published results. PMID:25276219

Automatic blood vessel based-liver segmentation using the portal phase abdominal CT

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Shimada, Mitsuo; Iinuma, Gen

2018-02-01

Liver segmentation is the basis for computer-based planning of hepatic surgical interventions. In diagnosis and analysis of hepatic diseases and surgery planning, automatic segmentation of liver has high importance. Blood vessel (BV) has showed high performance at liver segmentation. In our previous work, we developed a semi-automatic method that segments the liver through the portal phase abdominal CT images in two stages. First stage was interactive segmentation of abdominal blood vessels (ABVs) and subsequent classification into hepatic (HBVs) and non-hepatic (non-HBVs). This stage had 5 interactions that include selective threshold for bone segmentation, selecting two seed points for kidneys segmentation, selection of inferior vena cava (IVC) entrance for starting ABVs segmentation, identification of the portal vein (PV) entrance to the liver and the IVC-exit for classifying HBVs from other ABVs (non-HBVs). Second stage is automatic segmentation of the liver based on segmented ABVs as described in [4]. For full automation of our method we developed a method [5] that segments ABVs automatically tackling the first three interactions. In this paper, we propose full automation of classifying ABVs into HBVs and non- HBVs and consequently full automation of liver segmentation that we proposed in [4]. Results illustrate that the method is effective at segmentation of the liver through the portal abdominal CT images.

Poster — Thur Eve — 59: Atlas Selection for Automated Segmentation of Pelvic CT for Prostate Radiotherapy

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

Mallawi, A; Farrell, T; Diamond, K

2014-08-15

Automated atlas-based segmentation has recently been evaluated for use in planning prostate cancer radiotherapy. In the typical approach, the essential step is the selection of an atlas from a database that best matches the target image. This work proposes an atlas selection strategy and evaluates its impact on the final segmentation accuracy. Prostate length (PL), right femoral head diameter (RFHD), and left femoral head diameter (LFHD) were measured in CT images of 20 patients. Each subject was then taken as the target image to which all remaining 19 images were affinely registered. For each pair of registered images, the overlapmore » between prostate and femoral head contours was quantified using the Dice Similarity Coefficient (DSC). Finally, we designed an atlas selection strategy that computed the ratio of PL (prostate segmentation), RFHD (right femur segmentation), and LFHD (left femur segmentation) between the target subject and each subject in the atlas database. Five atlas subjects yielding ratios nearest to one were then selected for further analysis. RFHD and LFHD were excellent parameters for atlas selection, achieving a mean femoral head DSC of 0.82 ± 0.06. PL had a moderate ability to select the most similar prostate, with a mean DSC of 0.63 ± 0.18. The DSC obtained with the proposed selection method were slightly lower than the maximums established using brute force, but this does not include potential improvements expected with deformable registration. Atlas selection based on PL for prostate and femoral diameter for femoral heads provides reasonable segmentation accuracy.« less

Selective sensing of ozone and the chemically active gaseous species of the troposphere by using the C20 fullerene and graphene segment.

PubMed

Vessally, Esmail; Siadati, Seyyed Amir; Hosseinian, Akram; Edjlali, Ladan

2017-01-01

OZONE is a key species in forming a layer in the atmosphere of earth that brings vita for our planet and supports the complex life. This three-atom molecule in the ozone-layer, is healing the earth's ecosystem by protecting it from dangerous rays of the sun. Until this molecule is in the stratosphere, it would support the natural order of the life; but, when it appears in our environment, damages will begin against us. In this project, we have tried to find a new way for beaconing ozone species in our environment via physical adsorption by the C 20 fullerene and graphene segment as a sensor. To find the selectivity of this nano-sized segment in sensing ozone (O 3 ), compared to the usual chemically active gasses of the troposphere like O 2 , N 2 , CO 2 , H 2 O, CH 4 , H 2 , and CO, the density of state (DOS) plots were analyzed, for each interacting species. The results showed that ozone could significantly change the electrical conductivity of C 20 fullerene, for each adsorption step. Thus, this fullerene could clearly sense ozone in different adsorption steps; while, the graphene segment could do this only at the second step adsorption (/ΔE g-B /=0.016eV) (at the first adsorption step the /ΔE g-A / is 0.00eV). Copyright © 2016 Elsevier B.V. All rights reserved.

A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI

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

Liu, Hui; Liu, Yiping; Qiu, Tianshuang

2014-08-15

Purpose: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast. Methods: The authors propose a new background distribution-based active contour model using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure functionmore » which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors’ method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio. Results: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.). Conclusions: A new active contour model method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.« less

Strategy-aligned fuzzy approach for market segment evaluation and selection: a modular decision support system by dynamic network process (DNP)

NASA Astrophysics Data System (ADS)

Mohammadi Nasrabadi, Ali; Hosseinpour, Mohammad Hossein; Ebrahimnejad, Sadoullah

2013-05-01

In competitive markets, market segmentation is a critical point of business, and it can be used as a generic strategy. In each segment, strategies lead companies to their targets; thus, segment selection and the application of the appropriate strategies over time are very important to achieve successful business. This paper aims to model a strategy-aligned fuzzy approach to market segment evaluation and selection. A modular decision support system (DSS) is developed to select an optimum segment with its appropriate strategies. The suggested DSS has two main modules. The first one is SPACE matrix which indicates the risk of each segment. Also, it determines the long-term strategies. The second module finds the most preferred segment-strategies over time. Dynamic network process is applied to prioritize segment-strategies according to five competitive force factors. There is vagueness in pairwise comparisons, and this vagueness has been modeled using fuzzy concepts. To clarify, an example is illustrated by a case study in Iran's coffee market. The results show that success possibility of segments could be different, and choosing the best ones could help companies to be sure in developing their business. Moreover, changing the priority of strategies over time indicates the importance of long-term planning. This fact has been supported by a case study on strategic priority difference in short- and long-term consideration.

Verifying the error bound of numerical computation implemented in computer systems

DOEpatents

Sawada, Jun

2013-03-12

A verification tool receives a finite precision definition for an approximation of an infinite precision numerical function implemented in a processor in the form of a polynomial of bounded functions. The verification tool receives a domain for verifying outputs of segments associated with the infinite precision numerical function. The verification tool splits the domain into at least two segments, wherein each segment is non-overlapping with any other segment and converts, for each segment, a polynomial of bounded functions for the segment to a simplified formula comprising a polynomial, an inequality, and a constant for a selected segment. The verification tool calculates upper bounds of the polynomial for the at least two segments, beginning with the selected segment and reports the segments that violate a bounding condition.

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.

Phonetic basis of phonemic paraphasias in aphasia: Evidence for cascading activation.

PubMed

Kurowski, Kathleen; Blumstein, Sheila E

2016-02-01

Phonemic paraphasias are a common presenting symptom in aphasia and are thought to reflect a deficit in which selecting an incorrect phonemic segment results in the clear-cut substitution of one phonemic segment for another. The current study re-examines the basis of these paraphasias. Seven left hemisphere-damaged aphasics with a range of left hemisphere lesions and clinical diagnoses including Broca's, Conduction, and Wernicke's aphasia, were asked to produce syllable-initial voiced and voiceless fricative consonants, [z] and [s], in CV syllables followed by one of five vowels [i e a o u] in isolation and in a carrier phrase. Acoustic analyses were conducted focusing on two acoustic parameters signaling voicing in fricative consonants: duration and amplitude properties of the fricative noise. Results show that for all participants, regardless of clinical diagnosis or lesion site, phonemic paraphasias leave an acoustic trace of the original target in the error production. These findings challenge the view that phonemic paraphasias arise from a mis-selection of phonemic units followed by its correct implementation, as traditionally proposed. Rather, they appear to derive from a common mechanism with speech errors reflecting the co-activation of a target and competitor resulting in speech output that has some phonetic properties of both segments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Phase transformation changes in thermocycled nickel-titanium orthodontic wires.

PubMed

Berzins, David W; Roberts, Howard W

2010-07-01

In the oral environment, orthodontic wires will be subject to thermal fluctuations. The purpose of this study was to investigate the effect of thermocycling on nickel-titanium (NiTi) wire phase transformations. Straight segments from single 27 and 35 degrees C copper NiTi (Ormco), Sentalloy (GAC), and Nitinol Heat Activated (3M Unitek) archwires were sectioned into 5mm segments (n=20). A control group consisted of five randomly selected non-thermocycled segments. The remaining segments were thermocycled between 5 and 55 degrees C with five randomly selected segments analyzed with differential scanning calorimetry (DSC; -100<-->150 degrees C at 10 degrees C/min) after 1000, 5000, and 10,000 cycles. Thermal peaks were evaluated with results analyzed via ANOVA (alpha=0.05). Nitinol HA and Sentalloy did not demonstrate qualitative or quantitative phase transformation behavior differences. Significant differences were observed in some of the copper NiTi transformation temperatures, as well as the heating enthalpy with the 27 degrees C copper NiTi wires (p<0.05). Qualitatively, with increased thermocycling the extent of R-phase in the heating peaks decreased in the 35 degrees C copper NiTi, and an austenite to martensite peak shoulder developed during cooling in the 27 degrees C copper NiTi. Repeated temperature fluctuations may contribute to qualitative and quantitative phase transformation changes in some NiTi wires. Copyright 2010 Academy of Dental Materials. All rights reserved.

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

NASA Technical Reports Server (NTRS)

Tarabalka, Y.; Tilton, J. C.; Benediktsson, J. A.; Chanussot, J.

2012-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Reflection during Portfolio-Based Conversations

ERIC Educational Resources Information Center

Oosterbaan, Anne E.; van der Schaaf, Marieke F.; Baartman, Liesbeth K. J.; Stokking, Karel M.

2010-01-01

This study aims to explore the relationship between the occurrence of reflection (and non-reflection) and thinking activities (e.g., orientating, selecting, analysing) during portfolio-based conversations. Analysis of 21 transcripts of portfolio-based conversations revealed that 20% of the segments were made up of reflection (content reflection…

Representing Heterogeneity in Structural Relationships Among Multiple Choice Variables Using a Latent Segmentation Approach

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

Garikapati, Venu; Astroza, Sebastian; Pendyala, Ram M.

Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to depict relationships among activity-travel choices in travel demand model systems ignores the possibility that some choices are made jointly as a bundle as well as the possible presence of structural heterogeneity in the population with respect to decision-making processes. As different segments in the population may adopt and follow different causalmore » decision-making mechanisms when making selected choices jointly, it would be of value to develop simultaneous equations model systems relating multiple endogenous choice variables that are able to identify population subgroups following alternative causal decision structures. Because the segments are not known a priori, they are considered latent and determined endogenously within a joint modeling framework proposed in this paper. The methodology is applied to a national mobility survey data set to identify population segments that follow different causal structures relating residential location choice, vehicle ownership, and car-share and mobility service usage. It is found that the model revealing three distinct latent segments best describes the data, confirming the efficacy of the modeling approach and the existence of structural heterogeneity in decision-making in the population. Future versions of activity-travel model systems should strive to incorporate such structural heterogeneity to better reflect varying decision processes across population subgroups.« less

Neurokinin subtype receptors mediating substance P contraction in immature rabbit airways.

PubMed

Kazem, E; John, C; Tanaka, D T

1996-01-01

Two-week-old rabbit tracheal smooth muscle (TSM) and bronchial smooth muscle (BSM) segments were placed in organ baths, and isometric contractions to substance P (SP) were obtained. In the presence of phosphoramidon (PHOS), a neutral endopeptidase inhibitor, BSM segments were significantly more reactive and sensitive to SP than TSM segments. Neither neostigmine (NEO) nor atropine (ATR) eliminated these regional differences. Airway contractile responses to: 1) Senktide (NK-3 agonist); 2) neurokinin A (NKA, a NK-2 agonist); and 3) Septide (a highly selective NK-1 agonist) were separately obtained. In the presence of PHOS and NEO, Senktide was virtually inactive in both BSM and TSM. In the presence of PHOS, NEO, and ATR, NKA was equipotent in all airway segments; in contrast, the Septide response was significantly more reactive in BSM than in TSM segments. After inhibition of NK-1 activity with GR 82334, a competitive NK-1 receptor antagonist, the regional differences in SP reactivity were greatly diminished. This latter indication of a NK-1 contribution was confirmed using Septide-mediated inactivation of NK-1 receptors whereby the regional differences in airway sensitivity to SP were eliminated. These findings indicate that both endogenous neutral endopeptidase activity as well as NK-1 and NK-2 receptor influences may modulate the contractile responses to SP in immature rabbit airways.

Multi-object segmentation framework using deformable models for medical imaging analysis.

PubMed

Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

2016-08-01

Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed framework has a wide range of applications especially in the presence of adjacent structures of interest or under intra-structure inhomogeneities giving excellent quantitative results.

Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments

PubMed Central

Wichgers Schreur, Paul J.; Kortekaas, Jeroen

2016-01-01

The bunyavirus genome comprises a small (S), medium (M), and large (L) RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging. Accumulating evidence suggests that genomes of viruses with eight or more genome segments are incorporated into virions by highly selective processes. Remarkably, little is known about the genome packaging process of the tri-segmented bunyaviruses. Here, we evaluated, by single-molecule RNA fluorescence in situ hybridization (FISH), the intracellular spatio-temporal distribution and replication kinetics of the Rift Valley fever virus (RVFV) genome and determined the segment composition of mature virions. The results reveal that the RVFV genome segments start to replicate near the site of infection before spreading and replicating throughout the cytoplasm followed by translocation to the virion assembly site at the Golgi network. Despite the average intracellular S, M and L genome segments approached a 1:1:1 ratio, major differences in genome segment ratios were observed among cells. We also observed a significant amount of cells lacking evidence of M-segment replication. Analysis of two-segmented replicons and four-segmented viruses subsequently confirmed the previous notion that Golgi recruitment is mediated by the Gn glycoprotein. The absence of colocalization of the different segments in the cytoplasm and the successful rescue of a tri-segmented variant with a codon shuffled M-segment suggested that inter-segment interactions are unlikely to drive the copackaging of the different segments into a single virion. The latter was confirmed by direct visualization of RNPs inside mature virions which showed that the majority of virions lack one or more genome segments. Altogether, this study suggests that RVFV genome packaging is a non-selective process. PMID:27548280

Multi-atlas segmentation enables robust multi-contrast MRI spleen segmentation for splenomegaly

NASA Astrophysics Data System (ADS)

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L.; Assad, Albert; Abramson, Richard G.; Landman, Bennett A.

2017-02-01

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≍1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

Multi-atlas Segmentation Enables Robust Multi-contrast MRI Spleen Segmentation for Splenomegaly.

PubMed

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L; Assad, Albert; Abramson, Richard G; Landman, Bennett A

2017-02-11

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≈1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; Moore, Kathleen; Liu, Hong; Zheng, Bin

2017-03-01

Abdominal obesity is strongly associated with a number of diseases and accurately assessment of subtypes of adipose tissue volume plays a significant role in predicting disease risk, diagnosis and prognosis. The objective of this study is to develop and evaluate a new computer-aided detection (CAD) scheme based on deep learning models to automatically segment subcutaneous fat areas (SFA) and visceral (VFA) fat areas depicting on CT images. A dataset involving CT images from 40 patients were retrospectively collected and equally divided into two independent groups (i.e. training and testing group). The new CAD scheme consisted of two sequential convolutional neural networks (CNNs) namely, Selection-CNN and Segmentation-CNN. Selection-CNN was trained using 2,240 CT slices to automatically select CT slices belonging to abdomen areas and SegmentationCNN was trained using 84,000 fat-pixel patches to classify fat-pixels as belonging to SFA or VFA. Then, data from the testing group was used to evaluate the performance of the optimized CAD scheme. Comparing to manually labelled results, the classification accuracy of CT slices selection generated by Selection-CNN yielded 95.8%, while the accuracy of fat pixel segmentation using Segmentation-CNN yielded 96.8%. Therefore, this study demonstrated the feasibility of using deep learning based CAD scheme to recognize human abdominal section from CT scans and segment SFA and VFA from CT slices with high agreement compared with subjective segmentation results.

TARPARE: a method for selecting target audiences for public health interventions.

PubMed

Donovan, R J; Egger, G; Francas, M

1999-06-01

This paper presents a model to assist the health promotion practitioner systematically compare and select what might be appropriate target groups when there are a number of segments competing for attention and resources. TARPARE assesses previously identified segments on the following criteria: T: The Total number of persons in the segment; AR: The proportion of At Risk persons in the segment; P: The Persuability of the target audience; A: The Accessibility of the target audience; R: Resources required to meet the needs of the target audience; and E: Equity, social justice considerations. The assessment can be applied qualitatively or can be applied such that scores can be assigned to each segment. Two examples are presented. TARPARE is a useful and flexible model for understanding the various segments in a population of interest and for assessing the potential viability of interventions directed at each segment. The model is particularly useful when there is a need to prioritise segments in terms of available budgets. The model provides a disciplined approach to target selection and forces consideration of what weights should be applied to the different criteria, and how these might vary for different issues or for different objectives. TARPARE also assesses segments in terms of an overall likelihood of optimal impact for each segment. Targeting high scoring segments is likely to lead to greater program success than targeting low scoring segments.

Discriminative dictionary learning for abdominal multi-organ segmentation.

PubMed

Tong, Tong; Wolz, Robin; Wang, Zehan; Gao, Qinquan; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku; Hajnal, Joseph V; Rueckert, Daniel

2015-07-01

An automated segmentation method is presented for multi-organ segmentation in abdominal CT images. Dictionary learning and sparse coding techniques are used in the proposed method to generate target specific priors for segmentation. The method simultaneously learns dictionaries which have reconstructive power and classifiers which have discriminative ability from a set of selected atlases. Based on the learnt dictionaries and classifiers, probabilistic atlases are then generated to provide priors for the segmentation of unseen target images. The final segmentation is obtained by applying a post-processing step based on a graph-cuts method. In addition, this paper proposes a voxel-wise local atlas selection strategy to deal with high inter-subject variation in abdominal CT images. The segmentation performance of the proposed method with different atlas selection strategies are also compared. Our proposed method has been evaluated on a database of 150 abdominal CT images and achieves a promising segmentation performance with Dice overlap values of 94.9%, 93.6%, 71.1%, and 92.5% for liver, kidneys, pancreas, and spleen, respectively. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization

NASA Astrophysics Data System (ADS)

Li, Li

2018-03-01

In order to extract target from complex background more quickly and accurately, and to further improve the detection effect of defects, a method of dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization was proposed. Firstly, the method of single-threshold selection based on Arimoto entropy was extended to dual-threshold selection in order to separate the target from the background more accurately. Then intermediate variables in formulae of Arimoto entropy dual-threshold selection was calculated by recursion to eliminate redundant computation effectively and to reduce the amount of calculation. Finally, the local search phase of artificial bee colony algorithm was improved by chaotic sequence based on tent mapping. The fast search for two optimal thresholds was achieved using the improved bee colony optimization algorithm, thus the search could be accelerated obviously. A large number of experimental results show that, compared with the existing segmentation methods such as multi-threshold segmentation method using maximum Shannon entropy, two-dimensional Shannon entropy segmentation method, two-dimensional Tsallis gray entropy segmentation method and multi-threshold segmentation method using reciprocal gray entropy, the proposed method can segment target more quickly and accurately with superior segmentation effect. It proves to be an instant and effective method for image segmentation.

Information Behaviour of Slovenian Researchers: Investigation of Activities, Preferences and Characteristics

ERIC Educational Resources Information Center

Vilar, Polona; Juznic, Primoz; Bartol, Tomaz

2015-01-01

Introduction: The paper presents one segment of the first comprehensive national study investigating information behaviour of Slovenian researchers in all research disciplines in relation to selected demographic variables. Research questions addressed various types of information behaviour, format preferences, use of different types of sources,…

Gray matter segmentation of the spinal cord with active contours in MR images.

PubMed

Datta, Esha; Papinutto, Nico; Schlaeger, Regina; Zhu, Alyssa; Carballido-Gamio, Julio; Henry, Roland G

2017-02-15

Fully or partially automated spinal cord gray matter segmentation techniques for spinal cord gray matter segmentation will allow for pivotal spinal cord gray matter measurements in the study of various neurological disorders. The objective of this work was multi-fold: (1) to develop a gray matter segmentation technique that uses registration methods with an existing delineation of the cord edge along with Morphological Geodesic Active Contour (MGAC) models; (2) to assess the accuracy and reproducibility of the newly developed technique on 2D PSIR T1 weighted images; (3) to test how the algorithm performs on different resolutions and other contrasts; (4) to demonstrate how the algorithm can be extended to 3D scans; and (5) to show the clinical potential for multiple sclerosis patients. The MGAC algorithm was developed using a publicly available implementation of a morphological geodesic active contour model and the spinal cord segmentation tool of the software Jim (Xinapse Systems) for initial estimate of the cord boundary. The MGAC algorithm was demonstrated on 2D PSIR images of the C2/C3 level with two different resolutions, 2D T2* weighted images of the C2/C3 level, and a 3D PSIR image. These images were acquired from 45 healthy controls and 58 multiple sclerosis patients selected for the absence of evident lesions at the C2/C3 level. Accuracy was assessed though visual assessment, Hausdorff distances, and Dice similarity coefficients. Reproducibility was assessed through interclass correlation coefficients. Validity was assessed through comparison of segmented gray matter areas in images with different resolution for both manual and MGAC segmentations. Between MGAC and manual segmentations in healthy controls, the mean Dice similarity coefficient was 0.88 (0.82-0.93) and the mean Hausdorff distance was 0.61 (0.46-0.76) mm. The interclass correlation coefficient from test and retest scans of healthy controls was 0.88. The percent change between the manual segmentations from high and low-resolution images was 25%, while the percent change between the MGAC segmentations from high and low resolution images was 13%. Between MGAC and manual segmentations in MS patients, the average Dice similarity coefficient was 0.86 (0.8-0.92) and the average Hausdorff distance was 0.83 (0.29-1.37) mm. We demonstrate that an automatic segmentation technique, based on a morphometric geodesic active contours algorithm, can provide accurate and precise spinal cord gray matter segmentations on 2D PSIR images. We have also shown how this automated technique can potentially be extended to other imaging protocols. Copyright © 2016 Elsevier Inc. All rights reserved.

Efficacy of texture, shape, and intensity feature fusion for posterior-fossa tumor segmentation in MRI.

PubMed

Ahmed, Shaheen; Iftekharuddin, Khan M; Vossough, Arastoo

2011-03-01

Our previous works suggest that fractal texture feature is useful to detect pediatric brain tumor in multimodal MRI. In this study, we systematically investigate efficacy of using several different image features such as intensity, fractal texture, and level-set shape in segmentation of posterior-fossa (PF) tumor for pediatric patients. We explore effectiveness of using four different feature selection and three different segmentation techniques, respectively, to discriminate tumor regions from normal tissue in multimodal brain MRI. We further study the selective fusion of these features for improved PF tumor segmentation. Our result suggests that Kullback-Leibler divergence measure for feature ranking and selection and the expectation maximization algorithm for feature fusion and tumor segmentation offer the best results for the patient data in this study. We show that for T1 and fluid attenuation inversion recovery (FLAIR) MRI modalities, the best PF tumor segmentation is obtained using the texture feature such as multifractional Brownian motion (mBm) while that for T2 MRI is obtained by fusing level-set shape with intensity features. In multimodality fused MRI (T1, T2, and FLAIR), mBm feature offers the best PF tumor segmentation performance. We use different similarity metrics to evaluate quality and robustness of these selected features for PF tumor segmentation in MRI for ten pediatric patients.

Identity of the segment of human complement C8 recognized by complement regulatory protein CD59.

PubMed

Lockert, D H; Kaufman, K M; Chang, C P; Hüsler, T; Sodetz, J M; Sims, P J

1995-08-25

CD59 antigen is a membrane glycoprotein that inhibits the activity of the C5b-9 membrane attack complex (MAC), thereby protecting human cells from lysis by human complement. The inhibitory function of CD59 derives from its capacity to interact with both the C8 and C9 components of MAC, preventing assembly of membrane-inserted C9 polymer. MAC-inhibitory activity of CD59 is species-selective and is most effective when both C8 and C9 derive from human or other primate plasma. Rabbit C8 and C9, which can substitute for human C8 and C9 in MAC, mediate virtually unrestricted lysis of human cells expressing CD59. In order to identify the segment of human C8 that is recognized by CD59, recombinant peptides containing human or rabbit C8 sequence were expressed in Escherichia coli and purified. CD59 was found to specifically bind to a peptide corresponding to residues 334-385 of the human C8 alpha-subunit, and to require a disulfide bond between Cys345 and Cys369. No specific binding was observed to the corresponding sequence from rabbit C8 alpha (residues 334-386). To obtain functional evidence that this segment of human C8 alpha is selectively recognized by CD59, recombinant C8 proteins were prepared by co-transfecting COS-7 cells with human/rabbit chimeras of the C8 alpha cDNA, and cDNAs encoding the C8 beta and C8 gamma chains. Hemolytic activity of MAC formed with chimeric C8 was analyzed using target cells reconstituted with CD59. These experiments confirmed that CD59 recognizes a conformationally sensitive epitope that is within a segment of human C8 alpha internal to residues 320-415. Our data also suggest that optimal interaction of CD59 with this segment of human C8 alpha is influenced by N-terminal flanking sequence in C8 alpha and by human C8 beta, but is unaffected by C8 gamma.

A fast and efficient segmentation scheme for cell microscopic image.

PubMed

Lebrun, G; Charrier, C; Lezoray, O; Meurie, C; Cardot, H

2007-04-27

Microscopic cellular image segmentation schemes must be efficient for reliable analysis and fast to process huge quantity of images. Recent studies have focused on improving segmentation quality. Several segmentation schemes have good quality but processing time is too expensive to deal with a great number of images per day. For segmentation schemes based on pixel classification, the classifier design is crucial since it is the one which requires most of the processing time necessary to segment an image. The main contribution of this work is focused on how to reduce the complexity of decision functions produced by support vector machines (SVM) while preserving recognition rate. Vector quantization is used in order to reduce the inherent redundancy present in huge pixel databases (i.e. images with expert pixel segmentation). Hybrid color space design is also used in order to improve data set size reduction rate and recognition rate. A new decision function quality criterion is defined to select good trade-off between recognition rate and processing time of pixel decision function. The first results of this study show that fast and efficient pixel classification with SVM is possible. Moreover posterior class pixel probability estimation is easy to compute with Platt method. Then a new segmentation scheme using probabilistic pixel classification has been developed. This one has several free parameters and an automatic selection must dealt with, but criteria for evaluate segmentation quality are not well adapted for cell segmentation, especially when comparison with expert pixel segmentation must be achieved. Another important contribution in this paper is the definition of a new quality criterion for evaluation of cell segmentation. The results presented here show that the selection of free parameters of the segmentation scheme by optimisation of the new quality cell segmentation criterion produces efficient cell segmentation.

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.

Location of the internal carotid artery and ophthalmic artery segments for non-invasive intracranial pressure measurement by multi-depth TCD.

PubMed

Hamarat, Yasin; Deimantavicius, Mantas; Kalvaitis, Evaldas; Siaudvytyte, Lina; Januleviciene, Ingrida; Zakelis, Rolandas; Bartusis, Laimonas

2017-12-01

The aim of the present study was to locate the ophthalmic artery by using the edge of the internal carotid artery (ICA) as the reference depth to perform a reliable non-invasive intracranial pressure measurement via a multi-depth transcranial Doppler device and to then determine the positions and angles of an ultrasonic transducer (UT) on the closed eyelid in the case of located segments. High tension glaucoma (HTG) patients and healthy volunteers (HVs) undergoing non-invasive intracranial pressure measurement were selected for this prospective study. The depth of the edge of the ICA was identified, followed by a selection of the depths of the IOA and EOA segments. The positions and angles of the UT on the closed eyelid were measured. The mean depth of the identified ICA edge for HTG patients was 64.3 mm and was 63.0 mm for HVs (p = 0.21). The mean depth of the selected IOA segment for HTG patients was 59.2 mm and 59.3 mm for HVs (p = 0.91). The mean depth of the selected EOA segment for HTG patients was 48.5 mm and 49.8 mm for HVs (p = 0.14). The difference in the located depths of the segments between groups was not statistically significant. The results showed a significant difference in the measured UT angles in the case of the identified edge of the ICA and selected ophthalmic artery segments (p = 0.0002). We demonstrated that locating the IOA and EOA segments can be achieved using the edge of the ICA as a reference point. OA: ophthalmic artery; IOA: intracranial segments of the ophthalmic artery; EOA: extracranial segments of the ophthalmic artery; ICA: internal carotid artery; UT: ultrasonic transducer; HTG: high tension glaucoma; SD: standard deviation; ICP: intracranial pressure; TCD: transcranial Doppler.

A Way to Select Electrical Sheets of the Segment Stator Core Motors.

NASA Astrophysics Data System (ADS)

Enomoto, Yuji; Kitamura, Masashi; Sakai, Toshihiko; Ohara, Kouichiro

The segment stator core, high density winding coil, high-energy-product permanent magnet are indispensable technologies in the development of a compact and also high efficient motors. The conventional design method for the segment stator core mostly depended on experienced knowledge of selecting a suitable electromagnetic material, far from optimized design. Therefore, we have developed a novel design method in the selection of a suitable electromagnetic material based on the correlation evaluation between the material characteristics and motor performance. It enables the selection of suitable electromagnetic material that will meet the motor specification.

Identifying Benefit Segments among College Students.

ERIC Educational Resources Information Center

Brown, Joseph D.

1991-01-01

Using concept of market segmentation (dividing market into distinct groups requiring different product benefits), surveyed 398 college students to determine benefit segments among students selecting a college to attend and factors describing each benefit segment. Identified one major segment of students (classroomers) plus three minor segments…

Advances in selective activation of muscles for non-invasive motor neuroprostheses.

PubMed

Koutsou, Aikaterini D; Moreno, Juan C; Del Ama, Antonio J; Rocon, Eduardo; Pons, José L

2016-06-13

Non-invasive neuroprosthetic (NP) technologies for movement compensation and rehabilitation remain with challenges for their clinical application. Two of those major challenges are selective activation of muscles and fatigue management. This review discusses how electrode arrays improve the efficiency and selectivity of functional electrical stimulation (FES) applied via transcutaneous electrodes. In this paper we review the principles and achievements during the last decade on techniques for artificial motor unit recruitment to improve the selective activation of muscles. We review the key factors affecting the outcome of muscle force production via multi-pad transcutaneous electrical stimulation and discuss how stimulation parameters can be set to optimize external activation of body segments. A detailed review of existing electrode array systems proposed by different research teams is also provided. Furthermore, a review of the targeted applications of existing electrode arrays for control of upper and lower limb NPs is provided. Eventually, last section demonstrates the potential of electrode arrays to overcome the major challenges of NPs for compensation and rehabilitation of patient-specific impairments.

Active surface model improvement by energy function optimization for 3D segmentation.

PubMed

Azimifar, Zohreh; Mohaddesi, Mahsa

2015-04-01

This paper proposes an optimized and efficient active surface model by improving the energy functions, searching method, neighborhood definition and resampling criterion. Extracting an accurate surface of the desired object from a number of 3D images using active surface and deformable models plays an important role in computer vision especially medical image processing. Different powerful segmentation algorithms have been suggested to address the limitations associated with the model initialization, poor convergence to surface concavities and slow convergence rate. This paper proposes a method to improve one of the strongest and recent segmentation algorithms, namely the Decoupled Active Surface (DAS) method. We consider a gradient of wavelet edge extracted image and local phase coherence as external energy to extract more information from images and we use curvature integral as internal energy to focus on high curvature region extraction. Similarly, we use resampling of points and a line search for point selection to improve the accuracy of the algorithm. We further employ an estimation of the desired object as an initialization for the active surface model. A number of tests and experiments have been done and the results show the improvements with regards to the extracted surface accuracy and computational time of the presented algorithm compared with the best and recent active surface models. Copyright © 2015 Elsevier Ltd. All rights reserved.

Marker-Based Hierarchical Segmentation and Classification Approach for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.; Benediktsson, Jon Atli; Chanussot, Jocelyn

2011-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. First, pixelwise classification is performed and the most reliably classified pixels are selected as markers, with the corresponding class labels. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. The experimental results show that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for hyperspectral image analysis.

Semi-automated segmentation of a glioblastoma multiforme on brain MR images for radiotherapy planning.

PubMed

Hori, Daisuke; Katsuragawa, Shigehiko; Murakami, Ryuuji; Hirai, Toshinori

2010-04-20

We propose a computerized method for semi-automated segmentation of the gross tumor volume (GTV) of a glioblastoma multiforme (GBM) on brain MR images for radiotherapy planning (RTP). Three-dimensional (3D) MR images of 28 cases with a GBM were used in this study. First, a sphere volume of interest (VOI) including the GBM was selected by clicking a part of the GBM region in the 3D image. Then, the sphere VOI was transformed to a two-dimensional (2D) image by use of a spiral-scanning technique. We employed active contour models (ACM) to delineate an optimal outline of the GBM in the transformed 2D image. After inverse transform of the optimal outline to the 3D space, a morphological filter was applied to smooth the shape of the 3D segmented region. For evaluation of our computerized method, we compared the computer output with manually segmented regions, which were obtained by a therapeutic radiologist using a manual tracking method. In evaluating our segmentation method, we employed the Jaccard similarity coefficient (JSC) and the true segmentation coefficient (TSC) in volumes between the computer output and the manually segmented region. The mean and standard deviation of JSC and TSC were 74.2+/-9.8% and 84.1+/-7.1%, respectively. Our segmentation method provided a relatively accurate outline for GBM and would be useful for radiotherapy planning.

Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography

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

Zhou, Chuan, E-mail: chuan@umich.edu; Chan, Heang-

Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are thenmore » aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment quality. The performance of our automated method was evaluated by comparing the automatically identified best-quality segments identified by the computer to those selected by the observers. Results: For the 20 test cases, 254 groups of corresponding vessel segments were identified after multiple phase registration and recursive matching. The AI-BQ segments agreed with the radiologist’s top 2 ranked segments in 78.3% of the 254 groups (Cohen’s kappa 0.60), and with the 4 nonradiologist observers in 76.8%, 84.3%, 83.9%, and 85.8% of the 254 groups. In addition, 89.4% of the AI-BQ segments agreed with at least two observers’ top 2 rankings, and 96.5% agreed with at least one observer’s top 2 rankings. In comparison, agreement between the four observers’ top ranked segment and the radiologist’s top 2 ranked segments were 79.9%, 80.7%, 82.3%, and 76.8%, respectively, with kappa values ranging from 0.56 to 0.68. Conclusions: The performance of our automated method for selecting the best-quality coronary segments from a multiple-phase cCTA acquisition was comparable to the selection made by human observers. This study demonstrates the potential usefulness of the automated method in clinical practice, enabling interpreting physicians to fully utilize the best available information in cCTA for diagnosis of coronary disease, without requiring manual search through the multiple phases and minimizing the variability in image phase selection for evaluation of coronary artery segments across the diversity of human readers with variations in expertise.« less

Formation of nanogaps in InAs nanowires by selectively etching embedded InP segments.

PubMed

Schukfeh, M I; Storm, K; Hansen, A; Thelander, C; Hinze, P; Beyer, A; Weimann, T; Samuelson, L; Tornow, M

2014-11-21

We present a method to fabricate nanometer scale gaps within InAs nanowires by selectively etching InAs/InP heterostructure nanowires. We used vapor-liquid-solid grown InAs nanowires with embedded InP segments of 10-60 nm length and developed an etching recipe to selectively remove the InP segment. A photo-assisted wet etching process in a mixture of acetic acid and hydrobromic acid gave high selectivity, with accurate removal of InP segments down to 20 nm, leaving the InAs wire largely unattacked, as verified using scanning electron and transmission electron microscopy. The obtained nanogaps in InAs wires have potential as semiconducting electrodes to investigate electronic transport in nanoscale objects. We demonstrate this functionality by dielectrophoretically trapping 30 nm diameter gold nanoparticles into the gap.

Combined texture feature analysis of segmentation and classification of benign and malignant tumour CT slices.

PubMed

Padma, A; Sukanesh, R

2013-01-01

A computer software system is designed for the segmentation and classification of benign from malignant tumour slices in brain computed tomography (CT) images. This paper presents a method to find and select both the dominant run length and co-occurrence texture features of region of interest (ROI) of the tumour region of each slice to be segmented by Fuzzy c means clustering (FCM) and evaluate the performance of support vector machine (SVM)-based classifiers in classifying benign and malignant tumour slices. Two hundred and six tumour confirmed CT slices are considered in this study. A total of 17 texture features are extracted by a feature extraction procedure, and six features are selected using Principal Component Analysis (PCA). This study constructed the SVM-based classifier with the selected features and by comparing the segmentation results with the experienced radiologist labelled ground truth (target). Quantitative analysis between ground truth and segmented tumour is presented in terms of segmentation accuracy, segmentation error and overlap similarity measures such as the Jaccard index. The classification performance of the SVM-based classifier with the same selected features is also evaluated using a 10-fold cross-validation method. The proposed system provides some newly found texture features have an important contribution in classifying benign and malignant tumour slices efficiently and accurately with less computational time. The experimental results showed that the proposed system is able to achieve the highest segmentation and classification accuracy effectiveness as measured by jaccard index and sensitivity and specificity.

Two-stage atlas subset selection in multi-atlas based image segmentation.

PubMed

Zhao, Tingting; Ruan, Dan

2015-06-01

Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.

Object-based delineation and classification of alluvial fans by application of mean-shift segmentation and support vector machines

NASA Astrophysics Data System (ADS)

Pipaud, Isabel; Lehmkuhl, Frank

2017-09-01

In the field of geomorphology, automated extraction and classification of landforms is one of the most active research areas. Until the late 2000s, this task has primarily been tackled using pixel-based approaches. As these methods consider pixels and pixel neighborhoods as the sole basic entities for analysis, they cannot account for the irregular boundaries of real-world objects. Object-based analysis frameworks emerging from the field of remote sensing have been proposed as an alternative approach, and were successfully applied in case studies falling in the domains of both general and specific geomorphology. In this context, the a-priori selection of scale parameters or bandwidths is crucial for the segmentation result, because inappropriate parametrization will either result in over-segmentation or insufficient segmentation. In this study, we describe a novel supervised method for delineation and classification of alluvial fans, and assess its applicability using a SRTM 1‧‧ DEM scene depicting a section of the north-eastern Mongolian Altai, located in northwest Mongolia. The approach is premised on the application of mean-shift segmentation and the use of a one-class support vector machine (SVM) for classification. To consider variability in terms of alluvial fan dimension and shape, segmentation is performed repeatedly for different weightings of the incorporated morphometric parameters as well as different segmentation bandwidths. The final classification layer is obtained by selecting, for each real-world object, the most appropriate segmentation result according to fuzzy membership values derived from the SVM classification. Our results show that mean-shift segmentation and SVM-based classification provide an effective framework for delineation and classification of a particular landform. Variable bandwidths and terrain parameter weightings were identified as being crucial for consideration of intra-class variability, and, in turn, for a constantly high segmentation quality. Our analysis further reveals that incorporation of morphometric parameters quantifying specific morphological aspects of a landform is indispensable for developing an accurate classification scheme. Alluvial fans exhibiting accentuated composite morphologies were identified as a major challenge for automatic delineation, as they cannot be fully captured by a single segmentation run. There is, however, a high probability that this shortcoming can be overcome by enhancing the presented approach with a routine merging fan sub-entities based on their spatial relationships.

Novel Insights on Hantavirus Evolution: The Dichotomy in Evolutionary Pressures Acting on Different Hantavirus Segments.

PubMed

Sankar, Sathish; Upadhyay, Mohita; Ramamurthy, Mageshbabu; Vadivel, Kumaran; Sagadevan, Kalaiselvan; Nandagopal, Balaji; Vivekanandan, Perumal; Sridharan, Gopalan

2015-01-01

Hantaviruses are important emerging zoonotic pathogens. The current understanding of hantavirus evolution is complicated by the lack of consensus on co-divergence of hantaviruses with their animal hosts. In addition, hantaviruses have long-term associations with their reservoir hosts. Analyzing the relative abundance of dinucleotides may shed new light on hantavirus evolution. We studied the relative abundance of dinucleotides and the evolutionary pressures shaping different hantavirus segments. A total of 118 sequences were analyzed; this includes 51 sequences of the S segment, 43 sequences of the M segment and 23 sequences of the L segment. The relative abundance of dinucleotides, effective codon number (ENC), codon usage biases were analyzed. Standard methods were used to investigate the relative roles of mutational pressure and translational selection on the three hantavirus segments. All three segments of hantaviruses are CpG depleted. Mutational pressure is the predominant evolutionary force leading to CpG depletion among hantaviruses. Interestingly, the S segment of hantaviruses is GpU depleted and in contrast to CpG depletion, the depletion of GpU dinucleotides from the S segment is driven by translational selection. Our findings also suggest that mutational pressure is the primary evolutionary pressure acting on the S and the M segments of hantaviruses. While translational selection plays a key role in shaping the evolution of the L segment. Our findings highlight how different evolutionary pressures may contribute disproportionally to the evolution of the three hantavirus segments. These findings provide new insights on the current understanding of hantavirus evolution. There is a dichotomy among evolutionary pressures shaping a) the relative abundance of different dinucleotides in hantavirus genomes b) the evolution of the three hantavirus segments.

The Use of Attitude Segmentation in Selecting Market Targets and Choosing a New Product Name: Application to an Automated Teller System.

ERIC Educational Resources Information Center

Mauldin, Charles R.; And Others

Ninety-six subjects were randomly chosen from 386 bank customers who responded to a questionnaire using subjective variables to segment or label respondents. A review of subjective segmentation studies revealed that the studies can be divided into three approaches--benefit segmentation, attitude segmentation, and life style segmentation. Choosing…

High-resolution CISS MR imaging with and without contrast for evaluation of the upper cranial nerves: segmental anatomy and selected pathologic conditions of the cisternal through extraforaminal segments.

PubMed

Blitz, Ari M; Macedo, Leonardo L; Chonka, Zachary D; Ilica, Ahmet T; Choudhri, Asim F; Gallia, Gary L; Aygun, Nafi

2014-02-01

The authors review the course and appearance of the major segments of the upper cranial nerves from their apparent origin at the brainstem through the proximal extraforaminal region, focusing on the imaging and anatomic features of particular relevance to high-resolution magnetic resonance imaging evaluation. Selected pathologic entities are included in the discussion of the corresponding cranial nerve segments for illustrative purposes. Copyright © 2014 Elsevier Inc. All rights reserved.

The Avian-Origin PB1 Gene Segment Facilitated Replication and Transmissibility of the H3N2/1968 Pandemic Influenza Virus

PubMed Central

Wendel, Isabel; Rubbenstroth, Dennis; Doedt, Jennifer; Kochs, Georg; Wilhelm, Jochen; Staeheli, Peter; Klenk, Hans-Dieter

2015-01-01

ABSTRACT The H2N2/1957 and H3N2/1968 pandemic influenza viruses emerged via the exchange of genomic RNA segments between human and avian viruses. The avian hemagglutinin (HA) allowed the hybrid viruses to escape preexisting immunity in the human population. Both pandemic viruses further received the PB1 gene segment from the avian parent (Y. Kawaoka, S. Krauss, and R. G. Webster, J Virol 63:4603–4608, 1989), but the biological significance of this observation was not understood. To assess whether the avian-origin PB1 segment provided pandemic viruses with some selective advantage, either on its own or via cooperation with the homologous HA segment, we modeled by reverse genetics the reassortment event that led to the emergence of the H3N2/1968 pandemic virus. Using seasonal H2N2 virus A/California/1/66 (Cal) as a surrogate precursor human virus and pandemic virus A/Hong Kong/1/68 (H3N2) (HK) as a source of avian-derived PB1 and HA gene segments, we generated four reassortant recombinant viruses and compared pairs of viruses which differed solely by the origin of PB1. Replacement of the PB1 segment of Cal by PB1 of HK facilitated viral polymerase activity, replication efficiency in human cells, and contact transmission in guinea pigs. A combination of PB1 and HA segments of HK did not enhance replicative fitness of the reassortant virus compared with the single-gene PB1 reassortant. Our data suggest that the avian PB1 segment of the 1968 pandemic virus served to enhance viral growth and transmissibility, likely by enhancing activity of the viral polymerase complex. IMPORTANCE Despite the high impact of influenza pandemics on human health, some mechanisms underlying the emergence of pandemic influenza viruses still are poorly understood. Thus, it was unclear why both H2N2/1957 and H3N2/1968 reassortant pandemic viruses contained, in addition to the avian HA, the PB1 gene segment of the avian parent. Here, we addressed this long-standing question by modeling the emergence of the H3N2/1968 virus from its putative human and avian precursors. We show that the avian PB1 segment increased activity of the viral polymerase and facilitated viral replication. Our results suggest that in addition to the acquisition of antigenically novel HA (i.e., antigenic shift), enhanced viral polymerase activity is required for the emergence of pandemic influenza viruses from their seasonal human precursors. PMID:25631088

The avian-origin PB1 gene segment facilitated replication and transmissibility of the H3N2/1968 pandemic influenza virus.

PubMed

Wendel, Isabel; Rubbenstroth, Dennis; Doedt, Jennifer; Kochs, Georg; Wilhelm, Jochen; Staeheli, Peter; Klenk, Hans-Dieter; Matrosovich, Mikhail

2015-04-01

The H2N2/1957 and H3N2/1968 pandemic influenza viruses emerged via the exchange of genomic RNA segments between human and avian viruses. The avian hemagglutinin (HA) allowed the hybrid viruses to escape preexisting immunity in the human population. Both pandemic viruses further received the PB1 gene segment from the avian parent (Y. Kawaoka, S. Krauss, and R. G. Webster, J Virol 63:4603-4608, 1989), but the biological significance of this observation was not understood. To assess whether the avian-origin PB1 segment provided pandemic viruses with some selective advantage, either on its own or via cooperation with the homologous HA segment, we modeled by reverse genetics the reassortment event that led to the emergence of the H3N2/1968 pandemic virus. Using seasonal H2N2 virus A/California/1/66 (Cal) as a surrogate precursor human virus and pandemic virus A/Hong Kong/1/68 (H3N2) (HK) as a source of avian-derived PB1 and HA gene segments, we generated four reassortant recombinant viruses and compared pairs of viruses which differed solely by the origin of PB1. Replacement of the PB1 segment of Cal by PB1 of HK facilitated viral polymerase activity, replication efficiency in human cells, and contact transmission in guinea pigs. A combination of PB1 and HA segments of HK did not enhance replicative fitness of the reassortant virus compared with the single-gene PB1 reassortant. Our data suggest that the avian PB1 segment of the 1968 pandemic virus served to enhance viral growth and transmissibility, likely by enhancing activity of the viral polymerase complex. Despite the high impact of influenza pandemics on human health, some mechanisms underlying the emergence of pandemic influenza viruses still are poorly understood. Thus, it was unclear why both H2N2/1957 and H3N2/1968 reassortant pandemic viruses contained, in addition to the avian HA, the PB1 gene segment of the avian parent. Here, we addressed this long-standing question by modeling the emergence of the H3N2/1968 virus from its putative human and avian precursors. We show that the avian PB1 segment increased activity of the viral polymerase and facilitated viral replication. Our results suggest that in addition to the acquisition of antigenically novel HA (i.e., antigenic shift), enhanced viral polymerase activity is required for the emergence of pandemic influenza viruses from their seasonal human precursors. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Analysis of muscle activation in each body segment in response to the stimulation intensity of whole-body vibration.

PubMed

Lee, Dae-Yeon

2017-02-01

[Purpose] The purpose of this study was to investigate the effects of a whole-body vibration exercise, as well as to discuss the scientific basis to establish optimal intensity by analyzing differences between muscle activations in each body part, according to the stimulation intensity of the whole-body vibration. [Subjects and Methods ] The study subjects included 10 healthy men in their 20s without orthopedic disease. Representative muscles from the subjects' primary body segments were selected while the subjects were in upright positions on exercise machines; electromyography electrodes were attached to the selected muscles. Following that, the muscle activities of each part were measured at different intensities. No vibration, 50/80 in volume, and 10/25/40 Hz were mixed and applied when the subjects were on the whole-vibration exercise machines in upright positions. After that, electromyographic signals were collected and analyzed with the root mean square of muscular activation. [Results] As a result of the analysis, it was found that the muscle activation effects had statistically meaningful differences according to changes in exercise intensity in all 8 muscles. When the no-vibration status was standardized and analyzed as 1, the muscle effect became lower at higher frequencies, but became higher at larger volumes. [Conclusion] In conclusion, it was shown that the whole-body vibration stimulation promoted muscle activation across the entire body part, and the exercise effects in each muscle varied depending on the exercise intensities.

Image segmentation using local shape and gray-level appearance models

NASA Astrophysics Data System (ADS)

Seghers, Dieter; Loeckx, Dirk; Maes, Frederik; Suetens, Paul

2006-03-01

A new generic model-based segmentation scheme is presented, which can be trained from examples akin to the Active Shape Model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Because in the ASM approach the intensity and shape models are typically applied alternately during optimizing as first an optimal target location is selected for each landmark separately based on local gray-level appearance information only to which the shape model is fitted subsequently, the ASM may be misled in case of wrongly selected landmark locations. Instead, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized non-iteratively using dynamic programming which allows to find the optimal landmark positions using combined shape and intensity information, without the need for initialization.

Recommendations for the Use of Automated Gray Matter Segmentation Tools: Evidence from Huntington’s Disease

PubMed Central

Johnson, Eileanoir B.; Gregory, Sarah; Johnson, Hans J.; Durr, Alexandra; Leavitt, Blair R.; Roos, Raymund A.; Rees, Geraint; Tabrizi, Sarah J.; Scahill, Rachael I.

2017-01-01

The selection of an appropriate segmentation tool is a challenge facing any researcher aiming to measure gray matter (GM) volume. Many tools have been compared, yet there is currently no method that can be recommended above all others; in particular, there is a lack of validation in disease cohorts. This work utilizes a clinical dataset to conduct an extensive comparison of segmentation tools. Our results confirm that all tools have advantages and disadvantages, and we present a series of considerations that may be of use when selecting a GM segmentation method, rather than a ranking of these tools. Seven segmentation tools were compared using 3 T MRI data from 20 controls, 40 premanifest Huntington’s disease (HD), and 40 early HD participants. Segmented volumes underwent detailed visual quality control. Reliability and repeatability of total, cortical, and lobular GM were investigated in repeated baseline scans. The relationship between each tool was also examined. Longitudinal within-group change over 3 years was assessed via generalized least squares regression to determine sensitivity of each tool to disease effects. Visual quality control and raw volumes highlighted large variability between tools, especially in occipital and temporal regions. Most tools showed reliable performance and the volumes were generally correlated. Results for longitudinal within-group change varied between tools, especially within lobular regions. These differences highlight the need for careful selection of segmentation methods in clinical neuroimaging studies. This guide acts as a primer aimed at the novice or non-technical imaging scientist providing recommendations for the selection of cohort-appropriate GM segmentation software. PMID:29066997

Recommendations for the Use of Automated Gray Matter Segmentation Tools: Evidence from Huntington's Disease.

PubMed

Johnson, Eileanoir B; Gregory, Sarah; Johnson, Hans J; Durr, Alexandra; Leavitt, Blair R; Roos, Raymund A; Rees, Geraint; Tabrizi, Sarah J; Scahill, Rachael I

2017-01-01

The selection of an appropriate segmentation tool is a challenge facing any researcher aiming to measure gray matter (GM) volume. Many tools have been compared, yet there is currently no method that can be recommended above all others; in particular, there is a lack of validation in disease cohorts. This work utilizes a clinical dataset to conduct an extensive comparison of segmentation tools. Our results confirm that all tools have advantages and disadvantages, and we present a series of considerations that may be of use when selecting a GM segmentation method, rather than a ranking of these tools. Seven segmentation tools were compared using 3 T MRI data from 20 controls, 40 premanifest Huntington's disease (HD), and 40 early HD participants. Segmented volumes underwent detailed visual quality control. Reliability and repeatability of total, cortical, and lobular GM were investigated in repeated baseline scans. The relationship between each tool was also examined. Longitudinal within-group change over 3 years was assessed via generalized least squares regression to determine sensitivity of each tool to disease effects. Visual quality control and raw volumes highlighted large variability between tools, especially in occipital and temporal regions. Most tools showed reliable performance and the volumes were generally correlated. Results for longitudinal within-group change varied between tools, especially within lobular regions. These differences highlight the need for careful selection of segmentation methods in clinical neuroimaging studies. This guide acts as a primer aimed at the novice or non-technical imaging scientist providing recommendations for the selection of cohort-appropriate GM segmentation software.

Effects of penetrating traumatic brain injury on event segmentation and memory.

PubMed

Zacks, Jeffrey M; Kurby, Christopher A; Landazabal, Claudia S; Krueger, Frank; Grafman, Jordan

2016-01-01

Penetrating traumatic brain injury (pTBI) is associated with deficits in cognitive tasks including comprehension and memory, and also with impairments in tasks of daily living. In naturalistic settings, one important component of cognitive task performance is event segmentation, the ability to parse the ongoing stream of behavior into meaningful units. Event segmentation ability is associated with memory performance and with action control, but is not well assessed by standard neuropsychological assessments or laboratory tasks. Here, we measured event segmentation and memory in a sample of 123 male military veterans aged 59-81 who had suffered a traumatic brain injury as young men, and 34 demographically similar controls. Participants watched movies of everyday activities and segmented them to identify fine-grained or coarse-grained events, and then completed tests of recognition memory for pictures from the movies and of memory for the temporal order of actions in the movies. Lesion location and volume were assessed with computed tomography (CT) imaging. Patients with traumatic brain injury were impaired on event segmentation. Those with larger lesions had larger impairments for fine segmentation and also impairments for both memory measures. Further, the degree of memory impairment was statistically mediated by the degree of event segmentation impairment. There was some evidence that lesions to the ventromedial prefrontal cortex (vmPFC) selectively impaired coarse segmentation; however, lesions outside of a priori regions of interest also were associated with impaired segmentation. One possibility is that the effect of vmPFC damage reflects the role of prefrontal event knowledge representations in ongoing comprehension. These results suggest that assessment of naturalistic event comprehension can be a valuable component of cognitive assessment in cases of traumatic brain injury, and that interventions aimed at event segmentation could be clinically helpful. Copyright © 2015 Elsevier Ltd. All rights reserved.

Behavioral Flexibility Is Increased by Optogenetic Inhibition of Neurons in the Nucleus Accumbens Shell during Specific Time Segments

ERIC Educational Resources Information Center

Aquili, Luca; Liu, Andrew W.; Shindou, Mayumi; Shindou, Tomomi; Wickens, Jeffery R.

2014-01-01

Behavioral flexibility is vital for survival in an environment of changing contingencies. The nucleus accumbens may play an important role in behavioral flexibility, representing learned stimulus-reward associations in neural activity during response selection and learning from results. To investigate the role of nucleus accumbens neural activity…

Models of antimicrobial pressure on intestinal bacteria of the treated host populations.

PubMed

Volkova, V V; Cazer, C L; Gröhn, Y T

2017-07-01

Antimicrobial drugs are used to treat pathogenic bacterial infections in animals and humans. The by-stander enteric bacteria of the treated host's intestine can become exposed to the drug or its metabolites reaching the intestine in antimicrobially active form. We consider which processes and variables need to be accounted for to project the antimicrobial concentrations in the host's intestine. Those include: the drug's fraction (inclusive of any active metabolites) excreted in bile; the drug's fractions and intestinal segments of excretion via other mechanisms; the rates and intestinal segments of the drug's absorption and re-absorption; the rates and intestinal segments of the drug's abiotic and biotic degradation in the intestine; the digesta passage time through the intestinal segments; the rates, mechanisms, and reversibility of the drug's sorption to the digesta and enteric microbiome; and the volume of luminal contents in the intestinal segments. For certain antimicrobials, the antimicrobial activity can further depend on the aeration and chemical conditions in the intestine. Model forms that incorporate the inter-individual variation in those relevant variables can support projections of the intestinal antimicrobial concentrations in populations of treated host, such as food animals. To illustrate the proposed modeling framework, we develop two examples of treatments of bovine respiratory disease in beef steers by oral chlortetracycline and injectable third-generation cephalosporin ceftiofur. The host's diet influences the digesta passage time, volume, and digesta and microbiome composition, and may influence the antimicrobial loss due to degradation and sorption in the intestine. We consider two diet compositions in the illustrative simulations. The examples highlight the extent of current ignorance and need for empirical data on the variables influencing the selective pressures imposed by antimicrobial treatments on the host's intestinal bacteria.

Automated localization and segmentation techniques for B-mode ultrasound images: A review.

PubMed

Meiburger, Kristen M; Acharya, U Rajendra; Molinari, Filippo

2018-01-01

B-mode ultrasound imaging is used extensively in medicine. Hence, there is a need to have efficient segmentation tools to aid in computer-aided diagnosis, image-guided interventions, and therapy. This paper presents a comprehensive review on automated localization and segmentation techniques for B-mode ultrasound images. The paper first describes the general characteristics of B-mode ultrasound images. Then insight on the localization and segmentation of tissues is provided, both in the case in which the organ/tissue localization provides the final segmentation and in the case in which a two-step segmentation process is needed, due to the desired boundaries being too fine to locate from within the entire ultrasound frame. Subsequenly, examples of some main techniques found in literature are shown, including but not limited to shape priors, superpixel and classification, local pixel statistics, active contours, edge-tracking, dynamic programming, and data mining. Ten selected applications (abdomen/kidney, breast, cardiology, thyroid, liver, vascular, musculoskeletal, obstetrics, gynecology, prostate) are then investigated in depth, and the performances of a few specific applications are compared. In conclusion, future perspectives for B-mode based segmentation, such as the integration of RF information, the employment of higher frequency probes when possible, the focus on completely automatic algorithms, and the increase in available data are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tumor Burden Analysis on Computed Tomography by Automated Liver and Tumor Segmentation

PubMed Central

Linguraru, Marius George; Richbourg, William J.; Liu, Jianfei; Watt, Jeremy M.; Pamulapati, Vivek; Wang, Shijun; Summers, Ronald M.

2013-01-01

The paper presents the automated computation of hepatic tumor burden from abdominal CT images of diseased populations with images with inconsistent enhancement. The automated segmentation of livers is addressed first. A novel three-dimensional (3D) affine invariant shape parameterization is employed to compare local shape across organs. By generating a regular sampling of the organ's surface, this parameterization can be effectively used to compare features of a set of closed 3D surfaces point-to-point, while avoiding common problems with the parameterization of concave surfaces. From an initial segmentation of the livers, the areas of atypical local shape are determined using training sets. A geodesic active contour corrects locally the segmentations of the livers in abnormal images. Graph cuts segment the hepatic tumors using shape and enhancement constraints. Liver segmentation errors are reduced significantly and all tumors are detected. Finally, support vector machines and feature selection are employed to reduce the number of false tumor detections. The tumor detection true position fraction of 100% is achieved at 2.3 false positives/case and the tumor burden is estimated with 0.9% error. Results from the test data demonstrate the method's robustness to analyze livers from difficult clinical cases to allow the temporal monitoring of patients with hepatic cancer. PMID:22893379

Nitric oxide-mediated intersegmental modulation of cycle frequency in the crayfish swimmeret system.

PubMed

Yoshida, Misaki; Nagayama, Toshiki; Newland, Philip

2018-05-21

Crayfish swimmerets are paired appendages located on the ventral side of each abdominal segment that show rhythmic beating during forward swimming produced by central pattern generators in most abdominal segments. For animals with multiple body segments and limbs, intersegmental coordination of central pattern generators in each segment is crucial for the production of effective movements. Here we develop a novel pharmacological approach to analyse intersegmental modulation of swimmeret rhythm by selectively elevating nitric oxide levels and reducing them with pharmacological agents, in specific ganglia. Bath application of L-arginine, the substrate NO synthesis, increased the cyclical spike responses of the power-stroke motor neurons. By contrast the NOS inhibitor, L-NAME decreased them. To determine the role of the different local centres in producing and controlling the swimmeret rhythm, these two drugs were applied locally to two separate ganglia following bath application of carbachol. Results revealed that there was both ascending and descending intersegmental modulation of cycle frequency of the swimmeret rhythm in the abdominal ganglia and that synchrony of cyclical activity between segments of segments was maintained. We also found that there were gradients in the strength effectiveness in modulation, that ascending modulation of the swimmeret rhythm was stronger than descending modulation. © 2018. Published by The Company of Biologists Ltd.

A segmentation/clustering model for the analysis of array CGH data.

PubMed

Picard, F; Robin, S; Lebarbier, E; Daudin, J-J

2007-09-01

Microarray-CGH (comparative genomic hybridization) experiments are used to detect and map chromosomal imbalances. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose representative sequences share the same relative copy number on average. Segmentation methods constitute a natural framework for the analysis, but they do not provide a biological status for the detected segments. We propose a new model for this segmentation/clustering problem, combining a segmentation model with a mixture model. We present a new hybrid algorithm called dynamic programming-expectation maximization (DP-EM) to estimate the parameters of the model by maximum likelihood. This algorithm combines DP and the EM algorithm. We also propose a model selection heuristic to select the number of clusters and the number of segments. An example of our procedure is presented, based on publicly available data sets. We compare our method to segmentation methods and to hidden Markov models, and we show that the new segmentation/clustering model is a promising alternative that can be applied in the more general context of signal processing.

Screening and selection of artificial riboswitches.

PubMed

Harbaugh, Svetlana V; Martin, Jennifer; Weinstein, Jenna; Ingram, Grant; Kelley-Loughnane, Nancy

2018-05-17

Synthetic riboswitches are engineered to regulate gene expression in response to a variety of non-endogenous small molecules, and a challenge to select this engineered response requires robust screening tools. A new synthetic riboswitch can be created by linking an in vitro-selected aptamer library with a randomized expression platform followed by in vivo selection and screening. In order to determine response to analyte, we developed a dual-color reporter comprising elements of the E. coli fimbriae phase variation system: recombinase FimE controlled by a synthetic riboswitch and an invertible DNA segment (fimS) containing a constitutively active promoter placed between two fluorescent protein genes. Without an analyte, the fluorescent reporter constitutively expressed green fluorescent protein (GFPa1). Addition of the analyte initiated translation of fimE causing unidirectional inversion of the fimS segment and constitutive expression of red fluorescent protein (mKate2). The dual color reporter system can be used to select and to optimize artificial riboswitches in E. coli cells. In this work, the enriched library of aptamers incorporated into the riboswitch architecture reduces the sequence search space by offering a higher percentage of potential ligand binders. The study was designed to produce structure switching aptamers, a necessary feature for riboswitch function and efficiently quantify this function using the dual color reporter system. Copyright © 2018. Published by Elsevier Inc.

Two-stage atlas subset selection in multi-atlas based image segmentation

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

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu

2015-06-15

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stagemore » atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.« less

Rough-Fuzzy Clustering and Unsupervised Feature Selection for Wavelet Based MR Image Segmentation

PubMed Central

Maji, Pradipta; Roy, Shaswati

2015-01-01

Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices. PMID:25848961

Learning to rank atlases for multiple-atlas segmentation.

PubMed

Sanroma, Gerard; Wu, Guorong; Gao, Yaozong; Shen, Dinggang

2014-10-01

Recently, multiple-atlas segmentation (MAS) has achieved a great success in the medical imaging area. The key assumption is that multiple atlases have greater chances of correctly labeling a target image than a single atlas. However, the problem of atlas selection still remains unexplored. Traditionally, image similarity is used to select a set of atlases. Unfortunately, this heuristic criterion is not necessarily related to the final segmentation performance. To solve this seemingly simple but critical problem, we propose a learning-based atlas selection method to pick up the best atlases that would lead to a more accurate segmentation. Our main idea is to learn the relationship between the pairwise appearance of observed instances (i.e., a pair of atlas and target images) and their final labeling performance (e.g., using the Dice ratio). In this way, we select the best atlases based on their expected labeling accuracy. Our atlas selection method is general enough to be integrated with any existing MAS method. We show the advantages of our atlas selection method in an extensive experimental evaluation in the ADNI, SATA, IXI, and LONI LPBA40 datasets. As shown in the experiments, our method can boost the performance of three widely used MAS methods, outperforming other learning-based and image-similarity-based atlas selection methods.

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Chemical synthesis of erythropoietin glycoforms for insights into the relationship between glycosylation pattern and bioactivity

PubMed Central

Murakami, Masumi; Kiuchi, Tatsuto; Nishihara, Mika; Tezuka, Katsunari; Okamoto, Ryo; Izumi, Masayuki; Kajihara, Yasuhiro

2016-01-01

The role of sialyloligosaccharides on the surface of secreted glycoproteins is still unclear because of the difficulty in the preparation of sialylglycoproteins in a homogeneous form. We selected erythropoietin (EPO) as a target molecule and designed an efficient synthetic strategy for the chemical synthesis of a homogeneous form of five EPO glycoforms varying in glycosylation position and the number of human-type biantennary sialyloligosaccharides. A segment coupling strategy performed by native chemical ligation using six peptide segments including glycopeptides yielded homogeneous EPO glycopeptides, and folding experiments of these glycopeptides afforded the correctly folded EPO glycoforms. In an in vivo erythropoiesis assay in mice, all of the EPO glycoforms displayed biological activity, in particular the EPO bearing three sialyloligosaccharides, which exhibited the highest activity. Furthermore, we observed that the hydrophilicity and biological activity of the EPO glycoforms varied depending on the glycosylation pattern. This knowledge will pave the way for the development of homogeneous biologics by chemical synthesis. PMID:26824070

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

PubMed

Xu, Zhoubing; Burke, Ryan P; Lee, Christopher P; Baucom, Rebeccah B; Poulose, Benjamin K; Abramson, Richard G; Landman, Bennett A

2015-08-01

Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially robust solution by leveraging label atlases via image registration and statistical fusion. We posit that the efficiency of atlas selection requires further exploration in the context of substantial registration errors. The selective and iterative method for performance level estimation (SIMPLE) method is a MAS technique integrating atlas selection and label fusion that has proven effective for prostate radiotherapy planning. Herein, we revisit atlas selection and fusion techniques for segmenting 12 abdominal structures using clinically acquired CT. Using a re-derived SIMPLE algorithm, we show that performance on multi-organ classification can be improved by accounting for exogenous information through Bayesian priors (so called context learning). These innovations are integrated with the joint label fusion (JLF) approach to reduce the impact of correlated errors among selected atlases for each organ, and a graph cut technique is used to regularize the combined segmentation. In a study of 100 subjects, the proposed method outperformed other comparable MAS approaches, including majority vote, SIMPLE, JLF, and the Wolz locally weighted vote technique. The proposed technique provides consistent improvement over state-of-the-art approaches (median improvement of 7.0% and 16.2% in DSC over JLF and Wolz, respectively) and moves toward efficient segmentation of large-scale clinically acquired CT data for biomarker screening, surgical navigation, and data mining. Copyright © 2015 Elsevier B.V. All rights reserved.

A Novel Mechanism of Sugar Selection Utilized by a Human X-family DNA Polymerase†

PubMed Central

Brown, Jessica A.; Fiala, Kevin A.; Fowler, Jason D.; Sherrer, Shanen M.; Newmister, Sean A.; Dyum, Wade W.; Suo, Zucai

2009-01-01

During DNA synthesis, most DNA polymerases and reverse transcriptases select against ribonucleotides via a steric clash between the ribose 2′-hydroxyl group and the bulky side chain of an active site residue. Here, we demonstrated that human DNA polymerase λ used a novel sugar selection mechanism to discriminate against ribonucleotides, whereby the ribose 2′-hydroxyl group was excluded mostly by a backbone segment and slightly by the side chain of Y505. Such a steric clash was further demonstrated to be dependent on the size and orientation of the substituent covalently attached at the ribonucleotide C2′ position. PMID:19900463

Controlling retention, selectivity and magnitude of EOF by segmented monolithic columns consisting of octadecyl and naphthyl monolithic segments--applications to RP-CEC of both neutral and charged solutes.

PubMed

Karenga, Samuel; El Rassi, Ziad

2011-04-01

Monolithic capillaries made of two adjoining segments each filled with a different monolith were introduced for the control and manipulation of the electroosmotic flow (EOF), retention and selectivity in reversed phase-capillary electrochromatography (RP-CEC). These columns were called segmented monolithic columns (SMCs) where one segment was filled with a naphthyl methacrylate monolith (NMM) to provide hydrophobic and π-interactions, while the other segment was filled with an octadecyl acrylate monolith (ODM) to provide solely hydrophobic interaction. The ODM segment not only provided hydrophobic interactions but also functioned as the EOF accelerator segment. The average EOF of the SMC increased linearly with increasing the fractional length of the ODM segment. The neutral SMC provided a convenient way for tuning EOF, selectivity and retention in the absence of annoying electrostatic interactions and irreversible solute adsorption. The SMCs allowed the separation of a wide range of neutral solutes including polycyclic aromatic hydrocarbons (PAHs) that are difficult to separate using conventional alkyl-bonded stationary phases. In all cases, the k' of a given solute was a linear function of the fractional length of the ODM or NMM segment in the SMCs, thus facilitating the tailoring of a given SMC to solve a given separation problem. At some ODM fractional length, the fabricated SMC allowed the separation of charged solutes such as peptides and proteins that could not otherwise be achieved on a monolithic column made from NMM as an isotropic stationary phase due to the lower EOF exhibited by this monolith. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Unraveling Pancreatic Segmentation.

PubMed

Renard, Yohann; de Mestier, Louis; Perez, Manuela; Avisse, Claude; Lévy, Philippe; Kianmanesh, Reza

2018-04-01

Limited pancreatic resections are increasingly performed, but the rate of postoperative fistula is higher than after classical resections. Pancreatic segmentation, anatomically and radiologically identifiable, may theoretically help the surgeon removing selected anatomical portions with their own segmental pancreatic duct and thus might decrease the postoperative fistula rate. We aimed at systematically and comprehensively reviewing the previously proposed pancreatic segmentations and discuss their relevance and limitations. PubMed database was searched for articles investigating pancreatic segmentation, including human or animal anatomy, and cadaveric or surgical studies. Overall, 47/99 articles were selected and grouped into 4 main hypotheses of pancreatic segmentation methodology: anatomic, vascular, embryologic and lymphatic. The head, body and tail segments are gross description without distinct borders. The arterial territories defined vascular segments and isolate an isthmic paucivascular area. The embryological theory relied on the fusion plans of the embryological buds. The lymphatic drainage pathways defined the lymphatic segmentation. These theories had differences, but converged toward separating the head and body/tail parts, and the anterior from posterior and inferior parts of the pancreatic head. The rate of postoperative fistula was not decreased when surgical resection was performed following any of these segmentation theories; hence, none of them appeared relevant enough to guide pancreatic transections. Current pancreatic segmentation theories do not enable defining anatomical-surgical pancreatic segments. Other approaches should be explored, in particular focusing on pancreatic ducts, through pancreatic ducts reconstructions and embryologic 3D modelization.

Toward optimal feature and time segment selection by divergence method for EEG signals classification.

PubMed

Wang, Jie; Feng, Zuren; Lu, Na; Luo, Jing

2018-06-01

Feature selection plays an important role in the field of EEG signals based motor imagery pattern classification. It is a process that aims to select an optimal feature subset from the original set. Two significant advantages involved are: lowering the computational burden so as to speed up the learning procedure and removing redundant and irrelevant features so as to improve the classification performance. Therefore, feature selection is widely employed in the classification of EEG signals in practical brain-computer interface systems. In this paper, we present a novel statistical model to select the optimal feature subset based on the Kullback-Leibler divergence measure, and automatically select the optimal subject-specific time segment. The proposed method comprises four successive stages: a broad frequency band filtering and common spatial pattern enhancement as preprocessing, features extraction by autoregressive model and log-variance, the Kullback-Leibler divergence based optimal feature and time segment selection and linear discriminate analysis classification. More importantly, this paper provides a potential framework for combining other feature extraction models and classification algorithms with the proposed method for EEG signals classification. Experiments on single-trial EEG signals from two public competition datasets not only demonstrate that the proposed method is effective in selecting discriminative features and time segment, but also show that the proposed method yields relatively better classification results in comparison with other competitive methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

The use of atlas registration and graph cuts for prostate segmentation in magnetic resonance images

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

Korsager, Anne Sofie, E-mail: asko@hst.aau.dk; Østergaard, Lasse Riis; Fortunati, Valerio

2015-04-15

Purpose: An automatic method for 3D prostate segmentation in magnetic resonance (MR) images is presented for planning image-guided radiotherapy treatment of prostate cancer. Methods: A spatial prior based on intersubject atlas registration is combined with organ-specific intensity information in a graph cut segmentation framework. The segmentation is tested on 67 axial T{sub 2}-weighted MR images in a leave-one-out cross validation experiment and compared with both manual reference segmentations and with multiatlas-based segmentations using majority voting atlas fusion. The impact of atlas selection is investigated in both the traditional atlas-based segmentation and the new graph cut method that combines atlas andmore » intensity information in order to improve the segmentation accuracy. Best results were achieved using the method that combines intensity information, shape information, and atlas selection in the graph cut framework. Results: A mean Dice similarity coefficient (DSC) of 0.88 and a mean surface distance (MSD) of 1.45 mm with respect to the manual delineation were achieved. Conclusions: This approaches the interobserver DSC of 0.90 and interobserver MSD 0f 1.15 mm and is comparable to other studies performing prostate segmentation in MR.« less

Analysis of the project synthesis goal cluster orientation and inquiry emphasis of elementary science textbooks

NASA Astrophysics Data System (ADS)

Staver, John R.; Bay, Mary

The purpose of this descriptive study was to examine selected units of commonly used elementary science texts, using the Project Synthesis goal clusters as a framework for part of the examination. An inquiry classification scheme was used for the remaining segment. Four questions were answered: (1) To what extent do elementary science textbooks focus on each Project Synthesis goal cluster? (2) In which part of the text is such information found? (3) To what extent are the activities and experiments merely verifications of information already introduced in the text? (4) If inquiry is present in an activity, then what is the level of such inquiry?Eleven science textbook series, which comprise approximately 90 percent of the national market, were selected for analysis. Two units, one primary (K-3) and one intermediate (4-6), were selected for analysis by first identifying units common to most series, then randomly selecting one primary and one intermediate unit for analysis.Each randomly selected unit was carefully read, using the sentence as the unit of analysis. Each declarative and interrogative sentence in the body of the text was classified as: (1) academic; (2) personal; (3) career; or (4) societal in its focus. Each illustration, except those used in evaluation items, was similarly classified. Each activity/experiment and each miscellaneous sentence in end-of-chapter segments labelled review, summary, evaluation, etc., were similarly classified. Finally, each activity/experiment, as a whole, was categorized according to a four-category inquiry scheme (confirmation, structured inquiry, guided inquiry, open inquiry).In general, results of the analysis are: (1) most text prose focuses on academic science; (2) most remaining text prose focuses on the personal goal cluster; (3) the career and societal goal clusters receive only minor attention; (4) text illustrations exhibit a pattern similar to text prose; (5) text activities/experiments are academic in orientation, almost to the exclusion of other goal clusters; (6) end-of-chapter sentences are largely academic; (7) inquiry is absent or present only in limited forms in text activities/experiments; and (8) texts allocate only a minor portion of space to activities/experiments. Detailed findings are given as numeral, percentage, and decimal values. Discussion focuses on the implications of the results and a comparison of NSTA recommendations with the results of this analysis.

Geological indications for active deformation along Fethiye and G

NASA Astrophysics Data System (ADS)

Pavlides, S.; Chatzipetros, Anastasia Michailidou (1), Alexandros; Yağmurlu, Nevzat Özgür, Züheyr Kamaci, Murat Şentürk, Fuzuli

2009-04-01

Geological indications for active deformation along Fethiye and Gökova faults, SW Turkey Alexandros Chatzipetros, Spyros Pavlides, Anastasia Michailidou (1) Fuzuli Yağmurlu, Nevzat Özgür, Züheyr Kamaci, Murat Şentürk (2) 1Department of Geology, Aristotle University, 54124, Thessaloniki, Greece 2Department of Geological Engineering, Süleyman Demirel University, Isparta, Turkey Fethiye and Gökova faults (FF and GF respectively) are two long fault zones in SW Turkey, associated with minor to moderate historical seismic activity; their geological and geomorphological characteristics however are indicative of active deformation. FF is part of the Fethiye - Burdur Fault Zone (FBFZ), the inferred mainland continuation of the eastern part of the Hellenic Arc. FF, as well as FBFZ, is an oblique-slip (normal with significant dextral component) fault of NE-SW strike, dipping to the NW, that forms the SE border of Fethiye basin and controls its extension to the NE, while it also controls the development of the drainage network. Its geomorphological signature is characterized by steep bedrock fault scarps that are accompanied by thick sequences of alluvial fans and colluviums. Although it does not appear to disrupt the most recent generation of alluvial fans, geophysical prospecting showed that the deformation reaches all the way up to almost the superficial layers. Palaeoseismological trenching in selected sites along the fault yielded indications of at least two large, ground rupturing, seismic events in Holocene, as indicated by the inferred age of the trenched material. Indications include surface ruptures, faulted colluvial wedges and palaeosoils and microstratigraphical correlations. GF forms is divided into two main segments, the partly submarine Gökova-Kos segment trending E-W to NE-SW and the mainland NE-SW trending main Gökova segment, both dipping to the SE to S. They are predominantly normal with dextral component. The first segment defines the northern shore of Gökova gulf, which is the longest fault-controlled shoreline in Turkey. Bathymetric data indicate that its continuation is submarine and continues up to the southern shores of Kos island (Greece), posing a relatively unknown up to now probable seismic source for this part of the Aegean Sea in the Greek territory. The second segment forms a very impressive and dominant scarp that almost totally controls the geomorphology (drainage, alluvial fans and colluviums). Although this fault is not associated with significant historical seismicity, there are some archaeological indications of recent activity. Microstratigraphical analysis of paleoseismological trenches showed that indeed there are no recent earthquakes in the area, at least not any that caused significant ground deformations. Quantitative results regarding the dating of specific seismic events will be extrapolated after the results of 14C dating of selected samples from palaeoseismological trenches,currently under way, become available.

Investigation of random walks knee cartilage segmentation model using inter-observer reproducibility: Data from the osteoarthritis initiative.

PubMed

Hong-Seng, Gan; Sayuti, Khairil Amir; Karim, Ahmad Helmy Abdul

2017-01-01

Existing knee cartilage segmentation methods have reported several technical drawbacks. In essence, graph cuts remains highly susceptible to image noise despite extended research interest; active shape model is often constraint by the selection of training data while shortest path have demonstrated shortcut problem in the presence of weak boundary, which is a common problem in medical images. The aims of this study is to investigate the capability of random walks as knee cartilage segmentation method. Experts would scribble on knee cartilage image to initialize random walks segmentation. Then, reproducibility of the method is assessed against manual segmentation by using Dice Similarity Index. The evaluation consists of normal cartilage and diseased cartilage sections which is divided into whole and single cartilage categories. A total of 15 normal images and 10 osteoarthritic images were included. The results showed that random walks method has demonstrated high reproducibility in both normal cartilage (observer 1: 0.83±0.028 and observer 2: 0.82±0.026) and osteoarthritic cartilage (observer 1: 0.80±0.069 and observer 2: 0.83±0.029). Besides, results from both experts were found to be consistent with each other, suggesting the inter-observer variation is insignificant (Normal: P=0.21; Diseased: P=0.15). The proposed segmentation model has overcame technical problems reported by existing semi-automated techniques and demonstrated highly reproducible and consistent results against manual segmentation method.

Weakly supervised automatic segmentation and 3D modeling of the knee joint from MR images

NASA Astrophysics Data System (ADS)

Amami, Amal; Ben Azouz, Zouhour

2013-12-01

Automatic segmentation and 3D modeling of the knee joint from MR images, is a challenging task. Most of the existing techniques require the tedious manual segmentation of a training set of MRIs. We present an approach that necessitates the manual segmentation of one MR image. It is based on a volumetric active appearance model. First, a dense tetrahedral mesh is automatically created on a reference MR image that is arbitrary selected. Second, a pairwise non-rigid registration between each MRI from a training set and the reference MRI is computed. The non-rigid registration is based on a piece-wise affine deformation using the created tetrahedral mesh. The minimum description length is then used to bring all the MR images into a correspondence. An average image and tetrahedral mesh, as well as a set of main modes of variations, are generated using the established correspondence. Any manual segmentation of the average MRI can be mapped to other MR images using the AAM. The proposed approach has the advantage of simultaneously generating 3D reconstructions of the surface as well as a 3D solid model of the knee joint. The generated surfaces and tetrahedral meshes present the interesting property of fulfilling a correspondence between different MR images. This paper shows preliminary results of the proposed approach. It demonstrates the automatic segmentation and 3D reconstruction of a knee joint obtained by mapping a manual segmentation of a reference image.

Active edge control in the precessions polishing process for manufacturing large mirror segments

NASA Astrophysics Data System (ADS)

Li, Hongyu; Zhang, Wei; Walker, David; Yu, Gouyo

2014-09-01

The segmentation of the primary mirror is the only promising solution for building the next generation of ground telescopes. However, manufacturing segmented mirrors presents its own challenges. The edge mis-figure impacts directly on the telescope's scientific output. The `Edge effect' significantly dominates the polishing precision. Therefore, the edge control is regarded as one of the most difficult technical issues in the segment production that needs to be addressed urgently. This paper reports an active edge control technique for the mirror segments fabrication using the Precession's polishing technique. The strategy in this technique requires that the large spot be selected on the bulk area for fast polishing, and the small spot is used for edge figuring. This can be performed by tool lift and optimizing the dell time to compensate for non-uniform material removal at the edge zone. This requires accurate and stable edge tool influence functions. To obtain the full tool influence function at the edge, we have demonstrated in previous work a novel hybrid-measurement method which uses both simultaneous phase interferometry and profilometry. In this paper, the edge effect under `Bonnet tool' polishing is investigated. The pressure distribution is analyzed by means of finite element analysis (FEA). According to the `Preston' equation, the shape of the edge tool influence functions is predicted. With this help, the multiple process parameters at the edge zone are optimized. This is demonstrated on a 200mm crosscorners hexagonal part with a result of PV less than 200nm for entire surface.

Bacterial communities in different locations, seasons and segments of a dairy wastewater treatment system consisting of six segments.

PubMed

Hirota, Kikue; Yokota, Yuji; Sekimura, Toru; Uchiumi, Hiroshi; Guo, Yong; Ohta, Hiroyuki; Yumoto, Isao

2016-08-01

A dairy wastewater treatment system composed of the 1st segment (no aeration) equipped with a facility for the destruction of milk fat particles, four successive aerobic treatment segments with activated sludge and a final sludge settlement segment was developed. The activated sludge is circulated through the six segments by settling sediments (activated sludge) in the 6th segment and sending the sediments beck to the 1st and 2nd segments. Microbiota was examined using samples from the non-aerated 1st and aerated 2nd segments obtained from two farms using the same system in summer or winter. Principal component analysis showed that the change in microbiota from the 1st to 2nd segments concomitant with effective wastewater treatment is affected by the concentrations of activated sludge and organic matter (biological oxygen demand [BOD]), and dissolved oxygen (DO) content. Microbiota from five segments (1st and four successive aerobic segments) in one location was also examined. Although the activated sludge is circulating throughout all the segments, microbiota fluctuation was observed. The observed successive changes in microbiota reflected the changes in the concentrations of organic matter and other physicochemical conditions (such as DO), suggesting that the microbiota is flexibly changeable depending on the environmental condition in the segments. The genera Dechloromonas, Zoogloea and Leptothrix are frequently observed in this wastewater treatment system throughout the analyses of microbiota in this study. Copyright © 2016. Published by Elsevier B.V.

SU-E-J-128: Two-Stage Atlas Selection in Multi-Atlas-Based Image Segmentation

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

Zhao, T; Ruan, D

2015-06-15

Purpose: In the new era of big data, multi-atlas-based image segmentation is challenged by heterogeneous atlas quality and high computation burden from extensive atlas collection, demanding efficient identification of the most relevant atlases. This study aims to develop a two-stage atlas selection scheme to achieve computational economy with performance guarantee. Methods: We develop a low-cost fusion set selection scheme by introducing a preliminary selection to trim full atlas collection into an augmented subset, alleviating the need for extensive full-fledged registrations. More specifically, fusion set selection is performed in two successive steps: preliminary selection and refinement. An augmented subset is firstmore » roughly selected from the whole atlas collection with a simple registration scheme and the corresponding preliminary relevance metric; the augmented subset is further refined into the desired fusion set size, using full-fledged registration and the associated relevance metric. The main novelty of this work is the introduction of an inference model to relate the preliminary and refined relevance metrics, based on which the augmented subset size is rigorously derived to ensure the desired atlases survive the preliminary selection with high probability. Results: The performance and complexity of the proposed two-stage atlas selection method were assessed using a collection of 30 prostate MR images. It achieved comparable segmentation accuracy as the conventional one-stage method with full-fledged registration, but significantly reduced computation time to 1/3 (from 30.82 to 11.04 min per segmentation). Compared with alternative one-stage cost-saving approach, the proposed scheme yielded superior performance with mean and medium DSC of (0.83, 0.85) compared to (0.74, 0.78). Conclusion: This work has developed a model-guided two-stage atlas selection scheme to achieve significant cost reduction while guaranteeing high segmentation accuracy. The benefit in both complexity and performance is expected to be most pronounced with large-scale heterogeneous data.« less

A closer look at self-pay segmentation.

PubMed

Franklin, David; Ingramn, Coy; Levin, Steve

2010-09-01

Successful scoring approaches for self-pay accounts have three common characteristics: Thoughtful selection of a scoring model and segmentation approach. Deployment of workflows (either segmented or account prioritization) consistent with a hospital's capabilities and the likelihood of collection. Ongoing performance monitoring.

Automatic segmentation and supervised learning-based selection of nuclei in cancer tissue images.

PubMed

Nandy, Kaustav; Gudla, Prabhakar R; Amundsen, Ryan; Meaburn, Karen J; Misteli, Tom; Lockett, Stephen J

2012-09-01

Analysis of preferential localization of certain genes within the cell nuclei is emerging as a new technique for the diagnosis of breast cancer. Quantitation requires accurate segmentation of 100-200 cell nuclei in each tissue section to draw a statistically significant result. Thus, for large-scale analysis, manual processing is too time consuming and subjective. Fortuitously, acquired images generally contain many more nuclei than are needed for analysis. Therefore, we developed an integrated workflow that selects, following automatic segmentation, a subpopulation of accurately delineated nuclei for positioning of fluorescence in situ hybridization-labeled genes of interest. Segmentation was performed by a multistage watershed-based algorithm and screening by an artificial neural network-based pattern recognition engine. The performance of the workflow was quantified in terms of the fraction of automatically selected nuclei that were visually confirmed as well segmented and by the boundary accuracy of the well-segmented nuclei relative to a 2D dynamic programming-based reference segmentation method. Application of the method was demonstrated for discriminating normal and cancerous breast tissue sections based on the differential positioning of the HES5 gene. Automatic results agreed with manual analysis in 11 out of 14 cancers, all four normal cases, and all five noncancerous breast disease cases, thus showing the accuracy and robustness of the proposed approach. Published 2012 Wiley Periodicals, Inc.

Differential approach to strategies of segmental stabilisation in postural control.

PubMed

Isableu, Brice; Ohlmann, Théophile; Crémieux, Jacques; Amblard, Bernard

2003-05-01

The present paper attempts to clarify the between-subjects variability exhibited in both segmental stabilisation strategies and their subordinated or associated sensory contribution. Previous data have emphasised close relationships between the interindividual variability in both the visual control of posture and the spatial visual perception. In this study, we focused on the possible relationships that might link perceptual visual field dependence-independence and the visual contribution to segmental stabilisation strategies. Visual field dependent (FD) and field independent (FI) subjects were selected on the basis of their extreme score in a static rod and frame test where an estimation of the subjective vertical was required. In the postural test, the subjects stood in the sharpened Romberg position in darkness or under normal or stroboscopic illumination, in front of either a vertical or a tilted frame. Strategies of segmental stabilisation of the head, shoulders and hip in the roll plane were analysed by means of their anchoring index (AI). Our hypothesis was that FD subjects might use mainly visual cues for calibrating not only their spatial perception but also their strategies of segmental stabilisation. In the case of visual cue disturbances, a greater visual dependency to the strategies of segmental stabilisation in FD subjects should be validated by observing more systematic "en bloc" functioning (i.e. negative AI) between two adjacent segments. The main results are the following: 1. Strategies of segmental stabilisation differed between both groups and differences were amplified with the deprivation of either total vision and/or static visual cues. 2. In the absence of total vision and/or static visual cues, FD subjects have shown an increased efficiency of the hip stabilisation in space strategy and an "en bloc" operation of the shoulder-hip unit (whole trunk). The last "en bloc" operation was extended to the whole head-trunk unit in darkness, associated with a hip stabilisation in space. 3. The FI subjects have adopted neither a strategy of segmental stabilisation in space nor on the underlying segment, whatever the body segment considered and the visual condition. Thus, in this group, head, shoulder and hip moved independently from each other during stance control, roughly without taking into account the visual condition. The results, emphasising a differential weighting of sensory input involved in both perceptual and postural control, are discussed in terms of the differential choice and/or ability to select the adequate frame of reference common to both cognitive and motor spatial activities. We assumed that a motor-somesthetics "neglect" or a lack of mastering of these inputs/outputs rather than a mere visual dependence in FD subjects would generate these interindividual differences in both spatial perception and postural balance. This proprioceptive "neglect" is assumed to lead FD subjects to sensory reweighting, whereas proprioceptive dominance would lead FI subjects to a greater ability in selecting the adequate frame of reference in the case of intersensory disturbances. Finally, this study also provides evidence for a new interpretation of the visual field dependence-independence dimension in both spatial perception and postural control.

Thin film composition with biological substance and method of making

DOEpatents

Campbell, Allison A.; Song, Lin

1999-01-01

The invention provides a thin-film composition comprising an underlying substrate of a first material including a plurality of attachment sites; a plurality of functional groups chemically attached to the attachment sites of the underlying substrate; and a thin film of a second material deposited onto the attachment sites of the underlying substrate, and a biologically active substance deposited with the thin-film. Preferably the functional groups are attached to a self assembling monolayer attached to the underlying substrate. Preferred functional groups attached to the underlying substrate are chosen from the group consisting of carboxylates, sulfonates, phosphates, optionally substituted, linear or cyclo, alkyl, alkene, alkyne, aryl, alkylaryl, amine, hydroxyl, thiol, silyl, phosphoryl, cyano, metallocenyl, carbonyl, and polyphosphate. Preferred materials for the underlying substrate are selected from the group consisting of a metal, a metal alloy, a plastic, a polymer, a proteic film, a membrane, a glass or a ceramic. The second material is selected from the group consisting of inorganic crystalline structures, inorganic amorphus structures, organic crystalline structures, and organic amorphus structures. Preferred second materials are phosphates, especially calcium phosphates and most particularly calcium apatite. The biologically active molecule is a protein, peptide, DNA segment, RNA segment, nucleotide, polynucleotide, nucleoside, antibiotic, antimicrobal, radioisotope, chelated radioisotope, chelated metal, metal salt, anti-inflamatory, steriod, nonsteriod anti-inflammatory, analgesic, antihistamine, receptor binding agent, or chemotherapeutic agent, or other biologically active material. Preferably the biologically active molecule is an osteogenic factor the compositions listed above.

Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

NASA Astrophysics Data System (ADS)

Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

2013-12-01

The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

Gender differences in head-neck segment dynamic stabilization during head acceleration.

PubMed

Tierney, Ryan T; Sitler, Michael R; Swanik, C Buz; Swanik, Kathleen A; Higgins, Michael; Torg, Joseph

2005-02-01

Recent epidemiological research has revealed that gender differences exist in concussion incidence but no study has investigated why females may be at greater risk of concussion. Our purpose was to determine whether gender differences existed in head-neck segment kinematic and neuromuscular control variables responses to an external force application with and without neck muscle preactivation. Forty (20 females and 20 males) physically active volunteers participated in the study. The independent variables were gender, force application (known vs unknown), and force direction (forced flexion vs forced extension). The dependent variables were kinematic and EMG variables, head-neck segment stiffness, and head-neck segment flexor and extensor isometric strength. Statistical analyses consisted of multiple multivariate and univariate analyses of variance, follow-up univariate analyses of variance, and t-tests (P < or = 0.05). Gender differences existed in head-neck segment dynamic stabilization during head angular acceleration. Females exhibited significantly greater head-neck segment peak angular acceleration (50%) and displacement (39%) than males despite initiating muscle activity significantly earlier (SCM only) and using a greater percentage of their maximum head-neck segment muscle activity (79% peak activity and 117% muscle activity area). The head-neck segment angular acceleration differences may be because females exhibited significantly less isometric strength (49%), neck girth (30%), and head mass (43%), resulting in lower levels of head-neck segment stiffness (29%). For our subject demographic, the results revealed gender differences in head-neck segment dynamic stabilization during head acceleration in response to an external force application. Females exhibited significantly greater head-neck segment peak angular acceleration and displacement than males despite initiating muscle activity earlier (SCM only) and using a greater percentage of their maximum head-neck segment muscle activity.

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

The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation.

PubMed

Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

2015-12-23

The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy. In this study, the optimal number of selected atlases used was six, but for definitive conclusions about the optimal number of atlases and to improve the autosegmentation accuracy for clinical use, more atlases need to be included.

The prevalence of physical activity and its associated factors among Malaysian adults: findings from the National Health and Morbidity Survey 2011.

PubMed

Teh, C H; Lim, K K; Chan, Y Y; Lim, K H; Azahadi, O; Hamizatul Akmar, A H; Ummi Nadiah, Y; Syafinaz, M S; Kee, C C; Yeo, P S; Fadhli, Y

2014-05-01

Despite the health-enhancing benefits of physical activity, a large segment of the Malaysian population does not engage in regular physical activity at the recommended level. This study aimed to determine physical activity patterns and the associated sociodemographic correlates of physical activity. Data on physical activity were obtained from the National Health and Morbidity Survey (NHMS) 2011, a nationally representative, population-based cross-sectional study. A two-stage stratified sampling method was used to select a representative sample of Malaysian adults aged 16 years and above. A total of 19,145 adults aged 16 years and above were recruited, and face-to-face interviews were conducted using the International Physical Activity Questionnaire (IPAQ), short version. The correlates for physical activity were identified using multivariate analysis. In this study, 64.3% (95%CI: 63.1-65.5) of Malaysian adults aged 16 and above were physically active, but overall physical activity levels decreased with advancing age. Men, rural residents, 'other' ethnic groups, and married women were more likely to demonstrate higher levels of physical activity. Approximately 65% of Malaysian adults were physically active. However, it is recommended that health promotions for active lifestyles should be targeted to the least active segments, which constitute more than a quarter of the Malaysian population. Copyright © 2013 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

New Embedded Denotes Fuzzy C-Mean Application for Breast Cancer Density Segmentation in Digital Mammograms

NASA Astrophysics Data System (ADS)

Othman, Khairulnizam; Ahmad, Afandi

2016-11-01

In this research we explore the application of normalize denoted new techniques in advance fast c-mean in to the problem of finding the segment of different breast tissue regions in mammograms. The goal of the segmentation algorithm is to see if new denotes fuzzy c- mean algorithm could separate different densities for the different breast patterns. The new density segmentation is applied with multi-selection of seeds label to provide the hard constraint, whereas the seeds labels are selected based on user defined. New denotes fuzzy c- mean have been explored on images of various imaging modalities but not on huge format digital mammograms just yet. Therefore, this project is mainly focused on using normalize denoted new techniques employed in fuzzy c-mean to perform segmentation to increase visibility of different breast densities in mammography images. Segmentation of the mammogram into different mammographic densities is useful for risk assessment and quantitative evaluation of density changes. Our proposed methodology for the segmentation of mammograms on the basis of their region into different densities based categories has been tested on MIAS database and Trueta Database.

Thai Automatic Speech Recognition

DTIC Science & Technology

2005-01-01

used in an external DARPA evaluation involving medical scenarios between an American Doctor and a naïve monolingual Thai patient. 2. Thai Language... dictionary generation more challenging, and (3) the lack of word segmentation, which calls for automatic segmentation approaches to make n-gram language...requires a dictionary and provides various segmentation algorithms to automatically select suitable segmentations. Here we used a maximal matching

High-Throughput Identification of Loss-of-Function Mutations for Anti-Interferon Activity in the Influenza A Virus NS Segment

PubMed Central

Wu, Nicholas C.; Young, Arthur P.; Al-Mawsawi, Laith Q.; Olson, C. Anders; Feng, Jun; Qi, Hangfei; Luan, Harding H.; Li, Xinmin; Wu, Ting-Ting

2014-01-01

ABSTRACT Viral proteins often display several functions which require multiple assays to dissect their genetic basis. Here, we describe a systematic approach to screen for loss-of-function mutations that confer a fitness disadvantage under a specified growth condition. Our methodology was achieved by genetically monitoring a mutant library under two growth conditions, with and without interferon, by deep sequencing. We employed a molecular tagging technique to distinguish true mutations from sequencing error. This approach enabled us to identify mutations that were negatively selected against, in addition to those that were positively selected for. Using this technique, we identified loss-of-function mutations in the influenza A virus NS segment that were sensitive to type I interferon in a high-throughput fashion. Mechanistic characterization further showed that a single substitution, D92Y, resulted in the inability of NS to inhibit RIG-I ubiquitination. The approach described in this study can be applied under any specified condition for any virus that can be genetically manipulated. IMPORTANCE Traditional genetics focuses on a single genotype-phenotype relationship, whereas high-throughput genetics permits phenotypic characterization of numerous mutants in parallel. High-throughput genetics often involves monitoring of a mutant library with deep sequencing. However, deep sequencing suffers from a high error rate (∼0.1 to 1%), which is usually higher than the occurrence frequency for individual point mutations within a mutant library. Therefore, only mutations that confer a fitness advantage can be identified with confidence due to an enrichment in the occurrence frequency. In contrast, it is impossible to identify deleterious mutations using most next-generation sequencing techniques. In this study, we have applied a molecular tagging technique to distinguish true mutations from sequencing errors. It enabled us to identify mutations that underwent negative selection, in addition to mutations that experienced positive selection. This study provides a proof of concept by screening for loss-of-function mutations on the influenza A virus NS segment that are involved in its anti-interferon activity. PMID:24965464

Tempo and Mode in the Molecular Evolution of Influenza C

PubMed Central

Gatherer, Derek

2010-01-01

Abstract: Influenza C contributes to economic damage caused by working days lost through absence or inefficiency and may occasionally cause an acute respiratory illness in a paediatric setting. All Influenza C sequences from the NCBI Influenza Virus Resource were examined to determine the date of the most recent common ancestor (t-MRCA), the average nucleotide substitution rate, and the location of residues under positive selection, for each of the seven genome segments of this virus. The segment with the deepest phylogeny was found to be segment 4, encoding the haemagglutinin-esterase protein (HE) with mean t-MRCA at 1890 of the common era (AD), at a 95% highest posterior density (HPD) of 1857-1924 AD. Other genome segments have slightly more recent common ancestors, ranging from mean t-MRCAs of 1916 AD (HPD 1891-1937) for segment 7, encoding the two non-structural proteins (NS) to 1944 AD (HPD 1940-1948) for segment 2 encoding the type 1 basic polymerase (PB1). On the basis of the Bayesian analysis a reclassification of lineages within genome segments is proposed. Some evidence for positive selection was found in the receptor-binding domain of the haemagglutinin-esterase protein. However, average ω (omega) values ranged from 0.05 for polymerase basic protein 2 (PB2) to 0.38 for non-structural protein 2 (NS2), suggesting that strong to moderate purifying selection is the main trend. Characteristic combinations of segment lineages were identified (genome constellations) and shown to have a relatively short life-span before being broken up by reassortment. PMID:21127722

Label fusion based brain MR image segmentation via a latent selective model

NASA Astrophysics Data System (ADS)

Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

2018-04-01

Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

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.

Event segmentation improves event memory up to one month later.

PubMed

Flores, Shaney; Bailey, Heather R; Eisenberg, Michelle L; Zacks, Jeffrey M

2017-08-01

When people observe everyday activity, they spontaneously parse it into discrete meaningful events. Individuals who segment activity in a more normative fashion show better subsequent memory for the events. If segmenting events effectively leads to better memory, does asking people to attend to segmentation improve subsequent memory? To answer this question, participants viewed movies of naturalistic activity with instructions to remember the activity for a later test, and in some conditions additionally pressed a button to segment the movies into meaningful events or performed a control condition that required button-pressing but not attending to segmentation. In 5 experiments, memory for the movies was assessed at intervals ranging from immediately following viewing to 1 month later. Performing the event segmentation task led to superior memory at delays ranging from 10 min to 1 month. Further, individual differences in segmentation ability predicted individual differences in memory performance for up to a month following encoding. This study provides the first evidence that manipulating event segmentation affects memory over long delays and that individual differences in event segmentation are related to differences in memory over long delays. These effects suggest that attending to how an activity breaks down into meaningful events contributes to memory formation. Instructing people to more effectively segment events may serve as a potential intervention to alleviate everyday memory complaints in aging and clinical populations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements.

PubMed

van Pelt, Roy; Nguyen, Huy; ter Haar Romeny, Bart; Vilanova, Anna

2012-03-01

Quantitative analysis of vascular blood flow, acquired by phase-contrast MRI, requires accurate segmentation of the vessel lumen. In clinical practice, 2D-cine velocity-encoded slices are inspected, and the lumen is segmented manually. However, segmentation of time-resolved volumetric blood-flow measurements is a tedious and time-consuming task requiring automation. Automated segmentation of large thoracic arteries, based solely on the 3D-cine phase-contrast MRI (PC-MRI) blood-flow data, was done. An active surface model, which is fast and topologically stable, was used. The active surface model requires an initial surface, approximating the desired segmentation. A method to generate this surface was developed based on a voxel-wise temporal maximum of blood-flow velocities. The active surface model balances forces, based on the surface structure and image features derived from the blood-flow data. The segmentation results were validated using volunteer studies, including time-resolved 3D and 2D blood-flow data. The segmented surface was intersected with a velocity-encoded PC-MRI slice, resulting in a cross-sectional contour of the lumen. These cross-sections were compared to reference contours that were manually delineated on high-resolution 2D-cine slices. The automated approach closely approximates the manual blood-flow segmentations, with error distances on the order of the voxel size. The initial surface provides a close approximation of the desired luminal geometry. This improves the convergence time of the active surface and facilitates parametrization. An active surface approach for vessel lumen segmentation was developed, suitable for quantitative analysis of 3D-cine PC-MRI blood-flow data. As opposed to prior thresholding and level-set approaches, the active surface model is topologically stable. A method to generate an initial approximate surface was developed, and various features that influence the segmentation model were evaluated. The active surface segmentation results were shown to closely approximate manual segmentations.

Marketing ambulatory care to women: a segmentation approach.

PubMed

Harrell, G D; Fors, M F

1985-01-01

Although significant changes are occurring in health care delivery, in many instances the new offerings are not based on a clear understanding of market segments being served. This exploratory study suggests that important differences may exist among women with regard to health care selection. Five major women's segments are identified for consideration by health care executives in developing marketing strategies. Additional research is suggested to confirm this segmentation hypothesis, validate segmental differences and quantify the findings.

A novel mechanism of sugar selection utilized by a human X-family DNA polymerase.

PubMed

Brown, Jessica A; Fiala, Kevin A; Fowler, Jason D; Sherrer, Shanen M; Newmister, Sean A; Duym, Wade W; Suo, Zucai

2010-01-15

During DNA synthesis, most DNA polymerases and reverse transcriptases select against ribonucleotides via a steric clash between the ribose 2'-hydroxyl group and the bulky side chain of an active-site residue. In this study, we demonstrated that human DNA polymerase lambda used a novel sugar selection mechanism to discriminate against ribonucleotides, whereby the ribose 2'-hydroxyl group was excluded mostly by a backbone segment and slightly by the side chain of Y505. Such steric clash was further demonstrated to be dependent on the size and orientation of the substituent covalently attached at the ribonucleotide C2'-position. Copyright 2009 Elsevier Ltd. All rights reserved.

Segmented ceramic liner for induction furnaces

DOEpatents

Gorin, Andrew H.; Holcombe, Cressie E.

1994-01-01

A non-fibrous ceramic liner for induction furnaces is provided by vertically stackable ring-shaped liner segments made of ceramic material in a light-weight cellular form. The liner segments can each be fabricated as a single unit or from a plurality of arcuate segments joined together by an interlocking mechanism. Also, the liner segments can be formed of a single ceramic material or can be constructed of multiple concentric layers with the layers being of different ceramic materials and/or cellular forms. Thermomechanically damaged liner segments are selectively replaceable in the furnace.

Segmented ceramic liner for induction furnaces

DOEpatents

Gorin, A.H.; Holcombe, C.E.

1994-07-26

A non-fibrous ceramic liner for induction furnaces is provided by vertically stackable ring-shaped liner segments made of ceramic material in a light-weight cellular form. The liner segments can each be fabricated as a single unit or from a plurality of arcuate segments joined together by an interlocking mechanism. Also, the liner segments can be formed of a single ceramic material or can be constructed of multiple concentric layers with the layers being of different ceramic materials and/or cellular forms. Thermomechanically damaged liner segments are selectively replaceable in the furnace. 5 figs.

Choice-Based Segmentation as an Enrollment Management Tool

ERIC Educational Resources Information Center

Young, Mark R.

2002-01-01

This article presents an approach to enrollment management based on target marketing strategies developed from a choice-based segmentation methodology. Students are classified into "switchable" or "non-switchable" segments based on their probability of selecting specific majors. A modified multinomial logit choice model is used to identify…

syn-Selective crotylation of aldehydes using bismuth-crotyl bromide-(1-butyl-3-methylimidazolium bromide) combination: some synthetic applications.

PubMed

Goswami, Dibakar; Koli, Mrunesh R; Chatterjee, Sucheta; Chattopadhyay, Subrata; Sharma, Anubha

2017-05-03

The Bi-[bmim][Br] combination has been found to offer high syn-selectivity in the crotylation of aldehydes with crotyl bromide using practically stoichiometric amounts of the reagents. The room temperature ionic liquid (RTIL), [bmim][Br], activated Bi metal in the presence of oxygen to produce crotylbismuthdibromide, which reacted with the aldehydes at room temperature. The major anti-syn diastereomeric product obtained from the crotylation of (R)-cyclohexylideneglyceraldehyde was utilized for the synthesis of dictyostatin and cryptophycin segments, and (+)-cis-aerangis lactone, using standard synthetic protocols.

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.

Current density distributions, field distributions and impedance analysis of segmented deep brain stimulation electrodes

NASA Astrophysics Data System (ADS)

Wei, Xuefeng F.; Grill, Warren M.

2005-12-01

Deep brain stimulation (DBS) electrodes are designed to stimulate specific areas of the brain. The most widely used DBS electrode has a linear array of 4 cylindrical contacts that can be selectively turned on depending on the placement of the electrode and the specific area of the brain to be stimulated. The efficacy of DBS therapy can be improved by localizing the current delivery into specific populations of neurons and by increasing the power efficiency through a suitable choice of electrode geometrical characteristics. We investigated segmented electrode designs created by sectioning each cylindrical contact into multiple rings. Prototypes of these designs, made with different materials and larger dimensions than those of clinical DBS electrodes, were evaluated in vitro and in simulation. A finite element model was developed to study the effects of varying the electrode characteristics on the current density and field distributions in an idealized electrolytic medium and in vitro experiments were conducted to measure the electrode impedance. The current density over the electrode surface increased towards the edges of the electrode, and multiple edges increased the non-uniformity of the current density profile. The edge effects were more pronounced over the end segments than over the central segments. Segmented electrodes generated larger magnitudes of the second spatial difference of the extracellular potentials, and thus required lower stimulation intensities to achieve the same level of neuronal activation as solid electrodes. For a fixed electrode conductive area, increasing the number of segments (edges) decreased the impedance compared to a single solid electrode, because the average current density over the segments increased. Edge effects played a critical role in determining the current density distributions, neuronal excitation patterns, and impedance of cylindrical electrodes, and segmented electrodes provide a means to increase the efficiency of DBS.

An interactive toolbox for atlas-based segmentation and coding of volumetric images

NASA Astrophysics Data System (ADS)

Menegaz, G.; Luti, S.; Duay, V.; Thiran, J.-Ph.

2007-03-01

Medical imaging poses the great challenge of having compression algorithms that are lossless for diagnostic and legal reasons and yet provide high compression rates for reduced storage and transmission time. The images usually consist of a region of interest representing the part of the body under investigation surrounded by a "background", which is often noisy and not of diagnostic interest. In this paper, we propose a ROI-based 3D coding system integrating both the segmentation and the compression tools. The ROI is extracted by an atlas based 3D segmentation method combining active contours with information theoretic principles, and the resulting segmentation map is exploited for ROI based coding. The system is equipped with a GUI allowing the medical doctors to supervise the segmentation process and eventually reshape the detected contours at any point. The process is initiated by the user through the selection of either one pre-de.ned reference image or one image of the volume to be used as the 2D "atlas". The object contour is successively propagated from one frame to the next where it is used as the initial border estimation. In this way, the entire volume is segmented based on a unique 2D atlas. The resulting 3D segmentation map is exploited for adaptive coding of the different image regions. Two coding systems were considered: the JPEG3D standard and the 3D-SPITH. The evaluation of the performance with respect to both segmentation and coding proved the high potential of the proposed system in providing an integrated, low-cost and computationally effective solution for CAD and PAC systems.

News video story segmentation method using fusion of audio-visual features

NASA Astrophysics Data System (ADS)

Wen, Jun; Wu, Ling-da; Zeng, Pu; Luan, Xi-dao; Xie, Yu-xiang

2007-11-01

News story segmentation is an important aspect for news video analysis. This paper presents a method for news video story segmentation. Different form prior works, which base on visual features transform, the proposed technique uses audio features as baseline and fuses visual features with it to refine the results. At first, it selects silence clips as audio features candidate points, and selects shot boundaries and anchor shots as two kinds of visual features candidate points. Then this paper selects audio feature candidates as cues and develops different fusion method, which effectively using diverse type visual candidates to refine audio candidates, to get story boundaries. Experiment results show that this method has high efficiency and adaptability to different kinds of news video.

Design, selection, and characterization of a split chorismate mutase

PubMed Central

Müller, Manuel M; Kries, Hajo; Csuhai, Eva; Kast, Peter; Hilvert, Donald

2010-01-01

Split proteins are versatile tools for detecting protein–protein interactions and studying protein folding. Here, we report a new, particularly small split enzyme, engineered from a thermostable chorismate mutase (CM). Upon dissecting the helical-bundle CM from Methanococcus jannaschii into a short N-terminal helix and a 3-helix segment and attaching an antiparallel leucine zipper dimerization domain to the individual fragments, we obtained a weakly active heterodimeric mutase. Using combinatorial mutagenesis and in vivo selection, we optimized the short linker sequences connecting the leucine zipper to the enzyme domain. One of the selected CMs was characterized in detail. It spontaneously assembles from the separately inactive fragments and exhibits wild-type like CM activity. Owing to the availability of a well characterized selection system, the simple 4-helix bundle topology, and the small size of the N-terminal helix, the heterodimeric CM could be a valuable scaffold for enzyme engineering efforts and as a split sensor for specifically oriented protein–protein interactions. PMID:20306491

The Brain's Cutting-Room Floor: Segmentation of Narrative Cinema

PubMed Central

Zacks, Jeffrey M.; Speer, Nicole K.; Swallow, Khena M.; Maley, Corey J.

2010-01-01

Observers segment ongoing activity into meaningful events. Segmentation is a core component of perception that helps determine memory and guide planning. The current study tested the hypotheses that event segmentation is an automatic component of the perception of extended naturalistic activity, and that the identification of event boundaries in such activities results in part from processing changes in the perceived situation. Observers may identify boundaries between events as a result of processing changes in the observed situation. To test this hypothesis and study this potential mechanism, we measured brain activity while participants viewed an extended narrative film. Large transient responses were observed when the activity was segmented, and these responses were mediated by changes in the observed activity, including characters and their interactions, interactions with objects, spatial location, goals, and causes. These results support accounts that propose event segmentation is automatic and depends on processing meaningful changes in the perceived situation; they are the first to show such effects for extended naturalistic human activity. PMID:20953234

Integrated β-catenin, BMP, PTEN, and Notch signalling patterns the nephron.

PubMed

Lindström, Nils O; Lawrence, Melanie L; Burn, Sally F; Johansson, Jeanette A; Bakker, Elvira R M; Ridgway, Rachel A; Chang, C-Hong; Karolak, Michele J; Oxburgh, Leif; Headon, Denis J; Sansom, Owen J; Smits, Ron; Davies, Jamie A; Hohenstein, Peter

2015-02-03

The different segments of the nephron and glomerulus in the kidney balance the processes of water homeostasis, solute recovery, blood filtration, and metabolite excretion. When segment function is disrupted, a range of pathological features are presented. Little is known about nephron patterning during embryogenesis. In this study, we demonstrate that the early nephron is patterned by a gradient in β-catenin activity along the axis of the nephron tubule. By modifying β-catenin activity, we force cells within nephrons to differentiate according to the imposed β-catenin activity level, thereby causing spatial shifts in nephron segments. The β-catenin signalling gradient interacts with the BMP pathway which, through PTEN/PI3K/AKT signalling, antagonises β-catenin activity and promotes segment identities associated with low β-catenin activity. β-catenin activity and PI3K signalling also integrate with Notch signalling to control segmentation: modulating β-catenin activity or PI3K rescues segment identities normally lost by inhibition of Notch. Our data therefore identifies a molecular network for nephron patterning.

Multiresolution multiscale active mask segmentation of fluorescence microscope images

NASA Astrophysics Data System (ADS)

Srinivasa, Gowri; Fickus, Matthew; Kovačević, Jelena

2009-08-01

We propose an active mask segmentation framework that combines the advantages of statistical modeling, smoothing, speed and flexibility offered by the traditional methods of region-growing, multiscale, multiresolution and active contours respectively. At the crux of this framework is a paradigm shift from evolving contours in the continuous domain to evolving multiple masks in the discrete domain. Thus, the active mask framework is particularly suited to segment digital images. We demonstrate the use of the framework in practice through the segmentation of punctate patterns in fluorescence microscope images. Experiments reveal that statistical modeling helps the multiple masks converge from a random initial configuration to a meaningful one. This obviates the need for an involved initialization procedure germane to most of the traditional methods used to segment fluorescence microscope images. While we provide the mathematical details of the functions used to segment fluorescence microscope images, this is only an instantiation of the active mask framework. We suggest some other instantiations of the framework to segment different types of images.

Estimates of internal-dose equivalent from inhalation and ingestion of selected radionuclides

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

Dunning, D.E.

1982-01-01

This report presents internal radiation dose conversion factors for radionuclides of interest in environmental assessments of nuclear fuel cycles. This volume provides an updated summary of estimates of committed dose equivalent for radionuclides considered in three previous Oak Ridge National Laboratory (ORNL) reports. Intakes by inhalation and ingestion are considered. The International Commission on Radiological Protection (ICRP) Task Group Lung Model has been used to simulate the deposition and retention of particulate matter in the respiratory tract. Results corresponding to activity median aerodynamic diameters (AMAD) of 0.3, 1.0, and 5.0 ..mu..m are given. The gastorintestinal (GI) tract has been representedmore » by a four-segment catenary model with exponential transfer of radioactivity from one segment to the next. Retention of radionuclides in systemic organs is characterized by linear combinations of decaying exponential functions, recommended in ICRP Publication 30. The first-year annual dose rate, maximum annual dose rate, and fifty-year dose commitment per microcurie intake of each radionuclide is given for selected target organs and the effective dose equivalent. These estimates include contributions from specified source organs plus the systemic activity residing in the rest of the body; cross irradiation due to penetrating radiations has been incorporated into these estimates. 15 references.« less

Auto detection and segmentation of physical activities during a Timed-Up-and-Go (TUG) task in healthy older adults using multiple inertial sensors.

PubMed

Nguyen, Hung P; Ayachi, Fouaz; Lavigne-Pelletier, Catherine; Blamoutier, Margaux; Rahimi, Fariborz; Boissy, Patrick; Jog, Mandar; Duval, Christian

2015-04-11

Recently, much attention has been given to the use of inertial sensors for remote monitoring of individuals with limited mobility. However, the focus has been mostly on the detection of symptoms, not specific activities. The objective of the present study was to develop an automated recognition and segmentation algorithm based on inertial sensor data to identify common gross motor patterns during activity of daily living. A modified Time-Up-And-Go (TUG) task was used since it is comprised of four common daily living activities; Standing, Walking, Turning, and Sitting, all performed in a continuous fashion resulting in six different segments during the task. Sixteen healthy older adults performed two trials of a 5 and 10 meter TUG task. They were outfitted with 17 inertial motion sensors covering each body segment. Data from the 10 meter TUG were used to identify pertinent sensors on the trunk, head, hip, knee, and thigh that provided suitable data for detecting and segmenting activities associated with the TUG. Raw data from sensors were detrended to remove sensor drift, normalized, and band pass filtered with optimal frequencies to reveal kinematic peaks that corresponded to different activities. Segmentation was accomplished by identifying the time stamps of the first minimum or maximum to the right and the left of these peaks. Segmentation time stamps were compared to results from two examiners visually segmenting the activities of the TUG. We were able to detect these activities in a TUG with 100% sensitivity and specificity (n = 192) during the 10 meter TUG. The rate of success was subsequently confirmed in the 5 meter TUG (n = 192) without altering the parameters of the algorithm. When applying the segmentation algorithms to the 10 meter TUG, we were able to parse 100% of the transition points (n = 224) between different segments that were as reliable and less variable than visual segmentation performed by two independent examiners. The present study lays the foundation for the development of a comprehensive algorithm to detect and segment naturalistic activities using inertial sensors, in hope of evaluating automatically motor performance within the detected tasks.

A Typology of Middle School Girls: Audience Segmentation Related to Physical Activity

PubMed Central

Staten, Lisa K.; Birnbaum, Amanda S.; Jobe, Jared B.; Elder, John P.

2008-01-01

The Trial of Activity for Adolescent Girls (TAAG) combines social ecological and social marketing approaches to promote girls’ participation in physical activity programs implemented at 18 middle schools throughout the United States. Key to the TAAG approach is targeting materials to a variety of audience segments. TAAG segments are individuals who share one or more common characteristic that is expected to correlate with physical activity. Thirteen focus groups with seventh and eighth grade girls were conducted to identify and characterize segments. Potential messages and channels of communication were discussed for each segment. Based on participant responses, six primary segments were identified: athletic, preppy, quiet, rebel, smart, and tough. The focus group information was used to develop targeted promotional tools to appeal to a diversity of girls. Using audience segmentation for targeting persuasive communication is potentially useful for intervention programs but may be sensitive; therefore, ethical issues must be critically examined. PMID:16397160

A typology of middle school girls: audience segmentation related to physical activity.

PubMed

Staten, Lisa K; Birnbaum, Amanda S; Jobe, Jared B; Elder, John P

2006-02-01

The Trial of Activity for Adolescent Girls (TAAG) combines social ecological and social marketing approaches to promote girls' participation in physical activity programs implemented at 18 middle schools throughout the United States. Key to the TAAG approach is targeting materials to a variety of audience segments. TAAG segments are individuals who share one or more common characteristic that is expected to correlate with physical activity. Thirteen focus groups with seventh and eighth grade girls were conducted to identify and characterize segments. Potential messages and channels of communication were discussed for each segment. Based on participant responses, six primary segments were identified: athletic, preppy, quiet, rebel, smart, and tough. The focus group information was used to develop targeted promotional tools to appeal to a diversity of girls. Using audience segmentation for targeting persuasive communication is potentially useful for intervention programs but may be sensitive; therefore, ethical issues must be critically examined.

Marketing Education Through Benefit Segmentation. AIR Forum 1981 Paper.

ERIC Educational Resources Information Center

Goodnow, Wilma Elizabeth

The applicability of the "benefit segmentation" marketing technique to education was tested at the College of DuPage in 1979. Benefit segmentation identified target markets homogeneous in benefits expected from a program offering and may be useful in combatting declining enrollments. The 487 randomly selected students completed the 223…

Techniques to derive geometries for image-based Eulerian computations

PubMed Central

Dillard, Seth; Buchholz, James; Vigmostad, Sarah; Kim, Hyunggun; Udaykumar, H.S.

2014-01-01

Purpose The performance of three frequently used level set-based segmentation methods is examined for the purpose of defining features and boundary conditions for image-based Eulerian fluid and solid mechanics models. The focus of the evaluation is to identify an approach that produces the best geometric representation from a computational fluid/solid modeling point of view. In particular, extraction of geometries from a wide variety of imaging modalities and noise intensities, to supply to an immersed boundary approach, is targeted. Design/methodology/approach Two- and three-dimensional images, acquired from optical, X-ray CT, and ultrasound imaging modalities, are segmented with active contours, k-means, and adaptive clustering methods. Segmentation contours are converted to level sets and smoothed as necessary for use in fluid/solid simulations. Results produced by the three approaches are compared visually and with contrast ratio, signal-to-noise ratio, and contrast-to-noise ratio measures. Findings While the active contours method possesses built-in smoothing and regularization and produces continuous contours, the clustering methods (k-means and adaptive clustering) produce discrete (pixelated) contours that require smoothing using speckle-reducing anisotropic diffusion (SRAD). Thus, for images with high contrast and low to moderate noise, active contours are generally preferable. However, adaptive clustering is found to be far superior to the other two methods for images possessing high levels of noise and global intensity variations, due to its more sophisticated use of local pixel/voxel intensity statistics. Originality/value It is often difficult to know a priori which segmentation will perform best for a given image type, particularly when geometric modeling is the ultimate goal. This work offers insight to the algorithm selection process, as well as outlining a practical framework for generating useful geometric surfaces in an Eulerian setting. PMID:25750470

Optimizing the 3D-reconstruction technique for serial block-face scanning electron microscopy.

PubMed

Wernitznig, Stefan; Sele, Mariella; Urschler, Martin; Zankel, Armin; Pölt, Peter; Rind, F Claire; Leitinger, Gerd

2016-05-01

Elucidating the anatomy of neuronal circuits and localizing the synaptic connections between neurons, can give us important insights in how the neuronal circuits work. We are using serial block-face scanning electron microscopy (SBEM) to investigate the anatomy of a collision detection circuit including the Lobula Giant Movement Detector (LGMD) neuron in the locust, Locusta migratoria. For this, thousands of serial electron micrographs are produced that allow us to trace the neuronal branching pattern. The reconstruction of neurons was previously done manually by drawing cell outlines of each cell in each image separately. This approach was very time consuming and troublesome. To make the process more efficient a new interactive software was developed. It uses the contrast between the neuron under investigation and its surrounding for semi-automatic segmentation. For segmentation the user sets starting regions manually and the algorithm automatically selects a volume within the neuron until the edges corresponding to the neuronal outline are reached. Internally the algorithm optimizes a 3D active contour segmentation model formulated as a cost function taking the SEM image edges into account. This reduced the reconstruction time, while staying close to the manual reference segmentation result. Our algorithm is easy to use for a fast segmentation process, unlike previous methods it does not require image training nor an extended computing capacity. Our semi-automatic segmentation algorithm led to a dramatic reduction in processing time for the 3D-reconstruction of identified neurons. Copyright © 2016 Elsevier B.V. All rights reserved.

Random forest feature selection approach for image segmentation

NASA Astrophysics Data System (ADS)

Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina; Vaida, Mircea Florin

2017-03-01

In the field of image segmentation, discriminative models have shown promising performance. Generally, every such model begins with the extraction of numerous features from annotated images. Most authors create their discriminative model by using many features without using any selection criteria. A more reliable model can be built by using a framework that selects the important variables, from the point of view of the classification, and eliminates the unimportant once. In this article we present a framework for feature selection and data dimensionality reduction. The methodology is built around the random forest (RF) algorithm and its variable importance evaluation. In order to deal with datasets so large as to be practically unmanageable, we propose an algorithm based on RF that reduces the dimension of the database by eliminating irrelevant features. Furthermore, this framework is applied to optimize our discriminative model for brain tumor segmentation.

Comparison of the effects of isobutylmethylxanthine and milrinone on ischaemia-induced arrhythmias and platelet aggregation in anaesthetized rabbits.

PubMed Central

Holbrook, M.; Coker, S. J.

1989-01-01

1. The aim of this study was to compare the effects of the non-selective phosphodiesterase (PDE) inhibitor, isobutylmethylxanthine (IBMX) and the selective PDE III inhibitor, milrinone, in a rabbit model of acute myocardial ischaemia. 2. Coronary artery occlusion caused changes in the ST-segment of the ECG and ectopic activity in all control rabbits. Ventricular fibrillation occurred in 10 out of 14 (71%) of these animals. Pretreatment with IBMX 100 micrograms kg-1 plus 10 micrograms kg-1 min-1, starting 10 min before coronary artery occlusion, reduced ischaemia-induced ST-segment changes and ventricular fibrillation occurred in only 10% of this group (n = 10). A similar dose of milrinone had no antiarrhythmic activity, whereas with a lower dose of milrinone, 30 micrograms kg-1 plus 3 micrograms kg-1 min-1 (n = 10), only 30% of rabbits fibrillated and ST-segment changes were attenuated. 3. Acute administration of both IBMX and milrinone reduced arterial blood pressure. With the higher dose of milrinone a significant effect was still present after 10 min of drug infusion. A greater hypotensive response to the higher dose of milrinone was observed in the rabbits which subsequently fibrillated during ischaemia. A marked tachycardia was also observed after administration of the higher dose of milrinone. 4. At the end of the experiment platelet aggregation was studied ex vivo. ADP-induced aggregation was reduced by pretreatment of the rabbits with milrinone but not IBMX. Both PDE inhibitors enhanced the ability of isoprenaline to inhibit ADP-induced platelet aggregation but milrinone was more effective, particularly at the higher dose.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:2478245

Event Segmentation Improves Event Memory up to One Month Later

ERIC Educational Resources Information Center

Flores, Shaney; Bailey, Heather R.; Eisenberg, Michelle L.; Zacks, Jeffrey M.

2017-01-01

When people observe everyday activity, they spontaneously parse it into discrete meaningful events. Individuals who segment activity in a more normative fashion show better subsequent memory for the events. If segmenting events effectively leads to better memory, does asking people to attend to segmentation improve subsequent memory? To answer…

Automatic segmentation of lung parenchyma based on curvature of ribs using HRCT images in scleroderma studies

NASA Astrophysics Data System (ADS)

Prasad, M. N.; Brown, M. S.; Ahmad, S.; Abtin, F.; Allen, J.; da Costa, I.; Kim, H. J.; McNitt-Gray, M. F.; Goldin, J. G.

2008-03-01

Segmentation of lungs in the setting of scleroderma is a major challenge in medical image analysis. Threshold based techniques tend to leave out lung regions that have increased attenuation, for example in the presence of interstitial lung disease or in noisy low dose CT scans. The purpose of this work is to perform segmentation of the lungs using a technique that selects an optimal threshold for a given scleroderma patient by comparing the curvature of the lung boundary to that of the ribs. Our approach is based on adaptive thresholding and it tries to exploit the fact that the curvature of the ribs and the curvature of the lung boundary are closely matched. At first, the ribs are segmented and a polynomial is used to represent the ribs' curvature. A threshold value to segment the lungs is selected iteratively such that the deviation of the lung boundary from the polynomial is minimized. A Naive Bayes classifier is used to build the model for selection of the best fitting lung boundary. The performance of the new technique was compared against a standard approach using a simple fixed threshold of -400HU followed by regiongrowing. The two techniques were evaluated against manual reference segmentations using a volumetric overlap fraction (VOF) and the adaptive threshold technique was found to be significantly better than the fixed threshold technique.

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

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

Park, Sang Hyun; Gao, Yaozong, E-mail: yzgao@cs.unc.edu; Shi, Yinghuan, E-mail: syh@nju.edu.cn

Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correctmore » the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency and the robustness. The automatic segmentation results with the original average Dice similarity coefficient of 0.78 were improved to 0.865–0.872 after conducting 55–59 interactions by using the proposed method, where each editing procedure took less than 3 s. In addition, the proposed method obtained the most consistent editing results with respect to different user interactions, compared to other methods. Conclusions: The proposed method obtains robust editing results with few interactions for various wrong segmentation cases, by selecting the location-adaptive features and further imposing the manifold regularization. The authors expect the proposed method to largely reduce the laborious burdens of manual editing, as well as both the intra- and interobserver variability across clinicians.« less

Scene segmentation by spike synchronization in reciprocally connected visual areas. I. Local effects of cortical feedback.

PubMed

Knoblauch, Andreas; Palm, Günther

2002-09-01

To investigate scene segmentation in the visual system we present a model of two reciprocally connected visual areas using spiking neurons. Area P corresponds to the orientation-selective subsystem of the primary visual cortex, while the central visual area C is modeled as associative memory representing stimulus objects according to Hebbian learning. Without feedback from area C, a single stimulus results in relatively slow and irregular activity, synchronized only for neighboring patches (slow state), while in the complete model activity is faster with an enlarged synchronization range (fast state). When presenting a superposition of several stimulus objects, scene segmentation happens on a time scale of hundreds of milliseconds by alternating epochs of the slow and fast states, where neurons representing the same object are simultaneously in the fast state. Correlation analysis reveals synchronization on different time scales as found in experiments (designated as tower, castle, and hill peaks). On the fast time scale (tower peaks, gamma frequency range), recordings from two sites coding either different or the same object lead to correlograms that are either flat or exhibit oscillatory modulations with a central peak. This is in agreement with experimental findings, whereas standard phase-coding models would predict shifted peaks in the case of different objects.

Automatic exudate detection by fusing multiple active contours and regionwise classification.

PubMed

Harangi, Balazs; Hajdu, Andras

2014-11-01

In this paper, we propose a method for the automatic detection of exudates in digital fundus images. Our approach can be divided into three stages: candidate extraction, precise contour segmentation and the labeling of candidates as true or false exudates. For candidate detection, we borrow a grayscale morphology-based method to identify possible regions containing these bright lesions. Then, to extract the precise boundary of the candidates, we introduce a complex active contour-based method. Namely, to increase the accuracy of segmentation, we extract additional possible contours by taking advantage of the diverse behavior of different pre-processing methods. After selecting an appropriate combination of the extracted contours, a region-wise classifier is applied to remove the false exudate candidates. For this task, we consider several region-based features, and extract an appropriate feature subset to train a Naïve-Bayes classifier optimized further by an adaptive boosting technique. Regarding experimental studies, the method was tested on publicly available databases both to measure the accuracy of the segmentation of exudate regions and to recognize their presence at image-level. In a proper quantitative evaluation on publicly available datasets the proposed approach outperformed several state-of-the-art exudate detector algorithms. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

A Market Segmentation Approach for Higher Education Based on Rational and Emotional Factors

ERIC Educational Resources Information Center

Angulo, Fernando; Pergelova, Albena; Rialp, Josep

2010-01-01

Market segmentation is an important topic for higher education administrators and researchers. For segmenting the higher education market, we have to understand what factors are important for high school students in selecting a university. Extant literature has probed the importance of rational factors such as teaching staff, campus facilities,…

Semi-automated segmentation of neuroblastoma nuclei using the gradient energy tensor: a user driven approach

NASA Astrophysics Data System (ADS)

Kromp, Florian; Taschner-Mandl, Sabine; Schwarz, Magdalena; Blaha, Johanna; Weiss, Tamara; Ambros, Peter F.; Reiter, Michael

2015-02-01

We propose a user-driven method for the segmentation of neuroblastoma nuclei in microscopic fluorescence images involving the gradient energy tensor. Multispectral fluorescence images contain intensity and spatial information about antigene expression, fluorescence in situ hybridization (FISH) signals and nucleus morphology. The latter serves as basis for the detection of single cells and the calculation of shape features, which are used to validate the segmentation and to reject false detections. Accurate segmentation is difficult due to varying staining intensities and aggregated cells. It requires several (meta-) parameters, which have a strong influence on the segmentation results and have to be selected carefully for each sample (or group of similar samples) by user interactions. Because our method is designed for clinicians and biologists, who may have only limited image processing background, an interactive parameter selection step allows the implicit tuning of parameter values. With this simple but intuitive method, segmentation results with high precision for a large number of cells can be achieved by minimal user interaction. The strategy was validated on handsegmented datasets of three neuroblastoma cell lines.

Chain-Wise Generalization of Road Networks Using Model Selection

NASA Astrophysics Data System (ADS)

Bulatov, D.; Wenzel, S.; Häufel, G.; Meidow, J.

2017-05-01

Streets are essential entities of urban terrain and their automatized extraction from airborne sensor data is cumbersome because of a complex interplay of geometric, topological and semantic aspects. Given a binary image, representing the road class, centerlines of road segments are extracted by means of skeletonization. The focus of this paper lies in a well-reasoned representation of these segments by means of geometric primitives, such as straight line segments as well as circle and ellipse arcs. We propose the fusion of raw segments based on similarity criteria; the output of this process are the so-called chains which better match to the intuitive perception of what a street is. Further, we propose a two-step approach for chain-wise generalization. First, the chain is pre-segmented using circlePeucker and finally, model selection is used to decide whether two neighboring segments should be fused to a new geometric entity. Thereby, we consider both variance-covariance analysis of residuals and model complexity. The results on a complex data-set with many traffic roundabouts indicate the benefits of the proposed procedure.

Speed tuning of motion segmentation and discrimination

NASA Technical Reports Server (NTRS)

Masson, G. S.; Mestre, D. R.; Stone, L. S.

1999-01-01

Motion transparency requires that the visual system distinguish different motion vectors and selectively integrate similar motion vectors over space into the perception of multiple surfaces moving through or over each other. Using large-field (7 degrees x 7 degrees) displays containing two populations of random-dots moving in the same (horizontal) direction but at different speeds, we examined speed-based segmentation by measuring the speed difference above which observers can perceive two moving surfaces. We systematically investigated this 'speed-segmentation' threshold as a function of speed and stimulus duration, and found that it increases sharply for speeds above approximately 8 degrees/s. In addition, speed-segmentation thresholds decrease with stimulus duration out to approximately 200 ms. In contrast, under matched conditions, speed-discrimination thresholds stay low at least out to 16 degrees/s and decrease with increasing stimulus duration at a faster rate than for speed segmentation. Thus, motion segmentation and motion discrimination exhibit different speed selectivity and different temporal integration characteristics. Results are discussed in terms of the speed preferences of different neuronal populations within the primate visual cortex.

Molecular Mechanisms of Innate Immune Inhibition by Non-Segmented Negative-Sense RNA Viruses

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

Chatterjee, Srirupa; Basler, Christopher F.; Amarasinghe, Gaya K.

The host innate immune system serves as the first line of defense against viral infections. Germline-encoded pattern recognition receptors detect molecular patterns associated with pathogens and activate innate immune responses. Of particular relevance to viral infections are those pattern recognition receptors that activate type I interferon responses, which establish an antiviral state. The order Mononegavirales is composed of viruses that possess single-stranded, non-segmented negative-sense (NNS) RNA genomes and are important human pathogens that consistently antagonize signaling related to type I interferon responses. NNS viruses have limited encoding capacity compared to many DNA viruses, and as a likely consequence, most openmore » reading frames encode multifunctional viral proteins that interact with host factors in order to evade host cell defenses while promoting viral replication. In this review, we will discuss the molecular mechanisms of innate immune evasion by select NNS viruses. A greater understanding of these interactions will be critical in facilitating the development of effective therapeutics and viral countermeasures.« less

Mapping and characterizing selected canopy tree species at the Angkor World Heritage site in Cambodia using aerial data.

PubMed

Singh, Minerva; Evans, Damian; Tan, Boun Suy; Nin, Chan Samean

2015-01-01

At present, there is very limited information on the ecology, distribution, and structure of Cambodia's tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman's rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables.

Mapping and Characterizing Selected Canopy Tree Species at the Angkor World Heritage Site in Cambodia Using Aerial Data

PubMed Central

Singh, Minerva; Evans, Damian; Tan, Boun Suy; Nin, Chan Samean

2015-01-01

At present, there is very limited information on the ecology, distribution, and structure of Cambodia’s tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman’s rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables. PMID:25902148

Integrated β-catenin, BMP, PTEN, and Notch signalling patterns the nephron

PubMed Central

Lindström, Nils O; Lawrence, Melanie L; Burn, Sally F; Johansson, Jeanette A; Bakker, Elvira RM; Ridgway, Rachel A; Chang, C-Hong; Karolak, Michele J; Oxburgh, Leif; Headon, Denis J; Sansom, Owen J; Smits, Ron; Davies, Jamie A; Hohenstein, Peter

2015-01-01

The different segments of the nephron and glomerulus in the kidney balance the processes of water homeostasis, solute recovery, blood filtration, and metabolite excretion. When segment function is disrupted, a range of pathological features are presented. Little is known about nephron patterning during embryogenesis. In this study, we demonstrate that the early nephron is patterned by a gradient in β-catenin activity along the axis of the nephron tubule. By modifying β-catenin activity, we force cells within nephrons to differentiate according to the imposed β-catenin activity level, thereby causing spatial shifts in nephron segments. The β-catenin signalling gradient interacts with the BMP pathway which, through PTEN/PI3K/AKT signalling, antagonises β-catenin activity and promotes segment identities associated with low β-catenin activity. β-catenin activity and PI3K signalling also integrate with Notch signalling to control segmentation: modulating β-catenin activity or PI3K rescues segment identities normally lost by inhibition of Notch. Our data therefore identifies a molecular network for nephron patterning. DOI: http://dx.doi.org/10.7554/eLife.04000.001 PMID:25647637

Intelligent multi-spectral IR image segmentation

NASA Astrophysics Data System (ADS)

Lu, Thomas; Luong, Andrew; Heim, Stephen; Patel, Maharshi; Chen, Kang; Chao, Tien-Hsin; Chow, Edward; Torres, Gilbert

2017-05-01

This article presents a neural network based multi-spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. This article compares the neural network based segmentation method to the Wavelet-threshold and Grab-Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-spectral IR images.

HMO marketing and selection bias: are TEFRA HMOs skimming?

PubMed

Lichtenstein, R; Thomas, J W; Watkins, B; Puto, C; Lepkowski, J; Adams-Watson, J; Simone, B; Vest, D

1992-04-01

The research evidence indicates that health maintenance organizations (HMOs) participating in the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) At-Risk Program tend to experience favorable selection. Although favorable selection might result from patient decisions, a common conjecture is that it can be induced by HMOs through their marketing activities. The purpose of this study is to examine the relationship between HMO marketing strategies and selection bias in TEFRA At-Risk HMOs. A purposive sample of 22 HMOs that were actively marketing their TEFRA programs was selected and data on organizational characteristics, market area characteristics, and HMO marketing decisions were collected. To measure selection bias in these HMOs, the functional health status of approximately 300 enrollees in each HMO was compared to that of 300 non-enrolling beneficiaries in the same area. Three dependent variables, reflecting selection bias at the mean, the low health tail, and the high health tail of the health status distribution were created. Weighted least squares regressions were then used to identify relationships between marketing elements and selection bias. Subject to the statistical limitations of the study, our conclusion is that it is doubtful that HMO marketing decisions are responsible for the prevalence of favorable selection in HMO enrollment. It also appears unlikely that HMOs were differentially targeting healthy and unhealthy segments of the Medicare market.

Routine Use of Three-Dimensional Contrast-Enhanced Moving-Table MR Angiography in Patients with Peripheral Arterial Occlusive Disease: Comparison with Selective Digital Subtraction Angiography

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

Deutschmann, Hannes A.; Schoellnast, Helmut; Portugaller, Horst R.

2006-10-15

Purpose. To compare the diagnostic accuracy of contrast-enhanced (CE) three-dimensional (3D) moving-table magnetic resonance (MR) angiography with that of selective digital subtraction angiography (DSA) for routine clinical investigation in patients with peripheral arterial occlusive disease. Methods. Thirty-eight patients underwent CE 3D moving-table MR angiography of the pelvic and peripheral arteries. A commercially available large-field-of-view adapter and a dedicated peripheral vascular phased-array coil were used. MR angiograms were evaluated for grade of arterial stenosis, diagnostic quality, and presence of artifacts. MR imaging results for each patient were compared with those of selective DSA. Results. Two hundred and twenty-six arterial segments inmore » 38 patients were evaluated by both selective DSA and MR angiography. No complications related to MR angiography were observed. There was agreement in stenosis classification in 204 (90.3%) segments; MR angiography overgraded 16 (7%) segments and undergraded 6 (2.7%) segments. Compared with selective DSA, MR angiography provided high sensitivity and specificity and excellent interobserver agreement for detection of severe stenosis (97% and 95%, {kappa} = 0.9 {+-} 0.03) and moderate stenosis (96.5% and 94.3%, {kappa} = 0.9 {+-} 0.03). Conclusion. Compared with selective DSA, moving-table MR angiography proved to be an accurate, noninvasive method for evaluation of peripheral arterial occlusive disease and may thus serve as an alternative to DSA in clinical routine.« less

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Poster - 32: Atlas Selection for Automated Segmentation of Pelvic CT for Prostate Radiotherapy

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

Mallawi, Abrar; Farrell, TomTom; Diamond, Kevin-Ro

2016-08-15

Atlas based-segmentation has recently been evaluated for use in prostate radiotherapy. In a typical approach, the essential step is the selection of an atlas from a database that the best matches of the target image. This work proposes an atlas selection strategy and evaluate it impacts on final segmentation accuracy. Several anatomical parameters were measured to indicate the overall prostate and body shape, all of these measurements obtained on CT images. A brute force procedure was first performed for a training dataset of 20 patients using image registration to pair subject with similar contours; each subject was served as amore » target image to which all reaming 19 images were affinity registered. The overlap between the prostate and femoral heads was quantified for each pair using the Dice Similarity Coefficient (DSC). Finally, an atlas selection procedure was designed; relying on the computation of a similarity score defined as a weighted sum of differences between the target and atlas subject anatomical measurement. The algorithm ability to predict the most similar atlas was excellent, achieving mean DSCs of 0.78 ± 0.07 and 0.90 ± 0.02 for the CTV and either femoral head. The proposed atlas selection yielded 0.72 ± 0.11 and 0.87 ± 0.03 for CTV and either femoral head. The DSC obtained with the proposed selection method were slightly lower than the maximum established using brute force, but this does not include potential improvements expected with deformable registration. The proposed atlas selection method provides reasonable segmentation accuracy.« less

Global competition and local cooperation in a network of neural oscillators

NASA Astrophysics Data System (ADS)

Terman, David; Wang, DeLiang

An architecture of locally excitatory, globally inhibitory oscillator networks is proposed and investigated both analytically and by computer simulation. The model for each oscillator corresponds to a standard relaxation oscillator with two time scales. Oscillators are locally coupled by a scheme that resembles excitatory synaptic coupling, and each oscillator also inhibits other oscillators through a common inhibitor. Oscillators are driven to be oscillatory by external stimulation. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing the other oscillators from jumping up. We show analytically that with the selective gating mechanism, the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate the model's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding and may provide an effective computational framework for scene segmentation and figure/ ground segregation.

Applications of tuned mass dampers to improve performance of large space mirrors

NASA Astrophysics Data System (ADS)

Yingling, Adam J.; Agrawal, Brij N.

2014-01-01

In order for future imaging spacecraft to meet higher resolution imaging capability, it will be necessary to build large space telescopes with primary mirror diameters that range from 10 m to 20 m and do so with nanometer surface accuracy. Due to launch vehicle mass and volume constraints, these mirrors have to be deployable and lightweight, such as segmented mirrors using active optics to correct mirror surfaces with closed loop control. As a part of this work, system identification tests revealed that dynamic disturbances inherent in a laboratory environment are significant enough to degrade the optical performance of the telescope. Research was performed at the Naval Postgraduate School to identify the vibration modes most affecting the optical performance and evaluate different techniques to increase damping of those modes. Based on this work, tuned mass dampers (TMDs) were selected because of their simplicity in implementation and effectiveness in targeting specific modes. The selected damping mechanism was an eddy current damper where the damping and frequency of the damper could be easily changed. System identification of segments was performed to derive TMD specifications. Several configurations of the damper were evaluated, including the number and placement of TMDs, damping constant, and targeted structural modes. The final configuration consisted of two dampers located at the edge of each segment and resulted in 80% reduction in vibrations. The WFE for the system without dampers was 1.5 waves, with one TMD the WFE was 0.9 waves, and with two TMDs the WFE was 0.25 waves. This paper provides details of some of the work done in this area and includes theoretical predictions for optimum damping which were experimentally verified on a large aperture segmented system.

Segmentation and Recognition of Continuous Human Activity

DTIC Science & Technology

2001-01-01

This paper presents a methodology for automatic segmentation and recognition of continuous human activity . We segment a continuous human activity into...commencement or termination. We use single action sequences for the training data set. The test sequences, on the other hand, are continuous sequences of human ... activity that consist of three or more actions in succession. The system has been tested on continuous activity sequences containing actions such as

An Investigation of the Effects of Different Types of Activities during Pauses in a Segmented Instructional Animation

ERIC Educational Resources Information Center

Cheon, Jongpil; Chung, Sungwon; Crooks, Steven M.; Song, Jaeki; Kim, Jeakyeong

2014-01-01

Since the complex and transient information in instructional animations requires more cognitive resources, the segmenting principle has been proposed to reduce cognitive overload by providing smaller chunks with pauses between segments. This study examined the effects of different types of activities during pauses in a segmented animation. Four…

A general framework to learn surrogate relevance criterion for atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-09-01

Multi-atlas based image segmentation sees great opportunities in the big data era but also faces unprecedented challenges in identifying positive contributors from extensive heterogeneous data. To assess data relevance, image similarity criteria based on various image features widely serve as surrogates for the inaccessible geometric agreement criteria. This paper proposes a general framework to learn image based surrogate relevance criteria to better mimic the behaviors of segmentation based oracle geometric relevance. The validity of its general rationale is verified in the specific context of fusion set selection for image segmentation. More specifically, we first present a unified formulation for surrogate relevance criteria and model the neighborhood relationship among atlases based on the oracle relevance knowledge. Surrogates are then trained to be small for geometrically relevant neighbors and large for irrelevant remotes to the given targets. The proposed surrogate learning framework is verified in corpus callosum segmentation. The learned surrogates demonstrate superiority in inferring the underlying oracle value and selecting relevant fusion set, compared to benchmark surrogates.

A new Hessian - based approach for segmentation of CT porous media images

NASA Astrophysics Data System (ADS)

Timofey, Sizonenko; Marina, Karsanina; Dina, Gilyazetdinova; Kirill, Gerke

2017-04-01

Hessian matrix based methods are widely used in image analysis for features detection, e.g., detection of blobs, corners and edges. Hessian matrix of the imageis the matrix of 2nd order derivate around selected voxel. Most significant features give highest values of Hessian transform and lowest values are located at smoother parts of the image. Majority of conventional segmentation techniques can segment out cracks, fractures and other inhomogeneities in soils and rocks only if the rest of the image is significantly "oversigmented". To avoid this disadvantage, we propose to enhance greyscale values of voxels belonging to such specific inhomogeneities on X-ray microtomography scans. We have developed and implemented in code a two-step approach to attack the aforementioned problem. During the first step we apply a filter that enhances the image and makes outstanding features more sharply defined. During the second step we apply Hessian filter based segmentation. The values of voxels on the image to be segmented are calculated in conjunction with the values of other voxels within prescribed region. Contribution from each voxel within such region is computed by weighting according to the local Hessian matrix value. We call this approach as Hessian windowed segmentation. Hessian windowed segmentation has been tested on different porous media X-ray microtomography images, including soil, sandstones, carbonates and shales. We also compared this new method against others widely used methods such as kriging, Markov random field, converging active contours and region grow. We show that our approach is more accurate in regions containing special features such as small cracks, fractures, elongated inhomogeneities and other features with low contrast related to the background solid phase. Moreover, Hessian windowed segmentation outperforms some of these methods in computational efficiency. We further test our segmentation technique by computing permeability of segmented images and comparing them against laboratory based measurements. This work was partially supported by RFBR grant 15-34-20989 (X-ray tomography and image fusion) and RSF grant 14-17-00658 (image segmentation and pore-scale modelling).

Selective activation of the K(+)(ATP) channel is a mechanism by which sudden death is produced by low-energy chest-wall impact (Commotio cordis).

PubMed

Link, M S; Wang, P J; VanderBrink, B A; Avelar, E; Pandian, N G; Maron, B J; Estes, N A

1999-07-27

Sudden death due to relatively innocent chest-wall impact has been described in young individuals (commotio cordis). In our previously reported swine model of commotio cordis, ventricular fibrillation (with T-wave strikes) and ST-segment elevation (with QRS strikes) were produced by 30-mph baseball impacts to the precordium. Because activation of the K(+)(ATP) channel has been implicated in the pathogenesis of ST elevation and ventricular fibrillation in myocardial ischemia, we hypothesized that this channel could be responsible for the electrophysiologic findings in our experimental model and in victims of commotio cordis. In the initial experiment, 6 juvenile swine were given 0.5 mg/kg IV glibenclamide, a selective inhibitor of the K(+)(ATP) channel, and chest impact was given on the QRS. The results of these strikes were compared with animals in which no glibenclamide was given. In the second phase, 20 swine were randomized to receive glibenclamide or a control vehicle (in a double-blind fashion), with chest impact delivered just before the T-wave peak. With QRS impacts, the maximal ST elevation was significantly less in those animals given glibenclamide (0.16+/-0.10 mV) than in controls (0.35+/-0.20 mV; P=0.004). With T-wave impacts, the animals that received glibenclamide had significantly fewer occurrences of ventricular fibrillation (1 episode in 27 impacts; 4%) than controls (6 episodes in 18 impacts; 33%; P=0.01). In this experimental model of commotio cordis, blockade of the K(+)(ATP) channel reduced the incidence of ventricular fibrillation and the magnitude of ST-segment elevation. Therefore, selective K(+)(ATP) channel activation may be a pivotal mechanism in sudden death resulting from low-energy chest-wall trauma in young people during sporting activities.

Temporally selective attention modulates early perceptual processing: event-related potential evidence.

PubMed

Sanders, Lisa D; Astheimer, Lori B

2008-05-01

Some of the most important information we encounter changes so rapidly that our perceptual systems cannot process all of it in detail. Spatially selective attention is critical for perception when more information than can be processed in detail is presented simultaneously at distinct locations. When presented with complex, rapidly changing information, listeners may need to selectively attend to specific times rather than to locations. We present evidence that listeners can direct selective attention to time points that differ by as little as 500 msec, and that doing so improves target detection, affects baseline neural activity preceding stimulus presentation, and modulates auditory evoked potentials at a perceptually early stage. These data demonstrate that attentional modulation of early perceptual processing is temporally precise and that listeners can flexibly allocate temporally selective attention over short intervals, making it a viable mechanism for preferentially processing the most relevant segments in rapidly changing streams.

A Typology of Middle School Girls: Audience Segmentation Related to Physical Activity

ERIC Educational Resources Information Center

Staten, Lisa K.; Birnbaum, Amanda S.; Jobe, Jared B.; Elder, John P.

2006-01-01

The Trial of Activity for Adolescent Girls (TAAG) combines social ecological and social marketing approaches to promote girls' participation in physical activity programs implemented at 18 middle schools throughout the United States. Key to the TAAG approach is targeting materials to a variety of audience segments. TAAG segments are individuals…

Segmentation of whole cells and cell nuclei from 3-D optical microscope images using dynamic programming.

PubMed

McCullough, D P; Gudla, P R; Harris, B S; Collins, J A; Meaburn, K J; Nakaya, M A; Yamaguchi, T P; Misteli, T; Lockett, S J

2008-05-01

Communications between cells in large part drive tissue development and function, as well as disease-related processes such as tumorigenesis. Understanding the mechanistic bases of these processes necessitates quantifying specific molecules in adjacent cells or cell nuclei of intact tissue. However, a major restriction on such analyses is the lack of an efficient method that correctly segments each object (cell or nucleus) from 3-D images of an intact tissue specimen. We report a highly reliable and accurate semi-automatic algorithmic method for segmenting fluorescence-labeled cells or nuclei from 3-D tissue images. Segmentation begins with semi-automatic, 2-D object delineation in a user-selected plane, using dynamic programming (DP) to locate the border with an accumulated intensity per unit length greater that any other possible border around the same object. Then the two surfaces of the object in planes above and below the selected plane are found using an algorithm that combines DP and combinatorial searching. Following segmentation, any perceived errors can be interactively corrected. Segmentation accuracy is not significantly affected by intermittent labeling of object surfaces, diffuse surfaces, or spurious signals away from surfaces. The unique strength of the segmentation method was demonstrated on a variety of biological tissue samples where all cells, including irregularly shaped cells, were accurately segmented based on visual inspection.

Dynamic updating atlas for heart segmentation with a nonlinear field-based model.

PubMed

Cai, Ken; Yang, Rongqian; Yue, Hongwei; Li, Lihua; Ou, Shanxing; Liu, Feng

2017-09-01

Segmentation of cardiac computed tomography (CT) images is an effective method for assessing the dynamic function of the heart and lungs. In the atlas-based heart segmentation approach, the quality of segmentation usually relies upon atlas images, and the selection of those reference images is a key step. The optimal goal in this selection process is to have the reference images as close to the target image as possible. This study proposes an atlas dynamic update algorithm using a scheme of nonlinear deformation field. The proposed method is based on the features among double-source CT (DSCT) slices. The extraction of these features will form a base to construct an average model and the created reference atlas image is updated during the registration process. A nonlinear field-based model was used to effectively implement a 4D cardiac segmentation. The proposed segmentation framework was validated with 14 4D cardiac CT sequences. The algorithm achieved an acceptable accuracy (1.0-2.8 mm). Our proposed method that combines a nonlinear field-based model and dynamic updating atlas strategies can provide an effective and accurate way for whole heart segmentation. The success of the proposed method largely relies on the effective use of the prior knowledge of the atlas and the similarity explored among the to-be-segmented DSCT sequences. Copyright © 2016 John Wiley & Sons, Ltd.

Video Image Tracking Engine

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Bryan, ThomasC. (Inventor); Book, Michael L. (Inventor)

2004-01-01

A method and system for processing an image including capturing an image and storing the image as image pixel data. Each image pixel datum is stored in a respective memory location having a corresponding address. Threshold pixel data is selected from the image pixel data and linear spot segments are identified from the threshold pixel data selected.. Ihe positions of only a first pixel and a last pixel for each linear segment are saved. Movement of one or more objects are tracked by comparing the positions of fust and last pixels of a linear segment present in the captured image with respective first and last pixel positions in subsequent captured images. Alternatively, additional data for each linear data segment is saved such as sum of pixels and the weighted sum of pixels i.e., each threshold pixel value is multiplied by that pixel's x-location).

Software for hyperspectral, joint photographic experts group (.JPG), portable network graphics (.PNG) and tagged image file format (.TIFF) segmentation

NASA Astrophysics Data System (ADS)

Bruno, L. S.; Rodrigo, B. P.; Lucio, A. de C. Jorge

2016-10-01

This paper presents a system developed by an application of a neural network Multilayer Perceptron for drone acquired agricultural image segmentation. This application allows a supervised user training the classes that will posteriorly be interpreted by neural network. These classes will be generated manually with pre-selected attributes in the application. After the attribute selection a segmentation process is made to allow the relevant information extraction for different types of images, RGB or Hyperspectral. The application allows extracting the geographical coordinates from the image metadata, geo referencing all pixels on the image. In spite of excessive memory consume on hyperspectral images regions of interest, is possible to perform segmentation, using bands chosen by user that can be combined in different ways to obtain different results.

Statistical optimisation techniques in fatigue signal editing problem

NASA Astrophysics Data System (ADS)

Nopiah, Z. M.; Osman, M. H.; Baharin, N.; Abdullah, S.

2015-02-01

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window and fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.

Statistical optimisation techniques in fatigue signal editing problem

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

Nopiah, Z. M.; Osman, M. H.; Baharin, N.

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window andmore » fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.« less

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

Beaver-mediated lateral hydrologic connectivity, fluvial carbon and nutrient flux, and aquatic ecosystem metabolism

NASA Astrophysics Data System (ADS)

Wegener, Pam; Covino, Tim; Wohl, Ellen

2017-06-01

River networks that drain mountain landscapes alternate between narrow and wide valley segments. Within the wide segments, beaver activity can facilitate the development and maintenance of complex, multithread planform. Because the narrow segments have limited ability to retain water, carbon, and nutrients, the wide, multithread segments are likely important locations of retention. We evaluated hydrologic dynamics, nutrient flux, and aquatic ecosystem metabolism along two adjacent segments of a river network in the Rocky Mountains, Colorado: (1) a wide, multithread segment with beaver activity; and, (2) an adjacent (directly upstream) narrow, single-thread segment without beaver activity. We used a mass balance approach to determine the water, carbon, and nutrient source-sink behavior of each river segment across a range of flows. While the single-thread segment was consistently a source of water, carbon, and nitrogen, the beaver impacted multithread segment exhibited variable source-sink dynamics as a function of flow. Specifically, the multithread segment was a sink for water, carbon, and nutrients during high flows, and subsequently became a source as flows decreased. Shifts in river-floodplain hydrologic connectivity across flows related to higher and more variable aquatic ecosystem metabolism rates along the multithread relative to the single-thread segment. Our data suggest that beaver activity in wide valleys can create a physically complex hydrologic environment that can enhance hydrologic and biogeochemical buffering, and promote high rates of aquatic ecosystem metabolism. Given the widespread removal of beaver, determining the cumulative effects of these changes is a critical next step in restoring function in altered river networks.

Employee choice of a high-deductible health plan across multiple employers.

PubMed

Lave, Judith R; Men, Aiju; Day, Brian T; Wang, Wei; Zhang, Yuting

2011-02-01

To determine factors associated with selecting a high-deductible health plan (HDHP) rather than a preferred provider plan (PPO) and to examine switching and market segmentation after initial selection. Claims and benefit information for 2005-2007 from nine employers in western Pennsylvania first offering HDHP in 2006. We examined plan growth over time, used logistic regression to determine factors associated with choosing an HDHP, and examined the distribution of healthy and sick members across plan types. We linked employees with their dependents to determine family-level variables. We extracted risk scores, covered charges, employee age, and employee gender from claims data. We determined census-level race, education, and income information. Health status, gender, race, and education influenced the type of individual and family policies chosen. In the second year the HDHP was offered, few employees changed plans. Risk segmentation between HDHPs and PPOs existed, but it did not increase. When given a choice, those who are healthier are more likely to select an HDHP leading to risk segmentation. Risk segmentation did not increase in the second year that HDHPs were offered. © Health Research and Educational Trust.

Interictal EEG spikes identify the region of electrographic seizure onset in some, but not all, pediatric epilepsy patients.

PubMed

Marsh, Eric D; Peltzer, Bradley; Brown, Merritt W; Wusthoff, Courtney; Storm, Phillip B; Litt, Brian; Porter, Brenda E

2010-04-01

The role of sharps and spikes, interictal epileptiform discharges (IEDs), in guiding epilepsy surgery in children remains controversial, particularly with intracranial electroencephalography (IEEG). Although ictal recording is the mainstay of localizing epileptic networks for surgical resection, current practice dictates removing regions generating frequent IEDs if they are near the ictal onset zone. Indeed, past studies suggest an inconsistent relationship between IED and seizure-onset location, although these studies were based upon relatively short EEG epochs. We employ a previously validated, computerized spike detector to measure and localize IED activity over prolonged, representative segments of IEEG recorded from 19 children with intractable, mostly extratemporal lobe epilepsy. Approximately 8 h of IEEG, randomly selected 30-min segments of continuous interictal IEEG per patient, were analyzed over all intracranial electrode contacts. When spike frequency was averaged over the 16-time segments, electrodes with the highest mean spike frequency were found to be within the seizure-onset region in 11 of 19 patients. There was significant variability between individual 30-min segments in these patients, indicating that large statistical samples of interictal activity were required for improved localization. Low-voltage fast EEG at seizure onset was the only clinical factor predicting IED localization to the seizure-onset region. Our data suggest that automated IED detection over multiple representative samples of IEEG may be of utility in planning epilepsy surgery for children with intractable epilepsy. Further research is required to better determine which patients may benefit from this technique a priori.

Interictal EEG spikes identify the region of seizure onset in some, but not all pediatric epilepsy patients

PubMed Central

Marsh, Eric D.; Peltzer, Bradley; Brown, Merritt W.; Wusthoff, Courtney; Storm, Phillip B.; Litt, Brian; Porter, Brenda E.

2010-01-01

Purpose The role of sharps and spikes, interictal epileptiform discharges (IEDs), in guiding epilepsy surgery in children remains controversial, particularly with intracranial EEG (IEEG). While ictal recording is the mainstay of localizing epileptic networks for surgical resection, current practice dictates removing regions generating frequent IEDs if they are near the ictal onset zone. Indeed, past studies suggest an inconsistent relationship between IED and seizure onset location, though these studies were based upon relatively short EEG epochs. Methods We employ a previously validated, computerized spike detector, to measure and localize IED activity over prolonged, representative segments of IEEG recorded from 19 children with intractable, mostly extra temporal lobe epilepsy. Approximately 8 hours of IEEG, randomly selected thirty-minute segments of continuous interictal IEEG per patient were analyzed over all intracranial electrode contacts. Results When spike frequency was averaged over the 16-time segments, electrodes with the highest mean spike frequency were found to be within the seizure onset region in 11 of 19 patients. There was significant variability between individual 30-minute segments in these patients, indicating that large statistical samples of interictal activity were required for improved localization. Low voltage fast EEG at seizure onset was the only clinical factor predicting IED localization to the seizure onset region. Conclusions Our data suggest that automated IED detection over multiple representative samples of IEEG may be of utility in planning epilepsy surgery for children with intractable epilepsy. Further research is required to better determine which patients may benefit from this technique a priori. PMID:19780794

Global-to-local, shape-based, real and virtual landmarks for shape modeling by recursive boundary subdivision

NASA Astrophysics Data System (ADS)

Rueda, Sylvia; Udupa, Jayaram K.

2011-03-01

Landmark based statistical object modeling techniques, such as Active Shape Model (ASM), have proven useful in medical image analysis. Identification of the same homologous set of points in a training set of object shapes is the most crucial step in ASM, which has encountered challenges such as (C1) defining and characterizing landmarks; (C2) ensuring homology; (C3) generalizing to n > 2 dimensions; (C4) achieving practical computations. In this paper, we propose a novel global-to-local strategy that attempts to address C3 and C4 directly and works in Rn. The 2D version starts from two initial corresponding points determined in all training shapes via a method α, and subsequently by subdividing the shapes into connected boundary segments by a line determined by these points. A shape analysis method β is applied on each segment to determine a landmark on the segment. This point introduces more pairs of points, the lines defined by which are used to further subdivide the boundary segments. This recursive boundary subdivision (RBS) process continues simultaneously on all training shapes, maintaining synchrony of the level of recursion, and thereby keeping correspondence among generated points automatically by the correspondence of the homologous shape segments in all training shapes. The process terminates when no subdividing lines are left to be considered that indicate (as per method β) that a point can be selected on the associated segment. Examples of α and β are presented based on (a) distance; (b) Principal Component Analysis (PCA); and (c) the novel concept of virtual landmarks.

Fully automated contour detection of the ascending aorta in cardiac 2D phase-contrast MRI.

PubMed

Codari, Marina; Scarabello, Marco; Secchi, Francesco; Sforza, Chiarella; Baselli, Giuseppe; Sardanelli, Francesco

2018-04-01

In this study we proposed a fully automated method for localizing and segmenting the ascending aortic lumen with phase-contrast magnetic resonance imaging (PC-MRI). Twenty-five phase-contrast series were randomly selected out of a large population dataset of patients whose cardiac MRI examination, performed from September 2008 to October 2013, was unremarkable. The local Ethical Committee approved this retrospective study. The ascending aorta was automatically identified on each phase of the cardiac cycle using a priori knowledge of aortic geometry. The frame that maximized the area, eccentricity, and solidity parameters was chosen for unsupervised initialization. Aortic segmentation was performed on each frame using active contouring without edges techniques. The entire algorithm was developed using Matlab R2016b. To validate the proposed method, the manual segmentation performed by a highly experienced operator was used. Dice similarity coefficient, Bland-Altman analysis, and Pearson's correlation coefficient were used as performance metrics. Comparing automated and manual segmentation of the aortic lumen on 714 images, Bland-Altman analysis showed a bias of -6.68mm 2 , a coefficient of repeatability of 91.22mm 2 , a mean area measurement of 581.40mm 2 , and a reproducibility of 85%. Automated and manual segmentation were highly correlated (R=0.98). The Dice similarity coefficient versus the manual reference standard was 94.6±2.1% (mean±standard deviation). A fully automated and robust method for identification and segmentation of ascending aorta on PC-MRI was developed. Its application on patients with a variety of pathologic conditions is advisable. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

A threshold selection method based on edge preserving

NASA Astrophysics Data System (ADS)

Lou, Liantang; Dan, Wei; Chen, Jiaqi

2015-12-01

A method of automatic threshold selection for image segmentation is presented. An optimal threshold is selected in order to preserve edge of image perfectly in image segmentation. The shortcoming of Otsu's method based on gray-level histograms is analyzed. The edge energy function of bivariate continuous function is expressed as the line integral while the edge energy function of image is simulated by discretizing the integral. An optimal threshold method by maximizing the edge energy function is given. Several experimental results are also presented to compare with the Otsu's method.

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%.

Statistical shape (ASM) and appearance (AAM) models for the segmentation of the cerebellum in fetal ultrasound

NASA Astrophysics Data System (ADS)

Reyes López, Misael; Arámbula Cosío, Fernando

2017-11-01

The cerebellum is an important structure to determine the gestational age of the fetus, moreover most of the abnormalities it presents are related to growth disorders. In this work, we present the results of the segmentation of the fetal cerebellum applying statistical shape and appearance models. Both models were tested on ultrasound images of the fetal brain taken from 23 pregnant women, between 18 and 24 gestational weeks. The accuracy results obtained on 11 ultrasound images show a mean Hausdorff distance of 6.08 mm between the manual segmentation and the segmentation using active shape model, and a mean Hausdorff distance of 7.54 mm between the manual segmentation and the segmentation using active appearance model. The reported results demonstrate that the active shape model is more robust in the segmentation of the fetal cerebellum in ultrasound images.

Retina Image Vessel Segmentation Using a Hybrid CGLI Level Set Method

PubMed Central

Chen, Meizhu; Li, Jichun; Zhang, Encai

2017-01-01

As a nonintrusive method, the retina imaging provides us with a better way for the diagnosis of ophthalmologic diseases. Extracting the vessel profile automatically from the retina image is an important step in analyzing retina images. A novel hybrid active contour model is proposed to segment the fundus image automatically in this paper. It combines the signed pressure force function introduced by the Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) model with the local intensity property introduced by the Local Binary fitting (LBF) model to overcome the difficulty of the low contrast in segmentation process. It is more robust to the initial condition than the traditional methods and is easily implemented compared to the supervised vessel extraction methods. Proposed segmentation method was evaluated on two public datasets, DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (Structured Analysis of the Retina) (the average accuracy of 0.9390 with 0.7358 sensitivity and 0.9680 specificity on DRIVE datasets and average accuracy of 0.9409 with 0.7449 sensitivity and 0.9690 specificity on STARE datasets). The experimental results show that our method is effective and our method is also robust to some kinds of pathology images compared with the traditional level set methods. PMID:28840122

Segmenting a general practitioner market to improve recruitment outcomes.

PubMed

Hemphill, Elizabeth; Kulik, Carol T

2011-05-01

Recruitment is an ongoing challenge in the health industry with general practitioner (GP) shortages in many areas beyond rural and Indigenous communities. This paper suggests a marketing solution that identifies different segments of the GP market for recruitment strategy development. In February 2008, 96 GPs in Australia responded to a mail questionnaire (of which 85 questionnaires were useable). A total of 350 GPs were sent the questionnaire. Respondents considered small sets of attributes in the decision to accept a new job at a general practice and selected the most and least important attribute from each set. We identified latent class clusters (cohorts) of GPs from the most-least important data. Three cohorts were found in the GP market, distinguishing practitioners who emphasised job, family or practice attributes in their decision to join a practice. Few significant demographic differences exist between the cohorts. A segmented GP market suggests two alternative recruitment strategies. One option is for general practices to target members of a single cohort (family-, job-, or practice-focussed GPs). The other option is for general practices to diversify their recruitment strategies to target all three cohorts (family-, job- and practice-focussed GPs). A single brand (practice) can have multiple advertising strategies with each strategy involving advertising activities targeting a particular consumer segment.

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Segmented AC-coupled readout from continuous collection electrodes in semiconductor sensors

DOEpatents

Sadrozinski, Hartmut F. W.; Seiden, Abraham; Cartiglia, Nicolo

2017-04-04

Position sensitive radiation detection is provided using a continuous electrode in a semiconductor radiation detector, as opposed to the conventional use of a segmented electrode. Time constants relating to AC coupling between the continuous electrode and segmented contacts to the electrode are selected to provide position resolution from the resulting configurations. The resulting detectors advantageously have a more uniform electric field than conventional detectors having segmented electrodes, and are expected to have much lower cost of production and of integration with readout electronics.

A database of aerothermal measurements in hypersonic flow for CFD validation

NASA Technical Reports Server (NTRS)

Holden, M. S.; Moselle, J. R.

1992-01-01

This paper presents an experimental database selected and compiled from aerothermal measurements obtained on basic model configurations on which fundamental flow phenomena could be most easily examined. The experimental studies were conducted in hypersonic flows in 48-inch, 96-inch, and 6-foot shock tunnels. A special computer program was constructed to provide easy access to the measurements in the database as well as the means to plot the measurements and compare them with imported data. The database contains tabulations of model configurations, freestream conditions, and measurements of heat transfer, pressure, and skin friction for each of the studies selected for inclusion. The first segment contains measurements in laminar flow emphasizing shock-wave boundary-layer interaction. In the second segment, measurements in transitional flows over flat plates and cones are given. The third segment comprises measurements in regions of shock-wave/turbulent-boundary-layer interactions. Studies of the effects of surface roughness of nosetips and conical afterbodies are presented in the fourth segment of the database. Detailed measurements in regions of shock/shock boundary layer interaction are contained in the fifth segment. Measurements in regions of wall jet and transpiration cooling are presented in the final two segments.

Exploring 3D Human Action Recognition: from Offline to Online.

PubMed

Liu, Zhenyu; Li, Rui; Tan, Jianrong

2018-02-20

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems-including real-time performance and sequence segmentation-are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset.

A peculiar segmented flow microfluidics for isoquercitrin biosynthesis based on coupling of reaction and separation.

PubMed

Gong, An; Gu, Shuang-Shuang; Wang, Jun; Sheng, Sheng; Wu, Fu-An

2015-10-01

A segmented flow containing a buffer-ionic liquid/solvent in a micro-channel reactor was applied to synthesize isoquercitrin by the hesperidinase-catalyzed selective hydrolysis of rutin, based on a novel system of reaction coupling with separation. Within the developed microchannel reactor with one T-shaped inlet and outlet, the maximum isoquercitrin yield (101.7 ± 2.6%) was achieved in 20 min at 30 °C and 4 μL/min. Compared with a continuous-flow reactor, reaction rate was increased 4-fold due to a glycine-sodium hydroxide:[Bmim][BF4]/glycerol triacetate (1:1, v/v) system that formed a slug flow in microchannel and significantly increased mass transfer rates. The mass transfer coefficient significantly increased and exhibited a linear relationship with the flow rate. Hesperidinase could be efficiently reused at least 5 times, without losing any activity. The bonding mechanism and secondary structure of hesperidinase indicated that hesperidinase had a greater affinity to rutin at a production rate of 4 μL/min in this segmented flow microreactor. Copyright © 2015 Elsevier Ltd. All rights reserved.

Subsurface structures of the active reverse fault zones in Japan inferred from gravity anomalies.

NASA Astrophysics Data System (ADS)

Matsumoto, N.; Sawada, A.; Hiramatsu, Y.; Okada, S.; Tanaka, T.; Honda, R.

2016-12-01

The object of our study is to examine subsurface features such as continuity, segmentation and faulting type, of the active reverse fault zones. We use the gravity data published by the Gravity Research Group in Southwest Japan (2001), the Geographical Survey Institute (2006), Yamamoto et al. (2011), Honda et al. (2012), and the Geological Survey of Japan, AIST (2013) in this study. We obtained the Bouguer anomalies through terrain corrections with 10 m DEM (Sawada et al. 2015) under the assumed density of 2670 kg/m3, a band-pass filtering, and removal of linear trend. Several derivatives and structural parameters calculated from a gravity gradient tensor are applied to highlight the features, such as a first horizontal derivatives (HD), a first vertical derivatives (VD), a normalized total horizontal derivative (TDX), a dip angle (β), and a dimensionality index (Di). We analyzed 43 reverse fault zones in northeast Japan and the northern part of southwest Japan among major active fault zones selected by Headquarters for Earthquake Research Promotion. As the results, the subsurface structural boundaries clearly appear along the faults at 21 faults zones. The weak correlations appear at 13 fault zones, and no correlations are recognized at 9 fault zones. For example, in the Itoigawa-Shizuoka tectonic line, the subsurface structure boundary seems to extend further north than the surface trace. Also, a left stepping structure of the fault around Hakuba is more clearly observed with HD. The subsurface structures, which detected as the higher values of HD, are distributed on the east side of the surface rupture in the north segments and on the west side in the south segments, indicating a change of the dip direction, the east dipping to the west dipping, from north to south. In the Yokote basin fault zone, the subsurface structural boundary are clearly detected with HD, VD and TDX along the fault zone in the north segment, but less clearly in the south segment. Also, Di implies the existence of 3D-like structure with E-W trend around the segment boundary. The distribution of dip angle β along the fault zone implies a reverse faulting, corresponding to the faulting type of this fault zone reported by previous studies.

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.

Technical report on semiautomatic segmentation using the Adobe Photoshop.

PubMed

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae; Lee, Yong Sook; Har, Dong-Hwan

2005-12-01

The purpose of this research is to enable users to semiautomatically segment the anatomical structures in magnetic resonance images (MRIs), computerized tomographs (CTs), and other medical images on a personal computer. The segmented images are used for making 3D images, which are helpful to medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was scanned to make 557 MRIs. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL and manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a similar manner, 13 anatomical structures in 8,590 anatomical images were segmented. Proper segmentation was verified by making 3D images from the segmented images. Semiautomatic segmentation using Adobe Photoshop is expected to be widely used for segmentation of anatomical structures in various medical images.

Using movement and intentions to understand human activity.

PubMed

Zacks, Jeffrey M; Kumar, Shawn; Abrams, Richard A; Mehta, Ritesh

2009-08-01

During perception, people segment continuous activity into discrete events. They do so in part by monitoring changes in features of an ongoing activity. Characterizing these features is important for theories of event perception and may be helpful for designing information systems. The three experiments reported here asked whether the body movements of an actor predict when viewers will perceive event boundaries. Body movements were recorded using a magnetic motion tracking system and compared with viewers' segmentation of his activity into events. Changes in movement features were strongly associated with segmentation. This was more true for fine-grained than for coarse-grained boundaries, and was strengthened when the stimulus displays were reduced from live-action movies to simplified animations. These results suggest that movement variables play an important role in the process of segmenting activity into meaningful events, and that the influence of movement on segmentation depends on the availability of other information sources.

Aromatic–aromatic interactions between residues in KCa3.1 pore helix and S5 transmembrane segment control the channel gating process

PubMed Central

Garneau, Line; Klein, Hélène; Lavoie, Marie-France; Brochiero, Emmanuelle; Parent, Lucie

2014-01-01

The Ca2+-activated potassium channel KCa3.1 is emerging as a therapeutic target for a large variety of health disorders. One distinguishing feature of KCa3.1 is that the channel open probability at saturating Ca2+ concentrations (Pomax) is low, typically 0.1–0.2 for KCa3.1 wild type. This observation argues for the binding of Ca2+ to the calmodulin (CaM)–KCa3.1 complex, promoting the formation of a preopen closed-state configuration leading to channel opening. We have previously shown that the KCa3.1 active gate is most likely located at the level of the selectivity filter. As Ca2+-dependent gating of KCa3.1 originates from the binding of Ca2+ to CaM in the C terminus, the hypothesis of a gate located at the level of the selectivity filter requires that the conformational change initiated in the C terminus be transmitted to the S5 and S6 transmembrane helices, with a resulting effect on the channel pore helix directly connected to the selectivity filter. A study was thus undertaken to determine to what extent the interactions between the channel pore helix with the S5 and S6 transmembrane segments contribute to KCa3.1 gating. Molecular dynamics simulations first revealed that the largest contact area between the pore helix and the S5 plus S6 transmembrane helices involves residue F248 at the C-terminal end of the pore helix. Unitary current recordings next confirmed that modulating aromatic–aromatic interactions between F248 and W216 of the S5 transmembrane helical segment and/or perturbing the interactions between F248 and residues in S6 surrounding the glycine hinge G274 cause important changes in Pomax. This work thus provides the first evidence for a key contribution of the pore helix in setting Pomax by stabilizing the channel closed configuration through aromatic–aromatic interactions involving F248 of the pore helix. We propose that the interface pore helix/S5 constitutes a promising site for designing KCa3.1 potentiators. PMID:24470490

Development of a semi-automated combined PET and CT lung lesion segmentation framework

NASA Astrophysics Data System (ADS)

Rossi, Farli; Mokri, Siti Salasiah; Rahni, Ashrani Aizzuddin Abd.

2017-03-01

Segmentation is one of the most important steps in automated medical diagnosis applications, which affects the accuracy of the overall system. In this paper, we propose a semi-automated segmentation method for extracting lung lesions from thoracic PET/CT images by combining low level processing and active contour techniques. The lesions are first segmented in PET images which are first converted to standardised uptake values (SUVs). The segmented PET images then serve as an initial contour for subsequent active contour segmentation of corresponding CT images. To evaluate its accuracy, the Jaccard Index (JI) was used as a measure of the accuracy of the segmented lesion compared to alternative segmentations from the QIN lung CT segmentation challenge, which is possible by registering the whole body PET/CT images to the corresponding thoracic CT images. The results show that our proposed technique has acceptable accuracy in lung lesion segmentation with JI values of around 0.8, especially when considering the variability of the alternative segmentations.

Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials

NASA Astrophysics Data System (ADS)

Radivojevic, Milos; Jäckel, David; Altermatt, Michael; Müller, Jan; Viswam, Vijay; Hierlemann, Andreas; Bakkum, Douglas J.

2016-08-01

A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation. We developed strategies to electrically identify any neuron in the network, while subcellular spatial resolution recording of extracellular action potential (AP) traces enabled their assignment to the axon initial segment (AIS), axonal arbor and proximal somatodendritic compartments. Stimulation at the AIS required low voltages and provided immediate, selective and reliable neuronal activation, whereas stimulation at the soma required high voltages and produced delayed and unreliable responses. Subthreshold stimulation at the soma depolarized the somatic membrane potential without eliciting APs.

Identification of Matra Region and Overlapping Characters for OCR of Printed Bengali Scripts

NASA Astrophysics Data System (ADS)

Goswami, Subhra Sundar

One of the important reasons for poor recognition rate in optical character recognition (OCR) system is the error in character segmentation. In case of Bangla scripts, the errors occur due to several reasons, which include incorrect detection of matra (headline), over-segmentation and under-segmentation. We have proposed a robust method for detecting the headline region. Existence of overlapping characters (in under-segmented parts) in scanned printed documents is a major problem in designing an effective character segmentation procedure for OCR systems. In this paper, a predictive algorithm is developed for effectively identifying overlapping characters and then selecting the cut-borders for segmentation. Our method can be successfully used in achieving high recognition result.

Monolithic single mode interband cascade lasers with wide wavelength tunability

NASA Astrophysics Data System (ADS)

von Edlinger, M.; Weih, R.; Scheuermann, J.; Nähle, L.; Fischer, M.; Koeth, J.; Kamp, M.; Höfling, S.

2016-11-01

Monolithic two-section interband cascade lasers offering a wide wavelength tunability in the wavelength range around 3.7 μm are presented. Stable single mode emission in several wavelength channels was realized using the concept of binary superimposed gratings and two-segment Vernier-tuning. The wavelength selective elements in the two segments were based on specially designed lateral metal grating structures defined by electron beam lithography. A dual-step dry etch process provided electrical separation between the segments. Individual current control of the segments allowed wavelength channel selection as well as continuous wavelength tuning within channels. A discontinuous tuning range extending over 158 nm in up to six discrete wavelength channels was achieved. Mode hop free wavelength tuning up to 14 nm was observed within one channel. The devices can be operated in continuous wave mode up to 30 °C with the output powers of 3.5 mW around room temperature.

Importance of fishing as a segmentation variable in the application of a social worlds model

USGS Publications Warehouse

Gigliotti, Larry M.; Chase, Loren

2017-01-01

Market segmentation is useful to understanding and classifying the diverse range of outdoor recreation experiences sought by different recreationists. Although many different segmentation methodologies exist, many are complex and difficult to measure accurately during in-person intercepts, such as that of creel surveys. To address that gap in the literature, we propose a single-item measure of the importance of fishing as a surrogate to often overly- or needlesslycomplex segmentation techniques. The importance of fishing item is a measure of the value anglers place on the activity or a coarse quantification of how central the activity is to the respondent’s lifestyle (scale: 0 = not important, 1 = slightly, 2 = moderately, 3 = very, and 4 = fishing is my most important recreational activity). We suggest the importance scale may be a proxy measurement for segmenting anglers using the social worlds model as a theoretical framework. Vaske (1980) suggested that commitment to recreational activities may be best understood in relation to social group participation and the social worlds model provides a rich theoretical framework for understanding social group segments. Unruh (1983) identified four types of actor involvement in social worlds: strangers, tourists, regulars, and insiders, differentiated by four characteristics (orientation, experiences, relationships, and commitment). We evaluated the importance of fishing as a segmentation variable using data collected by a mixed-mode survey of South Dakota anglers fishing in 2010. We contend that this straightforward measurement may be useful for segmenting outdoor recreation activities when more complicated segmentation schemes are not suitable. Further, this index, when coupled with the social worlds model, provides a valuable framework for understanding the segments and making management decisions.

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

WE-EF-210-08: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in Ultrasound Images Using Patch-Based Anatomical Feature

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

Yang, X; Rossi, P; Jani, A

Purpose: Transrectal ultrasound (TRUS) is the standard imaging modality for the image-guided prostate-cancer interventions (e.g., biopsy and brachytherapy) due to its versatility and real-time capability. Accurate segmentation of the prostate plays a key role in biopsy needle placement, treatment planning, and motion monitoring. As ultrasound images have a relatively low signal-to-noise ratio (SNR), automatic segmentation of the prostate is difficult. However, manual segmentation during biopsy or radiation therapy can be time consuming. We are developing an automated method to address this technical challenge. Methods: The proposed segmentation method consists of two major stages: the training stage and the segmentation stage.more » During the training stage, patch-based anatomical features are extracted from the registered training images with patient-specific information, because these training images have been mapped to the new patient’ images, and the more informative anatomical features are selected to train the kernel support vector machine (KSVM). During the segmentation stage, the selected anatomical features are extracted from newly acquired image as the input of the well-trained KSVM and the output of this trained KSVM is the segmented prostate of this patient. Results: This segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentation. The mean volume Dice Overlap Coefficient was 89.7±2.3%, and the average surface distance was 1.52 ± 0.57 mm between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D ultrasound-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentation (gold standard). This segmentation technique could be a useful tool for image-guided interventions in prostate-cancer diagnosis and treatment. This research is supported in part by DOD PCRP Award W81XWH-13-1-0269, and National Cancer Institute (NCI) Grant CA114313.« less

Automatic construction of patient-specific finite-element mesh of the spine from IVDs and vertebra segmentations

NASA Astrophysics Data System (ADS)

Castro-Mateos, Isaac; Pozo, Jose M.; Lazary, Aron; Frangi, Alejandro F.

2016-03-01

Computational medicine aims at developing patient-specific models to help physicians in the diagnosis and treatment selection for patients. The spine, and other skeletal structures, is an articulated object, composed of rigid bones (vertebrae) and non-rigid parts (intervertebral discs (IVD), ligaments and muscles). These components are usually extracted from different image modalities, involving patient repositioning. In the case of the spine, these models require the segmentation of IVDs from MR and vertebrae from CT. In the literature, there exists a vast selection of segmentations methods, but there is a lack of approaches to align the vertebrae and IVDs. This paper presents a method to create patient-specific finite element meshes for biomechanical simulations, integrating rigid and non-rigid parts of articulated objects. First, the different parts are aligned in a complete surface model. Vertebrae extracted from CT are rigidly repositioned in between the IVDs, initially using the IVDs location and then refining the alignment using the MR image with a rigid active shape model algorithm. Finally, a mesh morphing algorithm, based on B-splines, is employed to map a template finite-element (volumetric) mesh to the patient-specific surface mesh. This morphing reduces possible misalignments and guarantees the convexity of the model elements. Results show that the accuracy of the method to align vertebrae into MR, together with IVDs, is similar to that of the human observers. Thus, this method is a step forward towards the automation of patient-specific finite element models for biomechanical simulations.

Learning a constrained conditional random field for enhanced segmentation of fallen trees in ALS point clouds

NASA Astrophysics Data System (ADS)

Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe

2018-06-01

In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline is composed of two steps. First, short stem segments of equal length are detected and a subset of them is selected for further processing, while in the second step the chosen segments are merged to form entire trees. The first step is accomplished using the specialized CRF defined on the space of segment labelings, capable of finding segment candidates which are easier to merge subsequently. To achieve this, the CRF considers not only the features of every candidate individually, but incorporates pairwise spatial interactions between adjacent segments into the model. In particular, pairwise interactions include a collinearity/angular deviation probability which is learned from training data as well as the ratio of spatial overlap, whereas unary potentials encode a learned probabilistic model of the laser point distribution around each segment. Each of these components enters the CRF energy with its own balance factor. To process previously unseen data, we first calculate the subset of segments for merging on a grid of balance factors by minimizing the CRF energy. Then, we perform the merging and rank the balance configurations according to the quality of their resulting merged trees, obtained from a learned tree appearance model. The final result is derived from the top-ranked configuration. We tested our approach on 5 plots from the Bavarian Forest National Park using reference data acquired in a field inventory. Compared to our previous segment selection method without pairwise interactions, an increase in detection correctness and completeness of up to 7 and 9 percentage points, respectively, was observed.

Strain analysis in CRT candidates using the novel segment length in cine (SLICE) post-processing technique on standard CMR cine images.

PubMed

Zweerink, Alwin; Allaart, Cornelis P; Kuijer, Joost P A; Wu, LiNa; Beek, Aernout M; van de Ven, Peter M; Meine, Mathias; Croisille, Pierre; Clarysse, Patrick; van Rossum, Albert C; Nijveldt, Robin

2017-12-01

Although myocardial strain analysis is a potential tool to improve patient selection for cardiac resynchronization therapy (CRT), there is currently no validated clinical approach to derive segmental strains. We evaluated the novel segment length in cine (SLICE) technique to derive segmental strains from standard cardiovascular MR (CMR) cine images in CRT candidates. Twenty-seven patients with left bundle branch block underwent CMR examination including cine imaging and myocardial tagging (CMR-TAG). SLICE was performed by measuring segment length between anatomical landmarks throughout all phases on short-axis cines. This measure of frame-to-frame segment length change was compared to CMR-TAG circumferential strain measurements. Subsequently, conventional markers of CRT response were calculated. Segmental strains showed good to excellent agreement between SLICE and CMR-TAG (septum strain, intraclass correlation coefficient (ICC) 0.76; lateral wall strain, ICC 0.66). Conventional markers of CRT response also showed close agreement between both methods (ICC 0.61-0.78). Reproducibility of SLICE was excellent for intra-observer testing (all ICC ≥0.76) and good for interobserver testing (all ICC ≥0.61). The novel SLICE post-processing technique on standard CMR cine images offers both accurate and robust segmental strain measures compared to the 'gold standard' CMR-TAG technique, and has the advantage of being widely available. • Myocardial strain analysis could potentially improve patient selection for CRT. • Currently a well validated clinical approach to derive segmental strains is lacking. • The novel SLICE technique derives segmental strains from standard CMR cine images. • SLICE-derived strain markers of CRT response showed close agreement with CMR-TAG. • Future studies will focus on the prognostic value of SLICE in CRT candidates.

Pulmonary airways tree segmentation from CT examinations using adaptive volume of interest

NASA Astrophysics Data System (ADS)

Park, Sang Cheol; Kim, Won Pil; Zheng, Bin; Leader, Joseph K.; Pu, Jiantao; Tan, Jun; Gur, David

2009-02-01

Airways tree segmentation is an important step in quantitatively assessing the severity of and changes in several lung diseases such as chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis. It can also be used in guiding bronchoscopy. The purpose of this study is to develop an automated scheme for segmenting the airways tree structure depicted on chest CT examinations. After lung volume segmentation, the scheme defines the first cylinder-like volume of interest (VOI) using a series of images depicting the trachea. The scheme then iteratively defines and adds subsequent VOIs using a region growing algorithm combined with adaptively determined thresholds in order to trace possible sections of airways located inside the combined VOI in question. The airway tree segmentation process is automatically terminated after the scheme assesses all defined VOIs in the iteratively assembled VOI list. In this preliminary study, ten CT examinations with 1.25mm section thickness and two different CT image reconstruction kernels ("bone" and "standard") were selected and used to test the proposed airways tree segmentation scheme. The experiment results showed that (1) adopting this approach affectively prevented the scheme from infiltrating into the parenchyma, (2) the proposed method reasonably accurately segmented the airways trees with lower false positive identification rate as compared with other previously reported schemes that are based on 2-D image segmentation and data analyses, and (3) the proposed adaptive, iterative threshold selection method for the region growing step in each identified VOI enables the scheme to segment the airways trees reliably to the 4th generation in this limited dataset with successful segmentation up to the 5th generation in a fraction of the airways tree branches.

Segmentation and tracking in echocardiographic sequences: active contours guided by optical flow estimates

NASA Technical Reports Server (NTRS)

Mikic, I.; Krucinski, S.; Thomas, J. D.

1998-01-01

This paper presents a method for segmentation and tracking of cardiac structures in ultrasound image sequences. The developed algorithm is based on the active contour framework. This approach requires initial placement of the contour close to the desired position in the image, usually an object outline. Best contour shape and position are then calculated, assuming that at this configuration a global energy function, associated with a contour, attains its minimum. Active contours can be used for tracking by selecting a solution from a previous frame as an initial position in a present frame. Such an approach, however, fails for large displacements of the object of interest. This paper presents a technique that incorporates the information on pixel velocities (optical flow) into the estimate of initial contour to enable tracking of fast-moving objects. The algorithm was tested on several ultrasound image sequences, each covering one complete cardiac cycle. The contour successfully tracked boundaries of mitral valve leaflets, aortic root and endocardial borders of the left ventricle. The algorithm-generated outlines were compared against manual tracings by expert physicians. The automated method resulted in contours that were within the boundaries of intraobserver variability.

Skeletal muscle fiber, nerve, and blood vessel breakdown in space-flown rats

NASA Technical Reports Server (NTRS)

Riley, D. A.; Ilyina-Kakueva, E. I.; Ellis, S.; Bain, J. L.; Slocum, G. R.; Sedlak, F. R.

1990-01-01

Histochemical and ultrastructural analyses were performed postflight on hind limb skeletal muscles of rats orbited for 12.5 days aboard the unmanned Cosmos 1887 biosatellite and returned to Earth 2 days before sacrifice. The antigravity adductor longus (AL), soleus, and plantaris muscles atrophied more than the non-weight-bearing extensor digitorum longus, and slow muscle fibers were more atrophic than fast fibers. Muscle fiber segmental necrosis occurred selectively in the AL and soleus muscles; primarily, macrophages and neutrophils infiltrated and phagocytosed cellular debris. Granule-rich mast cells were diminished in flight AL muscles compared with controls, indicating the mast cell secretion contributed to interstitial tissue edema. Increased ubiquitination of disrupted myofibrils implicated ubiquitin in myofilament degradation. Mitochondrial content and succinic dehydrogenase activity were normal, except for subsarcolemmal decreases. Myofibrillar ATPase activity of flight AL muscle fibers shifted toward the fast type. Absence of capillaries and extravasation of red blood cells indicated failed microcirculation. Muscle fiber regeneration from activated satellite cells was detected. About 17% of the flight AL end plates exhibited total or partial denervation. Thus, skeletal muscle weakness associated with spaceflight can result from muscle fiber atrophy and segmental necrosis, partial motor denervation, and disruption of the microcirculation.

Development of a pedestrian audit tool to assess rural neighborhood walkability.

PubMed

Scanlin, Kathleen; Haardoerfer, Regine; Kegler, Michelle C; Glanz, Karen

2014-08-01

Recently, investigators have begun to refine audit instruments for use in rural areas. However, no studies have developed a walkability summary score or have correlated built environment characteristics with physical activity behavior. The Rural Pedestrian Environmental Audit Instrument was developed specifically for use in rural areas. Segments surrounding participant's homes were selected to represent neighborhood streets (N = 116). Interrater reliability was conducted on a subset of streets (N = 42). Rural-specific domain and walkability scores were developed and correlated with individual-level data on perceptions of the neighborhood and self-reported physical activity behavior. Interrater reliability for the instrument was substantial and all domains had high agreement. Walkability in the audited area was low with even the best segments demonstrating only moderate support for walking. There were no significant correlations between the neighborhood walkability score and self-reported neighborhood walkability, time spent walking, sedentary behavior, or BMI; however, a few correlations within the social/dynamic domain were significant. This study expands recent research refining audit instruments for rural areas. Findings suggest the usefulness of summarizing environmental data at the domain level and linking it to physical activity behavior to identify aspects of the neighborhood environment that are most strongly correlated with actual behavior.

[Bacterial biofilms on PVC tubing's inner surface of hemodialysis water treatment system].

PubMed

Yang, Sha; Jia, Ke; Peng, Youming; Liu, Hong; Liu, Yinghong; Chen, Xing; Liu, Fuyou

2009-10-01

To determine the morphology, bacteria and endotoxin content of biofilms on the inner surface of PVC tubes in hemodialysis water treatment system. We dissolved biofilms of segments before and after reverse osmosis machine for bacterial count and identification. We studied biofilm structure of segments before and after reverse osmosis machine with eyes and scanning electron microscope. Biofilms of all 7 segments were dissolved for qualitative and quantitative assay of endotoxin. The inner surface of segment before reverse osmosis machine was homogeneously distributed with activated carbon powder deposition. The segment after reverse osmosis machine was normal. With scanning electron microscope, biofilm with successive surface and sandwich was found on the inner surface of segment before reverse osmosis machine, formed by clustering bacillus, activated carbon powder and some coccus. Bacteria of the same shape and length were found on segment after reverse osmosis machine, but fewer and looser. Bacterial culture and identification showed the former was mostly gram-negative bacillus, the latter was only a few micrococcus. Endotoxin of biofilm was between 2.0 EU/mL and 4.0 EU/mL. Quantitative assay showed: segment after softener (2.821+/-0.807) EU/mL; segment after active charcoal canister(3.635+/-0.427) EU/mL; segment before reverse osmosis machine (3.687+/-0.271) EU/mL; segment after reverse osmosis machine (2.041+/-0.295) EU/mL; exit of power pump (1.983+/-0.390)EU/mL;the 1st dead space (2.373+/-0.535) EU/mL; and the 2nd dead space (2.858+/-0.690)EU/mL. Biofilms are found on the inner surface of segment before and after reverse osmosis machine. Endotoxin level from high to low is as follows: segment before reverse osmosis machine, segment after active charcoal canister, the 2nd dead space, segment after softener, the 1st dead space, segment after reverse osmosis machine, exit of power pump. The character of the bacteria and endotoxin of the biofilm can help us find better ways to control them.

Automated Selection of Hotspots (ASH): enhanced automated segmentation and adaptive step finding for Ki67 hotspot detection in adrenal cortical cancer.

PubMed

Lu, Hao; Papathomas, Thomas G; van Zessen, David; Palli, Ivo; de Krijger, Ronald R; van der Spek, Peter J; Dinjens, Winand N M; Stubbs, Andrew P

2014-11-25

In prognosis and therapeutics of adrenal cortical carcinoma (ACC), the selection of the most active areas in proliferative rate (hotspots) within a slide and objective quantification of immunohistochemical Ki67 Labelling Index (LI) are of critical importance. In addition to intratumoral heterogeneity in proliferative rate i.e. levels of Ki67 expression within a given ACC, lack of uniformity and reproducibility in the method of quantification of Ki67 LI may confound an accurate assessment of Ki67 LI. We have implemented an open source toolset, Automated Selection of Hotspots (ASH), for automated hotspot detection and quantification of Ki67 LI. ASH utilizes NanoZoomer Digital Pathology Image (NDPI) splitter to convert the specific NDPI format digital slide scanned from the Hamamatsu instrument into a conventional tiff or jpeg format image for automated segmentation and adaptive step finding hotspots detection algorithm. Quantitative hotspot ranking is provided by the functionality from the open source application ImmunoRatio as part of the ASH protocol. The output is a ranked set of hotspots with concomitant quantitative values based on whole slide ranking. We have implemented an open source automated detection quantitative ranking of hotspots to support histopathologists in selecting the 'hottest' hotspot areas in adrenocortical carcinoma. To provide wider community easy access to ASH we implemented a Galaxy virtual machine (VM) of ASH which is available from http://bioinformatics.erasmusmc.nl/wiki/Automated_Selection_of_Hotspots . The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_216.

Rif1 is a global regulator of timing of replication origin firing in fission yeast

PubMed Central

Hayano, Motoshi; Kanoh, Yutaka; Matsumoto, Seiji; Renard-Guillet, Claire; Shirahige, Katsuhiko; Masai, Hisao

2012-01-01

One of the long-standing questions in eukaryotic DNA replication is the mechanisms that determine where and when a particular segment of the genome is replicated. Cdc7/Hsk1 is a conserved kinase required for initiation of DNA replication and may affect the site selection and timing of origin firing. We identified rif1Δ, a null mutant of rif1+, a conserved telomere-binding factor, as an efficient bypass mutant of fission yeast hsk1. Extensive deregulation of dormant origins over a wide range of the chromosomes occurs in rif1Δ in the presence or absence of hydroxyurea (HU). At the same time, many early-firing, efficient origins are suppressed or delayed in firing timing in rif1Δ. Rif1 binds not only to telomeres, but also to many specific locations on the arm segments that only partially overlap with the prereplicative complex assembly sites, although Rif1 tends to bind in the vicinity of the late/dormant origins activated in rif1Δ. The binding to the arm segments occurs through M to G1 phase in a manner independent of Taz1 and appears to be essential for the replication timing program during the normal cell cycle. Our data demonstrate that Rif1 is a critical determinant of the origin activation program on the fission yeast chromosomes. PMID:22279046

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

A hybrid segmentation method for partitioning the liver based on 4D DCE-MR images

NASA Astrophysics Data System (ADS)

Zhang, Tian; Wu, Zhiyi; Runge, Jurgen H.; Lavini, Cristina; Stoker, Jaap; van Gulik, Thomas; Cieslak, Kasia P.; van Vliet, Lucas J.; Vos, Frans M.

2018-03-01

The Couinaud classification of hepatic anatomy partitions the liver into eight functionally independent segments. Detection and segmentation of the hepatic vein (HV), portal vein (PV) and inferior vena cava (IVC) plays an important role in the subsequent delineation of the liver segments. To facilitate pharmacokinetic modeling of the liver based on the same data, a 4D DCE-MR scan protocol was selected. This yields images with high temporal resolution but low spatial resolution. Since the liver's vasculature consists of many tiny branches, segmentation of these images is challenging. The proposed framework starts with registration of the 4D DCE-MRI series followed by region growing from manually annotated seeds in the main branches of key blood vessels in the liver. It calculates the Pearson correlation between the time intensity curves (TICs) of a seed and all voxels. A maximum correlation map for each vessel is obtained by combining the correlation maps for all branches of the same vessel through a maximum selection per voxel. The maximum correlation map is incorporated in a level set scheme to individually delineate the main vessels. Subsequently, the eight liver segments are segmented based on three vertical intersecting planes fit through the three skeleton branches of HV and IVC's center of mass as well as a horizontal plane fit through the skeleton of PV. Our segmentation regarding delineation of the vessels is more accurate than the results of two state-of-the-art techniques on five subjects in terms of the average symmetric surface distance (ASSD) and modified Hausdorff distance (MHD). Furthermore, the proposed liver partitioning achieves large overlap with manual reference segmentations (expressed in Dice Coefficient) in all but a small minority of segments (mean values between 87% and 94% for segments 2-8). The lower mean overlap for segment 1 (72%) is due to the limited spatial resolution of our DCE-MR scan protocol.

Numerical arc segmentation algorithm for a radio conference: A software tool for communication satellite systems planning

NASA Technical Reports Server (NTRS)

Whyte, W. A.; Heyward, A. O.; Ponchak, D. S.; Spence, R. L.; Zuzek, J. E.

1988-01-01

The Numerical Arc Segmentation Algorithm for a Radio Conference (NASARC) provides a method of generating predetermined arc segments for use in the development of an allotment planning procedure to be carried out at the 1988 World Administrative Radio Conference (WARC) on the Use of the Geostationary Satellite Orbit and the Planning of Space Services Utilizing It. Through careful selection of the predetermined arc (PDA) for each administration, flexibility can be increased in terms of choice of system technical characteristics and specific orbit location while reducing the need for coordination among administrations. The NASARC software determines pairwise compatibility between all possible service areas at discrete arc locations. NASARC then exhaustively enumerates groups of administrations whose satellites can be closely located in orbit, and finds the arc segment over which each such compatible group exists. From the set of all possible compatible groupings, groups and their associated arc segments are selected using a heuristic procedure such that a PDA is identified for each administration. Various aspects of the NASARC concept and how the software accomplishes specific features of allotment planning are discussed.

A smooth muscle tone-dependent stretch-activated migrating motor pattern in isolated guinea-pig distal colon.

PubMed

Smith, Terence K; Oliver, Gavin R; Hennig, Grant W; O'Shea, Deirdre M; Vanden Berghe, Pieter; Kang, Sok Han; Spencer, Nick J

2003-09-15

We have investigated the tone dependence of the intrinsic nervous activity generated by localized wall distension in isolated segments of guinea-pig distal colon using mechanical recordings and video imaging of wall movements. A segment of colon was threaded through two partitions, which divided the colon for pharmacological purposes into oral, stimulation and anal regions. An intraluminal balloon was located in the stimulation region between the two partitions (12 mm apart). Maintained colonic distension by an intraluminal balloon or an artificial faecal pellet held at a fixed location generated rhythmic (frequency 0.3 contractions min(-1); duration approximately 60 s) peristaltic waves of contraction. Video imaging of colonic wall movements or the selective application of pharmacological agents suggested that peristaltic waves originated just oral (< or = 4 mm) to the pellet and propagated both orally (approximately 11 mm s(-1)) and anally (approximately 1 mm s(-1)). Also, during a peristaltic wave the colon appears to passively shorten in front of a pellet, as a result of an active contraction of the longitudinal muscle oral to the pellet. Faecal pellet movement only occurred when a rhythmic peristaltic wave was generated. Rhythmic peristaltic waves were abolished in all regions by the smooth muscle relaxants isoproterenol (1 microM), nicardipine (1 microM) or papavarine (10 microM), and by the neural antagonists tetrodotoxin (TTX; 0.6 microM), hexamethonium (100 microM) or atropine (1 microM), when added selectively to the stimulation region. Nicardipine, atropine, TTX, or hexamethonium (100 microM) also blocked the evoked peristaltic waves when selectively added to the oral region. Nomega-nitro-L-arginine (L-NA; 100 microM) added to the anal region reduced the anal relaxation but increased the anal contraction, leading to an increase in the apparent conduction velocity of each peristaltic wave. In conclusion, maintained distension by a fixed artificial pellet generates propulsive, rhythmic peristaltic waves, whose enteric neural activity is critically dependent upon smooth muscle tone. These peristaltic waves usually originate just oral to the pellet, and their apparent conduction velocity is generated by activation of descending inhibitory nerve pathways.

Association between Latest Activated Sites in the Left Ventricle and Akinetic Segments in Patients with Ischemic Cardiomyopathy.

PubMed

Sadeghian, Hakimeh; Kousari, Aliasghar; Majidi, Shahla; Rezvanfard, Mehrnaz; Kazemisaeid, Ali; Moezzi, Seyed Ali; Vasheghani Farahani, Ali; Abdar Esfahani, Morteza; Sahebjam, Mohammad; Zoroufian, Arezoo; Sadeghian, Afsaneh

2016-07-06

Background: It is not clear whether the latest activation sites in the left ventricle (LV) are matched with infracted regions in patients with ischemic cardiomyopathy (ICM). We aimed to investigate whether the latest activation sites in the LV are in agreement with the region of akinesia in patients with ICM. Methods: Data were analyzed in 106 patients (age = 60.5 ± 12.1 y, male = 88.7%) with ICM (ejection fraction ≤ 35%) who were refractory to pharmacological therapy and were referred to the echocardiography department for an evaluation of the feasibility of cardiac resynchronization therapy. Wall motion abnormalities, time to peak systolic myocardial velocity (Ts) of 6 basal and 6 mid-portion segments of the LV, and 4 frequently used dyssynchrony indices were measured using 2-dimensional echocardiography and tissue Doppler imaging (TDI). To evaluate the influence of the electrocardiographic pattern, we categorized the patients into 2 groups: patients with QRS ≤ 120 ms and those with QRS >120 ms. Results: A total of 1 272 segments were studied. The latest activation sites (with longest Ts) were most frequently located in the mid-anterior (n = 32, 30.2%) and basal-anterior segments (n = 29, 27.4%), while the most common sites of akinesia were the mid-anteroseptal (n = 65, 61.3%) and mid-septal (n = 51, 48.1%) segments. Generally, no significant concordance was found between the latest activated segments and akinesia either in all the patients or in the QRS groups. Detailed analysis within the segments indicated a good agreement between akinesia and delayed activation in the basal-lateral segment solely in the patients with QRS duration ≤ 120 ms (Φ = 0.707; p value ≤ 0.001). Conclusion: The akinetic segment on 2-dimensional echocardiogram was not matched with the latest activation sites in the LV determined by TDI in patients with ICM.

Association between Latest Activated Sites in the Left Ventricle and Akinetic Segments in Patients with Ischemic Cardiomyopathy

PubMed Central

Sadeghian, Hakimeh; Kousari, Aliasghar; Majidi, Shahla; Rezvanfard, Mehrnaz; Kazemisaeid, Ali; Moezzi, Seyed Ali; Vasheghani Farahani, Ali; Abdar Esfahani, Morteza; Sahebjam, Mohammad; Zoroufian, Arezoo; Sadeghian, Afsaneh

2016-01-01

Background: It is not clear whether the latest activation sites in the left ventricle (LV) are matched with infracted regions in patients with ischemic cardiomyopathy (ICM). We aimed to investigate whether the latest activation sites in the LV are in agreement with the region of akinesia in patients with ICM. Methods: Data were analyzed in 106 patients (age = 60.5 ± 12.1 y, male = 88.7%) with ICM (ejection fraction ≤ 35%) who were refractory to pharmacological therapy and were referred to the echocardiography department for an evaluation of the feasibility of cardiac resynchronization therapy. Wall motion abnormalities, time to peak systolic myocardial velocity (Ts) of 6 basal and 6 mid-portion segments of the LV, and 4 frequently used dyssynchrony indices were measured using 2-dimensional echocardiography and tissue Doppler imaging (TDI). To evaluate the influence of the electrocardiographic pattern, we categorized the patients into 2 groups: patients with QRS ≤ 120 ms and those with QRS >120 ms. Results: A total of 1 272 segments were studied. The latest activation sites (with longest Ts) were most frequently located in the mid-anterior (n = 32, 30.2%) and basal-anterior segments (n = 29, 27.4%), while the most common sites of akinesia were the mid-anteroseptal (n = 65, 61.3%) and mid-septal (n = 51, 48.1%) segments. Generally, no significant concordance was found between the latest activated segments and akinesia either in all the patients or in the QRS groups. Detailed analysis within the segments indicated a good agreement between akinesia and delayed activation in the basal-lateral segment solely in the patients with QRS duration ≤ 120 ms (Φ = 0.707; p value ≤ 0.001). Conclusion: The akinetic segment on 2-dimensional echocardiogram was not matched with the latest activation sites in the LV determined by TDI in patients with ICM. PMID:27956911

Employee Choice of a High-Deductible Health Plan across Multiple Employers

PubMed Central

Lave, Judith R; Men, Aiju; Day, Brian T; Wang, Wei; Zhang, Yuting

2011-01-01

Objective To determine factors associated with selecting a high-deductible health plan (HDHP) rather than a preferred provider plan (PPO) and to examine switching and market segmentation after initial selection. Data Sources/Study Setting Claims and benefit information for 2005–2007 from nine employers in western Pennsylvania first offering HDHP in 2006. Study Design We examined plan growth over time, used logistic regression to determine factors associated with choosing an HDHP, and examined the distribution of healthy and sick members across plan types. Data Extraction We linked employees with their dependents to determine family-level variables. We extracted risk scores, covered charges, employee age, and employee gender from claims data. We determined census-level race, education, and income information. Principal Findings Health status, gender, race, and education influenced the type of individual and family policies chosen. In the second year the HDHP was offered, few employees changed plans. Risk segmentation between HDHPs and PPOs existed, but it did not increase. Conclusions When given a choice, those who are healthier are more likely to select an HDHP leading to risk segmentation. Risk segmentation did not increase in the second year that HDHPs were offered. PMID:20849558

Mixture of Segmenters with Discriminative Spatial Regularization and Sparse Weight Selection*

PubMed Central

Chen, Ting; Rangarajan, Anand; Eisenschenk, Stephan J.

2011-01-01

This paper presents a novel segmentation algorithm which automatically learns the combination of weak segmenters and builds a strong one based on the assumption that the locally weighted combination varies w.r.t. both the weak segmenters and the training images. We learn the weighted combination during the training stage using a discriminative spatial regularization which depends on training set labels. A closed form solution to the cost function is derived for this approach. In the testing stage, a sparse regularization scheme is imposed to avoid overfitting. To the best of our knowledge, such a segmentation technique has never been reported in literature and we empirically show that it significantly improves on the performances of the weak segmenters. After showcasing the performance of the algorithm in the context of atlas-based segmentation, we present comparisons to the existing weak segmenter combination strategies on a hippocampal data set. PMID:22003748

A RT-PCR method for selective amplification and phenotypic characterization of all three serotypes of Sabin-related polioviruses from viral mixtures.

PubMed

Costa, Eliane Veiga da; Campos, Renata de Mendonça; Tavares, Fernando Neto; Grégio, Cátia Regina Valério; Burlandy, Fernanda Marcicano; Silva, Edson Elias da

2012-08-01

Outbreaks caused by vaccine-derived polioviruses are challenging the final eradication of paralytic poliomyelitis. Therefore, the surveillance of the acute flaccid paralysis cases based on poliovirus isolation and characterization remains an essential activity. Due to the use of trivalent oral poliovirus vaccine (OPV), mixtures containing more than one serotype of Sabin-related polioviruses are frequently isolated from clinical samples. Because each poliovirus isolate needs to be individually analyzed, we designed polymerase chain reaction primers that can selectively distinguish and amplify a genomic segment of the three Sabin-related poliovirus serotypes present in mixtures, thus, optimizing the diagnosis and providing prompt information to support epidemiologic actions.

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.

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

Marques da Silva, A; Narciso, L

Purpose: Commercial workstations usually have their own software to calculate dynamic renal functions. However, usually they have low flexibility and subjectivity on delimiting kidney and background areas. The aim of this paper is to present a public domain software, called RenalQuant, capable to semi-automatically draw regions of interest on dynamic renal scintigraphies, extracting data and generating renal function quantification parameters. Methods: The software was developed in Java and written as an ImageJ-based plugin. The preprocessing and segmentation steps include the user’s selection of one time frame with higher activity in kidney’s region, compared with background, and low activity in themore » liver. Next, the chosen time frame is smoothed using a Gaussian low pass spatial filter (σ = 3) for noise reduction and better delimitation of kidneys. The maximum entropy thresholding method is used for segmentation. A background area is automatically placed below each kidney, and the user confirms if these regions are correctly segmented and positioned. Quantitative data are extracted and each renogram and relative renal function (RRF) value is calculated and displayed. Results: RenalQuant plugin was validated using retrospective 20 patients’ 99mTc-DTPA exams, and compared with results produced by commercial workstation software, referred as reference. The renograms intraclass correlation coefficients (ICC) were calculated and false-negative and false-positive RRF values were analyzed. The results showed that ICC values between RenalQuant plugin and reference software for both kidneys’ renograms were higher than 0.75, showing excellent reliability. Conclusion: Our results indicated RenalQuant plugin can be trustingly used to generate renograms, using DICOM dynamic renal scintigraphy exams as input. It is user friendly and user’s interaction occurs at a minimum level. Further studies have to investigate how to increase RRF accuracy and explore how to solve limitations in the segmentation step, mainly when background region has higher activity compared to kidneys. Financial support by CAPES.« less

Audience segmentation to promote lifestyle for cancer prevention in the Korean community.

PubMed

Jo, Heui-Sug; Jung, Su-Mi

2011-01-01

This study was designed to segment the audience group of '10 lifestyle for cancer prevention' based on demographic characteristics and the level of knowledge about each guideline for cancer prevention among the community in South Korea. Participants were chosen through stratified random sampling according to the age and gender distribution of Gangwon province in South Korea. A telephone survey was conducted from 6 to 15 calls among 2,025 persons on October 2008. A total of 1,687 persons completed the survey (response rate: 83.3%). Survey items were composed of socio-demographic characteristics such as age, gender, income, education, and residence area and the knowledge level of '10 guidelines for cancer prevention', developed by 'Korean Ministry of Health and Welfare' and covering smoking cessation, appropriate drinking, condom use, and regular physical activity and so on. We selected the priority needed to promote awareness and segmented the audience group based on the demographic characteristics, homogeneous with respect to the knowledge level using Answer Tree 3.0 with CHAID as a data mining algorithm. The results of analysis showed that each guideline of ' 10 lifestyle for cancer prevention' had its own segmented subgroup characterized by each demographic. Especially, residence area, city or county, and ages were the first split on the perceived level of knowledge and these findings suggested that segmentation of audiences for targeting is needed to deliver more effective education of patients and community people. In developing the strategy for effective education, the method of social marketing using the decision tree analysis could be a useful and appropriate tool. The study findings demonstrate the potential value of using more sophisticated strategies of designing and providing health information based on audience segmentation.

ZResponse to selection, heritability and genetic correlations between body weight and body size in Pacific white shrimp, Litopenaeus vannamei

NASA Astrophysics Data System (ADS)

Andriantahina, Farafidy; Liu, Xiaolin; Huang, Hao; Xiang, Jianhai

2012-03-01

To quantify the response to selection, heritability and genetic correlations between weight and size of Litopenaeus vannamei, the body weight (BW), total length (TL), body length (BL), first abdominal segment depth (FASD), third abdominal segment depth (TASD), first abdominal segment width (FASW), and partial carapace length (PCL) of 5-month-old parents and of offspnng were measured by calculating seven body measunngs of offspnng produced by a nested mating design. Seventeen half-sib families and 42 full-sib families of L. vannamei were produced using artificial fertilization from 2-4 dams by each sire, and measured at around five months post-metamorphosis. The results show that hentabilities among vanous traits were high: 0.515±0.030 for body weight and 0.394±0.030 for total length. After one generation of selection. the selection response was 10.70% for offspring growth. In the 5th month, the realized heritability for weight was 0.296 for the offspnng generation. Genetic correlations between body weight and body size were highly variable. The results indicate that external morphological parameters can be applied dunng breeder selection for enhancing the growth without sacrificing animals for determining the body size and breed ability; and selective breeding can be improved significantly, simultaneously with increased production.

Synthesis and activity of novel analogs of hemiasterlin as inhibitors of tubulin polymerization: modification of the A segment.

PubMed

Yamashita, Ayako; Norton, Emily B; Kaplan, Joshua A; Niu, Chuan; Loganzo, Frank; Hernandez, Richard; Beyer, Carl F; Annable, Tami; Musto, Sylvia; Discafani, Carolyn; Zask, Arie; Ayral-Kaloustian, Semiramis

2004-11-01

Analogs of hemiasterlin (1) and HTI-286 (2), which contain various aromatic rings in the A segment, were synthesized as potential inhibitors of tubulin polymerization. The structure-activity relationships related to stereo- and regio-chemical effects of substituents on the aromatic ring in the A segment were studied. Analogs, which carry a meta-substituted phenyl ring in the A segment show comparable activity for inhibition of tubulin polymerization to 2, as well as in the cell proliferation assay using KB cells containing P-glycoprotein, compared to those of 1 and 2.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation.

PubMed

Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

2015-08-19

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation

PubMed Central

Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

2015-01-01

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions. PMID:26295395

Natural selection in the colloid world: active chiral spirals.

PubMed

Zhang, Jie; Granick, Steve

2016-10-06

We present a model system in which to study natural selection in the colloid world. In the assembly of active Janus particles into rotating pinwheels when mixed with trace amounts of homogeneous colloids in the presence of an AC electric field, broken symmetry in the rotation direction produces spiral, chiral shapes. Locked into a central rotation point by the centre particle, the spiral arms are found to trail rotation of the overall cluster. To achieve a steady state, the spiral arms undergo an evolutionary process to coordinate their motion. Because all the particles as segments of the pinwheel arms are self-propelled, asymmetric arm lengths are tolerated. Reconfiguration of these structures can happen in various ways and various mechanisms of this directed structural change are analyzed in detail. We introduce the concept of VIP (very important particles) to express that sustainability of active structures is most sensitive to only a few particles at strategic locations in the moving self-assembled structures.

A segmental pattern of alkaline phosphatase activity within the notochord coincides with the initial formation of the vertebral bodies.

PubMed

Grotmol, Sindre; Nordvik, Kari; Kryvi, Harald; Totland, Geir K

2005-05-01

This study shows that segmental expression of alkaline phosphatase (ALP) activity by the notochord of the Atlantic salmon (Salmo salar L.) coincides with the initial mineralization of the vertebral body (chordacentrum), and precedes ALP expression by presumed somite-derived cells external to the notochordal sheath. The early expression of ALP indicates that the notochord plays an instructive role in the segmental patterning of the vertebral column. The chordacentra form segmentally as mineralized rings within the notochordal sheath, and ALP activity spreads within the chordoblast layer from ventral to dorsal, displaying the same progression and spatial distribution as the mineralization process. No ALP activity was observed in sclerotomal mesenchyme surrounding the notochordal sheath during initial formation of the chordacentra. Our results support previous findings indicating that the chordoblasts initiate a segmental differentiation of the notochordal sheath into chordacentra and intervertebral regions.

Three-dimensional segmentation of luminal and adventitial borders in serial intravascular ultrasound images

NASA Technical Reports Server (NTRS)

Shekhar, R.; Cothren, R. M.; Vince, D. G.; Chandra, S.; Thomas, J. D.; Cornhill, J. F.

1999-01-01

Intravascular ultrasound (IVUS) provides exact anatomy of arteries, allowing accurate quantitative analysis. Automated segmentation of IVUS images is a prerequisite for routine quantitative analyses. We present a new three-dimensional (3D) segmentation technique, called active surface segmentation, which detects luminal and adventitial borders in IVUS pullback examinations of coronary arteries. The technique was validated against expert tracings by computing correlation coefficients (range 0.83-0.97) and William's index values (range 0.37-0.66). The technique was statistically accurate, robust to image artifacts, and capable of segmenting a large number of images rapidly. Active surface segmentation enabled geometrically accurate 3D reconstruction and visualization of coronary arteries and volumetric measurements.

Flexible methods for segmentation evaluation: results from CT-based luggage screening.

PubMed

Karimi, Seemeen; Jiang, Xiaoqian; Cosman, Pamela; Martz, Harry

2014-01-01

Imaging systems used in aviation security include segmentation algorithms in an automatic threat recognition pipeline. The segmentation algorithms evolve in response to emerging threats and changing performance requirements. Analysis of segmentation algorithms' behavior, including the nature of errors and feature recovery, facilitates their development. However, evaluation methods from the literature provide limited characterization of the segmentation algorithms. To develop segmentation evaluation methods that measure systematic errors such as oversegmentation and undersegmentation, outliers, and overall errors. The methods must measure feature recovery and allow us to prioritize segments. We developed two complementary evaluation methods using statistical techniques and information theory. We also created a semi-automatic method to define ground truth from 3D images. We applied our methods to evaluate five segmentation algorithms developed for CT luggage screening. We validated our methods with synthetic problems and an observer evaluation. Both methods selected the same best segmentation algorithm. Human evaluation confirmed the findings. The measurement of systematic errors and prioritization helped in understanding the behavior of each segmentation algorithm. Our evaluation methods allow us to measure and explain the accuracy of segmentation algorithms.

Brain Activity and Human Unilateral Chewing

PubMed Central

Quintero, A.; Ichesco, E.; Myers, C.; Schutt, R.; Gerstner, G.E.

2012-01-01

Brain mechanisms underlying mastication have been studied in non-human mammals but less so in humans. We used functional magnetic resonance imaging (fMRI) to evaluate brain activity in humans during gum chewing. Chewing was associated with activations in the cerebellum, motor cortex and caudate, cingulate, and brainstem. We also divided the 25-second chew-blocks into 5 segments of equal 5-second durations and evaluated activations within and between each of the 5 segments. This analysis revealed activation clusters unique to the initial segment, which may indicate brain regions involved with initiating chewing. Several clusters were uniquely activated during the last segment as well, which may represent brain regions involved with anticipatory or motor events associated with the end of the chew-block. In conclusion, this study provided evidence for specific brain areas associated with chewing in humans and demonstrated that brain activation patterns may dynamically change over the course of chewing sequences. PMID:23103631

Bio-Inspired Sensing and Display of Polarization Imagery

DTIC Science & Technology

2005-07-17

and weighting coefficients in this example. Panel 4D clearly shows a better visibility, feature extraction , and lesser effect from the background...of linear polarization. Panel E represents the segmentation of the degree of linear polarization, and then Panel F shows the extracted segment with...polarization, and Panel F shows the segment extraction with the finger print selected. Panel G illustrates the application of Canny edge detection to

Dissociated repetition deficits in aphasia can reflect flexible interactions between left dorsal and ventral streams and gender-dimorphic architecture of the right dorsal stream

PubMed Central

Berthier, Marcelo L.; Froudist Walsh, Seán; Dávila, Guadalupe; Nabrozidis, Alejandro; Juárez y Ruiz de Mier, Rocío; Gutiérrez, Antonio; De-Torres, Irene; Ruiz-Cruces, Rafael; Alfaro, Francisco; García-Casares, Natalia

2013-01-01

Assessment of brain-damaged subjects presenting with dissociated repetition deficits after selective injury to either the left dorsal or ventral auditory pathways can provide further insight on their respective roles in verbal repetition. We evaluated repetition performance and its neural correlates using multimodal imaging (anatomical MRI, DTI, fMRI, and18FDG-PET) in a female patient with transcortical motor aphasia (TCMA) and in a male patient with conduction aphasia (CA) who had small contiguous but non-overlapping left perisylvian infarctions. Repetition in the TCMA patient was fully preserved except for a mild impairment in nonwords and digits, whereas the CA patient had impaired repetition of nonwords, digits and word triplet lists. Sentence repetition was impaired, but he repeated novel sentences significantly better than clichés. The TCMA patient had tissue damage and reduced metabolism in the left sensorimotor cortex and insula. DTI showed damage to the left temporo-frontal and parieto-frontal segments of the arcuate fasciculus (AF) and part of the left ventral stream together with well-developed right dorsal and ventral streams, as has been reported in more than one-third of females. The CA patient had tissue damage and reduced metabolic activity in the left temporoparietal cortex with additional metabolic decrements in the left frontal lobe. DTI showed damage to the left temporo-parietal and temporo-frontal segments of the AF, but the ventral stream was spared. The direct segment of the AF in the right hemisphere was also absent with only vestigial remains of the other dorsal subcomponents present, as is often found in males. fMRI during word and nonword repetition revealed bilateral perisylvian activation in the TCMA patient suggesting recruitment of spared segments of the left dorsal stream and right dorsal stream with propagation of signals to temporal lobe structures suggesting a compensatory reallocation of resources via the ventral streams. The CA patient showed a greater activation of these cortical areas than the TCMA patient, but these changes did not result in normal performance. Repetition of word triplet lists activated bilateral perisylvian cortices in both patients, but activation in the CA patient with very poor performance was restricted to small frontal and posterior temporal foci bilaterally. These findings suggest that dissociated repetition deficits in our cases are probably reliant on flexible interactions between left dorsal stream (spared segments, short tracts remains) and left ventral stream and on gender-dimorphic architecture of the right dorsal stream. PMID:24391569

Dissociated repetition deficits in aphasia can reflect flexible interactions between left dorsal and ventral streams and gender-dimorphic architecture of the right dorsal stream.

PubMed

Berthier, Marcelo L; Froudist Walsh, Seán; Dávila, Guadalupe; Nabrozidis, Alejandro; Juárez Y Ruiz de Mier, Rocío; Gutiérrez, Antonio; De-Torres, Irene; Ruiz-Cruces, Rafael; Alfaro, Francisco; García-Casares, Natalia

2013-01-01

Assessment of brain-damaged subjects presenting with dissociated repetition deficits after selective injury to either the left dorsal or ventral auditory pathways can provide further insight on their respective roles in verbal repetition. We evaluated repetition performance and its neural correlates using multimodal imaging (anatomical MRI, DTI, fMRI, and(18)FDG-PET) in a female patient with transcortical motor aphasia (TCMA) and in a male patient with conduction aphasia (CA) who had small contiguous but non-overlapping left perisylvian infarctions. Repetition in the TCMA patient was fully preserved except for a mild impairment in nonwords and digits, whereas the CA patient had impaired repetition of nonwords, digits and word triplet lists. Sentence repetition was impaired, but he repeated novel sentences significantly better than clichés. The TCMA patient had tissue damage and reduced metabolism in the left sensorimotor cortex and insula. DTI showed damage to the left temporo-frontal and parieto-frontal segments of the arcuate fasciculus (AF) and part of the left ventral stream together with well-developed right dorsal and ventral streams, as has been reported in more than one-third of females. The CA patient had tissue damage and reduced metabolic activity in the left temporoparietal cortex with additional metabolic decrements in the left frontal lobe. DTI showed damage to the left temporo-parietal and temporo-frontal segments of the AF, but the ventral stream was spared. The direct segment of the AF in the right hemisphere was also absent with only vestigial remains of the other dorsal subcomponents present, as is often found in males. fMRI during word and nonword repetition revealed bilateral perisylvian activation in the TCMA patient suggesting recruitment of spared segments of the left dorsal stream and right dorsal stream with propagation of signals to temporal lobe structures suggesting a compensatory reallocation of resources via the ventral streams. The CA patient showed a greater activation of these cortical areas than the TCMA patient, but these changes did not result in normal performance. Repetition of word triplet lists activated bilateral perisylvian cortices in both patients, but activation in the CA patient with very poor performance was restricted to small frontal and posterior temporal foci bilaterally. These findings suggest that dissociated repetition deficits in our cases are probably reliant on flexible interactions between left dorsal stream (spared segments, short tracts remains) and left ventral stream and on gender-dimorphic architecture of the right dorsal stream.

Molecular Dynamics Simulations of Orai Reveal How the Third Transmembrane Segment Contributes to Hydration and Ca2+ Selectivity in Calcium Release-Activated Calcium Channels.

PubMed

Alavizargar, Azadeh; Berti, Claudio; Ejtehadi, Mohammad Reza; Furini, Simone

2018-04-26

Calcium release-activated calcium (CRAC) channels open upon depletion of Ca 2+ from the endoplasmic reticulum, and when open, they are permeable to a selective flux of calcium ions. The atomic structure of Orai, the pore domain of CRAC channels, from Drosophila melanogaster has revealed many details about conduction and selectivity in this family of ion channels. However, it is still unclear how residues on the third transmembrane helix can affect the conduction properties of the channel. Here, molecular dynamics and Brownian dynamics simulations were employed to analyze how a conserved glutamate residue on the third transmembrane helix (E262) contributes to selectivity. The comparison between the wild-type and mutated channels revealed a severe impact of the mutation on the hydration pattern of the pore domain and on the dynamics of residues K270, and Brownian dynamics simulations proved that the altered configuration of residues K270 in the mutated channel impairs selectivity to Ca 2+ over Na + . The crevices of water molecules, revealed by molecular dynamics simulations, are perfectly located to contribute to the dynamics of the hydrophobic gate and the basic gate, suggesting a possible role in channel opening and in selectivity function.

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

PubMed Central

Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

2014-01-01

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images. PMID:24989402

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning.

PubMed

Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

2014-07-01

Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images.

Variable power distribution for zoned regeneration of an electrically heated particulate filter

DOEpatents

Bhatia, Garima [Bangalore, IN; Gonze, Eugene V [Pinckney, MI

2012-04-03

A system includes a particulate matter (PM) filter with multiple zones, an electric heater and a control module. The electrical heater includes heater segments, which each correspond with a respective one of the zones. The electrical heater is arranged upstream from and is proximate with the PM filter. The control module selectively applies a first energy level to a first one of the zones via a first one of the heater segments to initiate regeneration in the first zone. The control module also selectively applies a second energy level that is less than the first energy level to a second one of the zones via a second one of the heater segments to initiate regeneration in the second zone.

Exploration of the pore structure of a peptide-gated Na+channel

PubMed Central

Poët, Mallorie; Tauc, Michel; Lingueglia, Eric; Cance, Peggy; Poujeol, Philippe; Lazdunski, Michel; Counillon, Laurent

2001-01-01

The FMRF-amide-activated sodium channel (FaNaC), a member of the ENaC/Degenerin family, is a homotetramer, each subunit containing two transmembrane segments. We changed independently every residue of the first transmembrane segment (TM1) into a cysteine and tested each position’s accessibility to the cysteine covalent reagents MTSET and MTSES. Eleven mutants were accessible to the cationic MTSET, showing that TM1 faces the ion translocation pathway. This was confirmed by the accessibility of cysteines present in the acid-sensing ion channels and other mutations introduced in FaNaC TM1. Modification of accessibilities for positions 69, 71 and 72 in the open state shows that the gating mechanism consists of the opening of a constriction close to the intracellular side. The anionic MTSES did not penetrate into the channel, indicating the presence of a charge selectivity filter in the outer vestibule. Furthermore, amiloride inhibition resulted in the channel occlusion in the middle of the pore. Summarizing, the ionic pore of FaNaC includes a large aqueous cavity, with a charge selectivity filter in the outer vestibule and the gate close to the interior. PMID:11598003

(Electro)Mechanical Properties of Olefinic Block Copolymers

NASA Astrophysics Data System (ADS)

Spontak, Richard

2014-03-01

Conventional styrenic triblock copolymers (SBCs) swollen with a midblock-selective oil have been previously shown to exhibit excellent electromechanical properties as dielectric elastomers. In this class of electroactive polymers, compliant electrodes applied as active areas to opposing surfaces of an elastomer attract each other, and thus compress the elastomer due to the onset of a Maxwell stress, upon application of an external electric field. This isochoric process is accompanied by an increase in lateral area, which yields the electroactuation strain (measuring beyond 300% in SBC systems). Performance parameters such as the Maxwell stress, transverse strain, dielectric breakdown, energy density and electromechanical efficiency are determined directly from the applied electric field and resulting electroactuation strain. In this study, the same principle used to evaluate SBC systems is extended to olefinic block copolymers (OBCs), which can be described as randomly-coupled multiblock copolymers that consist of crystallizable polyethylene hard segments and rubbery poly(ethylene-co-octene) soft segments. Considerations governing the development of a methodology to fabricate electroresponsive OBC systems are first discussed for several OBCs differing in composition and bulk properties. Evidence of electroactuation in selectively-solvated OBC systems is presented and performance metrics measured therefrom are quantitatively compared with dielectric elastomers derived from SBC and related materials.

Multi-scale Gaussian representation and outline-learning based cell image segmentation.

PubMed

Farhan, Muhammad; Ruusuvuori, Pekka; Emmenlauer, Mario; Rämö, Pauli; Dehio, Christoph; Yli-Harja, Olli

2013-01-01

High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks.

Multi-scale Gaussian representation and outline-learning based cell image segmentation

PubMed Central

2013-01-01

Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

A new fractional order derivative based active contour model for colon wall segmentation

NASA Astrophysics Data System (ADS)

Chen, Bo; Li, Lihong C.; Wang, Huafeng; Wei, Xinzhou; Huang, Shan; Chen, Wensheng; Liang, Zhengrong

2018-02-01

Segmentation of colon wall plays an important role in advancing computed tomographic colonography (CTC) toward a screening modality. Due to the low contrast of CT attenuation around colon wall, accurate segmentation of the boundary of both inner and outer wall is very challenging. In this paper, based on the geodesic active contour model, we develop a new model for colon wall segmentation. First, tagged materials in CTC images were automatically removed via a partial volume (PV) based electronic colon cleansing (ECC) strategy. We then present a new fractional order derivative based active contour model to segment the volumetric colon wall from the cleansed CTC images. In this model, the regionbased Chan-Vese model is incorporated as an energy term to the whole model so that not only edge/gradient information but also region/volume information is taken into account in the segmentation process. Furthermore, a fractional order differentiation derivative energy term is also developed in the new model to preserve the low frequency information and improve the noise immunity of the new segmentation model. The proposed colon wall segmentation approach was validated on 16 patient CTC scans. Experimental results indicate that the present scheme is very promising towards automatically segmenting colon wall, thus facilitating computer aided detection of initial colonic polyp candidates via CTC.

Selective removal of caffeine from tea extracts using macroporous crosslinked polyvinyl alcohol adsorbents.

PubMed

Ma, Ning; Wang, Peng; Kong, Xia; Shi, Rongfu; Yuan, Zhi; Wang, Chunhong

2012-01-01

The hydrolysis reaction of ester groups in vinyl acetate (VAc) was used to introduce hydroxyl groups into the matrix of a macroporous adsorbent, which was itself prepared by free radical suspension copolymerization of triallyl isocyanurate (TAIC) and VAc. Therefore, the copolymerization incompatibility between the hydrophilic and the hydrophobic monomer was overcome successfully and the hydrophobic matrix of the polymeric adsorbent containing a polyvinyl alcohol (PVA) segment was obtained. Introduction of the PVA segment decreased the hydrophobic adsorption affinity of the adsorbent while producing the hydrogen-bonding interaction. When isolating the two active components, polyphenols (TPh) and caffeine (CAF), from green tea extracts, this polymeric adsorbent, namely poly(TAIC-co-VA), exhibited good adsorption selectivity towards TPh over CAF. The adsorption mechanism leading to this selectivity involved a hydrophobic interaction mechanism for CAF and multiple weak hydrophobic and hydrogen-bonding interactions for TPh. The adsorption thermodynamics for TPh on poly(TAIC-co-VA) were studied. The effects of adsorbent structure and gradient desorption conditions on isolation were investigated. The result showed that adsorbent, with 20% TAIC content, was able to efficiently remove CAF from different tea extracts with different ratios of TPh and CAF. Finally, almost no CAF was detected in the TPh fraction and the recovery of TPh was greater than 95%. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Axonal transports of tripeptidyl peptidase II in rat sciatic nerves.

PubMed

Chikuma, Toshiyuki; Shimizu, Maki; Tsuchiya, Yukihiro; Kato, Takeshi; Hojo, Hiroshi

2007-01-01

Axonal transport of tripeptidyl peptidase II, a putative cholecystokinin inactivating serine peptidase, was examined in the proximal, middle, and distal segments of rat sciatic nerves using a double ligation technique. Enzyme activity significantly increased not only in the proximal segment but also in the distal segment 12-72h after ligation, and the maximal enzyme activity was found in the proximal and distal segments at 72h. Western blot analysis of tripeptidyl peptidase II showed that its immunoreactivities in the proximal and distal segments were 3.1- and 1.7-fold higher than that in the middle segment. The immunohistochemical analysis of the segments also showed an increase in immunoreactive tripeptidyl peptidase II level in the proximal and distal segments in comparison with that in the middle segment, indicating that tripeptidyl peptidase II is transported by anterograde and retrograde axonal flow. The results suggest that tripeptidyl peptidase II may be involved in the metabolism of neuropeptides in nerve terminals or synaptic clefts.

Functional magnetic resonance imaging of the human spinal cord during vibration stimulation of different dermatomes.

PubMed

Lawrence, Jane M; Stroman, Patrick W; Kollias, Spyros S

2008-03-01

We investigated noninvasively areas of the healthy human spinal cord that become active in response to vibration stimulation of different dermatomes using functional magnetic resonance imaging (fMRI). The objectives of this study were to: (1) examine the patterns of consistent activity in the spinal cord during vibration stimulation of the skin, and (2) investigate the rostrocaudal distribution of active pixels when stimulation was applied to different dermatomes. FMRI of the cervical and lumbar spinal cord of seven healthy human subjects was carried out during vibration stimulation of six different dermatomes. In separate experiments, vibratory stimulation (about 50 Hz) was applied to the right biceps, wrist, palm, patella, Achilles tendon and left palm. The segmental distribution of activity observed by fMRI corresponded well with known spinal cord neuroanatomy. The peak number of active pixels was observed at the expected level of the spinal cord with some activity in the adjacent segments. The rostrocaudal distribution of activity was observed to correspond to the dermatome being stimulated. Cross-sectional localization of activity was primarily in dorsal areas but also spread into ventral and intermediate areas of the gray matter and a distinct laterality ipsilateral to the stimulated limb was not observed. We demonstrated that fMRI can detect a dermatome-dependent pattern of spinal cord activity during vibratory stimulation and can be used as a passive stimulus for the noninvasive assessment of the functional integrity of the human spinal cord. Demonstration of cross-sectional selectivity of the activation awaits further methodological and experimental refinements.

A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

PubMed Central

Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

2013-01-01

In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

Age and sex differences in ranges of motion and motion patterns.

PubMed

Hwang, Jaejin; Jung, Myung-Chul

2015-01-01

This study investigated the effects of age and sex on joint ranges of motion (ROMs) and motion patterns. Forty participants performed 18 motions using eight body segments at self-selected speeds. Older subjects showed smaller ROMs than younger subjects for 11 motions; the greatest difference in ROM was 44.9% for eversion/inversion of the foot. Older subjects also required more time than younger subjects to approach the peak angular velocity for six motions. In contrast, sex significantly affected ROMs but not motion patterns. Male subjects exhibited smaller ROMs than female subjects for four motions; the greatest sex-dependent difference in ROM was 29.7% for ulnar/radial deviation of the hand. The age and sex effects depended on the specific segments used and motions performed, possibly because of differences in anatomical structures and frequencies of use of the joints in habitual physical activities between the groups.

Intrauterine device for laser light diffusion and method of using the same

DOEpatents

Tadir, Yona; Berns, Michael W.; Svaasand, Lars O.; Tromberg, Bruce J.

1995-01-01

An improved device for delivery of photoenergy from a light source, such as a laser, into a uterine cavity for photodynamic therapy is comprised of a plurality of optic fibers, which are bundled together and inserted into the uterine cavity by means of a uterine cannula. The cannula is positioned within the uterine cavity at a preferred location and then withdrawn thereby allowing the plurality of optic fibers to splay or diverge one from the other within the cavity. Different portions of the distal tip of the optic fiber is provided with a light diffusing tip, the remainder being provided with a nondiffusing tip portion. The fiber optic shape, as well as the segment which is permitted to actively diffuse light through the tip, is selected in order to provide a more uniform exposure intensity of the photo energy or at least sufficient radiation directed to each segment of the uterine walls.

Intrauterine device for laser light diffusion and method of using the same

DOEpatents

Tadir, Y.; Berns, M.W.; Svaasand, L.O.; Tromberg, B.J.

1995-12-26

An improved device for delivery of photoenergy from a light source, such as a laser, into a uterine cavity for photodynamic therapy is comprised of a plurality of optic fibers, which are bundled together and inserted into the uterine cavity by means of a uterine cannula. The cannula is positioned within the uterine cavity at a preferred location and then withdrawn thereby allowing the plurality of optic fibers to splay or diverge one from the other within the cavity. Different portions of the distal tip of the optic fiber is provided with a light diffusing tip, the remainder being provided with a nondiffusing tip portion. The fiber optic shape, as well as the segment which is permitted to actively diffuse light through the tip, is selected in order to provide a more uniform exposure intensity of the photo energy or at least sufficient radiation directed to each segment of the uterine walls. 5 figs.

IC layout adjustment method and tool for improving dielectric reliability at interconnects

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

Kahng, Andrew B.; Chan, Tuck Boon

Method for adjusting a layout used in making an integrated circuit includes one or more interconnects in the layout that are susceptible to dielectric breakdown are selected. One or more selected interconnects are adjusted to increase via to wire spacing with respect to at least one via and one wire of the one or more selected interconnects. Preferably, the selecting analyzes signal patterns of interconnects, and estimates the stress ratio based on state probability of routed signal nets in the layout. An annotated layout is provided that describes distances by which one or more via or wire segment edges aremore » to be shifted. Adjustments can include thinning and shifting of wire segments, and rotation of vias.« less

Direct Penguin Counting Using Unmanned Aerial Vehicle Image

NASA Astrophysics Data System (ADS)

Hyun, C. U.; Kim, H. C.; Kim, J. H.; Hong, S. G.

2015-12-01

This study presents an application of unmanned aerial vehicle (UAV) images to monitor penguin colony in Baton Peninsula, King George Island, Antarctica. The area around Narębski Point located on the southeast coast of Barton Peninsula was designated as Antarctic Specially Protected Area No. 171 (ASPA 171), and Chinstrap and Gentoo penguins inhabit in this area. The UAV images were acquired in a part of ASPA 171 from four flights in a single day, Jan 18, 2014. About 360 images were mosaicked as an image of about 3 cm spatial resolution and then a subset including representative penguin rookeries was selected. The subset image was segmented based on gradient map of pixel values, and spectral and spatial attributes were assigned to each segment. The object based image analysis (OBIA) was conducted with consideration of spectral attributes including mean and minimum values of each segment and various shape attributes such as area, length, compactness and roundness to detect individual penguin. The segments indicating individual penguin were effectively detected on rookeries with high contrasts in the spectral and shape attributes. The importance of periodic and precise monitoring of penguins has been recognized because variations of their populations reflect environmental changes and disturbance from human activities. Utilization of very high resolution imaging method shown in this study can be applied to other penguin habitats in Antarctica, and the results will be able to support establishing effective environmental management plans.

Automatic segmentation of fluorescence lifetime microscopy images of cells using multiresolution community detection--a first study.

PubMed

Hu, D; Sarder, P; Ronhovde, P; Orthaus, S; Achilefu, S; Nussinov, Z

2014-01-01

Inspired by a multiresolution community detection based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Furthermore, using the proposed method, the mean-square error in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The multiresolution community detection method appeared to perform better than a popular spectral clustering-based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in mean-square error with increasing resolution. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Automatic Segmentation of Fluorescence Lifetime Microscopy Images of Cells Using Multi-Resolution Community Detection -A First Study

PubMed Central

Hu, Dandan; Sarder, Pinaki; Ronhovde, Peter; Orthaus, Sandra; Achilefu, Samuel; Nussinov, Zohar

2014-01-01

Inspired by a multi-resolution community detection (MCD) based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Further, using the proposed method, the mean-square error (MSE) in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The MCD method appeared to perform better than a popular spectral clustering based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in MSE with increasing resolution. PMID:24251410

Comparing demographic, health status and psychosocial strategies of audience segmentation to promote physical activity.

PubMed

Boslaugh, Sarah E; Kreuter, Matthew W; Nicholson, Robert A; Naleid, Kimberly

2005-08-01

The goal of audience segmentation is to identify population subgroups that are homogeneous with respect to certain variables associated with a given outcome or behavior. When such groups are identified and understood, targeted intervention strategies can be developed to address their unique characteristics and needs. This study compares the results of audience segmentation for physical activity that is based on either demographic, health status or psychosocial variables alone, or a combination of all three types of variables. Participants were 1090 African-American and White adults from two public health centers in St Louis, MO. Using a classification-tree algorithm to form homogeneous groups, analyses showed that more segments with greater variability in physical activity were created using psychosocial versus health status or demographic variables and that a combination of the three outperformed any individual set of variables. Simple segmentation strategies such as those relying on demographic variables alone provided little improvement over no segmentation at all. Audience segmentation appears to yield more homogeneous subgroups when psychosocial and health status factors are combined with demographic variables.

Wireless zoned particulate matter filter regeneration control system

DOEpatents

Gonze, Eugene V [Pinckney, MI; Kirby, Kevin W [Calabasas Hills, CA; Phelps, Amanda [Malibu, CA; Gregoire, Daniel J [Thousand Oaks, CA

2011-10-04

An assembly includes a particulate matter (PM) filter that comprises an upstream end for receiving exhaust gas, a downstream end and multiple zones. An absorbing layer absorbs microwave energy in one of N frequency ranges and is arranged with the upstream end. N is an integer. A frequency selective filter has M frequency selective segments and receives microwave energy in the N frequency ranges. M is an integer. One of the M frequency selective segments permits passage of the microwave energy in one of the N frequency ranges and does not permit passage of microwave energy in the other of the N frequency ranges.

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.

Evaluation of a segment-based LANDSAT full-frame approach to corp area estimation

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Hixson, M. M.; Davis, S. M.

1981-01-01

As the registration of LANDSAT full frames enters the realm of current technology, sampling methods should be examined which utilize other than the segment data used for LACIE. The effect of separating the functions of sampling for training and sampling for area estimation. The frame selected for analysis was acquired over north central Iowa on August 9, 1978. A stratification of he full-frame was defined. Training data came from segments within the frame. Two classification and estimation procedures were compared: statistics developed on one segment were used to classify that segment, and pooled statistics from the segments were used to classify a systematic sample of pixels. Comparisons to USDA/ESCS estimates illustrate that the full-frame sampling approach can provide accurate and precise area estimates.

Monitoring fish distributions along electrofishing segments

USGS Publications Warehouse

Miranda, Leandro E.

2014-01-01

Electrofishing is widely used to monitor fish species composition and relative abundance in streams and lakes. According to standard protocols, multiple segments are selected in a body of water to monitor population relative abundance as the ratio of total catch to total sampling effort. The standard protocol provides an assessment of fish distribution at a macrohabitat scale among segments, but not within segments. An ancillary protocol was developed for assessing fish distribution at a finer scale within electrofishing segments. The ancillary protocol was used to estimate spacing, dispersion, and association of two species along shore segments in two local reservoirs. The added information provided by the ancillary protocol may be useful for assessing fish distribution relative to fish of the same species, to fish of different species, and to environmental or habitat characteristics.

Influence of spaceflight on succinate dehydrogenase activity and soma size of rat ventral horn neurons

NASA Technical Reports Server (NTRS)

Ishihara, A.; Ohira, Y.; Roy, R. R.; Nagaoka, S.; Sekiguchi, C.; Hinds, W. E.; Edgerton, V. R.

1996-01-01

Succinate dehydrogenase (SDH) activities and soma cross-sectional areas (CSA) of neurons in the dorsolateral region of the ventral horn at the L5 segmental level of the spinal cord in the rat were determined after 14 days of spaceflight and after 9 days of recovery on earth. The results were compared to those in age-matched ground-based control rats. Spinal cords were quick-frozen, and the SDH activity and CSA of a sample of neurons with a visible nucleus were determined using a digitizer and a computer-assisted image analysis system. An inverse relationship between CSA and SDH activity of neurons was observed in all groups of rats. No change in mean CSA or mean SDH activity or in the size distribution of neurons was observed following spaceflight or recovery. However, there was a selective decrease in the SDH activity of neurons with soma CSA between 500 and 800 microns2 in the flight rats, and this effect persisted for at least 9 days following return to 1 g. It remains to be determined whether the selected population of motoneurons or the specific motor pools affected by spaceflight may be restricted to specific muscles.

Efficient Third-Order Distributed Feedback Laser with Enhanced Beam Pattern

NASA Technical Reports Server (NTRS)

Hu, Qing (Inventor); Lee, Alan Wei Min (Inventor); Kao, Tsung-Yu (Inventor)

2015-01-01

A third-order distributed feedback laser has an active medium disposed on a substrate as a linear array of segments having a series of periodically spaced interstices therebetween and a first conductive layer disposed on a surface of the active medium on each of the segments and along a strip from each of the segments to a conductive electrical contact pad for application of current along a path including the active medium. Upon application of a current through the active medium, the active medium functions as an optical waveguide, and there is established an alternating electric field, at a THz frequency, both in the active medium and emerging from the interstices. Spacing of adjacent segments is approximately half of a wavelength of the THz frequency in free space or an odd integral multiple thereof, so that the linear array has a coherence length greater than the length of the linear array.

Text Detection and Translation from Natural Scenes

DTIC Science & Technology

2001-06-01

is no explicit tags around Chinese words. A module for Chinese word segmentation is included in the system. This segmentor uses a word- frequency ... list to make segmentation decisions. We tested the EBMT based method using randomly selected 50 signs from our database, assuming perfect sign

Vehicle occupants' exposure to aromatic volatile organic compounds while commuting on an urban-suburban route in Korea.

PubMed

Jo, W K; Choi, S J

1996-08-01

This study identified in-auto and in-bus exposures to six selected aromatic volatile organic compounds (VOCs) for commutes on an urban-suburban route in Korea. A bus-service route was selected to include three segments of Taegu and one suburban segment (Hayang) to satisfy the criteria specified for this study. This study indicates that motor vehicle exhaust and evaporative emissions are major sources of both auto and bus occupants' exposures to aromatic VOCs in both Taegu and Hayang. A nonparametric statistical test (Wilcoxon test) showed that in-auto benzene levels were significantly different from in-bus benzene levels for both urban-segment and suburban-segment commutes. The test also showed that the benzene-level difference between urban-segment and suburban-segment commutes was significant for both autos and buses. An F-test showed the same statistical results for the comparison of the summed in-vehicle concentration of the six target VOCs (benzene, toluene, ethylbenzene, and o,m,p-xylenes) as those for the comparison of the in-vehicle benzene concentration. On the other hand, the in-vehicle benzene level only and the sum were not significantly different among the three urban-segment commutes and between the morning and evening commutes. The in-auto VOC concentrations were intermediate between the results for the Los Angeles and Boston. The in-bus VOC concentrations were about one-tenth of the Taipei, Taiwan results.

Missing observations in multiyear rotation sampling designs

NASA Technical Reports Server (NTRS)

Gbur, E. E.; Sielken, R. L., Jr. (Principal Investigator)

1982-01-01

Because Multiyear estimation of at-harvest stratum crop proportions is more efficient than single year estimation, the behavior of multiyear estimators in the presence of missing acquisitions was studied. Only the (worst) case when a segment proportion cannot be estimated for the entire year is considered. The effect of these missing segments on the variance of the at-harvest stratum crop proportion estimator is considered when missing segments are not replaced, and when missing segments are replaced by segments not sampled in previous years. The principle recommendations are to replace missing segments according to some specified strategy, and to use a sequential procedure for selecting a sampling design; i.e., choose an optimal two year design and then, based on the observed two year design after segment losses have been taken into account, choose the best possible three year design having the observed two year parent design.

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.

Fusion set selection with surrogate metric in multi-atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-02-01

Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation.

Angular Spacing Control for Segmented Data Pages in Angle-Multiplexed Holographic Memory

NASA Astrophysics Data System (ADS)

Kinoshita, Nobuhiro; Muroi, Tetsuhiko; Ishii, Norihiko; Kamijo, Koji; Kikuchi, Hiroshi; Shimidzu, Naoki; Ando, Toshio; Masaki, Kazuyoshi; Shimizu, Takehiro

2011-09-01

To improve the recording density of angle-multiplexed holographic memory, it is effective to increase the numerical aperture of the lens and to shorten the wavelength of the laser source as well as to increase the multiplexing number. The angular selectivity of a hologram, which determines the multiplexing number, is dependent on the incident angle of not only the reference beam but also the signal beam to the holographic recording medium. The actual signal beam, which is a convergent or divergent beam, is regarded as the sum of plane waves that have different propagation directions, angular selectivities, and optimal angular spacings. In this paper, focusing on the differences in the optimal angular spacing, we proposed a method to control the angular spacing for each segmented data page. We investigated the angular selectivity of a hologram and crosstalk for segmented data pages using numerical simulation. The experimental results showed a practical bit-error rate on the order of 10-3.

Targeting as the basis for pre-test market of lithium-ion battery

NASA Astrophysics Data System (ADS)

Yuniaristanto, Zakaria, R.; Saputri, V. H. L.; Sutopo, W.; Kadir, E. A.

2017-11-01

This article discusses about market segmentation and targeting as a first step in pre-test market of a new technology. The benefits of targeting towards pre-test market are pre-test market can be conducted to focus on selected target markets so there is no bias during the pre-test market. In determining the target market then do some surveys to identify the state of market in the future, so that the marketing process is not misplaced. Lithium ion battery which is commercialized through start-up companies is the case study. This start-up companies must be able to respond the changes and bring in customers as well as maintain them so that companies can survive and evolve to achieve its objectives. The research aims to determine market segments and target market effectively. Marketing strategy (segmentation and targeting) is used to make questionnaire and cluster analysis in data processing. Respondents were selected by purposive sampling and have obtained data as many as 80 samples. As the results study, there are three segments for lithium ion battery with their own distinguished characteristics and there are two segments that can be used as the target market for the company.

Facilitative glucose transporter Glut1 is actively excluded from rod outer segments.

PubMed

Gospe, Sidney M; Baker, Sheila A; Arshavsky, Vadim Y

2010-11-01

Photoreceptors are among the most metabolically active cells in the body, relying on both oxidative phosphorylation and glycolysis to satisfy their high energy needs. Local glycolysis is thought to be particularly crucial in supporting the function of the photoreceptor's light-sensitive outer segment compartment, which is devoid of mitochondria. Accordingly, it has been commonly accepted that the facilitative glucose transporter Glut1 responsible for glucose entry into photoreceptors is localized in part to the outer segment plasma membrane. However, we now demonstrate that Glut1 is entirely absent from the rod outer segment and is actively excluded from this compartment by targeting information present in its cytosolic C-terminal tail. Our data indicate that glucose metabolized in the outer segment must first enter through other parts of the photoreceptor cell. Consequently, the entire energy supply of the outer segment is dependent on diffusion of energy-rich substrates through the thin connecting cilium that links this compartment to the rest of the cell.

Soybean (Glycine max) expansin gene superfamily origins: segmental and tandem duplication events followed by divergent selection among subfamilies

PubMed Central

2014-01-01

Background Expansins are plant cell wall loosening proteins that are involved in cell enlargement and a variety of other developmental processes. The expansin superfamily contains four subfamilies; namely, α-expansin (EXPA), β-expansin (EXPB), expansin-like A (EXLA), and expansin-like B (EXLB). Although the genome sequencing of soybeans is complete, our knowledge about the pattern of expansion and evolutionary history of soybean expansin genes remains limited. Results A total of 75 expansin genes were identified in the soybean genome, and grouped into four subfamilies based on their phylogenetic relationships. Structural analysis revealed that the expansin genes are conserved in each subfamily, but are divergent among subfamilies. Furthermore, in soybean and Arabidopsis, the expansin gene family has been mainly expanded through tandem and segmental duplications; however, in rice, segmental duplication appears to be the dominant process that generates this superfamily. The transcriptome atlas revealed notable differential expression in either transcript abundance or expression patterns under normal growth conditions. This finding was consistent with the differential distribution of the cis-elements in the promoter region, and indicated wide functional divergence in this superfamily. Moreover, some critical amino acids that contribute to functional divergence and positive selection were detected. Finally, site model and branch-site model analysis of positive selection indicated that the soybean expansin gene superfamily is under strong positive selection, and that divergent selection constraints might have influenced the evolution of the four subfamilies. Conclusion This study demonstrated that the soybean expansin gene superfamily has expanded through tandem and segmental duplication. Differential expression indicated wide functional divergence in this superfamily. Furthermore, positive selection analysis revealed that divergent selection constraints might have influenced the evolution of the four subfamilies. In conclusion, the results of this study contribute novel detailed information about the molecular evolution of the expansin gene superfamily in soybean. PMID:24720629

Promon's participation in the Brasilsat program: first & second generations

NASA Astrophysics Data System (ADS)

Depaiva, Ricardo N.

This paper presents an overview of the Brasilsat program, space and ground segments, developed by Hughes and Promon. Promon is a Brazilian engineering company that has been actively participating in the Brasilsat Satellite Telecommunications Program since its beginning. During the first generation, as subcontractor of the Spar/Hughes/SED consortium, Promon had a significant participation in the site installation of the Ground Segment, including the antennas. During the second generation, as partner of a consortium with Hughes, Promon participated in the upgrade of Brasilsat's Ground Segment systems: the TT&C (TCR1, TCR2, and SCC) and the COCC (Communications and Operations Control Center). This upgrade consisted of the design and development of hardware and software to support the second generation requirements, followed by integration and tests, factory acceptance tests, transport to site, site installation, site acceptance tests and warranty support. The upgraded systems are distributed over four sites with remote access to the main ground station. The solutions adopted provide a high level of automation, and easy operator interaction. The hardware and software technologies were selected to provide the flexibility to incorporate new technologies and services from the demanding satellite telecommunications market.

Estrogen receptor ESR1 mediates activation of ERK1/2, CREB, and ELK1 in the corpus of the epididymis.

PubMed

Cavalcanti, Fernanda N; Lucas, Thais F G; Lazari, Maria Fatima M; Porto, Catarina S

2015-06-01

Expression of the estrogen receptor ESR1 is higher in the corpus than it is in the initial segment/caput and cauda of the epididymis. ESR1 immunostaining in the corpus has been localized not only in the nuclei but also in the cytoplasm and apical membrane, which indicates that ESR1 plays a role in membrane-initiated signaling. The present study investigated whether ESR1 mediates the activation of rapid signaling pathways by estradiol (E2) in the epididymis. We investigated the effect of E2 and the ESR1-selective agonist (4,4',4''-(4-propyl-(1H)-pyrazole-1,3,5-triyl)trisphenol (PPT) on the activation of extracellular signal-regulated protein kinases (ERK1/2), CREB protein, and ETS oncogene-related protein (ELK1). Treatment with PPT did not affect ERK1/2 phosphorylation in the cauda, but it rapidly increased ERK1/2 phosphorylation in the initial segment/caput and corpus of the epididymis. PPT also activated CREB and ELK1 in the corpus of the epididymis. The PPT-induced phosphorylation of ERK1/2, CREB, and ELK1 was blocked by the ESR1-selective antagonist MPP and by pretreatment with a non-receptor tyrosine kinase SRC inhibitor, an EGFR kinase inhibitor, an MEK1/2 inhibitor, and a phosphatidylinositol-3-kinase inhibitor. In conclusion, these results indicate that the corpus, which is a region with high expression of the estrogen receptor ESR1, is a major target in the epididymis for the activation of rapid signaling by E2. The sequence of events that follow E2 interaction with ESR1 includes the SRC-mediated transactivation of EGFR and the phosphorylation of ERK1/2, CREB, and ELK1. This rapid estrogen signaling may modulate gene expression in the corpus of the epididymis, and it may play a role in the dynamic microenvironment of the epididymal lumen. © 2015 Society for Endocrinology.

Denoising and segmentation of retinal layers in optical coherence tomography images

NASA Astrophysics Data System (ADS)

Dash, Puspita; Sigappi, A. N.

2018-04-01

Optical Coherence Tomography (OCT) is an imaging technique used to localize the intra-retinal boundaries for the diagnostics of macular diseases. Due to speckle noise, low image contrast and accurate segmentation of individual retinal layers is difficult. Due to this, a method for retinal layer segmentation from OCT images is presented. This paper proposes a pre-processing filtering approach for denoising and segmentation methods for segmenting retinal layers OCT images using graph based segmentation technique. These techniques are used for segmentation of retinal layers for normal as well as patients with Diabetic Macular Edema. The algorithm based on gradient information and shortest path search is applied to optimize the edge selection. In this paper the four main layers of the retina are segmented namely Internal limiting membrane (ILM), Retinal pigment epithelium (RPE), Inner nuclear layer (INL) and Outer nuclear layer (ONL). The proposed method is applied on a database of OCT images of both ten normal and twenty DME affected patients and the results are found to be promising.

Assignment of simian rotavirus SA11 temperature-sensitive mutant groups B and E to genome segments

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

Gombold, J.L.; Estes, M.K.; Ramig, R.F.

1985-05-01

Recombinant (reassortant) viruses were selected from crosses between temperature-sensitive (ts) mutants of simian rotavirus SA11 and wild-type human rotavirus Wa. The double-stranded genome RNAs of the reassortants were examined by electrophoresis in Tris-glycine-buffered polyacrylamide gels and by dot hybridization with a cloned DNA probe for genome segment 2. Analysis of replacements of genome segments in the reassortants allowed construction of a map correlating genome segments providing functions interchangeable between SA11 and Wa. The reassortants revealed a functional correspondence in order of increasing electrophoretic mobility of genome segments. Analysis of the parental origin of genome segments in ts+ SA11/Wa reassortants derivedmore » from the crosses SA11 tsB(339) X Wa and SA11 tsE(1400) X Wa revealed that the group B lesion of tsB(339) was located on genome segment 3 and the group E lesion of tsE(1400) was on segment 8.« less

Automatic Structural Parcellation of Mouse Brain MRI Using Multi-Atlas Label Fusion

PubMed Central

Ma, Da; Cardoso, Manuel J.; Modat, Marc; Powell, Nick; Wells, Jack; Holmes, Holly; Wiseman, Frances; Tybulewicz, Victor; Fisher, Elizabeth; Lythgoe, Mark F.; Ourselin, Sébastien

2014-01-01

Multi-atlas segmentation propagation has evolved quickly in recent years, becoming a state-of-the-art methodology for automatic parcellation of structural images. However, few studies have applied these methods to preclinical research. In this study, we present a fully automatic framework for mouse brain MRI structural parcellation using multi-atlas segmentation propagation. The framework adopts the similarity and truth estimation for propagated segmentations (STEPS) algorithm, which utilises a locally normalised cross correlation similarity metric for atlas selection and an extended simultaneous truth and performance level estimation (STAPLE) framework for multi-label fusion. The segmentation accuracy of the multi-atlas framework was evaluated using publicly available mouse brain atlas databases with pre-segmented manually labelled anatomical structures as the gold standard, and optimised parameters were obtained for the STEPS algorithm in the label fusion to achieve the best segmentation accuracy. We showed that our multi-atlas framework resulted in significantly higher segmentation accuracy compared to single-atlas based segmentation, as well as to the original STAPLE framework. PMID:24475148

A NDVI assisted remote sensing image adaptive scale segmentation method

NASA Astrophysics Data System (ADS)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Automatic seed selection for segmentation of liver cirrhosis in laparoscopic sequences

NASA Astrophysics Data System (ADS)

Sinha, Rahul; Marcinczak, Jan Marek; Grigat, Rolf-Rainer

2014-03-01

For computer aided diagnosis based on laparoscopic sequences, image segmentation is one of the basic steps which define the success of all further processing. However, many image segmentation algorithms require prior knowledge which is given by interaction with the clinician. We propose an automatic seed selection algorithm for segmentation of liver cirrhosis in laparoscopic sequences which assigns each pixel a probability of being cirrhotic liver tissue or background tissue. Our approach is based on a trained classifier using SIFT and RGB features with PCA. Due to the unique illumination conditions in laparoscopic sequences of the liver, a very low dimensional feature space can be used for classification via logistic regression. The methodology is evaluated on 718 cirrhotic liver and background patches that are taken from laparoscopic sequences of 7 patients. Using a linear classifier we achieve a precision of 91% in a leave-one-patient-out cross-validation. Furthermore, we demonstrate that with logistic probability estimates, seeds with high certainty of being cirrhotic liver tissue can be obtained. For example, our precision of liver seeds increases to 98.5% if only seeds with more than 95% probability of being liver are used. Finally, these automatically selected seeds can be used as priors in Graph Cuts which is demonstrated in this paper.

Flexible methods for segmentation evaluation: Results from CT-based luggage screening

PubMed Central

Karimi, Seemeen; Jiang, Xiaoqian; Cosman, Pamela; Martz, Harry

2017-01-01

BACKGROUND Imaging systems used in aviation security include segmentation algorithms in an automatic threat recognition pipeline. The segmentation algorithms evolve in response to emerging threats and changing performance requirements. Analysis of segmentation algorithms’ behavior, including the nature of errors and feature recovery, facilitates their development. However, evaluation methods from the literature provide limited characterization of the segmentation algorithms. OBJECTIVE To develop segmentation evaluation methods that measure systematic errors such as oversegmentation and undersegmentation, outliers, and overall errors. The methods must measure feature recovery and allow us to prioritize segments. METHODS We developed two complementary evaluation methods using statistical techniques and information theory. We also created a semi-automatic method to define ground truth from 3D images. We applied our methods to evaluate five segmentation algorithms developed for CT luggage screening. We validated our methods with synthetic problems and an observer evaluation. RESULTS Both methods selected the same best segmentation algorithm. Human evaluation confirmed the findings. The measurement of systematic errors and prioritization helped in understanding the behavior of each segmentation algorithm. CONCLUSIONS Our evaluation methods allow us to measure and explain the accuracy of segmentation algorithms. PMID:24699346

Hybrid active contour model for inhomogeneous image segmentation with background estimation

NASA Astrophysics Data System (ADS)

Sun, Kaiqiong; Li, Yaqin; Zeng, Shan; Wang, Jun

2018-03-01

This paper proposes a hybrid active contour model for inhomogeneous image segmentation. The data term of the energy function in the active contour consists of a global region fitting term in a difference image and a local region fitting term in the original image. The difference image is obtained by subtracting the background from the original image. The background image is dynamically estimated from a linear filtered result of the original image on the basis of the varying curve locations during the active contour evolution process. As in existing local models, fitting the image to local region information makes the proposed model robust against an inhomogeneous background and maintains the accuracy of the segmentation result. Furthermore, fitting the difference image to the global region information makes the proposed model robust against the initial contour location, unlike existing local models. Experimental results show that the proposed model can obtain improved segmentation results compared with related methods in terms of both segmentation accuracy and initial contour sensitivity.

Multiple Active Contours Guided by Differential Evolution for Medical Image Segmentation

PubMed Central

Cruz-Aceves, I.; Avina-Cervantes, J. G.; Lopez-Hernandez, J. M.; Rostro-Gonzalez, H.; Garcia-Capulin, C. H.; Torres-Cisneros, M.; Guzman-Cabrera, R.

2013-01-01

This paper presents a new image segmentation method based on multiple active contours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical active contour model. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical active contour model and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation. PMID:23983809

Effect of segmentation algorithms on the performance of computerized detection of lung nodules in CT

PubMed Central

Guo, Wei; Li, Qiang

2014-01-01

Purpose: The purpose of this study is to reveal how the performance of lung nodule segmentation algorithm impacts the performance of lung nodule detection, and to provide guidelines for choosing an appropriate segmentation algorithm with appropriate parameters in a computer-aided detection (CAD) scheme. Methods: The database consisted of 85 CT scans with 111 nodules of 3 mm or larger in diameter from the standard CT lung nodule database created by the Lung Image Database Consortium. The initial nodule candidates were identified as those with strong response to a selective nodule enhancement filter. A uniform viewpoint reformation technique was applied to a three-dimensional nodule candidate to generate 24 two-dimensional (2D) reformatted images, which would be used to effectively distinguish between true nodules and false positives. Six different algorithms were employed to segment the initial nodule candidates in the 2D reformatted images. Finally, 2D features from the segmented areas in the 24 reformatted images were determined, selected, and classified for removal of false positives. Therefore, there were six similar CAD schemes, in which only the segmentation algorithms were different. The six segmentation algorithms included the fixed thresholding (FT), Otsu thresholding (OTSU), fuzzy C-means (FCM), Gaussian mixture model (GMM), Chan and Vese model (CV), and local binary fitting (LBF). The mean Jaccard index and the mean absolute distance (Dmean) were employed to evaluate the performance of segmentation algorithms, and the number of false positives at a fixed sensitivity was employed to evaluate the performance of the CAD schemes. Results: For the segmentation algorithms of FT, OTSU, FCM, GMM, CV, and LBF, the highest mean Jaccard index between the segmented nodule and the ground truth were 0.601, 0.586, 0.588, 0.563, 0.543, and 0.553, respectively, and the corresponding Dmean were 1.74, 1.80, 2.32, 2.80, 3.48, and 3.18 pixels, respectively. With these segmentation results of the six segmentation algorithms, the six CAD schemes reported 4.4, 8.8, 3.4, 9.2, 13.6, and 10.4 false positives per CT scan at a sensitivity of 80%. Conclusions: When multiple algorithms are available for segmenting nodule candidates in a CAD scheme, the “optimal” segmentation algorithm did not necessarily lead to the “optimal” CAD detection performance. PMID:25186393

Taurine Supplementation Improves Functional Capacity, Myocardial Oxygen Consumption, and Electrical Activity in Heart Failure.

PubMed

Ahmadian, Mehdi; Dabidi Roshan, Valiollah; Ashourpore, Eadeh

2017-07-04

Taurine is an amino acid found abundantly in the heart in very high concentrations. It is assumed that taurine contributes to several physiological functions of mammalian cells, such as osmoregulation, anti-inflammation, membrane stabilization, ion transport modulation, and regulation of oxidative stress and mitochondrial protein synthesis. The objective of the current study was to evaluate the effectiveness of taurine supplementation on functional capacity, myocardial oxygen consumption, and electrical activity in patients with heart failure. In a double-blind and randomly designed study, 16 patients with heart failure were assigned to two groups: taurine (TG, n = 8) and placebo (PG, n = 8). TG received 500-mg taurine supplementation three times per day for two weeks. Significant decrease in the values of Q-T segments (p < 0.01) and significant increase in the values of P-R segments (p < 0.01) were detected following exercise post-supplementation in TG rather than in PG. Significantly higher values of taurine concentration, T wave, Q-T segment, physical capacities, and lower values of cardiovascular capacities were detected post-supplementation in TG as compared with PG (all p values <0.01). Taurine significantly enhanced the physical function and significantly reduced the cardiovascular function parameters following exercise. Our results also suggest that the short-term taurine supplementation is an effective strategy for improving some selected hemodynamic parameters in heart failure patients. Together, these findings support the view that taurine improves cardiac function and functional capacity in patients with heart failure. This idea warrants further study.

Stimulation and inhibition of bacterial growth by caffeine dependent on chloramphenicol and a phenolic uncoupler--a ternary toxicity study using microfluid segment technique.

PubMed

Cao, Jialan; Kürsten, Dana; Schneider, Steffen; Köhler, J Michael

2012-10-01

A droplet-based microfluidic technique for the fast generation of three dimensional concentration spaces within nanoliter segments was introduced. The technique was applied for the evaluation of the effect of two selected antibiotic substances on the toxicity and activation of bacterial growth by caffeine. Therefore a three-dimensional concentration space was completely addressed by generating large sequences with about 1150 well separated microdroplets containing 216 different combinations of concentrations. To evaluate the toxicity of the ternary mixtures a time-resolved miniaturized optical double endpoint detection unit using a microflow-through fluorimeter and a two channel microflow-through photometer was used for the simultaneous analysis of changes on the endogenous cellular fluorescence signal and on the cell density of E. coli cultivated inside 500 nL microfluid segments. Both endpoints supplied similar results for the dose related cellular response. Strong non-linear combination effects, concentration dependent stimulation and the formation of activity summits on bolographic maps were determined. The results reflect a complex response of growing bacterial cultures in dependence on the combined effectors. A strong caffeine induced enhancement of bacterial growth was found at sublethal chloramphenicol and sublethal 2,4-dinitrophenol concentrations. The reliability of the method was proved by a high redundancy of fluidic experiments. The results indicate the importance of multi-parameter investigations for toxicological studies and prove the potential of the microsegmented flow technique for such requirements.

Lesioning of TRPV1 Expressing Primary Afferent Neurons Prevents PAR-2 Induced Motility, but Not Mechanical Hypersensitivity in the Rat Colon

PubMed Central

Suckow, Shelby K.; Anderson, Ethan M.; Caudle, Robert M.

2011-01-01

Background Proteinase activated receptor 2 (PAR-2) is expressed by many neurons in the colon, including primary afferent neurons that co-express transient receptor potential vanilloid 1 (TRPV1). Activation of PAR-2 receptors was previously found to enhance colonic motility, increase secretion and produce hypersensitivity to mechanical stimuli. This study examined the functional role of TRPV1/PAR-2 expressing neurons that innervate the colon by lesioning TRPV1 bearing neurons with the highly selective and potent TRPV1 agonist resiniferatoxin. Methods Colonic motility in response to PAR-2 activation was evaluated in vitro using isolated segments of descending colon and in vivo using manometry. Colonic mechanical nociceptive thresholds were measured using colorectal distension. TRPV1 expressing neurons were selectively lesioned with resiniferatoxin. Key Results In vitro the PAR-2 agonists trypsin and SLIGRL did not alter contractions of colon segments when applied alone, however, the agents enhanced acetylcholine stimulated contraction. In vivo, PAR-2 agonists administered intraluminally induced contractions of the colon and produced hypersensitivity to colorectal distention. The PAR-2 agonist enhancement of colonic contraction was eliminated when TRPV1 expressing neurons were lesioned with resiniferatoxin, but the PAR-2 agonist induced hypersensitivity remained in the lesioned animals. Conclusions and Inferences Our findings indicate that TRPV1/PAR-2 expressing primary afferent neurons mediate an extrinsic motor reflex pathway in the colon. These data, coupled with our previous studies, also indicate that the recently described colospinal afferent neurons are nociceptive, suggesting that these neurons may be useful targets for the pharmacological control of pain in diseases such as irritable bowel syndrome. PMID:22168801

Lesioning of TRPV1 expressing primary afferent neurons prevents PAR-2 induced motility, but not mechanical hypersensitivity in the rat colon.

PubMed

Suckow, S K; Anderson, E M; Caudle, R M

2012-03-01

Proteinase activated receptor 2 (PAR-2) is expressed by many neurons in the colon, including primary afferent neurons that co-express transient receptor potential vanilloid 1 (TRPV1). Activation of PAR-2 receptors was previously found to enhance colonic motility, increase secretion and produce hypersensitivity to mechanical stimuli. This study examined the functional role of TRPV1/PAR-2 expressing neurons that innervate the colon by lesioning TRPV1 bearing neurons with the highly selective and potent TRPV1 agonist resiniferatoxin. Colonic motility in response to PAR-2 activation was evaluated in vitro using isolated segments of descending colon and in vivo using manometry. Colonic mechanical nociceptive thresholds were measured using colorectal distension. Transient receptor potential vanilloid 1 expressing neurons were selectively lesioned with resiniferatoxin. In vitro, the PAR-2 agonists, trypsin and SLIGRL did not alter contractions of colon segments when applied alone, however, the agents enhanced acetylcholine stimulated contraction. In vivo, PAR-2 agonists administered intraluminally induced contractions of the colon and produced hypersensitivity to colorectal distention. The PAR-2 agonist enhancement of colonic contraction was eliminated when TRPV1 expressing neurons were lesioned with resiniferatoxin, but the PAR-2 agonist induced hypersensitivity remained in the lesioned animals. Our findings indicate that TRPV1/PAR-2 expressing primary afferent neurons mediate an extrinsic motor reflex pathway in the colon. These data, coupled with our previous studies, also indicate that the recently described colospinal afferent neurons are nociceptive, suggesting that these neurons may be useful targets for the pharmacological control of pain in diseases such as irritable bowel syndrome. © 2011 Blackwell Publishing Ltd.

A Novel Face-on-Face Contact Method for Nonlinear Solid Mechanics

NASA Astrophysics Data System (ADS)

Wopschall, Steven Robert

The implicit solution to contact problems in nonlinear solid mechanics poses many difficulties. Traditional node-to-segment methods may suffer from locking and experience contact force chatter in the presence of sliding. More recent developments include mortar based methods, which resolve local contact interactions over face-pairs and feature a kinematic constraint in integral form that smoothes contact behavior, especially in the presence of sliding. These methods have been shown to perform well in the presence of geometric nonlinearities and are demonstratively more robust than node-to-segment methods. These methods are typically biased, however, interpolating contact tractions and gap equations on a designated non-mortar face, which leads to an asymmetry in the formulation. Another challenge is constraint enforcement. The general selection of the active set of constraints is brought with difficulty, often leading to non-physical solutions and easily resulting in missed face-pair interactions. Details on reliable constraint enforcement methods are lacking in the greater contact literature. This work presents an unbiased contact formulation utilizing a median-plane methodology. Up to linear polynomials are used for the discrete pressure representation and integral gap constraints are enforced using a novel subcycling procedure. This procedure reliably determines the active set of contact constraints leading to physical and kinematically admissible solutions void of heuristics and user action. The contact method presented herein successfully solves difficult quasi-static contact problems in the implicit computational setting. These problems feature finite deformations, material nonlinearity, and complex interface geometries, all of which are challenging characteristics for contact implementations and constraint enforcement algorithms. The subcycling procedure is a key feature of this method, handling active constraint selection for complex interfaces and mesh geometries.

Tumor or abnormality identification from magnetic resonance images using statistical region fusion based segmentation.

PubMed

Subudhi, Badri Narayan; Thangaraj, Veerakumar; Sankaralingam, Esakkirajan; Ghosh, Ashish

2016-11-01

In this article, a statistical fusion based segmentation technique is proposed to identify different abnormality in magnetic resonance images (MRI). The proposed scheme follows seed selection, region growing-merging and fusion of multiple image segments. In this process initially, an image is divided into a number of blocks and for each block we compute the phase component of the Fourier transform. The phase component of each block reflects the gray level variation among the block but contains a large correlation among them. Hence a singular value decomposition (SVD) technique is adhered to generate a singular value of each block. Then a thresholding procedure is applied on these singular values to identify edgy and smooth regions and some seed points are selected for segmentation. By considering each seed point we perform a binary segmentation of the complete MRI and hence with all seed points we get an equal number of binary images. A parcel based statistical fusion process is used to fuse all the binary images into multiple segments. Effectiveness of the proposed scheme is tested on identifying different abnormalities: prostatic carcinoma detection, tuberculous granulomas identification and intracranial neoplasm or brain tumor detection. The proposed technique is established by comparing its results against seven state-of-the-art techniques with six performance evaluation measures. Copyright © 2016 Elsevier Inc. All rights reserved.

Active hexagonally segmented mirror to investigate new optical phasing technologies for segmented telescopes.

PubMed

Gonté, Frédéric; Dupuy, Christophe; Luong, Bruno; Frank, Christoph; Brast, Roland; Sedghi, Baback

2009-11-10

The primary mirror of the future European Extremely Large Telescope will be equipped with 984 hexagonal segments. The alignment of the segments in piston, tip, and tilt within a few nanometers requires an optical phasing sensor. A test bench has been designed to study four different optical phasing sensor technologies. The core element of the test bench is an active segmented mirror composed of 61 flat hexagonal segments with a size of 17 mm side to side. Each of them can be controlled in piston, tip, and tilt by three piezoactuators with a precision better than 1 nm. The context of this development, the requirements, the design, and the integration of this system are explained. The first results on the final precision obtained in closed-loop control are also presented.

Behavior-Dependent Activity and Synaptic Organization of Septo-hippocampal GABAergic Neurons Selectively Targeting the Hippocampal CA3 Area.

PubMed

Joshi, Abhilasha; Salib, Minas; Viney, Tim James; Dupret, David; Somogyi, Peter

2017-12-20

Rhythmic medial septal (MS) GABAergic input coordinates cortical theta oscillations. However, the rules of innervation of cortical cells and regions by diverse septal neurons are unknown. We report a specialized population of septal GABAergic neurons, the Teevra cells, selectively innervating the hippocampal CA3 area bypassing CA1, CA2, and the dentate gyrus. Parvalbumin-immunopositive Teevra cells show the highest rhythmicity among MS neurons and fire with short burst duration (median, 38 ms) preferentially at the trough of both CA1 theta and slow irregular oscillations, coincident with highest hippocampal excitability. Teevra cells synaptically target GABAergic axo-axonic and some CCK interneurons in restricted septo-temporal CA3 segments. The rhythmicity of their firing decreases from septal to temporal termination of individual axons. We hypothesize that Teevra neurons coordinate oscillatory activity across the septo-temporal axis, phasing the firing of specific CA3 interneurons, thereby contributing to the selection of pyramidal cell assemblies at the theta trough via disinhibition. VIDEO ABSTRACT. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Automated compromised right lung segmentation method using a robust atlas-based active volume model with sparse shape composition prior in CT.

PubMed

Zhou, Jinghao; Yan, Zhennan; Lasio, Giovanni; Huang, Junzhou; Zhang, Baoshe; Sharma, Navesh; Prado, Karl; D'Souza, Warren

2015-12-01

To resolve challenges in image segmentation in oncologic patients with severely compromised lung, we propose an automated right lung segmentation framework that uses a robust, atlas-based active volume model with a sparse shape composition prior. The robust atlas is achieved by combining the atlas with the output of sparse shape composition. Thoracic computed tomography images (n=38) from patients with lung tumors were collected. The right lung in each scan was manually segmented to build a reference training dataset against which the performance of the automated segmentation method was assessed. The quantitative results of this proposed segmentation method with sparse shape composition achieved mean Dice similarity coefficient (DSC) of (0.72, 0.81) with 95% CI, mean accuracy (ACC) of (0.97, 0.98) with 95% CI, and mean relative error (RE) of (0.46, 0.74) with 95% CI. Both qualitative and quantitative comparisons suggest that this proposed method can achieve better segmentation accuracy with less variance than other atlas-based segmentation methods in the compromised lung segmentation. Published by Elsevier Ltd.

A robust and fast active contour model for image segmentation with intensity inhomogeneity

NASA Astrophysics Data System (ADS)

Ding, Keyan; Weng, Guirong

2018-04-01

In this paper, a robust and fast active contour model is proposed for image segmentation in the presence of intensity inhomogeneity. By introducing the local image intensities fitting functions before the evolution of curve, the proposed model can effectively segment images with intensity inhomogeneity. And the computation cost is low because the fitting functions do not need to be updated in each iteration. Experiments have shown that the proposed model has a higher segmentation efficiency compared to some well-known active contour models based on local region fitting energy. In addition, the proposed model is robust to initialization, which allows the initial level set function to be a small constant function.

Temporally consistent segmentation of point clouds

NASA Astrophysics Data System (ADS)

Owens, Jason L.; Osteen, Philip R.; Daniilidis, Kostas

2014-06-01

We consider the problem of generating temporally consistent point cloud segmentations from streaming RGB-D data, where every incoming frame extends existing labels to new points or contributes new labels while maintaining the labels for pre-existing segments. Our approach generates an over-segmentation based on voxel cloud connectivity, where a modified k-means algorithm selects supervoxel seeds and associates similar neighboring voxels to form segments. Given the data stream from a potentially mobile sensor, we solve for the camera transformation between consecutive frames using a joint optimization over point correspondences and image appearance. The aligned point cloud may then be integrated into a consistent model coordinate frame. Previously labeled points are used to mask incoming points from the new frame, while new and previous boundary points extend the existing segmentation. We evaluate the algorithm on newly-generated RGB-D datasets.

Lung segment geometry study: simulation of largest possible tumours that fit into bronchopulmonary segments.

PubMed

Welter, S; Stöcker, C; Dicken, V; Kühl, H; Krass, S; Stamatis, G

2012-03-01

Segmental resection in stage I non-small cell lung cancer (NSCLC) has been well described and is considered to have similar survival rates as lobectomy but with increased rates of local tumour recurrence due to inadequate parenchymal margins. In consequence, today segmentectomy is only performed when the tumour is smaller than 2 cm. Three-dimensional reconstructions from 11 thin-slice CT scans of bronchopulmonary segments were generated, and virtual spherical tumours were placed over the segments, respecting all segmental borders. As a next step, virtual parenchymal safety margins of 2 cm and 3 cm were subtracted and the size of the remaining tumour calculated. The maximum tumour diameters with a 30-mm parenchymal safety margin ranged from 26.1 mm in right-sided segments 7 + 8 to 59.8 mm in the left apical segments 1-3. Using a three-dimensional reconstruction of lung CT scans, we demonstrated that segmentectomy or resection of segmental groups should be feasible with adequate margins, even for larger tumours in selected cases. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Recovery of choline oxidase activity by in vitro recombination of individual segments.

PubMed

Heinze, Birgit; Hoven, Nina; O'Connell, Timothy; Maurer, Karl-Heinz; Bartsch, Sebastian; Bornscheuer, Uwe T

2008-11-01

Initial attempts to express a choline oxidase from Arthrobacter pascens (APChO-syn) in Escherichia coli starting from a synthetic gene only led to inactive protein. However, activity was regained by the systematic exchange of individual segments of the gene with segments from a choline oxidase-encoding gene from Arthrobacter globiformis yielding a functional chimeric enzyme. Next, a sequence alignment of the exchanged segment with other choline oxidases revealed a mutation in the APChO-syn, showing that residue 200 was a threonine instead of an asparagine, which is, thus, crucial for confering enzyme activity and, hence, provides an explanation for the initial lack of activity. The active recombinant APChO-syn-T200N variant was biochemically characterized showing an optimum at pH 8.0 and at 37 degrees C. Furthermore, the substrate specificity was examined using N,N-dimethylethanolamine, N-methylethanolamine and 3,3-dimethyl-1-butanol.

Temporal redistribution of inhibition over neuronal subcellular domains underlies state-dependent rhythmic change of excitability in the hippocampus

PubMed Central

Somogyi, Peter; Katona, Linda; Klausberger, Thomas; Lasztóczi, Bálint; Viney, Tim J.

2014-01-01

The behaviour-contingent rhythmic synchronization of neuronal activity is reported by local field potential oscillations in the theta, gamma and sharp wave-related ripple (SWR) frequency ranges. In the hippocampus, pyramidal cell assemblies representing temporal sequences are coordinated by GABAergic interneurons selectively innervating specific postsynaptic domains, and discharging phase locked to network oscillations. We compare the cellular network dynamics in the CA1 and CA3 areas recorded with or without anaesthesia. All parts of pyramidal cells, except the axon initial segment, receive GABA from multiple interneuron types, each with distinct firing dynamics. The axon initial segment is exclusively innervated by axo-axonic cells, preferentially firing after the peak of the pyramidal layer theta cycle, when pyramidal cells are least active. Axo-axonic cells are inhibited during SWRs, when many pyramidal cells fire synchronously. This dual inverse correlation demonstrates the key inhibitory role of axo-axonic cells. Parvalbumin-expressing basket cells fire phase locked to field gamma activity in both CA1 and CA3, and also strongly increase firing during SWRs, together with dendrite-innervating bistratified cells, phasing pyramidal cell discharge. Subcellular domain-specific GABAergic innervation probably developed for the coordination of multiple glutamatergic inputs on different parts of pyramidal cells through the temporally distinct activity of GABAergic interneurons, which differentially change their firing during different network states. PMID:24366131

Automatic liver segmentation in computed tomography using general-purpose shape modeling methods.

PubMed

Spinczyk, Dominik; Krasoń, Agata

2018-05-29

Liver segmentation in computed tomography is required in many clinical applications. The segmentation methods used can be classified according to a number of criteria. One important criterion for method selection is the shape representation of the segmented organ. The aim of the work is automatic liver segmentation using general purpose shape modeling methods. As part of the research, methods based on shape information at various levels of advancement were used. The single atlas based segmentation method was used as the simplest shape-based method. This method is derived from a single atlas using the deformable free-form deformation of the control point curves. Subsequently, the classic and modified Active Shape Model (ASM) was used, using medium body shape models. As the most advanced and main method generalized statistical shape models, Gaussian Process Morphable Models was used, which are based on multi-dimensional Gaussian distributions of the shape deformation field. Mutual information and sum os square distance were used as similarity measures. The poorest results were obtained for the single atlas method. For the ASM method in 10 analyzed cases for seven test images, the Dice coefficient was above 55[Formula: see text], of which for three of them the coefficient was over 70[Formula: see text], which placed the method in second place. The best results were obtained for the method of generalized statistical distribution of the deformation field. The DICE coefficient for this method was 88.5[Formula: see text] CONCLUSIONS: This value of 88.5 [Formula: see text] Dice coefficient can be explained by the use of general-purpose shape modeling methods with a large variance of the shape of the modeled object-the liver and limitations on the size of our training data set, which was limited to 10 cases. The obtained results in presented fully automatic method are comparable with dedicated methods for liver segmentation. In addition, the deforamtion features of the model can be modeled mathematically by using various kernel functions, which allows to segment the liver on a comparable level using a smaller learning set.

An Approach for Identifying Benefit Segments among Prospective College Students.

ERIC Educational Resources Information Center

Miller, Patrick; And Others

1990-01-01

A study investigated the importance to 578 applicants of various benefits offered by a moderately selective private university. Applicants rated the institution on 43 academic, social, financial, religious, and curricular attributes. The objective was to test the efficacy of one approach to college market segmentation. Results support the utility…

Offering-level strategy formulation in health service organizations.

PubMed

Pointer, D D

1990-01-01

One of six different strategies must be selected for a health service offering to provide consumers with distinctive value and achieve sustainable competitive advantage in a market or market segment. Decisions must be made regarding objectives sought, market segmentation, market scope, and the customer-value proposition that will be pursued.

Military display market segment: avionics (Invited Paper)

NASA Astrophysics Data System (ADS)

Desjardins, Daniel D.; Hopper, Darrel G.

2005-05-01

The military display market is analyzed in terms of one of its segments: avionics. Requirements are summarized for 13 technology-driving parameters for direct-view and virtual-view displays in cockpits and cabins. Technical specifications are discussed for selected programs. Avionics stresses available technology and usually requires custom display designs.

40 CFR 761.257 - Determining the regulatory status of sampled pipe.

Code of Federal Regulations, 2010 CFR

2010-07-01

... COMMERCE, AND USE PROHIBITIONS Determining a PCB Concentration for Purposes of Abandonment or Disposal of Natural Gas Pipeline: Selecting Sample Sites, Collecting Surface Samples, and Analyzing Standard PCB Wipe... disposal of a pipe segment that has been sampled, the sample results for that segment determines its PCB...

Marketing the Community College Starts with Understanding Students' Perspectives.

ERIC Educational Resources Information Center

Absher, Keith; Crawford, Gerald

1996-01-01

Examines variables taken into account by community college students in choosing a college, arguing that increased competition for students means that colleges must employ marketing strategies. Discusses the use of the selection factors as market segmentation tools. Identifies five principal market segments based on student classifications of…

Design unbiased estimation in line intersect sampling using segmented transects

Treesearch

David L.R. Affleck; Timothy G. Gregoire; Harry T. Valentine; Harry T. Valentine

2005-01-01

In many applications of line intersect sampling. transects consist of multiple, connected segments in a prescribed configuration. The relationship between the transect configuration and the selection probability of a population element is illustrated and a consistent sampling protocol, applicable to populations composed of arbitrarily shaped elements, is proposed. It...

Efficient hyperspectral image segmentation using geometric active contour formulation

NASA Astrophysics Data System (ADS)

Albalooshi, Fatema A.; Sidike, Paheding; Asari, Vijayan K.

2014-10-01

In this paper, we present a new formulation of geometric active contours that embeds the local hyperspectral image information for an accurate object region and boundary extraction. We exploit self-organizing map (SOM) unsupervised neural network to train our model. The segmentation process is achieved by the construction of a level set cost functional, in which, the dynamic variable is the best matching unit (BMU) coming from SOM map. In addition, we use Gaussian filtering to discipline the deviation of the level set functional from a signed distance function and this actually helps to get rid of the re-initialization step that is computationally expensive. By using the properties of the collective computational ability and energy convergence capability of the active control models (ACM) energy functional, our method optimizes the geometric ACM energy functional with lower computational time and smoother level set function. The proposed algorithm starts with feature extraction from raw hyperspectral images. In this step, the principal component analysis (PCA) transformation is employed, and this actually helps in reducing dimensionality and selecting best sets of the significant spectral bands. Then the modified geometric level set functional based ACM is applied on the optimal number of spectral bands determined by the PCA. By introducing local significant spectral band information, our proposed method is capable to force the level set functional to be close to a signed distance function, and therefore considerably remove the need of the expensive re-initialization procedure. To verify the effectiveness of the proposed technique, we use real-life hyperspectral images and test our algorithm in varying textural regions. This framework can be easily adapted to different applications for object segmentation in aerial hyperspectral imagery.

Identification of Inhibitory Premotor Interneurons Activated at a Late Phase in a Motor Cycle during Drosophila Larval Locomotion

PubMed Central

Itakura, Yuki; Kohsaka, Hiroshi; Ohyama, Tomoko; Zlatic, Marta

2015-01-01

Rhythmic motor patterns underlying many types of locomotion are thought to be produced by central pattern generators (CPGs). Our knowledge of how CPG networks generate motor patterns in complex nervous systems remains incomplete, despite decades of work in a variety of model organisms. Substrate borne locomotion in Drosophila larvae is driven by waves of muscular contraction that propagate through multiple body segments. We use the motor circuitry underlying crawling in larval Drosophila as a model to try to understand how segmentally coordinated rhythmic motor patterns are generated. Whereas muscles, motoneurons and sensory neurons have been well investigated in this system, far less is known about the identities and function of interneurons. Our recent study identified a class of glutamatergic premotor interneurons, PMSIs (period-positive median segmental interneurons), that regulate the speed of locomotion. Here, we report on the identification of a distinct class of glutamatergic premotor interneurons called Glutamatergic Ventro-Lateral Interneurons (GVLIs). We used calcium imaging to search for interneurons that show rhythmic activity and identified GVLIs as interneurons showing wave-like activity during peristalsis. Paired GVLIs were present in each abdominal segment A1-A7 and locally extended an axon towards a dorsal neuropile region, where they formed GRASP-positive putative synaptic contacts with motoneurons. The interneurons expressed vesicular glutamate transporter (vGluT) and thus likely secrete glutamate, a neurotransmitter known to inhibit motoneurons. These anatomical results suggest that GVLIs are premotor interneurons that locally inhibit motoneurons in the same segment. Consistent with this, optogenetic activation of GVLIs with the red-shifted channelrhodopsin, CsChrimson ceased ongoing peristalsis in crawling larvae. Simultaneous calcium imaging of the activity of GVLIs and motoneurons showed that GVLIs’ wave-like activity lagged behind that of motoneurons by several segments. Thus, GVLIs are activated when the front of a forward motor wave reaches the second or third anterior segment. We propose that GVLIs are part of the feedback inhibition system that terminates motor activity once the front of the motor wave proceeds to anterior segments. PMID:26335437

Identification of Inhibitory Premotor Interneurons Activated at a Late Phase in a Motor Cycle during Drosophila Larval Locomotion.

PubMed

Itakura, Yuki; Kohsaka, Hiroshi; Ohyama, Tomoko; Zlatic, Marta; Pulver, Stefan R; Nose, Akinao

2015-01-01

Rhythmic motor patterns underlying many types of locomotion are thought to be produced by central pattern generators (CPGs). Our knowledge of how CPG networks generate motor patterns in complex nervous systems remains incomplete, despite decades of work in a variety of model organisms. Substrate borne locomotion in Drosophila larvae is driven by waves of muscular contraction that propagate through multiple body segments. We use the motor circuitry underlying crawling in larval Drosophila as a model to try to understand how segmentally coordinated rhythmic motor patterns are generated. Whereas muscles, motoneurons and sensory neurons have been well investigated in this system, far less is known about the identities and function of interneurons. Our recent study identified a class of glutamatergic premotor interneurons, PMSIs (period-positive median segmental interneurons), that regulate the speed of locomotion. Here, we report on the identification of a distinct class of glutamatergic premotor interneurons called Glutamatergic Ventro-Lateral Interneurons (GVLIs). We used calcium imaging to search for interneurons that show rhythmic activity and identified GVLIs as interneurons showing wave-like activity during peristalsis. Paired GVLIs were present in each abdominal segment A1-A7 and locally extended an axon towards a dorsal neuropile region, where they formed GRASP-positive putative synaptic contacts with motoneurons. The interneurons expressed vesicular glutamate transporter (vGluT) and thus likely secrete glutamate, a neurotransmitter known to inhibit motoneurons. These anatomical results suggest that GVLIs are premotor interneurons that locally inhibit motoneurons in the same segment. Consistent with this, optogenetic activation of GVLIs with the red-shifted channelrhodopsin, CsChrimson ceased ongoing peristalsis in crawling larvae. Simultaneous calcium imaging of the activity of GVLIs and motoneurons showed that GVLIs' wave-like activity lagged behind that of motoneurons by several segments. Thus, GVLIs are activated when the front of a forward motor wave reaches the second or third anterior segment. We propose that GVLIs are part of the feedback inhibition system that terminates motor activity once the front of the motor wave proceeds to anterior segments.

Interactions between posture and locomotion: motor patterns in humans walking with bent posture versus erect posture.

PubMed

Grasso, R; Zago, M; Lacquaniti, F

2000-01-01

Human erect locomotion is unique among living primates. Evolution selected specific biomechanical features that make human locomotion mechanically efficient. These features are matched by the motor patterns generated in the CNS. What happens when humans walk with bent postures? Are normal motor patterns of erect locomotion maintained or completely reorganized? Five healthy volunteers walked straight and forward at different speeds in three different postures (regular, knee-flexed, and knee- and trunk-flexed) while their motion, ground reaction forces, and electromyographic (EMG) activity were recorded. The three postures imply large differences in the position of the center of body mass relative to the body segments. The elevation angles of the trunk, pelvis, and lower limb segments relative to the vertical in the sagittal plane, the ground reaction forces and the rectified EMGs were analyzed over the gait cycle. The waveforms of the elevation angles along the gait cycle remained essentially unchanged irrespective of the adopted postures. The first two harmonics of these kinematic waveforms explain >95% of their variance. The phase shift but not the amplitude ratio between the first harmonic of the elevation angle waveforms of adjacent pairs was affected systematically by changes in posture. Thigh, shank, and foot angles covaried close to a plane in all conditions, but the plane orientation was systematically different in bent versus erect locomotion. This was explained by the changes in the temporal coupling among the three segments. For walking speeds >1 m s(-1), the plane orientation of bent locomotion indicates a much lower mechanical efficiency relative to erect locomotion. Ground reaction forces differed prominently in bent versus erect posture displaying characteristics intermediate between those typical of walking and those of running. Mean EMG activity was greater in bent postures for all recorded muscles independent of the functional role. The waveforms of the muscle activities and muscle synergies also were affected by the adopted posture. We conclude that maintaining bent postures does not interfere either with the generation of segmental kinematic waveforms or with the planar constraint of intersegmental covariation. These characteristics are maintained at the expense of adjustments in kinetic parameters, muscle synergies and the temporal coupling among the oscillating body segments. We argue that an integrated control of gait and posture is made possible because these two motor functions share some common principles of spatial organization.

Variable Camber Continuous Aerodynamic Control Surfaces and Methods for Active Wing Shaping Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T. (Inventor)

2016-01-01

An aerodynamic control apparatus for an air vehicle improves various aerodynamic performance metrics by employing multiple spanwise flap segments that jointly form a continuous or a piecewise continuous trailing edge to minimize drag induced by lift or vortices. At least one of the multiple spanwise flap segments includes a variable camber flap subsystem having multiple chordwise flap segments that may be independently actuated. Some embodiments also employ a continuous leading edge slat system that includes multiple spanwise slat segments, each of which has one or more chordwise slat segment. A method and an apparatus for implementing active control of a wing shape are also described and include the determination of desired lift distribution to determine the improved aerodynamic deflection of the wings. Flap deflections are determined and control signals are generated to actively control the wing shape to approximate the desired deflection.

Optimal Shape of a Gamma-ray Collimator: single vs double knife edge

NASA Astrophysics Data System (ADS)

Metz, Albert; Hogenbirk, Alfred

2017-09-01

Gamma-ray collimators in nuclear waste scanners are used for selecting a narrow vertical segment in activity measurements of waste vessels. The system that is used by NRG uses tapered slit collimators of both the single and double knife edge type. The properties of these collimators were investigated by means of Monte Carlo simulations. We found that single knife edge collimators are highly preferable for a conservative estimate of the activity of the waste vessels. These collimators show much less dependence on the angle of incidence of the radiation than double knife edge collimators. This conclusion also applies to cylindrical collimators of the single knife edge type, that are generally used in medical imaging spectroscopy.

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

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

Guo, Yanrong; Shao, Yeqin; Gao, Yaozong

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integratemore » the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images.« less

The time course of shape discrimination in the human brain.

PubMed

Ales, Justin M; Appelbaum, L Gregory; Cottereau, Benoit R; Norcia, Anthony M

2013-02-15

The lateral occipital cortex (LOC) activates selectively to images of intact objects versus scrambled controls, is selective for the figure-ground relationship of a scene, and exhibits at least some degree of invariance for size and position. Because of these attributes, it is considered to be a crucial part of the object recognition pathway. Here we show that human LOC is critically involved in perceptual decisions about object shape. High-density EEG was recorded while subjects performed a threshold-level shape discrimination task on texture-defined figures segmented by either phase or orientation cues. The appearance or disappearance of a figure region from a uniform background generated robust visual evoked potentials throughout retinotopic cortex as determined by inverse modeling of the scalp voltage distribution. Contrasting responses from trials containing shape changes that were correctly detected (hits) with trials in which no change occurred (correct rejects) revealed stimulus-locked, target-selective activity in the occipital visual areas LOC and V4 preceding the subject's response. Activity that was locked to the subjects' reaction time was present in the LOC. Response-locked activity in the LOC was determined to be related to shape discrimination for several reasons: shape-selective responses were silenced when subjects viewed identical stimuli but their attention was directed away from the shapes to a demanding letter discrimination task; shape-selectivity was present across four different stimulus configurations used to define the figure; LOC responses correlated with participants' reaction times. These results indicate that decision-related activity is present in the LOC when subjects are engaged in threshold-level shape discriminations. Copyright © 2012 Elsevier Inc. All rights reserved.

Instances selection algorithm by ensemble margin

NASA Astrophysics Data System (ADS)

Saidi, Meryem; Bechar, Mohammed El Amine; Settouti, Nesma; Chikh, Mohamed Amine

2018-05-01

The main limit of data mining algorithms is their inability to deal with the huge amount of available data in a reasonable processing time. A solution of producing fast and accurate results is instances and features selection. This process eliminates noisy or redundant data in order to reduce the storage and computational cost without performances degradation. In this paper, a new instance selection approach called Ensemble Margin Instance Selection (EMIS) algorithm is proposed. This approach is based on the ensemble margin. To evaluate our approach, we have conducted several experiments on different real-world classification problems from UCI Machine learning repository. The pixel-based image segmentation is a field where the storage requirement and computational cost of applied model become higher. To solve these limitations we conduct a study based on the application of EMIS and other instance selection techniques for the segmentation and automatic recognition of white blood cells WBC (nucleus and cytoplasm) in cytological images.

Universal null DTE (data terminal equipment)

DOEpatents

George, M.; Pierson, L.G.; Wilkins, M.E.

1987-11-09

A communication device in the form of data terminal equipment permits two data communication equipments, each having its own master clock and operating at substantially the same nominal clock rate, to communicate with each other in a multi-segment circuit configuration of a general communication network even when phase or frequency errors exist between the two clocks. Data transmitted between communication equipments of two segments of the communication network is buffered. A variable buffer fill circuit is provided to fill the buffer to a selectable extent prior to initiation of data output clocking. Selection switches are provided to select the degree of buffer preload. A dynamic buffer fill circuit may be incorporated for automatically selecting the buffer fill level as a function of the difference in clock frequencies of the two equipments. Controllable alarm circuitry is provided for selectively generating an underflow or an overflow alarm to one or both of the communicating equipments. 5 figs.

Universal null DTE

DOEpatents

George, Michael; Pierson, Lyndon G.; Wilkins, Mark E.

1989-01-01

A communication device in the form of data terminal equipment permits two data communication equipments, each having its own master clock and operating at substantially the same nominal clock rate, to communicate with each other in a multi-segment circuit configuration of a general communication network even when phase or frequency errors exist between the two clocks. Data transmitted between communication equipments of two segments of the communication network is buffered. A variable buffer fill circuit is provided to fill the buffer to a selectable extent prior to initiation of data output clocking. Selection switches are provided to select the degree of buffer preload. A dynamic buffer fill circuit may be incorporated for automatically selecting the buffer fill level as a function of the difference in clock frequencies of the two equipments. Controllable alarm circuitry is provided for selectively generating an underflow or an overflow alarm to one or both of the communicating equipments.

A hydrophobic filter confers the cation selectivity of Zygosaccharomyces rouxii plasma-membrane Na+/H+ antiporter.

PubMed

Kinclova-Zimmermannova, Olga; Falson, Pierre; Cmunt, Denis; Sychrova, Hana

2015-04-24

Na(+)/H(+) antiporters may recognize all alkali-metal cations as substrates but may transport them selectively. Plasma-membrane Zygosaccharomyces rouxii Sod2-22 antiporter exports Na(+) and Li(+), but not K(+). The molecular basis of this selectivity is unknown. We combined protein structure modeling, site-directed mutagenesis, phenotype analysis and cation efflux measurements to localize and characterize the cation selectivity region. A three-dimensional model of the ZrSod2-22 transmembrane domain was generated based on the X-ray structure of the Escherichia coli NhaA antiporter and primary sequence alignments with homologous yeast antiporters. The model suggested a close proximity of Thr141, Ala179 and Val375 from transmembrane segments 4, 5 and 11, respectively, forming a hydrophobic hole in the putative cation pathway's core. A series of mutagenesis experiments verified the model and showed that structural modifications of the hole resulted in altered cation selectivity and transport activity. The triple ZrSod2-22 mutant T141S-A179T-V375I gained K(+) transport capacity. The point mutation A179T restricted the antiporter substrate specificity to Li(+) and reduced its transport activity, while serine at this position preserved the native cation selectivity. The negative effect of the A179T mutation can be eliminated by introducing a second mutation, T141S or T141A, in the preceding transmembrane domain. Our experimental results confirm that the three residues found through modeling play a central role in the determination of cation selectivity and transport activity in Z. rouxii Na(+)/H(+) antiporter and that the cation selectivity can be modulated by repositioning a single local methyl group. Copyright © 2015 Elsevier Ltd. All rights reserved.

A new user-assisted segmentation and tracking technique for an object-based video editing system

NASA Astrophysics Data System (ADS)

Yu, Hong Y.; Hong, Sung-Hoon; Lee, Mike M.; Choi, Jae-Gark

2004-03-01

This paper presents a semi-automatic segmentation method which can be used to generate video object plane (VOP) for object based coding scheme and multimedia authoring environment. Semi-automatic segmentation can be considered as a user-assisted segmentation technique. A user can initially mark objects of interest around the object boundaries and then the user-guided and selected objects are continuously separated from the unselected areas through time evolution in the image sequences. The proposed segmentation method consists of two processing steps: partially manual intra-frame segmentation and fully automatic inter-frame segmentation. The intra-frame segmentation incorporates user-assistance to define the meaningful complete visual object of interest to be segmentation and decides precise object boundary. The inter-frame segmentation involves boundary and region tracking to obtain temporal coherence of moving object based on the object boundary information of previous frame. The proposed method shows stable efficient results that could be suitable for many digital video applications such as multimedia contents authoring, content based coding and indexing. Based on these results, we have developed objects based video editing system with several convenient editing functions.

Scene segmentation of natural images using texture measures and back-propagation

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Phatak, Anil; Chatterji, Gano

1993-01-01

Knowledge of the three-dimensional world is essential for many guidance and navigation applications. A sequence of images from an electro-optical sensor can be processed using optical flow algorithms to provide a sparse set of ranges as a function of azimuth and elevation. A natural way to enhance the range map is by interpolation. However, this should be undertaken with care since interpolation assumes continuity of range. The range is continuous in certain parts of the image and can jump at object boundaries. In such situations, the ability to detect homogeneous object regions by scene segmentation can be used to determine regions in the range map that can be enhanced by interpolation. The use of scalar features derived from the spatial gray-level dependence matrix for texture segmentation is explored. Thresholding of histograms of scalar texture features is done for several images to select scalar features which result in a meaningful segmentation of the images. Next, the selected scalar features are used with a neural net to automate the segmentation procedure. Back-propagation is used to train the feed forward neural network. The generalization of the network approach to subsequent images in the sequence is examined. It is shown that the use of multiple scalar features as input to the neural network result in a superior segmentation when compared with a single scalar feature. It is also shown that the scalar features, which are not useful individually, result in a good segmentation when used together. The methodology is applied to both indoor and outdoor images.

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.

Segmentation of white blood cells and comparison of cell morphology by linear and naïve Bayes classifiers.

PubMed

Prinyakupt, Jaroonrut; Pluempitiwiriyawej, Charnchai

2015-06-30

Blood smear microscopic images are routinely investigated by haematologists to diagnose most blood diseases. However, the task is quite tedious and time consuming. An automatic detection and classification of white blood cells within such images can accelerate the process tremendously. In this paper we propose a system to locate white blood cells within microscopic blood smear images, segment them into nucleus and cytoplasm regions, extract suitable features and finally, classify them into five types: basophil, eosinophil, neutrophil, lymphocyte and monocyte. Two sets of blood smear images were used in this study's experiments. Dataset 1, collected from Rangsit University, were normal peripheral blood slides under light microscope with 100× magnification; 555 images with 601 white blood cells were captured by a Nikon DS-Fi2 high-definition color camera and saved in JPG format of size 960 × 1,280 pixels at 15 pixels per 1 μm resolution. In dataset 2, 477 cropped white blood cell images were downloaded from CellaVision.com. They are in JPG format of size 360 × 363 pixels. The resolution is estimated to be 10 pixels per 1 μm. The proposed system comprises a pre-processing step, nucleus segmentation, cell segmentation, feature extraction, feature selection and classification. The main concept of the segmentation algorithm employed uses white blood cell's morphological properties and the calibrated size of a real cell relative to image resolution. The segmentation process combined thresholding, morphological operation and ellipse curve fitting. Consequently, several features were extracted from the segmented nucleus and cytoplasm regions. Prominent features were then chosen by a greedy search algorithm called sequential forward selection. Finally, with a set of selected prominent features, both linear and naïve Bayes classifiers were applied for performance comparison. This system was tested on normal peripheral blood smear slide images from two datasets. Two sets of comparison were performed: segmentation and classification. The automatically segmented results were compared to the ones obtained manually by a haematologist. It was found that the proposed method is consistent and coherent in both datasets, with dice similarity of 98.9 and 91.6% for average segmented nucleus and cell regions, respectively. Furthermore, the overall correction rate in the classification phase is about 98 and 94% for linear and naïve Bayes models, respectively. The proposed system, based on normal white blood cell morphology and its characteristics, was applied to two different datasets. The results of the calibrated segmentation process on both datasets are fast, robust, efficient and coherent. Meanwhile, the classification of normal white blood cells into five types shows high sensitivity in both linear and naïve Bayes models, with slightly better results in the linear classifier.

Active mask segmentation of fluorescence microscope images.

PubMed

Srinivasa, Gowri; Fickus, Matthew C; Guo, Yusong; Linstedt, Adam D; Kovacević, Jelena

2009-08-01

We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the "contour" to that of "inside and outside," or masks, allowing for easy multidimensional segmentation. It adapts to the topology of the image through the use of multiple masks. The algorithm is almost invariant under initialization, allowing for random initialization, and uses a few easily tunable parameters. Experiments show that the active mask algorithm matches the ground truth well and outperforms the algorithm widely used in fluorescence microscopy, seeded watershed, both qualitatively, as well as quantitatively.

New Stopping Criteria for Segmenting DNA Sequences

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

Li, Wentian

2001-06-18

We propose a solution on the stopping criterion in segmenting inhomogeneous DNA sequences with complex statistical patterns. This new stopping criterion is based on Bayesian information criterion in the model selection framework. When this criterion is applied to telomere of S.cerevisiae and the complete sequence of E.coli, borders of biologically meaningful units were identified, and a more reasonable number of domains was obtained. We also introduce a measure called segmentation strength which can be used to control the delineation of large domains. The relationship between the average domain size and the threshold of segmentation strength is determined for several genomemore » sequences.« less

Selective suppression of high-order harmonics within phase-matched spectral regions.

PubMed

Lerner, Gavriel; Diskin, Tzvi; Neufeld, Ofer; Kfir, Ofer; Cohen, Oren

2017-04-01

Phase matching in high-harmonic generation leads to enhancement of multiple harmonics. It is sometimes desired to control the spectral structure within the phase-matched spectral region. We propose a scheme for selective suppression of high-order harmonics within the phase-matched spectral region while weakly influencing the other harmonics. The method is based on addition of phase-mismatched segments within a phase-matched medium. We demonstrate the method numerically in two examples. First, we show that one phase-mismatched segment can significantly suppress harmonic orders 9, 15, and 21. Second, we show that two phase-mismatched segments can efficiently suppress circularly polarized harmonics with one helicity over the other when driven by a bi-circular field. The new method may be useful for various applications, including the generation of highly helical bright attosecond pulses.

Lacie phase 1 Classification and Mensuration Subsystem (CAMS) rework experiment

NASA Technical Reports Server (NTRS)

Chhikara, R. S.; Hsu, E. M.; Liszcz, C. J.

1976-01-01

An experiment was designed to test the ability of the Classification and Mensuration Subsystem rework operations to improve wheat proportion estimates for segments that had been processed previously. Sites selected for the experiment included three in Kansas and three in Texas, with the remaining five distributed in Montana and North and South Dakota. The acquisition dates were selected to be representative of imagery available in actual operations. No more than one acquisition per biophase were used, and biophases were determined by actual crop calendars. All sites were worked by each of four Analyst-Interpreter/Data Processing Analyst Teams who reviewed the initial processing of each segment and accepted or reworked it for an estimate of the proportion of small grains in the segment. Classification results, acquisitions and classification errors and performance results between CAMS regular and ITS rework are tabulated.

MSuPDA: A Memory Efficient Algorithm for Sequence Alignment.

PubMed

Khan, Mohammad Ibrahim; Kamal, Md Sarwar; Chowdhury, Linkon

2016-03-01

Space complexity is a million dollar question in DNA sequence alignments. In this regard, memory saving under pushdown automata can help to reduce the occupied spaces in computer memory. Our proposed process is that anchor seed (AS) will be selected from given data set of nucleotide base pairs for local sequence alignment. Quick splitting techniques will separate the AS from all the DNA genome segments. Selected AS will be placed to pushdown automata's (PDA) input unit. Whole DNA genome segments will be placed into PDA's stack. AS from input unit will be matched with the DNA genome segments from stack of PDA. Match, mismatch and indel of nucleotides will be popped from the stack under the control unit of pushdown automata. During the POP operation on stack, it will free the memory cell occupied by the nucleotide base pair.

Impact of freeway weaving segment design on light-duty vehicle exhaust emissions.

PubMed

Li, Qing; Qiao, Fengxiang; Yu, Lei; Chen, Shuyan; Li, Tiezhu

2018-06-01

In the United States, 26% of greenhouse gas emissions is emitted from the transportation sector; these emisssions meanwhile are accompanied by enormous toxic emissions to humans, such as carbon monoxide (CO), nitrogen oxides (NO x ), and hydrocarbon (HC), approximately 2.5% and 2.44% of a total exhaust emissions for a petrol and a diesel engine, respectively. These exhaust emissions are typically subject to vehicles' intermittent operations, such as hard acceleration and hard braking. In practice, drivers are inclined to operate intermittently while driving through a weaving segment, due to complex vehicle maneuvering for weaving. As a result, the exhaust emissions within a weaving segment ought to vary from those on a basic segment. However, existing emission models usually rely on vehicle operation information, and compute a generalized emission result, regardless of road configuration. This research proposes to explore the impacts of weaving segment configuration on vehicle emissions, identify important predictors for emission estimations, and develop a nonlinear normalized emission factor (NEF) model for weaving segments. An on-board emission test was conducted on 12 subjects on State Highway 288 in Houston, Texas. Vehicles' activity information, road conditions, and real-time exhaust emissions were collected by on-board diagnosis (OBD), a smartphone-based roughness app, and a portable emission measurement system (PEMS), respectively. Five feature selection algorithms were used to identify the important predictors for the response of NEF and the modeling algorithm. The predictive power of four algorithm-based emission models was tested by 10-fold cross-validation. Results showed that emissions are also susceptible to the type and length of a weaving segment. Bagged decision tree algorithm was chosen to develop a 50-grown-tree NEF model, which provided a validation error of 0.0051. The estimated NEFs are highly correlated with the observed NEFs in the training data set as well as in the validation data set, with the R values of 0.91 and 0.90, respectively. Existing emission models usually rely on vehicle operation information to compute a generalized emission result, regardless of road configuration. In practice, while driving through a weaving segment, drivers are inclined to perform erratic maneuvers, such as hard braking and hard acceleration due to the complex weaving maneuver required. As a result, the exhaust emissions within a weaving segment vary from those on a basic segment. This research proposes to involve road configuration, in terms of the type and length of a weaving segment, in constructing an emission nonlinear model, which significantly improves emission estimations at a microscopic level.

Predicted consequences of diabetes and SGLT inhibition on transport and oxygen consumption along a rat nephron

PubMed Central

Vallon, Volker; Edwards, Aurélie

2016-01-01

Diabetes increases the reabsorption of Na+ (TNa) and glucose via the sodium-glucose cotransporter SGLT2 in the early proximal tubule (S1-S2 segments) of the renal cortex. SGLT2 inhibitors enhance glucose excretion and lower hyperglycemia in diabetes. We aimed to investigate how diabetes and SGLT2 inhibition affect TNa and sodium transport-dependent oxygen consumption QO2active along the whole nephron. To do so, we developed a mathematical model of water and solute transport from the Bowman space to the papillary tip of a superficial nephron of the rat kidney. Model simulations indicate that, in the nondiabetic kidney, acute and chronic SGLT2 inhibition enhances active TNa in all nephron segments, thereby raising QO2active by 5–12% in the cortex and medulla. Diabetes increases overall TNa and QO2active by ∼50 and 100%, mainly because it enhances glomerular filtration rate (GFR) and transport load. In diabetes, acute and chronic SGLT2 inhibition lowers QO2active in the cortex by ∼30%, due to GFR reduction that lowers proximal tubule active TNa, but raises QO2active in the medulla by ∼7%. In the medulla specifically, chronic SGLT2 inhibition is predicted to increase QO2active by 26% in late proximal tubules (S3 segments), by 2% in medullary thick ascending limbs (mTAL), and by 9 and 21% in outer and inner medullary collecting ducts (OMCD and IMCD), respectively. Additional blockade of SGLT1 in S3 segments enhances glucose excretion, reduces QO2active by 33% in S3 segments, and raises QO2active by <1% in mTAL, OMCD, and IMCD. In summary, the model predicts that SGLT2 blockade in diabetes lowers cortical QO2active and raises medullary QO2active, particularly in S3 segments. PMID:26764207

Community pharmacy customer segmentation based on factors influencing their selection of pharmacy and over-the-counter medicines.

PubMed

Kevrekidis, Dimitrios Phaedon; Minarikova, Daniela; Markos, Angelos; Malovecka, Ivona; Minarik, Peter

2018-01-01

Within the competitive pharmacy market environment, community pharmacies are required to develop efficient marketing strategies based on contemporary information about consumer behavior in order to attract clients and develop customer loyalty. This study aimed to investigate the consumers' preferences concerning the selection of pharmacy and over-the-counter (OTC) medicines, and to identify customer segments in relation to these preferences. A cross-sectional study was conducted between February and March 2016 on a convenient quota sample of 300 participants recruited in the metropolitan area of Thessaloniki, Greece. The main instrument used for data collection was a structured questionnaire with close-ended, multiple choice questions. To identify customer segments, Two-Step cluster analysis was conducted. Three distinct pharmacy customer clusters emerged. Customers of the largest cluster (49%; 'convenience customers') were mostly younger consumers. They gave moderate to positive ratings to factors affecting the selection of pharmacy and OTCs; convenience, and previous experience and the pharmacist's opinion, received the highest ratings. Customers of the second cluster (35%; 'loyal customers') were mainly retired; most of them reported visiting a single pharmacy. They gave high ratings to all factors that influence pharmacy selection, especially the pharmacy's staff, and factors influencing the purchase of OTCs, particularly previous experience and the pharmacist's opinion. Customers of the smallest cluster (16%; 'convenience and price-sensitive customers') were mainly retired or unemployed with low to moderate education, and low personal income. They gave the lowest ratings to most of the examined factors; convenience among factors influencing pharmacy selection, whereas previous experience, the pharmacist's opinion and product price among those affecting the purchase of OTCs, received the highest ratings. The community pharmacy market comprised of distinct customer segments that varied in the consumer preferences concerning the selection of pharmacy and OTCs, the evaluation of pharmaceutical services and products, and demographic characteristics.

Atlas ranking and selection for automatic segmentation of the esophagus from CT scans

NASA Astrophysics Data System (ADS)

Yang, Jinzhong; Haas, Benjamin; Fang, Raymond; Beadle, Beth M.; Garden, Adam S.; Liao, Zhongxing; Zhang, Lifei; Balter, Peter; Court, Laurence

2017-12-01

In radiation treatment planning, the esophagus is an important organ-at-risk that should be spared in patients with head and neck cancer or thoracic cancer who undergo intensity-modulated radiation therapy. However, automatic segmentation of the esophagus from CT scans is extremely challenging because of the structure’s inconsistent intensity, low contrast against the surrounding tissues, complex and variable shape and location, and random air bubbles. The goal of this study is to develop an online atlas selection approach to choose a subset of optimal atlases for multi-atlas segmentation to the delineate esophagus automatically. We performed atlas selection in two phases. In the first phase, we used the correlation coefficient of the image content in a cubic region between each atlas and the new image to evaluate their similarity and to rank the atlases in an atlas pool. A subset of atlases based on this ranking was selected, and deformable image registration was performed to generate deformed contours and deformed images in the new image space. In the second phase of atlas selection, we used Kullback-Leibler divergence to measure the similarity of local-intensity histograms between the new image and each of the deformed images, and the measurements were used to rank the previously selected atlases. Deformed contours were overlapped sequentially, from the most to the least similar, and the overlap ratio was examined. We further identified a subset of optimal atlases by analyzing the variation of the overlap ratio versus the number of atlases. The deformed contours from these optimal atlases were fused together using a modified simultaneous truth and performance level estimation algorithm to produce the final segmentation. The approach was validated with promising results using both internal data sets (21 head and neck cancer patients and 15 thoracic cancer patients) and external data sets (30 thoracic patients).

Hybrid Active/Passive Jet Engine Noise Suppression System

NASA Technical Reports Server (NTRS)

Parente, C. A.; Arcas, N.; Walker, B. E.; Hersh, A. S.; Rice, E. J.

1999-01-01

A novel adaptive segmented liner concept has been developed that employs active control elements to modify the in-duct sound field to enhance the tone-suppressing performance of passive liner elements. This could potentially allow engine designs that inherently produce more tone noise but less broadband noise, or could allow passive liner designs to more optimally address high frequency broadband noise. A proof-of-concept validation program was undertaken, consisting of the development of an adaptive segmented liner that would maximize attenuation of two radial modes in a circular or annular duct. The liner consisted of a leading active segment with dual annuli of axially spaced active Helmholtz resonators, followed by an optimized passive liner and then an array of sensing microphones. Three successively complex versions of the adaptive liner were constructed and their performances tested relative to the performance of optimized uniform passive and segmented passive liners. The salient results of the tests were: The adaptive segmented liner performed well in a high flow speed model fan inlet environment, was successfully scaled to a high sound frequency and successfully attenuated three radial modes using sensor and active resonator arrays that were designed for a two mode, lower frequency environment.

Automatic lung nodule graph cuts segmentation with deep learning false positive reduction

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Tseng, Tzu-Liang Bill; Qian, Wei

2017-03-01

To automatic detect lung nodules from CT images, we designed a two stage computer aided detection (CAD) system. The first stage is graph cuts segmentation to identify and segment the nodule candidates, and the second stage is convolutional neural network for false positive reduction. The dataset contains 595 CT cases randomly selected from Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI) and the 305 pulmonary nodules achieved diagnosis consensus by all four experienced radiologists were our detection targets. Consider each slice as an individual sample, 2844 nodules were included in our database. The graph cuts segmentation was conducted in a two-dimension manner, 2733 lung nodule ROIs are successfully identified and segmented. With a false positive reduction by a seven-layer convolutional neural network, 2535 nodules remain detected while the false positive dropped to 31.6%. The average F-measure of segmented lung nodule tissue is 0.8501.

Using wavelet denoising and mathematical morphology in the segmentation technique applied to blood cells images.

PubMed

Boix, Macarena; Cantó, Begoña

2013-04-01

Accurate image segmentation is used in medical diagnosis since this technique is a noninvasive pre-processing step for biomedical treatment. In this work we present an efficient segmentation method for medical image analysis. In particular, with this method blood cells can be segmented. For that, we combine the wavelet transform with morphological operations. Moreover, the wavelet thresholding technique is used to eliminate the noise and prepare the image for suitable segmentation. In wavelet denoising we determine the best wavelet that shows a segmentation with the largest area in the cell. We study different wavelet families and we conclude that the wavelet db1 is the best and it can serve for posterior works on blood pathologies. The proposed method generates goods results when it is applied on several images. Finally, the proposed algorithm made in MatLab environment is verified for a selected blood cells.

Sample Training Based Wildfire Segmentation by 2D Histogram θ-Division with Minimum Error

PubMed Central

Dong, Erqian; Sun, Mingui; Jia, Wenyan; Zhang, Dengyi; Yuan, Zhiyong

2013-01-01

A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. Based on minimum error principle and 2D color histogram, the θ-division methods were presented recently, but application of prior knowledge on them has not been explored. For the specific problem of wildfire segmentation, we collect sample images with manually labeled fire pixels. Then we define the probability function of error division to evaluate θ-division segmentations, and the optimal angle θ is determined by sample training. Performances in different color channels are compared, and the suitable channel is selected. To further improve the accuracy, the combination approach is presented with both θ-division and other segmentation methods such as GMM. Our approach is tested on real images, and the experiments prove its efficiency for wildfire segmentation. PMID:23878526

LACIE performance predictor final operational capability program description, volume 2

NASA Technical Reports Server (NTRS)

1976-01-01

Given the swath table files, the segment set for one country and cloud cover data, the SAGE program determines how many times and under what conditions each segment is accessed by satellites. The program writes a record for each segment on a data file which contains the pertinent acquisition data. The weather data file can also be generated from a NASA supplied tape. The Segment Acquisition Selector Program (SACS) selects data from the segment reference file based upon data input manually and from a crop window file. It writes the extracted data to a data acquisition file and prints two summary reports. The POUT program reads from associated LACIE files and produces printed reports. The major types of reports that can be produced are: (1) Substrate Reference Data Reports, (2) Population Mean, Standard Deviation and Histogram Reports, (3) Histograms of Monte Carlo Statistics Reports, and (4) Frequency of Sample Segment Acquisitions Reports.

A general system for automatic biomedical image segmentation using intensity neighborhoods.

PubMed

Chen, Cheng; Ozolek, John A; Wang, Wei; Rohde, Gustavo K

2011-01-01

Image segmentation is important with applications to several problems in biology and medicine. While extensively researched, generally, current segmentation methods perform adequately in the applications for which they were designed, but often require extensive modifications or calibrations before being used in a different application. We describe an approach that, with few modifications, can be used in a variety of image segmentation problems. The approach is based on a supervised learning strategy that utilizes intensity neighborhoods to assign each pixel in a test image its correct class based on training data. We describe methods for modeling rotations and variations in scales as well as a subset selection for training the classifiers. We show that the performance of our approach in tissue segmentation tasks in magnetic resonance and histopathology microscopy images, as well as nuclei segmentation from fluorescence microscopy images, is similar to or better than several algorithms specifically designed for each of these applications.

A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier.

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

The proposed system provides new textural information for segmenting tumours, efficiently and accurately and with less computational time, from benign and malignant tumour images, especially in smaller dimensions of tumour regions of computed tomography (CT) images. Region-based segmentation of tumour from brain CT image data is an important but time-consuming task performed manually by medical experts. The objective of this work is to segment brain tumour from CT images using combined grey and texture features with new edge features and nonlinear support vector machine (SVM) classifier. The selected optimal features are used to model and train the nonlinear SVM classifier to segment the tumour from computed tomography images and the segmentation accuracies are evaluated for each slice of the tumour image. The method is applied on real data of 80 benign, malignant tumour images. The results are compared with the radiologist labelled ground truth. Quantitative analysis between ground truth and the segmented tumour is presented in terms of segmentation accuracy and the overlap similarity measure dice metric. From the analysis and performance measures such as segmentation accuracy and dice metric, it is inferred that better segmentation accuracy and higher dice metric are achieved with the normalized cut segmentation method than with the fuzzy c-means clustering method.

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.

Differential regulation of proximal and distal Vbeta segments upstream of a functional VDJbeta1 rearrangement upon beta-selection.

PubMed

Brady, Brenna L; Bassing, Craig H

2011-09-15

Developmental stage-specific regulation of transcriptional accessibility helps control V(D)J recombination. Vβ segments on unrearranged TCRβ alleles are accessible in CD4(-)/CD8(-) (double-negative [DN]) thymocytes, when they recombine, and inaccessible in CD4(+)/CD8(+) (double-positive [DP]) thymocytes, when they do not rearrange. Downregulation of Vβ accessibility on unrearranged alleles is linked with Lat-dependent β-selection signals that inhibit Vβ rearrangement, stimulate Ccnd3-driven proliferation, and promote DN-to-DP differentiation. Transcription and recombination of Vβs on VDJβ-rearranged alleles in DN cells has not been studied; Vβs upstream of functional VDJβ rearrangements have been found to remain accessible, yet not recombine, in DP cells. To elucidate contributions of β-selection signals in regulating Vβ transcription and recombination on VDJβ-rearranged alleles, we analyzed wild-type, Ccnd3(-/-), and Lat(-/-) mice containing a preassembled functional Vβ1DJCβ1 (Vβ1(NT)) gene. Vβ10 segments located just upstream of this VDJCβ1 gene were the predominant germline Vβs that rearranged in Vβ1(NT/NT) and Vβ1(NT/NT)Ccnd3(-/-) thymocytes, whereas Vβ4 and Vβ16 segments located further upstream rearranged at similar levels as Vβ10 in Vβ1(NT/NT)Lat(-/-) DN cells. We previously showed that Vβ4 and Vβ16, but not Vβ10, are transcribed on Vβ1(NT) alleles in DP thymocytes; we now demonstrate that Vβ4, Vβ16, and Vβ10 are transcribed at similar levels in Vβ1(NT/NT)Lat(-/-) DN cells. These observations indicate that suppression of Vβ rearrangements is not dependent on Ccnd3-driven proliferation, and DN residence can influence the repertoire of Vβs that recombine on alleles containing an assembled VDJCβ1 gene. Our findings also reveal that β-selection can differentially silence rearrangement of germline Vβ segments located proximal and distal to functional VDJβ genes.

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.

Rapid Phenotyping of Root Systems of Brachypodium Plants Using X-ray Computed Tomography: a Comparative Study of Soil Types and Segmentation Tools

NASA Astrophysics Data System (ADS)

Varga, T.; McKinney, A. L.; Bingham, E.; Handakumbura, P. P.; Jansson, C.

2017-12-01

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as in processes with important implications to farming and thus human food supply. X-ray computed tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. Selected Brachypodium distachyon phenotypes were grown in both natural and artificial soil mixes. The specimens were imaged by XCT, and the root architectures were extracted from the data using three different software-based methods; RooTrak, ImageJ-based WEKA segmentation, and the segmentation feature in VG Studio MAX. The 3D root image was successfully segmented at 30 µm resolution by all three methods. In this presentation, ease of segmentation and the accuracy of the extracted quantitative information (root volume and surface area) will be compared between soil types and segmentation methods. The best route to easy and accurate segmentation and root analysis will be highlighted.

An audience-channel-message-evaluation (ACME) framework for health communication campaigns.

PubMed

Noar, Seth M

2012-07-01

Recent reviews of the literature have indicated that a number of health communication campaigns continue to fail to adhere to principles of effective campaign design. The lack of an integrated, organizing framework for the design, implementation, and evaluation of health communication campaigns may contribute to this state of affairs. The current article introduces an audience-channel-message-evaluation (ACME) framework that organizes the major principles of health campaign design, implementation, and evaluation. ACME also explicates the relationships and linkages between the varying principles. Insights from ACME include the following: The choice of audience segment(s) to focus on in a campaign affects all other campaign design choices, including message strategy and channel/component options. Although channel selection influences options for message design, choice of message design also influences channel options. Evaluation should not be thought of as a separate activity, but rather should be infused and integrated throughout the campaign design and implementation process, including formative, process, and outcome evaluation activities. Overall, health communication campaigns that adhere to this integrated set of principles of effective campaign design will have a greater chance of success than those using principles idiosyncratically. These design, implementation, and evaluation principles are embodied in the ACME framework.

Intensity-based segmentation and visualization of cells in 3D microscopic images using the GPU

NASA Astrophysics Data System (ADS)

Kang, Mi-Sun; Lee, Jeong-Eom; Jeon, Woong-ki; Choi, Heung-Kook; Kim, Myoung-Hee

2013-02-01

3D microscopy images contain abundant astronomical data, rendering 3D microscopy image processing time-consuming and laborious on a central processing unit (CPU). To solve these problems, many people crop a region of interest (ROI) of the input image to a small size. Although this reduces cost and time, there are drawbacks at the image processing level, e.g., the selected ROI strongly depends on the user and there is a loss in original image information. To mitigate these problems, we developed a 3D microscopy image processing tool on a graphics processing unit (GPU). Our tool provides efficient and various automatic thresholding methods to achieve intensity-based segmentation of 3D microscopy images. Users can select the algorithm to be applied. Further, the image processing tool provides visualization of segmented volume data and can set the scale, transportation, etc. using a keyboard and mouse. However, the 3D objects visualized fast still need to be analyzed to obtain information for biologists. To analyze 3D microscopic images, we need quantitative data of the images. Therefore, we label the segmented 3D objects within all 3D microscopic images and obtain quantitative information on each labeled object. This information can use the classification feature. A user can select the object to be analyzed. Our tool allows the selected object to be displayed on a new window, and hence, more details of the object can be observed. Finally, we validate the effectiveness of our tool by comparing the CPU and GPU processing times by matching the specification and configuration.

Accurate cytogenetic biodosimetry through automated dicentric chromosome curation and metaphase cell selection

PubMed Central

Wilkins, Ruth; Flegal, Farrah; Knoll, Joan H.M.; Rogan, Peter K.

2017-01-01

Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs arising primarily from sister chromatid separation, chromosome fragmentation, and cellular debris. This reduced FPs by an average of 55% and was highly specific to these abnormal structures (≥97.7%) in three samples. Additional filters selectively removed images with incomplete, highly overlapped, or missing metaphase cells, or with poor overall chromosome morphologies that increased FP rates. Image selection is optimized and FP DCs are minimized by combining multiple feature based segmentation filters and a novel image sorting procedure based on the known distribution of chromosome lengths. Applying the same image segmentation filtering procedures to both calibration and test samples reduced the average dose estimation error from 0.4 Gy to <0.2 Gy, obviating the need to first manually review these images. This reliable and scalable solution enables batch processing for multiple samples of unknown dose, and meets current requirements for triage radiation biodosimetry of high quality metaphase cell preparations. PMID:29026522

White Ethnics, Racial Prejudice, and Labor Market Segmentation.

ERIC Educational Resources Information Center

Cummings, Scott

The contemporary conflict between blacks and selected white ethnic groups (Catholic immigrants, Jews) is the product of competition for jobs in the secondary labor market. Radical economists have described the existence of a dual labor market within the American economy. The idea of this segmented labor market provides a useful way to integrate…

Effective Marketing Strategies Flow from Sound Segmentation Data.

ERIC Educational Resources Information Center

Chen, Henry C. K.; And Others

The paper investigates the potential market segments of an upper division university in transition to 4-year status, and explores selection criteria and the influence of various information sources on the choice of university by the potential target students. Data sources for the study included a survey of 142 freshmen students of whom 120…

Managing the market. Focusing on a select group of customers can keep an organization competitive.

PubMed

MacStravic, R S

1989-05-01

The real challenge in healthcare marketing today is managing markets, focusing on selected groups of customers rather than on the organization or its services. Market management includes three distinct but related levels: Strategic market management assesses current and potential markets and chooses those the organization can serve best; segment management focuses on the needs and wants of subsets of chosen customers; and customer management reinforces long-term commitments to the organization. The patient care experience can be broken down into specific contacts with each staff member. The key to managing the experience is to identify and achieve standards of performance for each contact by examining what each event means to the patients and how patients judge each staff member, as well as the overall care experience. Regular feedback helps. An unavoidable risk in market management is that a given segment may decline in size, in need for services, or in cohesiveness as a segment. Yet those organizations which can identify the right segments and "manage" them effectively will have an advantage in a competitive market.

A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung.

PubMed

Guo, Shengwen; Fei, Baowei

2009-03-27

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

A minimal path searching approach for active shape model (ASM)-based segmentation of the lung

NASA Astrophysics Data System (ADS)

Guo, Shengwen; Fei, Baowei

2009-02-01

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung

PubMed Central

Guo, Shengwen; Fei, Baowei

2013-01-01

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs. PMID:24386531

MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

PubMed

Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

2013-01-01

Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

Poly-Pattern Compressive Segmentation of ASTER Data for GIS

NASA Technical Reports Server (NTRS)

Myers, Wayne; Warner, Eric; Tutwiler, Richard

2007-01-01

Pattern-based segmentation of multi-band image data, such as ASTER, produces one-byte and two-byte approximate compressions. This is a dual segmentation consisting of nested coarser and finer level pattern mappings called poly-patterns. The coarser A-level version is structured for direct incorporation into geographic information systems in the manner of a raster map. GIs renderings of this A-level approximation are called pattern pictures which have the appearance of color enhanced images. The two-byte version consisting of thousands of B-level segments provides a capability for approximate restoration of the multi-band data in selected areas or entire scenes. Poly-patterns are especially useful for purposes of change detection and landscape analysis at multiple scales. The primary author has implemented the segmentation methodology in a public domain software suite.

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.

Event segmentation ability uniquely predicts event memory.

PubMed

Sargent, Jesse Q; Zacks, Jeffrey M; Hambrick, David Z; Zacks, Rose T; Kurby, Christopher A; Bailey, Heather R; Eisenberg, Michelle L; Beck, Taylor M

2013-11-01

Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. Copyright © 2013 Elsevier B.V. All rights reserved.

Event Segmentation Ability Uniquely Predicts Event Memory

PubMed Central

Sargent, Jesse Q.; Zacks, Jeffrey M.; Hambrick, David Z.; Zacks, Rose T.; Kurby, Christopher A.; Bailey, Heather R.; Eisenberg, Michelle L.; Beck, Taylor M.

2013-01-01

Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79 years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. PMID:23942350

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

NASA Astrophysics Data System (ADS)

Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

The Intricacies of Children's Physical Activity.

PubMed

Brusseau, Timothy A

2015-09-29

Understanding the physical activity patterns of youth is an essential step in preparing programming and interventions needed to change behavior. To date, little is known about the intricacies of youth physical activity across various physical activity segments (i.e. in school, out of school, recess, classroom physical activity, physical education, weekends, etc.). Therefore, the purpose of the study was to examine the physical activity patterns of elementary school children across various segments and during two seasons. A total of 287 fourth and fifth graders from the Southwest US wore the Yamax Digiwalker SW-200 pedometer for 7 consecutive days during the Fall and Spring seasons. Children were prompted to record their step counts when arriving and leaving school, before and after physical education and recess, as well as on the weekends. Means and standard deviations were calculated and ANOVAs and t tests were utilized to examine difference by sex, season, and segment. Youth were more active outside of school and on weekdays (p<0.05). Boys were generally more active than girls and all youth were more active during the milder Spring season. There is a clear need for Comprehensive School Physical Activity Programming and weekend physical activity opportunities. Furthermore, greater emphasis is needed on PE and across other activity segments for girls to increase their physical activity levels.

The Intricacies of Children’s Physical Activity

PubMed Central

Brusseau, Timothy A

2015-01-01

Understanding the physical activity patterns of youth is an essential step in preparing programming and interventions needed to change behavior. To date, little is known about the intricacies of youth physical activity across various physical activity segments (i.e. in school, out of school, recess, classroom physical activity, physical education, weekends, etc.). Therefore, the purpose of the study was to examine the physical activity patterns of elementary school children across various segments and during two seasons. A total of 287 fourth and fifth graders from the Southwest US wore the Yamax Digiwalker SW-200 pedometer for 7 consecutive days during the Fall and Spring seasons. Children were prompted to record their step counts when arriving and leaving school, before and after physical education and recess, as well as on the weekends. Means and standard deviations were calculated and ANOVAs and t tests were utilized to examine difference by sex, season, and segment. Youth were more active outside of school and on weekdays (p<0.05). Boys were generally more active than girls and all youth were more active during the milder Spring season. There is a clear need for Comprehensive School Physical Activity Programming and weekend physical activity opportunities. Furthermore, greater emphasis is needed on PE and across other activity segments for girls to increase their physical activity levels. PMID:26557210

Segmentally distributed metamorphic changes in neural circuits controlling abdominal bending in the hawk moth Manduca sexta.

PubMed

Lemon, W C; Levine, R B

1997-06-01

During the metamorphosis of Manduca sexta the larval nervous system is reorganized to allow the generation of behaviors that are specific to the pupal and adult stages. In some instances, metamorphic changes in neurons that persist from the larval stage are segment-specific and lead to expression of segment-specific behavior in later stages. At the larval-pupal transition, the larval abdominal bending behavior, which is distributed throughout the abdomen, changes to the pupal gin trap behavior which is restricted to three abdominal segments. This study suggests that the neural circuit that underlies larval bending undergoes segment specific modifications to produce the segmentally restricted gin trap behavior. We show, however, that non-gin trap segments go through a developmental change similar to that seen in gin trap segments. Pupal-specific motor patterns are produced by stimulation of sensory neurons in abdominal segments that do not have gin traps and cannot produce the gin trap behavior. In particular, sensory stimulation in non-gin trap pupal segments evokes a motor response that is faster than the larval response and that displays the triphasic contralateral-ipsilateral-contralateral activity pattern that is typical of the pupal gin trap behavior. Despite the alteration of reflex activity in all segments, developmental changes in sensory neuron morphology are restricted to those segments that form gin traps. In non-gin trap segments, persistent sensory neurons do not expand their terminal arbors, as do sensory neurons in gin trap segments, yet are capable of eliciting gin trap-like motor responses.

The use of selected community groups to elicit and understand the values underlying attitudes towards biotechnology.

PubMed

Gamble, Joanna; Kassardjian, Elsa

2008-04-01

Focus groups were used to examine the social, cultural and spiritual dimensions of biotechnology through an analysis of five selected community groups (total n = 68): scientists, Buddhists, business people, mothers with young children and the environmentally active. Participants from all groups were united in their perspective on three of the value spheres explored: health and welfare of family/society; maintaining/preserving the environment; and ethical considerations (e.g. welfare of animals, sanctity of life). However, values regarding science and business differentiated scientists and business people from the remaining community segments. Business people were more likely to adhere to "productionism," resulting in a greater acceptance of biotechnology, since business people did not hold the same resentment toward the business sphere held by other community segments. Scientists were far more accepting of the norms and values inherent in the sphere of science, believing science to be more predictable and controllable than general public perceptions. The disparity in worldviews for this value sphere meant scientists and laypeople did not communicate at the same level, in spite of having the same concerns for health and the environment. This resulted in feelings of frustration and powerlessness on the part of the layperson and the scientist.

Seasonal Differences in Segmented-Day Physical Activity and Sedentary Behaviour in Primary School Children

ERIC Educational Resources Information Center

Loucaides, Constantinos A.

2018-01-01

This study examined seasonal differences in children's segmented-day physical activity (PA) and time engaged in sedentary activities. Seventy-three children wore a pedometer during winter and spring and completed a diary relating to their after-school sedentary activities and time playing outside. Children recorded higher steps in spring compared…

Implications of segment mismatch for influenza A virus evolution

PubMed Central

White, Maria C.; Lowen, Anice C.

2018-01-01

Influenza A virus (IAV) is an RNA virus with a segmented genome. These viral properties allow for the rapid evolution of IAV under selective pressure, due to mutation occurring from error-prone replication and the exchange of gene segments within a co-infected cell, termed reassortment. Both mutation and reassortment give rise to genetic diversity, but constraints shape their impact on viral evolution: just as most mutations are deleterious, most reassortment events result in genetic incompatibilities. The phenomenon of segment mismatch encompasses both RNA- and protein-based incompatibilities between co-infecting viruses and results in the production of progeny viruses with fitness defects. Segment mismatch is an important determining factor of the outcomes of mixed IAV infections and has been addressed in multiple risk assessment studies undertaken to date. However, due to the complexity of genetic interactions among the eight viral gene segments, our understanding of segment mismatch and its underlying mechanisms remain incomplete. Here, we summarize current knowledge regarding segment mismatch and discuss the implications of this phenomenon for IAV reassortment and diversity. PMID:29244017

Sensor-oriented feature usability evaluation in fingerprint segmentation

NASA Astrophysics Data System (ADS)

Li, Ying; Yin, Yilong; Yang, Gongping

2013-06-01

Existing fingerprint segmentation methods usually process fingerprint images captured by different sensors with the same feature or feature set. We propose to improve the fingerprint segmentation result in view of an important fact that images from different sensors have different characteristics for segmentation. Feature usability evaluation, which means to evaluate the usability of features to find the personalized feature or feature set for different sensors to improve the performance of segmentation. The need for feature usability evaluation for fingerprint segmentation is raised and analyzed as a new issue. To address this issue, we present a decision-tree-based feature-usability evaluation method, which utilizes a C4.5 decision tree algorithm to evaluate and pick the best suitable feature or feature set for fingerprint segmentation from a typical candidate feature set. We apply the novel method on the FVC2002 database of fingerprint images, which are acquired by four different respective sensors and technologies. Experimental results show that the accuracy of segmentation is improved, and time consumption for feature extraction is dramatically reduced with selected feature(s).

Methods, media, and systems for detecting attack on a digital processing device

DOEpatents

Stolfo, Salvatore J.; Li, Wei-Jen; Keromylis, Angelos D.; Androulaki, Elli

2014-07-22

Methods, media, and systems for detecting attack are provided. In some embodiments, the methods include: comparing at least part of a document to a static detection model; determining whether attacking code is included in the document based on the comparison of the document to the static detection model; executing at least part of the document; determining whether attacking code is included in the document based on the execution of the at least part of the document; and if attacking code is determined to be included in the document based on at least one of the comparison of the document to the static detection model and the execution of the at least part of the document, reporting the presence of an attack. In some embodiments, the methods include: selecting a data segment in at least one portion of an electronic document; determining whether the arbitrarily selected data segment can be altered without causing the electronic document to result in an error when processed by a corresponding program; in response to determining that the arbitrarily selected data segment can be altered, arbitrarily altering the data segment in the at least one portion of the electronic document to produce an altered electronic document; and determining whether the corresponding program produces an error state when the altered electronic document is processed by the corresponding program.

Methods, media, and systems for detecting attack on a digital processing device

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

Stolfo, Salvatore J.; Li, Wei-Jen; Keromytis, Angelos D.

Methods, media, and systems for detecting attack are provided. In some embodiments, the methods include: comparing at least part of a document to a static detection model; determining whether attacking code is included in the document based on the comparison of the document to the static detection model; executing at least part of the document; determining whether attacking code is included in the document based on the execution of the at least part of the document; and if attacking code is determined to be included in the document based on at least one of the comparison of the document tomore » the static detection model and the execution of the at least part of the document, reporting the presence of an attack. In some embodiments, the methods include: selecting a data segment in at least one portion of an electronic document; determining whether the arbitrarily selected data segment can be altered without causing the electronic document to result in an error when processed by a corresponding program; in response to determining that the arbitrarily selected data segment can be altered, arbitrarily altering the data segment in the at least one portion of the electronic document to produce an altered electronic document; and determining whether the corresponding program produces an error state when the altered electronic document is processed by the corresponding program.« less

Feasibility of quantitative diffuse reflectance spectroscopy for targeted measurement of renal ischemia during laparoscopic partial nephrectomy.

PubMed

Goel, Utsav O; Maddox, Michael M; Elfer, Katherine N; Dorsey, Philip J; Wang, Mei; McCaslin, Ian Ross; Brown, J Quincy; Lee, Benjamin R

2014-01-01

Reduction of warm ischemia time during partial nephrectomy (PN) is critical to minimizing ischemic damage and improving postoperative kidney function, while maintaining tumor resection efficacy. Recently, methods for localizing the effects of warm ischemia to the region of the tumor via selective clamping of higher-order segmental artery branches have been shown to have superior outcomes compared with clamping the main renal artery. However, artery identification can prolong operative time and increase the blood loss and reduce the positive effects of selective ischemia. Quantitative diffuse reflectance spectroscopy (DRS) can provide a convenient, real-time means to aid in artery identification during laparoscopic PN. The feasibility of quantitative DRS for real-time longitudinal measurement of tissue perfusion and vascular oxygenation in laparoscopic nephrectomy was investigated in vivo in six Yorkshire swine kidneys (n=three animals ). DRS allowed for rapid identification of ischemic areas after selective vessel occlusion. In addition, the rates of ischemia induction and recovery were compared for main renal artery versus tertiary segmental artery occlusion, and it was found that the tertiary segmental artery occlusion trends toward faster recovery after ischemia, which suggests a potential benefit of selective ischemia. Quantitative DRS could provide a convenient and fast tool for artery identification and evaluation of the depth, spatial extent, and duration of selective tissue ischemia in laparoscopic PN.

Feasibility of quantitative diffuse reflectance spectroscopy for targeted measurement of renal ischemia during laparoscopic partial nephrectomy

NASA Astrophysics Data System (ADS)

Goel, Utsav O.; Maddox, Michael M.; Elfer, Katherine N.; Dorsey, Philip J.; Wang, Mei; McCaslin, Ian Ross; Brown, J. Quincy; Lee, Benjamin R.

2014-10-01

Reduction of warm ischemia time during partial nephrectomy (PN) is critical to minimizing ischemic damage and improving postoperative kidney function, while maintaining tumor resection efficacy. Recently, methods for localizing the effects of warm ischemia to the region of the tumor via selective clamping of higher-order segmental artery branches have been shown to have superior outcomes compared with clamping the main renal artery. However, artery identification can prolong operative time and increase the blood loss and reduce the positive effects of selective ischemia. Quantitative diffuse reflectance spectroscopy (DRS) can provide a convenient, real-time means to aid in artery identification during laparoscopic PN. The feasibility of quantitative DRS for real-time longitudinal measurement of tissue perfusion and vascular oxygenation in laparoscopic nephrectomy was investigated in vivo in six Yorkshire swine kidneys (n=three animals). DRS allowed for rapid identification of ischemic areas after selective vessel occlusion. In addition, the rates of ischemia induction and recovery were compared for main renal artery versus tertiary segmental artery occlusion, and it was found that the tertiary segmental artery occlusion trends toward faster recovery after ischemia, which suggests a potential benefit of selective ischemia. Quantitative DRS could provide a convenient and fast tool for artery identification and evaluation of the depth, spatial extent, and duration of selective tissue ischemia in laparoscopic PN.

Structure and Neotectonics of the Southern Chile Forearc 35°S - 40°S

NASA Astrophysics Data System (ADS)

Geersen, Jacob; Völker, David; Weinrebe, Wilhelm; Krastel-Gudegast, Sebastian; Behrmann, Jan H.

2010-05-01

The Southern Chile Forearc exhibits an extreme level of neotectonic deformation. On-land studies have documented a pronounced segmentation in the region 36°S - 41°S. However, information on the seaward continuation of the individual segments towards the Chile Trench is rare, as direct observations end at the coastline and are replaced by a less dense set of marine geophysical data. In this study we use swath bathymetric data combined with high and low-frequency reflection seismic data as well as results from heat-flow measurements to: (A) map and identify active deformation structures and investigate their spatial distribution, and (B) analyse the factors controlling segmentation along the Southern Chile Forearc. Considering the region 35°S to 40°S we found evidence for a division into four major segments; Concepcion North, Concepcion South, Nahuelbuta, and Tolten (from North to South). Within all four segments, the lower continental slope is dissected by distinct margin-parallel thrust ridges overlying active landward-dipping thrust faults, indicating the presence of an active accretionary prism. The middle and upper slope, however, shows major differences between the four segments. The Concepcion North Segment is dominated by a large margin-parallel thrust ridge. The Concepcion South Segment shows large up to 600 m high north-south aligned normal fault scarps highlighting east-west extension. The change from thrust to normal faulting domains is accompanied by a drastic decrease in surface heat-flow by a factor of up to four. Further south in the Nahuelbuta Segment, east-west trending active thrust ridges indicate north-south compression of this part of the forearc. Shortening in this segment is not only limited to the middle and upper slope, but includes the entire marine forearc and occurs perpendicular to the direction of plate convergence. In the southernmost Tolten Segment the middle and upper continental slope shows no signs of compressive or extensional deformation. For the factors controlling segmentation our data suggest that when considering the whole forearc variations in the overriding plate such as the position of continental fault zones are responsible for the large scale tectonic segmentation. The east-west oriented shortening structures in the Nahuelbuta Segment (perpendicular to the direction of plate motion) probably originate from the collision of the Chiloe Microplate with a marine buttress situated below the Concepcion South Segment. The Chiloe Microplate represents a 1000 km-sized forearc sliver, which is kinematically decoupled from stable South America along the Liquine-Ofqui and Lanalhue Fault Zones. The important transition from wholesale forearc compression to extension observed between the two Concepcion segments, however, is more likely related to plate boundary processes, i.e. different degrees of coupling and/or friction in the plate boundary itself.

A medical imaging analysis system for trigger finger using an adaptive texture-based active shape model (ATASM) in ultrasound images

PubMed Central

Chuang, Bo-I; Kuo, Li-Chieh; Yang, Tai-Hua; Su, Fong-Chin; Jou, I-Ming; Lin, Wei-Jr; Sun, Yung-Nien

2017-01-01

Trigger finger has become a prevalent disease that greatly affects occupational activity and daily life. Ultrasound imaging is commonly used for the clinical diagnosis of trigger finger severity. Due to image property variations, traditional methods cannot effectively segment the finger joint’s tendon structure. In this study, an adaptive texture-based active shape model method is used for segmenting the tendon and synovial sheath. Adapted weights are applied in the segmentation process to adjust the contribution of energy terms depending on image characteristics at different positions. The pathology is then determined according to the wavelet and co-occurrence texture features of the segmented tendon area. In the experiments, the segmentation results have fewer errors, with respect to the ground truth, than contours drawn by regular users. The mean values of the absolute segmentation difference of the tendon and synovial sheath are 3.14 and 4.54 pixels, respectively. The average accuracy of pathological determination is 87.14%. The segmentation results are all acceptable in data of both clear and fuzzy boundary cases in 74 images. And the symptom classifications of 42 cases are also a good reference for diagnosis according to the expert clinicians’ opinions. PMID:29077737

SU-E-J-110: A Novel Level Set Active Contour Algorithm for Multimodality Joint Segmentation/Registration Using the Jensen-Rényi Divergence.

PubMed

Markel, D; Naqa, I El; Freeman, C; Vallières, M

2012-06-01

To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. It was found that JR divergence when used for segmentation has an improved robustness to noise compared to using mutual information, or other entropy-based metrics. The MI metric failed at around 2/3 the noise power than the JR divergence. The JR divergence metric is useful for the task of joint segmentation/registration of multimodality images and shows improved results compared entropy based metric. The algorithm can be easily modified to incorporate non-intensity based images, which would allow applications into multi-modality and texture analysis. © 2012 American Association of Physicists in Medicine.

Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

NASA Astrophysics Data System (ADS)

Polan, Daniel F.; Brady, Samuel L.; Kaufman, Robert A.

2016-09-01

There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 n , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21 patient image sections, were analyzed. The automated algorithm produced segmentation of seven material classes with a median DSC of 0.86  ±  0.03 for pediatric patient protocols, and 0.85  ±  0.04 for adult patient protocols. Additionally, 100 randomly selected patient examinations were segmented and analyzed, and a mean sensitivity of 0.91 (range: 0.82-0.98), specificity of 0.89 (range: 0.70-0.98), and accuracy of 0.90 (range: 0.76-0.98) were demonstrated. In this study, we demonstrate that this fully automated segmentation tool was able to produce fast and accurate segmentation of the neck and trunk of the body over a wide range of patient habitus and scan parameters.

Efficient globally optimal segmentation of cells in fluorescence microscopy images using level sets and convex energy functionals.

PubMed

Bergeest, Jan-Philip; Rohr, Karl

2012-10-01

In high-throughput applications, accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression and the understanding of cell function. We propose an approach for segmenting cell nuclei which is based on active contours using level sets and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We consider three different well-known energy functionals for active contour-based segmentation and introduce convex formulations of these functionals. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images from different experiments comprising different cell types. We have also performed a quantitative comparison with previous segmentation approaches. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimum location of external markers using feature selection algorithms for real‐time tumor tracking in external‐beam radiotherapy: a virtual phantom study

PubMed Central

Nankali, Saber; Miandoab, Payam Samadi; Baghizadeh, Amin

2016-01-01

In external‐beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation‐based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two “Genetic” and “Ranker” searching procedures. The performance of these algorithms has been evaluated using four‐dimensional extended cardiac‐torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro‐fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F‐test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation‐based feature selection algorithm, in combination with a genetic search algorithm, proved to yield best performance accuracy for selecting optimum markers. PACS numbers: 87.55.km, 87.56.Fc PMID:26894358

Optimum location of external markers using feature selection algorithms for real-time tumor tracking in external-beam radiotherapy: a virtual phantom study.

PubMed

Nankali, Saber; Torshabi, Ahmad Esmaili; Miandoab, Payam Samadi; Baghizadeh, Amin

2016-01-08

In external-beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation-based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two "Genetic" and "Ranker" searching procedures. The performance of these algorithms has been evaluated using four-dimensional extended cardiac-torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro-fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F-test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation-based feature selection algorithm, in combination with a genetic search algorithm, proved to yield best performance accuracy for selecting optimum markers.

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.

Method of fabricating a prestressed cast iron vessel

DOEpatents

Lampe, Robert F.

1982-01-01

A method of fabricating a prestressed cast iron vessel wherein double wall cast iron body segments each have an arcuate inner wall and a spaced apart substantially parallel outer wall with a plurality of radially extending webs interconnecting the inner wall and the outer wall, the bottom surface and the two exposed radial side surfaces of each body segment are machined and eight body segments are formed into a ring. The top surfaces and outer surfaces of the outer walls are machined and keyways are provided across the juncture of adjacent end walls of the body segments. A liner segment complementary in shape to a selected inner wall of one of the body segments is mounted to each of the body segments and again formed into a ring. The liner segments of each ring are welded to form unitary liner rings and thereafter the cast iron body segments are prestressed to complete the ring assembly. Ring assemblies are stacked to form the vessel and adjacent unitary liner rings are welded. A top head covers the top ring assembly to close the vessel and axially extending tendons retain the top and bottom heads in place under pressure.

A-FABP and oxidative stress underlie the impairment of endothelium-dependent relaxations to serotonin and the intima-medial thickening in the porcine coronary artery with regenerated endothelium.

PubMed

Chan, Calvin K; Zhao, Yingzi; Liao, Song Yan; Zhang, Yue Lin; Lee, Mary Y K; Xu, Aimin; Tse, Hung Fat; Vanhoutte, Paul M

2013-01-16

Experiments were designed to determine the cause of the selective dysfunction of G(i) proteins, characterized by a reduced endothelium-dependent relaxation to serotonin (5-hydroxytryptamine), in coronary arteries lined with regenerated endothelial cells. Part of the endothelium of the left anterior descending coronary artery of female pigs was removed in vivo to induce regeneration. The animals were treated chronically with vehicle (control), apocynin (antioxidant), or BMS309403 (A-FABP inhibitor) for 28 days before functional examination and histological analysis of segments of coronary arteries with native or regenerated endothelium of the same hearts. Isometric tension was recorded in organ chambers and cumulative concentration-relaxation curves obtained in response to endothelium-dependent [serotonin (G(i) protein mediated activation of eNOS) and bradykinin (G(q) protein mediated activation of eNOS)] and independent [detaNONOate (cGMP-mediated), isoproterenol (cAMP-mediated)] vasodilators. The two inhibitors tested did not acutely affect relaxations of preparations with either native or regenerated endothelium. In the chronically treated groups, however, both apocynin and BMS309403 abolished the reduction in relaxation to serotonin in segments covered with regenerated endothelium and prevented the intima-medial thickening caused by endothelial regeneration, without affecting responses to bradykinin or endothelium-independent agonists (detaNONOate and isoproterenol). Thus, inhibition of either oxidative stress or A-FABP likely prevents both the selective dysfunction of G(i) protein mediated relaxation to serotonin and the neointimal thickening resulting from endothelial regeneration.

Mechanistic Peptidomics: Factors That Dictate Specificity in the Formation of Endogenous Peptides in Human Milk*

PubMed Central

Guerrero, Andres; Dallas, David C.; Contreras, Stephanie; Chee, Sabrina; Parker, Evan A.; Sun, Xin; Dimapasoc, Lauren; Barile, Daniela; German, J. Bruce; Lebrilla, Carlito B.

2014-01-01

An extensive mass spectrometry analysis of the human milk peptidome has revealed almost 700 endogenous peptides from 30 different proteins. Two in-house computational tools were created and used to visualize and interpret the data through both alignment of the peptide quasi-molecular ion intensities and estimation of the differential enzyme participation. These results reveal that the endogenous proteolytic activity in the mammary gland is remarkably specific and well conserved. Certain proteins—not necessarily the most abundant ones—are digested by the proteases present in milk, yielding endogenous peptides from selected regions. Our results strongly suggest that factors such as the presence of specific proteases, the position and concentration of cleavage sites, and, more important, the intrinsic disorder of segments of the protein drive this proteolytic specificity in the mammary gland. As a consequence of this selective hydrolysis, proteins that typically need to be cleaved at specific positions in order to exert their activity are properly digested, and bioactive peptides encoded in certain protein sequences are released. Proteins that must remain intact in order to maintain their activity in the mammary gland or in the neonatal gastrointestinal tract are unaffected by the hydrolytic environment present in milk. These results provide insight into the intrinsic structural mechanisms that facilitate the selectivity of the endogenous milk protease activity and might be useful to those studying the peptidomes of other biofluids. PMID:25172956

Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection.

PubMed

Zhuang, Xiahai; Bai, Wenjia; Song, Jingjing; Zhan, Songhua; Qian, Xiaohua; Shi, Wenzhe; Lian, Yanyun; Rueckert, Daniel

2015-07-01

Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors' proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve with higher WHS Dice scores compared to the conventional schemes (p < 0.03). In the atlas database study, the authors showed that the MAS using larger atlas databases generated better performance curves than the MAS using smaller ones, indicating larger atlas databases could produce more accurate segmentation. The authors have developed a new MAS framework for automatic WHS of CTA and investigated alternative implementations of MAS. With the proposed atlas ranking algorithm and joint label fusion, the MAS scheme is able to generate accurate segmentation within practically acceptable computation time. This method can be useful for the development of new clinical applications of cardiac CT.

Dance Class Structure Affects Youth Physical Activity and Sedentary Behavior: A Study of Seven Dance Types.

PubMed

Lopez Castillo, Maria A; Carlson, Jordan A; Cain, Kelli L; Bonilla, Edith A; Chuang, Emmeline; Elder, John P; Sallis, James F

2015-01-01

The study aims were to determine: (a) how class structure varies by dance type, (b) how moderate-to-vigorous physical activity (MVPA) and sedentary behavior vary by dance class segments, and (c) how class structure relates to total MVPA in dance classes. Participants were 291 boys and girls ages 5 to 18 years old enrolled in 58 dance classes at 21 dance studios in Southern California. MVPA and sedentary behavior were assessed with accelerometry, with data aggregated to 15-s epochs. Percent and minutes of MVPA and sedentary behavior during dance class segments and percent of class time and minutes spent in each segment were calculated using Freedson age-specific cut points. Differences in MVPA (Freedson 3 Metabolic Equivalents of Tasks age-specific cut points) and sedentary behavior ( < 100 counts/min) were examined using mixed-effects linear regression. The length of each class segment was fairly consistent across dance types, with the exception that in ballet, more time was spent in technique as compared with private jazz/hip-hop classes and Latin-flamenco and less time was spent in routine/practice as compared with Latin-salsa/ballet folklorico. Segment type accounted for 17% of the variance in the proportion of the segment spent in MVPA. The proportion of the segment in MVPA was higher for routine/practice (44.2%) than for technique (34.7%). The proportion of the segment in sedentary behavior was lowest for routine/practice (22.8%). The structure of dance lessons can impact youths' physical activity. Working with instructors to increase time in routine/practice during dance classes could contribute to physical activity promotion in youth.

Body Segment Kinematics and Energy Expenditure in Active Videogames.

PubMed

Böhm, Birgit; Hartmann, Michael; Böhm, Harald

2016-06-01

Energy expenditure (EE) in active videogames (AVGs) is a component for assessing its benefit for cardiovascular health. Existing evidence suggests that AVGs are able to increase EE above rest and when compared with playing passive videogames. However, the association between body movement and EE remains unclear. Furthermore, for goal-directed game design, it is important to know the contribution of body segments to EE. This knowledge will help to acquire a certain level of exercise intensity during active gaming. Therefore, the purpose of this study was to determine the best predictors of EE from body segment energies, acceleration, and heart rate during different game situations. EE and body segment movement of 17 subjects, aged 22.1 ± 2.5 years, were measured in two different AVGs. In randomized order, the subjects played a handheld-controlled Nintendo(®) Wii™ tennis (NWT) game and a whole body-controlled Sony EyeToy(®) waterfall (ETW) game. Body segment movement was analyzed using a three-dimensional motion capture system. From the video data, mean values of mechanical energy change and acceleration of 10 body segments were analyzed. Measured EE was significantly higher in ETW (7.8 ± 1.4 metabolic equivalents [METs]) than in NWT (3.4 ± 1.0 METs). The best prediction parameter for the more intense ETW game was the energy change of the right thigh and for the less intense hand-controlled NWT game was the energy change of the upper torso. Segment acceleration was less accurate in predicting EE. The best predictors of metabolic EE were the thighs and the upper torso in whole body and handheld-controlled games, respectively. Increasing movement of these body segments would lead to higher physical activity intensity during gaming, reducing sedentary behavior.

Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease

PubMed Central

Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B.; Torres, Vicente E.; Yu, Alan S.L.; Mrug, Michal; Bennett, William M.; Flessner, Michael F.; Landsittel, Doug P.

2016-01-01

Background and objectives Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Design, setting, participants, & measurements Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2–weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Results Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable. Conclusions We have developed a fully automated method for segmentation of kidneys from abdominal magnetic resonance images in patients with autosomal dominant polycystic kidney disease with varying kidney volumes. The performance of the automated method was in good agreement with that of manual method. PMID:26797708

Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease.

PubMed

Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B; Torres, Vicente E; Yu, Alan S L; Mrug, Michal; Bennett, William M; Flessner, Michael F; Landsittel, Doug P; Bae, Kyongtae T

2016-04-07

Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2-weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable. We have developed a fully automated method for segmentation of kidneys from abdominal magnetic resonance images in patients with autosomal dominant polycystic kidney disease with varying kidney volumes. The performance of the automated method was in good agreement with that of manual method. Copyright © 2016 by the American Society of Nephrology.

A novel content-based active contour model for brain tumor segmentation.

PubMed

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2012-06-01

Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the performance of intensity-based techniques for homogeneous tumors on brain magnetic resonance (MR) images. The analysis shows that the state-of-art methods fail to segment homogeneous tumors against similar background or when these tumors show partial diversity toward the background. They also have preconvergence problem in case of false edges/saddle points. However, the presence of weak edges and diffused edges (due to edema around the tumor) leads to oversegmentation by intensity-based techniques. Therefore, the proposed method content-based active contour (CBAC) uses both intensity and texture information present within the active contour to overcome above-stated problems capturing large range in an image. It also proposes a novel use of Gray-Level Co-occurrence Matrix to define texture space for tumor segmentation. The effectiveness of this method is tested on two different real data sets (55 patients - more than 600 images) containing five different types of homogeneous, heterogeneous, diffused tumors and synthetic images (non-MR benchmark images). Remarkable results are obtained in segmenting homogeneous tumors of uniform intensity, complex content heterogeneous, diffused tumors on MR images (T1-weighted, postcontrast T1-weighted and T2-weighted) and synthetic images (non-MR benchmark images of varying intensity, texture, noise content and false edges). Further, tumor volume is efficiently extracted from 2-dimensional slices and is named as 2.5-dimensional segmentation. Copyright © 2012 Elsevier Inc. All rights reserved.

The respective contribution of lumbar segments to the generation of locomotion in the isolated spinal cord of newborn rat.

PubMed

Bertrand, S; Cazalets, Jean-René

2002-11-01

Various studies on isolated neonatal rat spinal cord have pointed to the predominant role played by the rostral lumbar area in the generation of locomotor activity. In the present study, the role of the various regions of the lumbar spinal cord in locomotor genesis was further examined using compartmentalization and transections of the cord. We report that the synaptic drive received by caudal motoneurons following N-methyl-d-l-aspartate (NMA)/5-HT superfusion on the entire lumbar cord is different from that triggered by the same compounds specifically applied on the rostral segments. These differences appear to be due to the direct action of NMA/5-HT on motoneuron membrane potential, rather than on premotoneuronal input activation. In order to assess the possible participation of the caudal lumbar segments in locomotor rhythm generation, the segments were over-stimulated with high concentrations of NMA or K+. We find that significant variations in motor cycle period occurred during the over-activation of the rostral segments. Over-activation of caudal segments only si+gnificantly increased the caudal ventral roots burst amplitude. We find that low 5-HT concentrations were unable to induce fictive locomotion under our experimental conditions. When a hemi-transection of the cord was performed between the L2-L3 segments, rhythmic bursting in the ipsilateral L5 disappeared while rhythmicity persisted on the contralateral side. Sectioning of the remaining L2-L3 side totally suppressed rhythmic activity in both L5 ventral roots. These results show that the thoracolumbar part of the cord constitutes the key area for locomotor pattern generation.

WE-E-213CD-08: A Novel Level Set Active Contour Algorithm Using the Jensen-Renyi Divergence for Tumor Segmentation in PET.

PubMed

Markel, D; Naqa, I El

2012-06-01

Positron emission tomography (PET) presents a valuable resource for delineating the biological tumor volume (BTV) for image-guided radiotherapy. However, accurate and consistent image segmentation is a significant challenge within the context of PET, owing to its low spatial resolution and high levels of noise. Active contour methods based on the level set methods can be sensitive to noise and susceptible to failing in low contrast regions. Therefore, this work evaluates a novel active contour algorithm applied to the task of PET tumor segmentation. A novel active contour segmentation algorithm based on maximizing the Jensen-Renyi Divergence between regions of interest was applied to the task of segmenting lesions in 7 patients with T3-T4 pharyngolaryngeal squamous cell carcinoma. The algorithm was implemented on an NVidia GEFORCE GTV 560M GPU. The cases were taken from the Louvain database, which includes contours of the macroscopically defined BTV drawn using histology of resected tissue. The images were pre-processed using denoising/deconvolution. The segmented volumes agreed well with the macroscopic contours, with an average concordance index and classification error of 0.6 ± 0.09 and 55 ± 16.5%, respectively. The algorithm in its present implementation requires approximately 0.5-1.3 sec per iteration and can reach convergence within 10-30 iterations. The Jensen-Renyi active contour method was shown to come close to and in terms of concordance, outperforms a variety of PET segmentation methods that have been previously evaluated using the same data. Further evaluation on a larger dataset along with performance optimization is necessary before clinical deployment. © 2012 American Association of Physicists in Medicine.

Shape-driven 3D segmentation using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2006-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details.

Active Contours Driven by Multi-Feature Gaussian Distribution Fitting Energy with Application to Vessel Segmentation.

PubMed

Wang, Lei; Zhang, Huimao; He, Kan; Chang, Yan; Yang, Xiaodong

2015-01-01

Active contour models are of great importance for image segmentation and can extract smooth and closed boundary contours of the desired objects with promising results. However, they cannot work well in the presence of intensity inhomogeneity. Hence, a novel region-based active contour model is proposed by taking image intensities and 'vesselness values' from local phase-based vesselness enhancement into account simultaneously to define a novel multi-feature Gaussian distribution fitting energy in this paper. This energy is then incorporated into a level set formulation with a regularization term for accurate segmentations. Experimental results based on publicly available STructured Analysis of the Retina (STARE) demonstrate our model is more accurate than some existing typical methods and can successfully segment most small vessels with varying width.

Lactoferricin-related peptides with inhibitory effects on ACE-dependent vasoconstriction.

PubMed

Centeno, José M; Burguete, María C; Castelló-Ruiz, María; Enrique, María; Vallés, Salvador; Salom, Juan B; Torregrosa, Germán; Marcos, José F; Alborch, Enrique; Manzanares, Paloma

2006-07-26

A selection of lactoferricin B (LfcinB)-related peptides with an angiotensin I-converting enzyme (ACE) inhibitory effect have been examined using in vitro and ex vivo functional assays. Peptides that were analyzed included a set of sequence-related antimicrobial hexapeptides previously reported and two representative LfcinB-derived peptides. In vitro assays using hippuryl-L-histidyl-L-leucine (HHL) and angiotensin I as substrates allowed us to select two hexapeptides, PACEI32 (Ac-RKWHFW-NH2) and PACEI34 (Ac-RKWLFW-NH2), and also a LfcinB-derived peptide, LfcinB17-31 (Ac-FKCRRWQWRMKKLGA-NH2). Ex vivo functional assays using rabbit carotid arterial segments showed PACEI32 (both D- and L-enantiomers) and LfcinB17-31 have inhibitory effects on ACE-dependent angiotensin I-induced contraction. None of the peptides exhibited in vitro ACE inhibitory activity using bradykinin as the substrate. In conclusion, three bioactive lactoferricin-related peptides exhibit inhibitory effects on both ACE activity and ACE-dependent vasoconstriction with potential to modulate hypertension that deserves further investigation.

Quartz ball valve

NASA Technical Reports Server (NTRS)

Goetz, C.; Ingle, W. M. (Inventor)

1980-01-01

A ball valve particularly suited for use in the handling of highly corrosive fluids is described. It is characterized by a valve housing formed of communicating segments of quartz tubing, a pair of communicating sockets disposed in coaxial alignment with selected segments of tubing for establishing a pair of inlet ports communicating with a common outlet port, a ball formed of quartz material supported for displacement between the sockets and configured to be received alternately thereby, and a valve actuator including a rod attached to the ball for selectively displacing the ball relative to each of the sockets for controlling fluid flow through the inlet ports.

Influenza Virus PB1 and Neuraminidase Gene Segments Can Cosegregate during Vaccine Reassortment Driven by Interactions in the PB1 Coding Region

PubMed Central

Cobbin, Joanna C. A.; Ong, Chi; Verity, Erin; Gilbertson, Brad P.; Rockman, Steven P.

2014-01-01

ABSTRACT Egg-grown influenza vaccine yields are maximized by infection with a seed virus produced by “classical reassortment” of a seasonal isolate with a highly egg-adapted strain. Seed viruses are selected based on a high-growth phenotype and the presence of the seasonal hemagglutinin (HA) and neuraminidase (NA) surface antigens. Retrospective analysis of H3N2 vaccine seed viruses indicated that, unlike other internal proteins that were predominantly derived from the high-growth parent A/Puerto Rico/8/34 (PR8), the polymerase subunit PB1 could be derived from either parent depending on the seasonal strain. We have recently shown that A/Udorn/307/72 (Udorn) models a seasonal isolate that yields reassortants bearing the seasonal PB1 gene. This is despite the fact that the reverse genetics-derived virus that includes Udorn PB1 with Udorn HA and NA on a PR8 background has inferior growth compared to the corresponding virus with PR8 PB1. Here we use competitive plasmid transfections to investigate the mechanisms driving selection of a less fit virus and show that the Udorn PB1 gene segment cosegregates with the Udorn NA gene segment. Analysis of chimeric PB1 genes revealed that the coselection of NA and PB1 segments was not directed through the previously identified packaging sequences but through interactions involving the internal coding region of the PB1 gene. This study identifies associations between viral genes that can direct selection in classical reassortment for vaccine production and which may also be of relevance to the gene constellations observed in past antigenic shift events where creation of a pandemic virus has involved reassortment. IMPORTANCE Influenza vaccine must be produced and administered in a timely manner in order to provide protection during the winter season, and poor-growing vaccine seed viruses can compromise this process. To maximize vaccine yields, manufacturers create hybrid influenza viruses with gene segments encoding the surface antigens from a seasonal virus isolate, important for immunity, and others from a virus with high growth properties. This involves coinfection of cells with both parent viruses and selection of dominant progeny bearing the seasonal antigens. We show that this method of creating hybrid viruses does not necessarily select for the best yielding virus because preferential pairing of gene segments when progeny viruses are produced determines the genetic makeup of the hybrids. This not only has implications for how hybrid viruses are selected for vaccine production but also sheds light on what drives and limits hybrid gene combinations that arise in nature, leading to pandemics. PMID:24872588

Influenza virus PB1 and neuraminidase gene segments can cosegregate during vaccine reassortment driven by interactions in the PB1 coding region.

PubMed

Cobbin, Joanna C A; Ong, Chi; Verity, Erin; Gilbertson, Brad P; Rockman, Steven P; Brown, Lorena E

2014-08-01

Egg-grown influenza vaccine yields are maximized by infection with a seed virus produced by "classical reassortment" of a seasonal isolate with a highly egg-adapted strain. Seed viruses are selected based on a high-growth phenotype and the presence of the seasonal hemagglutinin (HA) and neuraminidase (NA) surface antigens. Retrospective analysis of H3N2 vaccine seed viruses indicated that, unlike other internal proteins that were predominantly derived from the high-growth parent A/Puerto Rico/8/34 (PR8), the polymerase subunit PB1 could be derived from either parent depending on the seasonal strain. We have recently shown that A/Udorn/307/72 (Udorn) models a seasonal isolate that yields reassortants bearing the seasonal PB1 gene. This is despite the fact that the reverse genetics-derived virus that includes Udorn PB1 with Udorn HA and NA on a PR8 background has inferior growth compared to the corresponding virus with PR8 PB1. Here we use competitive plasmid transfections to investigate the mechanisms driving selection of a less fit virus and show that the Udorn PB1 gene segment cosegregates with the Udorn NA gene segment. Analysis of chimeric PB1 genes revealed that the coselection of NA and PB1 segments was not directed through the previously identified packaging sequences but through interactions involving the internal coding region of the PB1 gene. This study identifies associations between viral genes that can direct selection in classical reassortment for vaccine production and which may also be of relevance to the gene constellations observed in past antigenic shift events where creation of a pandemic virus has involved reassortment. Influenza vaccine must be produced and administered in a timely manner in order to provide protection during the winter season, and poor-growing vaccine seed viruses can compromise this process. To maximize vaccine yields, manufacturers create hybrid influenza viruses with gene segments encoding the surface antigens from a seasonal virus isolate, important for immunity, and others from a virus with high growth properties. This involves coinfection of cells with both parent viruses and selection of dominant progeny bearing the seasonal antigens. We show that this method of creating hybrid viruses does not necessarily select for the best yielding virus because preferential pairing of gene segments when progeny viruses are produced determines the genetic makeup of the hybrids. This not only has implications for how hybrid viruses are selected for vaccine production but also sheds light on what drives and limits hybrid gene combinations that arise in nature, leading to pandemics. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

A hybrid approach of using symmetry technique for brain tumor segmentation.

PubMed

Saddique, Mubbashar; Kazmi, Jawad Haider; Qureshi, Kalim

2014-01-01

Tumor and related abnormalities are a major cause of disability and death worldwide. Magnetic resonance imaging (MRI) is a superior modality due to its noninvasiveness and high quality images of both the soft tissues and bones. In this paper we present two hybrid segmentation techniques and their results are compared with well-recognized techniques in this area. The first technique is based on symmetry and we call it a hybrid algorithm using symmetry and active contour (HASA). In HASA, we take refection image, calculate the difference image, and then apply the active contour on the difference image to segment the tumor. To avoid unimportant segmented regions, we improve the results by proposing an enhancement in the form of the second technique, EHASA. In EHASA, we also take reflection of the original image, calculate the difference image, and then change this image into a binary image. This binary image is mapped onto the original image followed by the application of active contouring to segment the tumor region.

Semi-automatic central-chest lymph-node definition from 3D MDCT images

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Higgins, William E.

2010-03-01

Central-chest lymph nodes play a vital role in lung-cancer staging. The three-dimensional (3D) definition of lymph nodes from multidetector computed-tomography (MDCT) images, however, remains an open problem. This is because of the limitations in the MDCT imaging of soft-tissue structures and the complicated phenomena that influence the appearance of a lymph node in an MDCT image. In the past, we have made significant efforts toward developing (1) live-wire-based segmentation methods for defining 2D and 3D chest structures and (2) a computer-based system for automatic definition and interactive visualization of the Mountain central-chest lymph-node stations. Based on these works, we propose new single-click and single-section live-wire methods for segmenting central-chest lymph nodes. The single-click live wire only requires the user to select an object pixel on one 2D MDCT section and is designed for typical lymph nodes. The single-section live wire requires the user to process one selected 2D section using standard 2D live wire, but it is more robust. We applied these methods to the segmentation of 20 lymph nodes from two human MDCT chest scans (10 per scan) drawn from our ground-truth database. The single-click live wire segmented 75% of the selected nodes successfully and reproducibly, while the success rate for the single-section live wire was 85%. We are able to segment the remaining nodes, using our previously derived (but more interaction intense) 2D live-wire method incorporated in our lymph-node analysis system. Both proposed methods are reliable and applicable to a wide range of pulmonary lymph nodes.

Adaptive evolution during the establishment of European avian-like H1N1 influenza A virus in swine.

PubMed

Joseph, Udayan; Vijaykrishna, Dhanasekaran; Smith, Gavin J D; Su, Yvonne C F

2018-04-01

An H1N1 subtype influenza A virus with all eight gene segments derived from wild birds (including mallards), ducks and chickens, caused severe disease outbreaks in swine populations in Europe beginning in 1979 and successfully adapted to form the European avian-like swine (EA-swine) influenza lineage. Genes of the EA-swine lineage that are clearly segregated from its closest avian relatives continue to circulate in swine populations globally and represent a unique opportunity to study the adaptive process of an avian-to-mammalian cross-species transmission. Here, we used a relaxed molecular clock model to test whether the EA-swine virus originated through the introduction of a single avian ancestor as an entire genome, followed by an analysis of host-specific selection pressures among different gene segments. Our data indicated independent introduction of gene segments via transmission of avian viruses into swine followed by reassortment events that occurred at least 1-4 years prior to the EA-swine outbreak. All EA-swine gene segments exhibit greater selection pressure than avian viruses, reflecting both adaptive pressures and relaxed selective constraints that are associated with host switching. Notably, we identified key amino acid mutations in the viral surface proteins (H1 and N1) that play a role in adaptation to new hosts. Following the establishment of EA-swine lineage, we observed an increased frequency of intrasubtype reassortment of segments compared to the earlier strains that has been associated with adaptive amino acid replacements, disease severity and vaccine escape. Taken together, our study provides key insights into the adaptive changes in viral genomes following the transmission of avian influenza viruses to swine and the early establishment of the EA-swine lineage.

Gluteus Minimus and Gluteus Medius Muscle Activity During Common Rehabilitation Exercises in Healthy Postmenopausal Women.

PubMed

Ganderton, Charlotte; Pizzari, Tania; Cook, Jill; Semciw, Adam

2017-12-01

Study Design Controlled laboratory study, cross-sectional. Background The gluteus medius (GMed) and gluteus minimus (GMin) provide dynamic stability of the hip joint and pelvis. These muscles are susceptible to atrophy and injury in individuals during menopause, aging, and disease. Numerous studies have reported on the ability of exercises to elicit high levels of GMed activity; however, few studies have differentiated between the portions of the GMed, and none have examined the GMin. Objectives To quantify and rank the level of muscle activity of the 2 segments of the GMin (anterior and posterior fibers) and 3 segments of the GMed (anterior, middle, and posterior fibers) during 4 isometric and 3 dynamic exercises in a group of healthy, postmenopausal women. Methods Intramuscular electrodes were inserted into each segment of the GMed and GMin in 10 healthy, postmenopausal women. Participants completed 7 gluteal rehabilitation exercises, and average normalized muscle activity was used to rank the exercises from highest to lowest. Results The isometric standing hip hitch with contralateral hip swing was the highest-ranked exercise for all muscle segments except the anterior GMin, where it was ranked second. The highest-ranked dynamic exercise for all muscle segments was the dip test. Conclusion The hip hitch and its variations maximally activate the GMed and GMin muscle segments, and may be useful in hip muscle rehabilitation in postmenopausal women. J Orthop Sports Phys Ther 2017;47(12):914-922. Epub 15 Oct 2017. doi:10.2519/jospt.2017.7229.

Analysis of Phosphorylation of the Receptor-Like Protein Kinase HAESA during Arabidopsis Floral Abscission

PubMed Central

Taylor, Isaiah; Wang, Ying; Seitz, Kati; Baer, John; Bennewitz, Stefan; Mooney, Brian P.; Walker, John C.

2016-01-01

Receptor-like protein kinases (RLKs) are the largest family of plant transmembrane signaling proteins. Here we present functional analysis of HAESA, an RLK that regulates floral organ abscission in Arabidopsis. Through in vitro and in vivo analysis of HAE phosphorylation, we provide evidence that a conserved phosphorylation site on a region of the HAE protein kinase domain known as the activation segment positively regulates HAE activity. Additional analysis has identified another putative activation segment phosphorylation site common to multiple RLKs that potentially modulates HAE activity. Comparative analysis suggests that phosphorylation of this second activation segment residue is an RLK specific adaptation that may regulate protein kinase activity and substrate specificity. A growing number of RLKs have been shown to exhibit biologically relevant dual specificity toward serine/threonine and tyrosine residues, but the mechanisms underlying dual specificity of RLKs are not well understood. We show that a phospho-mimetic mutant of both HAE activation segment residues exhibits enhanced tyrosine auto-phosphorylation in vitro, indicating phosphorylation of this residue may contribute to dual specificity of HAE. These results add to an emerging framework for understanding the mechanisms and evolution of regulation of RLK activity and substrate specificity. PMID:26784444

Segment-specific expression of alkaline phosphatase in the Tubifex embryo requires DNA replication and mRNA synthesis.

PubMed

Kitamura, Kaoru; Shimizu, Takashi

2002-04-15

During embryogenesis of the oligochaete annelid Tubifex, segments VII and VIII specifically express mesodermal alkaline phosphatase (ALP) activity in the ventrolateral region. In this study, using specific inhibitors, we examined whether this segment-specific expression of ALP activity depends on DNA replication and RNA transcription. BrdU-incorporation experiments showed that presumptive ALP-expressing cells undergo the last round of DNA replication at 12-24 hr prior to emergence of ALP activity. When this DNA replication was inhibited by aphidicolin, ALP development was completely abrogated in the ventrolateral mesoderm. Similar inhibition of ALP development was also observed in alpha-amanitin-injected embryos. While injection of alpha-amanitin at 24 hr prior to the emergence of ALP activity exerted inhibitory effects on ALP development, injection at 14 hr was no longer effective. In contrast, ALP activity developed normally in cytochalasin-D-treated embryos in which cytokinesis was prevented from occurring for 36 hs prior to appearance of ALP activity. These results suggest that the segment-specific development of ALP activity in the Tubifex embryo depends on DNA replication and mRNA transcription, both of which occur long before the emergence of ALP activity. Copyright 2002 Wiley-Liss, Inc.

Modulation of δ-Aminolevulinic Acid Dehydratase Activity by the Sorbitol-Induced Osmotic Stress in Maize Leaf Segments.

PubMed

Jain, M; Tiwary, S; Gadre, R

2018-01-01

Osmotic stress induced with 1 M sorbitol inhibited δ-aminolevulinic acid dehydratase (ALAD) and aminolevulinic acid (ALA) synthesizing activities in etiolated maize leaf segments during greening; the ALAD activity was inhibited to a greater extent than the ALA synthesis. When the leaves were exposed to light, the ALAD activity increased for the first 8 h, followed by a decrease observed at 16 and 24 h in both sorbitol-treated and untreated leaf tissues. The maximum inhibition of the enzyme activity was observed in the leaf segments incubated with sorbitol for 4 to 8 h. Glutamate increased the ALAD activity in the in vitro enzymatic preparations obtained from the sorbitol-treated leaf segments; sorbitol inhibited the ALAD activity in the preparations from both sorbitol-treated and untreated leaves. It was suggested that sorbitol-induced osmotic stress inhibits the enzyme activity by affecting the ALAD induction during greening and regulating the ALAD steady-state level of ALAD in leaf cells. The protective effect of glutamate on ALAD in the preparations from the sorbitol-treated leaves might be due to its stimulatory effect on the enzyme.

Development of A Two-Stage Procedure for the Automatic Recognition of Dysfluencies in the Speech of Children Who Stutter: I. Psychometric Procedures Appropriate for Selection of Training Material for Lexical Dysfluency Classifiers

PubMed Central

Howell, Peter; Sackin, Stevie; Glenn, Kazan

2007-01-01

This program of work is intended to develop automatic recognition procedures to locate and assess stuttered dysfluencies. This and the following article together, develop and test recognizers for repetitions and prolongations. The automatic recognizers classify the speech in two stages: In the first, the speech is segmented and in the second the segments are categorized. The units that are segmented are words. Here assessments by human judges on the speech of 12 children who stutter are described using a corresponding procedure. The accuracy of word boundary placement across judges, categorization of the words as fluent, repetition or prolongation, and duration of the different fluency categories are reported. These measures allow reliable instances of repetitions and prolongations to be selected for training and assessing the recognizers in the subsequent paper. PMID:9328878

Generating Ground Reference Data for a Global Impervious Surface Survey

NASA Technical Reports Server (NTRS)

Tilton, James C.; De Colstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

We are developing an approach for generating ground reference data in support of a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. Since sufficient ground reference data for training and validation is not available from ground surveys, we are developing an interactive tool, called HSegLearn, to facilitate the photo-interpretation of 1 to 2 m spatial resolution imagery data, which we will use to generate the needed ground reference data at 30m. Through the submission of selected region objects and positive or negative examples of impervious surfaces, HSegLearn enables an analyst to automatically select groups of spectrally similar objects from a hierarchical set of image segmentations produced by the HSeg image segmentation program at an appropriate level of segmentation detail, and label these region objects as either impervious or nonimpervious.

A Binary Segmentation Approach for Boxing Ribosome Particles in Cryo EM Micrographs

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

Adiga, Umesh P.S.; Malladi, Ravi; Baxter, William

Three-dimensional reconstruction of ribosome particles from electron micrographs requires selection of many single-particle images. Roughly 100,000 particles are required to achieve approximately 10 angstrom resolution. Manual selection of particles, by visual observation of the micrographs on a computer screen, is recognized as a bottleneck in automated single particle reconstruction. This paper describes an efficient approach for automated boxing of ribosome particles in micrographs. Use of a fast, anisotropic non-linear reaction-diffusion method to pre-process micrographs and rank-leveling to enhance the contrast between particles and the background, followed by binary and morphological segmentation constitute the core of this technique. Modifying the shapemore » of the particles to facilitate segmentation of individual particles within clusters and boxing the isolated particles is successfully attempted. Tests on a limited number of micrographs have shown that over 80 percent success is achieved in automatic particle picking.« less

Low-Stroke Actuation for a Serial Robot

NASA Technical Reports Server (NTRS)

Ihrke, Chris A. (Inventor); Gao, Dalong (Inventor)

2014-01-01

A serial robot includes a base, first and second segments, a proximal joint joining the base to the first segment, and a distal joint. The distal joint that joins the segments is serially arranged and distal with respect to the proximal joint. The robot includes first and second actuators. A first tendon extends from the first actuator to the proximal joint and is selectively moveable via the first actuator. A second tendon extends from the second actuator to the distal joint and is selectively moveable via the second actuator. The robot includes a transmission having at least one gear element which assists rotation of the distal joint when an input force is applied to the proximal and/or distal joints by the first and/or second actuators. A robotic hand having the above robot is also disclosed, as is a robotic system having a torso, arm, and the above-described hand.

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.

MSuPDA: A memory efficient algorithm for sequence alignment.

PubMed

Khan, Mohammad Ibrahim; Kamal, Md Sarwar; Chowdhury, Linkon

2015-01-16

Space complexity is a million dollar question in DNA sequence alignments. In this regards, MSuPDA (Memory Saving under Pushdown Automata) can help to reduce the occupied spaces in computer memory. Our proposed process is that Anchor Seed (AS) will be selected from given data set of Nucleotides base pairs for local sequence alignment. Quick Splitting (QS) techniques will separate the Anchor Seed from all the DNA genome segments. Selected Anchor Seed will be placed to pushdown Automata's (PDA) input unit. Whole DNA genome segments will be placed into PDA's stack. Anchor Seed from input unit will be matched with the DNA genome segments from stack of PDA. Whatever matches, mismatches or Indel, of Nucleotides will be POP from the stack under the control of control unit of Pushdown Automata. During the POP operation on stack it will free the memory cell occupied by the Nucleotide base pair.

The association of sidewalk walkability and physical disorder with area-level race and poverty.

PubMed

Kelly, Cheryl M; Schootman, Mario; Baker, Elizabeth A; Barnidge, Ellen K; Lemes, Amanda

2007-11-01

There are significant differences in physical inactivity in various geographical areas and among demographic groups. Previous research suggests that walking is the most common form of physical activity; however, not all built environments support walking for recreational or transportation purposes. The purpose of this study was to assess the extent to which area-level factors, poverty rate and racial distribution, are associated with aspects of the street-scale environment (i.e. sidewalk walkability and physical disorder) using community audits. Street segments were randomly selected from 210 block groups. Pairs of trained auditors walked each street segment using an audit tool designed to capture aspects of the street environment. Multilevel logistic regression was used to assess the degree of neighborhood (i.e. block group) variation in sidewalk unevenness, sidewalk obstruction and the presence of physical disorder and the association with area-level characteristics. 1780 street segments were audited. Block groups that were predominantly African-American were 38 times more likely to have a lot of unevenness, 15 times more likely to have many obstructions, and 12 times more likely to have physical disorder. Poverty rate was not independently associated with sidewalk walkability; however, block groups with the highest poverty rates were 21 times more likely to have physical disorder. The results indicate that aspects of the built environment vary by characteristics of the neighborhood. This suggests that there is a differential investment in community infrastructures and resources in neighborhoods that are mostly African-American. This differential investment is likely to influence disparities in rates of physical activity.

Scene segmentation by spike synchronization in reciprocally connected visual areas. II. Global assemblies and synchronization on larger space and time scales.

PubMed

Knoblauch, Andreas; Palm, Günther

2002-09-01

We present further simulation results of the model of two reciprocally connected visual areas proposed in the first paper [Knoblauch and Palm (2002) Biol Cybern 87:151-167]. One area corresponds to the orientation-selective subsystem of the primary visual cortex, the other is modeled as an associative memory representing stimulus objects according to Hebbian learning. We examine the scene-segmentation capability of our model on larger time and space scales, and relate it to experimental findings. Scene segmentation is achieved by attention switching on a time-scale longer than the gamma range. We find that the time-scale can vary depending on habituation parameters in the range of tens to hundreds of milliseconds. The switching process can be related to findings concerning attention and biased competition, and we reproduce experimental poststimulus time histograms (PSTHs) of single neurons under different stimulus and attentional conditions. In a larger variant the model exhibits traveling waves of activity on both slow and fast time-scales, with properties similar to those found in experiments. An apparent weakness of our standard model is the tendency to produce anti-phase correlations for fast activity from the two areas. Increasing the inter-areal delays in our model produces alternations of in-phase and anti-phase oscillations. The experimentally observed in-phase correlations can most naturally be obtained by the involvement of both fast and slow inter-areal connections; e.g., by two axon populations corresponding to fast-conducting myelinated and slow-conducting unmyelinated axons.

Comprehension: The Challenge for Children's Television.

ERIC Educational Resources Information Center

Storm, Susan R.

The purpose of this research was to determine young children's comprehension of selected TV program content. The subjects were 210 children in grades K-2. All subjects in groups of five, were shown segments from four TV programs: a scalloped potatoes commercial, a "Batman" and Robin episode, a news story on the MIG-25 and a segment of the…

[Medical image segmentation based on the minimum variation snake model].

PubMed

Zhou, Changxiong; Yu, Shenglin

2007-02-01

It is difficult for traditional parametric active contour (Snake) model to deal with automatic segmentation of weak edge medical image. After analyzing snake and geometric active contour model, a minimum variation snake model was proposed and successfully applied to weak edge medical image segmentation. This proposed model replaces constant force in the balloon snake model by variable force incorporating foreground and background two regions information. It drives curve to evolve with the criterion of the minimum variation of foreground and background two regions. Experiments and results have proved that the proposed model is robust to initial contours placements and can segment weak edge medical image automatically. Besides, the testing for segmentation on the noise medical image filtered by curvature flow filter, which preserves edge features, shows a significant effect.

Active appearance model and deep learning for more accurate prostate segmentation on MRI

NASA Astrophysics Data System (ADS)

Cheng, Ruida; Roth, Holger R.; Lu, Le; Wang, Shijun; Turkbey, Baris; Gandler, William; McCreedy, Evan S.; Agarwal, Harsh K.; Choyke, Peter; Summers, Ronald M.; McAuliffe, Matthew J.

2016-03-01

Prostate segmentation on 3D MR images is a challenging task due to image artifacts, large inter-patient prostate shape and texture variability, and lack of a clear prostate boundary specifically at apex and base levels. We propose a supervised machine learning model that combines atlas based Active Appearance Model (AAM) with a Deep Learning model to segment the prostate on MR images. The performance of the segmentation method is evaluated on 20 unseen MR image datasets. The proposed method combining AAM and Deep Learning achieves a mean Dice Similarity Coefficient (DSC) of 0.925 for whole 3D MR images of the prostate using axial cross-sections. The proposed model utilizes the adaptive atlas-based AAM model and Deep Learning to achieve significant segmentation accuracy.

Phenotypic characterization of glioblastoma identified through shape descriptors

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

This paper proposes quantitatively describing the shape of glioblastoma (GBM) tissue phenotypes as a set of shape features derived from segmentations, for the purposes of discriminating between GBM phenotypes and monitoring tumor progression. GBM patients were identified from the Cancer Genome Atlas, and quantitative MR imaging data were obtained from the Cancer Imaging Archive. Three GBM tissue phenotypes are considered including necrosis, active tumor and edema/invasion. Volumetric tissue segmentations are obtained from registered T1˗weighted (T1˗WI) postcontrast and fluid-attenuated inversion recovery (FLAIR) MRI modalities. Shape features are computed from respective tissue phenotype segmentations, and a Kruskal-Wallis test was employed to select features capable of classification with a significance level of p < 0.05. Several classifier models are employed to distinguish phenotypes, where a leave-one-out cross-validation was performed. Eight features were found statistically significant for classifying GBM phenotypes with p <0.05, orientation is uninformative. Quantitative evaluations show the SVM results in the highest classification accuracy of 87.50%, sensitivity of 94.59% and specificity of 92.77%. In summary, the shape descriptors proposed in this work show high performance in predicting GBM tissue phenotypes. They are thus closely linked to morphological characteristics of GBM phenotypes and could potentially be used in a computer assisted labeling system.

Exposure to fine particulate, black carbon, and particle number concentration in transportation microenvironments

NASA Astrophysics Data System (ADS)

Morales Betancourt, R.; Galvis, B.; Balachandran, S.; Ramos-Bonilla, J. P.; Sarmiento, O. L.; Gallo-Murcia, S. M.; Contreras, Y.

2017-05-01

This research determined intake dose of fine particulate matter (PM2.5), equivalent black carbon (eBC), and number of sub-micron particles (Np) for commuters in Bogotá, Colombia. Doses were estimated through measurements of exposure concentration, a surrogate of physical activity, as well as travel times and speeds. Impacts of travel mode, traffic load, and street configuration on dose and exposure were explored. Three road segments were selected because of their different traffic loads and composition, and dissimilar street configuration. The transport modes considered include active modes (walking and cycling) and motorized modes (bus, car, taxi, and motorcycle). Measurements were performed simultaneously in the available modes at each road segment. High average eBC concentrations were observed throughout the campaign, ranging from 20 to 120 μgm-3 . Commuters in motorized modes experienced significantly higher exposure concentrations than pedestrians and bicyclists. The highest average concentrations of PM2.5, eBC , and Np were measured inside the city's Bus Rapid Transit (BRT) system vehicles. Pedestrians and bicycle users in an open street configuration were exposed to the lowest average concentrations of PM2.5 and eBC , six times lower than those experienced by commuters using the BRT in the same street segment. Pedestrians experienced the highest particulate matter intake dose in the road segments studied, despite being exposed to lower concentrations than commuters in motorized modes. Average potential dose of PM2.5 and eBC per unit length traveled were nearly three times higher for pedestrians in a street canyon configuration compared to commuters in public transport. Slower travel speed and elevated inhalation rates dominate PM dose for pedestrians. The presence of dedicated bike lanes on sidewalks has a significant impact on reducing the exposure concentration for bicyclists compared to those riding in mixed traffic lanes. This study proposes a simple method to perform loading effect correction for measurements of black carbon using multiple portable aethalometers.

COMPARISON OF RANDOM AND SYSTEMATIC SITE SELECTION FOR ASSESSING ATTAINMENT OF AQUATIC LIFE USES IN SEGMENTS OF THE OHIO RIVER

EPA Science Inventory

This report is a description of field work and data analysis results comparing a design comparable to systematic site selection with one based on random selection of sites. The report is expected to validate the use of random site selection in the bioassessment program for the O...

Volumetric analysis of pelvic hematomas after blunt trauma using semi-automated seeded region growing segmentation: a method validation study.

PubMed

Dreizin, David; Bodanapally, Uttam K; Neerchal, Nagaraj; Tirada, Nikki; Patlas, Michael; Herskovits, Edward

2016-11-01

Manually segmented traumatic pelvic hematoma volumes are strongly predictive of active bleeding at conventional angiography, but the method is time intensive, limiting its clinical applicability. We compared volumetric analysis using semi-automated region growing segmentation to manual segmentation and diameter-based size estimates in patients with pelvic hematomas after blunt pelvic trauma. A 14-patient cohort was selected in an anonymous randomized fashion from a dataset of patients with pelvic binders at MDCT, collected retrospectively as part of a HIPAA-compliant IRB-approved study from January 2008 to December 2013. To evaluate intermethod differences, one reader (R1) performed three volume measurements using the manual technique and three volume measurements using the semi-automated technique. To evaluate interobserver differences for semi-automated segmentation, a second reader (R2) performed three semi-automated measurements. One-way analysis of variance was used to compare differences in mean volumes. Time effort was also compared. Correlation between the two methods as well as two shorthand appraisals (greatest diameter, and the ABC/2 method for estimating ellipsoid volumes) was assessed with Spearman's rho (r). Intraobserver variability was lower for semi-automated compared to manual segmentation, with standard deviations ranging between ±5-32 mL and ±17-84 mL, respectively (p = 0.0003). There was no significant difference in mean volumes between the two readers' semi-automated measurements (p = 0.83); however, means were lower for the semi-automated compared with the manual technique (manual: mean and SD 309.6 ± 139 mL; R1 semi-auto: 229.6 ± 88.2 mL, p = 0.004; R2 semi-auto: 243.79 ± 99.7 mL, p = 0.021). Despite differences in means, the correlation between the two methods was very strong and highly significant (r = 0.91, p < 0.001). Correlations with diameter-based methods were only moderate and nonsignificant. Mean semi-automated segmentation time effort was 2 min and 6 s and 2 min and 35 s for R1 and R2, respectively, vs. 22 min and 8 s for manual segmentation. Semi-automated pelvic hematoma volumes correlate strongly with manually segmented volumes. Since semi-automated segmentation can be performed reliably and efficiently, volumetric analysis of traumatic pelvic hematomas is potentially valuable at the point-of-care.

Three parameters optimizing closed-loop control in sequential segmental neuromuscular stimulation.

PubMed

Zonnevijlle, E D; Somia, N N; Perez Abadia, G; Stremel, R W; Maldonado, C J; Werker, P M; Kon, M; Barker, J H

1999-05-01

In conventional dynamic myoplasties, the force generation is poorly controlled. This causes unnecessary fatigue of the transposed/transplanted electrically stimulated muscles and causes damage to the involved tissues. We introduced sequential segmental neuromuscular stimulation (SSNS) to reduce muscle fatigue by allowing part of the muscle to rest periodically while the other parts work. Despite this improvement, we hypothesize that fatigue could be further reduced in some applications of dynamic myoplasty if the muscles were made to contract according to need. The first necessary step is to gain appropriate control over the contractile activity of the dynamic myoplasty. Therefore, closed-loop control was tested on a sequentially stimulated neosphincter to strive for the best possible control over the amount of generated pressure. A selection of parameters was validated for optimizing control. We concluded that the frequency of corrections, the threshold for corrections, and the transition time are meaningful parameters in the controlling algorithm of the closed-loop control in a sequentially stimulated myoplasty.

Knowledge-based low-level image analysis for computer vision systems

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.; Baxi, Himanshu; Ranganath, M. V.

1988-01-01

Two algorithms for entry-level image analysis and preliminary segmentation are proposed which are flexible enough to incorporate local properties of the image. The first algorithm involves pyramid-based multiresolution processing and a strategy to define and use interlevel and intralevel link strengths. The second algorithm, which is designed for selected window processing, extracts regions adaptively using local histograms. The preliminary segmentation and a set of features are employed as the input to an efficient rule-based low-level analysis system, resulting in suboptimal meaningful segmentation.

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.

Automated breast segmentation in ultrasound computer tomography SAFT images

NASA Astrophysics Data System (ADS)

Hopp, T.; You, W.; Zapf, M.; Tan, W. Y.; Gemmeke, H.; Ruiter, N. V.

2017-03-01

Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.

Late Pleistocene - Holocene ruptures of the Lima Reservoir fault, SW Montana

NASA Astrophysics Data System (ADS)

Anastasio, David J.; Majerowicz, Christina N.; Pazzaglia, Frank J.; Regalla, Christine A.

2010-12-01

Active tectonics within the northern Basin and Range province provide a natural laboratory for the study of normal fault growth, linkage, and interaction. Here, we present new geologic mapping and morphologic fault-scarp modeling within the Centennial Valley, Montana to characterize Pleistocene - Holocene ruptures of the young and active Lima Reservoir fault. Geologic relationships and rupture ages indicate Middle Pleistocene activity on the Henry Gulch (>50 ka and 23-10 ka), Trail Creek (>43 ka and ˜13 ka), and reservoir (˜23 ka) segments. Offset Quaternary deposits also record Holocene rupture of the reservoir segment (˜8 ka), but unfaulted modern streams show that no segments of the Lima Reservoir fault have experienced a large earthquake in at least several millennia. The clustered pattern of rupture ages on the Lima Reservoir fault segments suggests a seismogenic linkage though segment length and spacing make a physical connection at depth unlikely. Trail Creek and reservoir segment slip rates were non-steady and appear to be increasing. The fault helps accommodate differential horizontal surface velocity measured by GPS geodesy across the boundary between the northern Basin and Range province and the Snake River Plain.

Feature selection for wearable smartphone-based human activity recognition with able bodied, elderly, and stroke patients.

PubMed

Capela, Nicole A; Lemaire, Edward D; Baddour, Natalie

2015-01-01

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.

Feature Selection for Wearable Smartphone-Based Human Activity Recognition with Able bodied, Elderly, and Stroke Patients

PubMed Central

2015-01-01

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations. PMID:25885272

Activity recognition using Video Event Segmentation with Text (VEST)

NASA Astrophysics Data System (ADS)

Holloway, Hillary; Jones, Eric K.; Kaluzniacki, Andrew; Blasch, Erik; Tierno, Jorge

2014-06-01

Multi-Intelligence (multi-INT) data includes video, text, and signals that require analysis by operators. Analysis methods include information fusion approaches such as filtering, correlation, and association. In this paper, we discuss the Video Event Segmentation with Text (VEST) method, which provides event boundaries of an activity to compile related message and video clips for future interest. VEST infers meaningful activities by clustering multiple streams of time-sequenced multi-INT intelligence data and derived fusion products. We discuss exemplar results that segment raw full-motion video (FMV) data by using extracted commentary message timestamps, FMV metadata, and user-defined queries.

Motor contributions to the temporal precision of auditory attention

PubMed Central

Morillon, Benjamin; Schroeder, Charles E.; Wyart, Valentin

2014-01-01

In temporal—or dynamic—attending theory, it is proposed that motor activity helps to synchronize temporal fluctuations of attention with the timing of events in a task-relevant stream, thus facilitating sensory selection. Here we develop a mechanistic behavioural account for this theory by asking human participants to track a slow reference beat, by noiseless finger pressing, while extracting auditory target tones delivered on-beat and interleaved with distractors. We find that overt rhythmic motor activity improves the segmentation of auditory information by enhancing sensitivity to target tones while actively suppressing distractor tones. This effect is triggered by cyclic fluctuations in sensory gain locked to individual motor acts, scales parametrically with the temporal predictability of sensory events and depends on the temporal alignment between motor and attention fluctuations. Together, these findings reveal how top-down influences associated with a rhythmic motor routine sharpen sensory representations, enacting auditory ‘active sensing’. PMID:25314898

FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements) isolates active regulatory elements from human chromatin

PubMed Central

Giresi, Paul G.; Kim, Jonghwan; McDaniell, Ryan M.; Iyer, Vishwanath R.; Lieb, Jason D.

2007-01-01

DNA segments that actively regulate transcription in vivo are typically characterized by eviction of nucleosomes from chromatin and are experimentally identified by their hypersensitivity to nucleases. Here we demonstrate a simple procedure for the isolation of nucleosome-depleted DNA from human chromatin, termed FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements). To perform FAIRE, chromatin is crosslinked with formaldehyde in vivo, sheared by sonication, and phenol-chloroform extracted. The DNA recovered in the aqueous phase is fluorescently labeled and hybridized to a DNA microarray. FAIRE performed in human cells strongly enriches DNA coincident with the location of DNaseI hypersensitive sites, transcriptional start sites, and active promoters. Evidence for cell-type–specific patterns of FAIRE enrichment is also presented. FAIRE has utility as a positive selection for genomic regions associated with regulatory activity, including regions traditionally detected by nuclease hypersensitivity assays. PMID:17179217

Motor contributions to the temporal precision of auditory attention.

PubMed

Morillon, Benjamin; Schroeder, Charles E; Wyart, Valentin

2014-10-15

In temporal-or dynamic-attending theory, it is proposed that motor activity helps to synchronize temporal fluctuations of attention with the timing of events in a task-relevant stream, thus facilitating sensory selection. Here we develop a mechanistic behavioural account for this theory by asking human participants to track a slow reference beat, by noiseless finger pressing, while extracting auditory target tones delivered on-beat and interleaved with distractors. We find that overt rhythmic motor activity improves the segmentation of auditory information by enhancing sensitivity to target tones while actively suppressing distractor tones. This effect is triggered by cyclic fluctuations in sensory gain locked to individual motor acts, scales parametrically with the temporal predictability of sensory events and depends on the temporal alignment between motor and attention fluctuations. Together, these findings reveal how top-down influences associated with a rhythmic motor routine sharpen sensory representations, enacting auditory 'active sensing'.

Integrated exhaust and electrically heated particulate filter regeneration systems

DOEpatents

Gonze, Eugene V.; Paratore, Jr., Michael J.

2013-01-08

A system includes a particulate matter (PM) filter that includes multiple zones. An electrical heater includes heater segments that are associated with respective ones of the zones. The electrical heater is arranged upstream from and proximate with the PM filter. A post-fuel injection system injects fuel into at least one of a cylinder of an engine and an exhaust system. A control module is configured to operate in a first mode that includes activating the electrical heater to heat exhaust of the engine. The control module is also configured to operate in a second mode that includes activating the post-injection system to heat the exhaust. The control module selectively operates in at least one of the first mode and the second mode.

Characteristics of Urban Sidewalks/Streets and Objectively Measured Physical Activity

PubMed Central

Heinrich, Katie M.; Poston, Walker S.C.; Hyder, Melissa; Pyle, Sara

2007-01-01

Several studies have found significant relationships between environmental characteristics (e.g., number of destinations, aesthetics) and physical activity. While a few of these studies verified that the physical activities assessed were performed in the environments examined, none have done this in an urban, neighborhood setting. This information will help efforts to inform policy decisions regarding the design of more “physically active” communities. Fourteen environmental characteristics of 60, 305-m-long segments, located in an urban, residential setting, were directly measured using standardized procedures. The number of individuals walking, jogging, and biking in the segments was assessed using an observation technique. The segments were heterogeneous with regards to several of the environmental characteristics. A total of 473 individuals were seen walking, bicycling, or jogging in the segments during 3,600 min of observation (60 min/segment). Of the 473 seen, 315 were walking, 116 bicycling, and 42 jogging. A greater number of individuals were seen walking in segments with more traffic, sidewalk defects, graffiti, and litter and less desirable property aesthetics. Only one environmental characteristic was associated with bicycling and none were significantly related with jogging. This study provides further evidence that environmental characteristics and walking are related. It also adds new information regarding the importance of scale (e.g., micro, macro) and how some environmental characteristics of urban, residential sidewalks and streets relate to physical activity. PMID:18161026

TH-CD-202-05: DECT Based Tissue Segmentation as Input to Monte Carlo Simulations for Proton Treatment Verification Using PET Imaging

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

Berndt, B; Wuerl, M; Dedes, G

Purpose: To improve agreement of predicted and measured positron emitter yields in patients, after proton irradiation for PET-based treatment verification, using a novel dual energy CT (DECT) tissue segmentation approach, overcoming known deficiencies from single energy CT (SECT). Methods: DECT head scans of 5 trauma patients were segmented and compared to existing decomposition methods with a first focus on the brain. For validation purposes, three brain equivalent solutions [water, white matter (WM) and grey matter (GM) – equivalent with respect to their reference carbon and oxygen contents and CT numbers at 90kVp and 150kVp] were prepared from water, ethanol, sucrosemore » and salt. The activities of all brain solutions, measured during a PET scan after uniform proton irradiation, were compared to Monte Carlo simulations. Simulation inputs were various solution compositions obtained from different segmentation approaches from DECT, SECT scans, and known reference composition. Virtual GM solution salt concentration corrections were applied based on DECT measurements of solutions with varying salt concentration. Results: The novel tissue segmentation showed qualitative improvements in %C for patient brain scans (ground truth unavailable). The activity simulations based on reference solution compositions agree with the measurement within 3–5% (4–8Bq/ml). These reference simulations showed an absolute activity difference between WM (20%C) and GM (10%C) to H2O (0%C) of 43 Bq/ml and 22 Bq/ml, respectively. Activity differences between reference simulations and segmented ones varied from −6 to 1 Bq/ml for DECT and −79 to 8 Bq/ml for SECT. Conclusion: Compared to the conventionally used SECT segmentation, the DECT based segmentation indicates a qualitative and quantitative improvement. In controlled solutions, a MC input based on DECT segmentation leads to better agreement with the reference. Future work will address the anticipated improvement of quantification accuracy in patients, comparing different tissue decomposition methods with an MR brain segmentation. Acknowledgement: DFG-MAP and HIT-Heidelberg Deutsche Forschungsgemeinschaft (MAP); Bundesministerium fur Bildung und Forschung (01IB13001)« less

Limb segment vibration modulates spinal reflex excitability and muscle mRNA expression after spinal cord injury

PubMed Central

Chang, Shuo-Hsiu; Tseng, Shih-Chiao; McHenry, Colleen L.; Littmann, Andrew E.; Suneja, Manish; Shields, Richard K.

2012-01-01

Objective We investigated the effect of various doses of vertical oscillation (vibration) on soleus H-reflex amplitude and post-activation depression in individuals with and without SCI. We also explored the acute effect of short-term limb vibration on skeletal muscle mRNA expression of genes associated with spinal plasticity. Methods Six healthy adults and five chronic complete SCI subjects received vibratory stimulation of their tibia over three different gravitational accelerations (0.3g, 0.6g, and 1.2g) at a fixed frequency (30 Hz). Soleus H-reflexes were measured before, during, and after vibration. Two additional chronic complete SCI subjects had soleus muscle biopsies 3 h following a single bout of vibration. Results H-reflex amplitude was depressed over 83% in both groups during vibration. This vibratory-induced inhibition lasted over 2 min in the control group, but not in the SCI group. Post-activation depression was modulated during the long-lasting vibratory inhibition. A single bout of mechanical oscillation altered mRNA expression from selected genes associated with synaptic plasticity. Conclusions Vibration of the lower leg inhibits the H-reflex amplitude, influences post-activation depression, and alters skeletal muscle mRNA expression of genes associated with synaptic plasticity. Significance Limb segment vibration may offer a long term method to reduce spinal reflex excitability after SCI. PMID:21963319

P2Y receptors and atherosclerosis in apolipoprotein E-deficient mice

PubMed Central

Guns, Pieter-Jan DF; Hendrickx, Jan; Van Assche, Tim; Fransen, Paul; Bult, Hidde

2010-01-01

Background and purpose: P2Y nucleotide receptors are involved in the regulation of vascular tone, smooth muscle cell (SMC) proliferation and inflammatory responses. The present study investigated whether they are involved in atherosclerosis. Experimental approach: mRNA of P2Y receptors was quantified (RT-PCR) in atherosclerotic and plaque-free aorta segments of apolipoprotein E-deficient (apoE–/–) mice. Macrophage activation was assessed in J774 macrophages, and effects of non-selective purinoceptor antagonists on atherosclerosis were evaluated in cholesterol-fed apoE–/– mice. Key results: P2Y6 receptor mRNA was consistently elevated in segments with atherosclerosis, whereas P2Y2 receptor expression remained unchanged. Expression of P2Y1 or P2Y4 receptor mRNA was low or undetectable, and not influenced by atherosclerosis. P2Y6 mRNA expression was higher in cultured J774 macrophages than in cultured aortic SMCs. Furthermore, immunohistochemical staining of plaques demonstrated P2Y6-positive macrophages, but few SMCs, suggesting that macrophage recruitment accounted for the increase in P2Y6 receptor mRNA during atherosclerosis. In contrast to ATP, the P2Y6-selective agonist UDP increased mRNA expression and activity of inducible nitric oxide synthase and interleukin-6 in J774 macrophages; this effect was blocked by suramin (100–300 µM) or pyridoxal-phosphate-6-azophenyl-2′-4′-disulphonic acid (PPADS, 10–30 µM). Finally, 4-week treatment of cholesterol-fed apoE–/– mice with suramin or PPADS (50 and 25 mg·kg−1·day−1 respectively) reduced plaque size, without changing plaque composition (relative SMC and macrophage content) or cell replication. Conclusions and implications: These results suggest involvement of nucleotide receptors, particularly P2Y6 receptors, during atherosclerosis, and warrant further research with selective purinoceptor antagonists or P2Y6 receptor-deficient mice. PMID:20050854

Attentional priorities and access to short-term memory: parietal interactions.

PubMed

Gillebert, Céline R; Dyrholm, Mads; Vangkilde, Signe; Kyllingsbæk, Søren; Peeters, Ronald; Vandenberghe, Rik

2012-09-01

The intraparietal sulcus (IPS) has been implicated in selective attention as well as visual short-term memory (VSTM). To contrast mechanisms of target selection, distracter filtering, and access to VSTM, we combined behavioral testing, computational modeling and functional magnetic resonance imaging. Sixteen healthy subjects participated in a change detection task in which we manipulated both target and distracter set sizes. We directly compared the IPS response as a function of the number of targets and distracters in the display and in VSTM. When distracters were not present, the posterior and middle segments of IPS showed the predicted asymptotic activity increase with an increasing target set size. When distracters were added to a single target, activity also increased as predicted. However, the addition of distracters to multiple targets suppressed both middle and posterior IPS activities, thereby displaying a significant interaction between the two factors. The interaction between target and distracter set size in IPS could not be accounted for by a simple explanation in terms of number of items accessing VSTM. Instead, it led us to a model where items accessing VSTM receive differential weights depending on their behavioral relevance, and secondly, a suppressive effect originates during the selection phase when multiple targets and multiple distracters are simultaneously present. The reverse interaction between target and distracter set size was significant in the right temporoparietal junction (TPJ), where activity was highest for a single target compared to any other condition. Our study reconciles the role of middle IPS in attentional selection and biased competition with its role in VSTM access. Copyright © 2012 Elsevier Inc. All rights reserved.

Shape-Driven 3D Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2013-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details. PMID:17354875

Mobile satellite communications technology - A summary of NASA activities

NASA Technical Reports Server (NTRS)

Dutzi, E. J.; Knouse, G. H.

1986-01-01

Studies in recent years indicate that future high-capacity mobile satellite systems are viable only if certain high-risk enabling technologies are developed. Accordingly, NASA has structured an advanced technology development program aimed at efficient utilization of orbit, spectrum, and power. Over the last two years, studies have concentrated on developing concepts and identifying cost drivers and other issues associated with the major technical areas of emphasis: vehicle antennas, speech compression, bandwidth-efficient digital modems, network architecture, mobile satellite channel characterization, and selected space segment technology. The program is now entering the next phase - breadboarding, development, and field experimentation.

Problems in mechanistic theoretical models for cell transformation by ionizing radiation

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

Chatterjee, A.; Holley, W.R.

1991-10-01

A mechanistic model based on yields of double strand breaks has been developed to determine the dose response curves for cell transformation frequencies. At its present stage the model is applicable to immortal cell lines and to various qualities (X-rays, Neon and Iron) of ionizing radiation. Presently, we have considered four types of processes which can lead to activation phenomena: (1) point mutation events on a regulatory segment of selected oncogenes, (2) inactivation of suppressor genes, through point mutation, (3) deletion of a suppressor gene by a single track, and (4) deletion of a suppressor gene by two tracks.

Diversity, cellular origin and autoreactivity of antibody-secreting cell expansions in acute Systemic Lupus Erythematosus

PubMed Central

Tipton, Christopher M; Fucile, Christopher F; Darce, Jaime; Chida, Asiya; Ichikawa, Travis; Gregoretti, Ivan; Schieferl, Sandra; Hom, Jennifer; Jenks, Scott; Feldman, Ron J; Mehr, Ramit; Wei, Chungwen; Lee, F. Eun-Hyung; Cheung, Wan Cheung; Rosenberg, Alexander F; Sanz, Iñaki

2015-01-01

Acute SLE courses with antibody-secreting cells (ASC) surges whose origin, diversity, and contribution to serum autoantibodies remain unknown. Deep sequencing, autoantibody proteome and single-cell analysis demonstrated highly diversified ASC punctuated by VH4-34 clones that produce dominant serum autoantibodies. A fraction of ASC clones contained unmutated autoantibodies, a finding consistent with differentiation outside the germinal centers. A substantial ASC segment derived from a distinct subset of newly activated naïve cells of significant clonality that persist in the circulation for several months. Thus, selection of SLE autoreactivities occurred during polyclonal activation with prolonged recruitment of recently activated naïve B cells. These findings shed light into SLE pathogenesis, help explain the benefit of anti-B cell agents and facilitate the design of future therapies. PMID:26006014

Wavelength-selective ultraviolet (Mg,Zn)O photodiodes: Tuning of parallel composition gradients with oxygen pressure

NASA Astrophysics Data System (ADS)

Zhang, Zhipeng; von Wenckstern, Holger; Lenzner, Jörg; Grundmann, Marius

2016-06-01

We report on ultraviolet photodiodes with integrated optical filter based on the wurtzite (Mg,Zn)O thin films. Tuning of the bandgap of filter and active layers was realized by employing a continuous composition spread approach relying on the ablation of a single segmented target in pulsed-laser deposition. Filter and active layers of the device were deposited on opposite sides of a sapphire substrate with nearly parallel compositional gradients. Ensure that for each sample position the bandgap of the filter layer blocking the high energy radiation is higher than that of the active layer. Different oxygen pressures during the two depositions runs. The absorption edge is tuned over 360 meV and the spectral bandwidth of photodiodes is typically 100 meV and as low as 50 meV.

Accelerometry-Derived Physical Activity of First through Third Grade Children during the Segmented School Day

ERIC Educational Resources Information Center

Weaver, R. Glenn; Crimarco, Anthony; Brusseau, Timothy A.; Webster, Collin A.; Burns, Ryan D.; Hannon, James C.

2016-01-01

Background: Schools should provide children 30 minutes/day of moderate-to-vigorous-physical-activity (MVPA). Determining school day segments that contribute to children's MVPA can inform school-based activity promotion. The purpose of this paper was to identify the proportion of children accumulating 30 minutes/day of school-based MVPA, and to…

Association of ST segment depression >5 min after exercise testing with severity of coronary artery disease.

PubMed

Shaikh, Ayaz Hussain; Hanif, Bashir; Siddiqui, Adeel M; Shahab, Hunaina; Qazi, Hammad Ali; Mujtaba, Iqbal

2010-04-01

To determine the association of prolonged ST segment depression after an exercise test with severity of coronary artery disease. A cross sectional study of 100 consecutive patients referred to the cardiology laboratory for stress myocardial perfusion imaging (MPI) conducted between April-August 2008. All selected patients were monitored until their ST segment depression was recovered to baseline. ST segment recovery time was categorized into less and more than 5 minutes. Subsequent gated SPECT-MPI was performed and stratified according to severity of perfusion defect. Association was determined between post exercise ST segment depression recovery time (<5 minutes and >5 minutes) and severity of perfusion defect on MPI. The mean age of the patients was 57.12 +/- 9.0 years. The results showed statistically insignificant association (p > 0.05) between ST segment recovery time of <5 minutes and >5 minutes with low, intermediate or high risk MPI. Our findings suggest that the commonly used cut-off levels used in literature for prolonged, post exercise ST segment depression (>5 minutes into recovery phase) does not correlate with severity of ischaemia based on MPI results.

Performance evaluation of image segmentation algorithms on microscopic image data.

PubMed

Beneš, Miroslav; Zitová, Barbara

2015-01-01

In our paper, we present a performance evaluation of image segmentation algorithms on microscopic image data. In spite of the existence of many algorithms for image data partitioning, there is no universal and 'the best' method yet. Moreover, images of microscopic samples can be of various character and quality which can negatively influence the performance of image segmentation algorithms. Thus, the issue of selecting suitable method for a given set of image data is of big interest. We carried out a large number of experiments with a variety of segmentation methods to evaluate the behaviour of individual approaches on the testing set of microscopic images (cross-section images taken in three different modalities from the field of art restoration). The segmentation results were assessed by several indices used for measuring the output quality of image segmentation algorithms. In the end, the benefit of segmentation combination approach is studied and applicability of achieved results on another representatives of microscopic data category - biological samples - is shown. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Chemical engineering and structural and pharmacological characterization of the α-scorpion toxin OD1.

PubMed

Durek, Thomas; Vetter, Irina; Wang, Ching-I Anderson; Motin, Leonid; Knapp, Oliver; Adams, David J; Lewis, Richard J; Alewood, Paul F

2013-01-01

Scorpion α-toxins are invaluable pharmacological tools for studying voltage-gated sodium channels, but few structure-function studies have been undertaken due to their challenging synthesis. To address this deficiency, we report a chemical engineering strategy based upon native chemical ligation. The chemical synthesis of α-toxin OD1 was achieved by chemical ligation of three unprotected peptide segments. A high resolution X-ray structure (1.8 Å) of synthetic OD1 showed the typical βαββ α-toxin fold and revealed important conformational differences in the pharmacophore region when compared with other α-toxin structures. Pharmacological analysis of synthetic OD1 revealed potent α-toxin activity (inhibition of fast inactivation) at Nav1.7, as well as Nav1.4 and Nav1.6. In addition, OD1 also produced potent β-toxin activity at Nav1.4 and Nav1.6 (shift of channel activation in the hyperpolarizing direction), indicating that OD1 might interact at more than one site with Nav1.4 and Nav1.6. Investigation of nine OD1 mutants revealed that three residues in the reverse turn contributed significantly to selectivity, with the triple OD1 mutant (D9K, D10P, K11H) being 40-fold more selective for Nav1.7 over Nav1.6, while OD1 K11V was 5-fold more selective for Nav1.6 than Nav1.7. This switch in selectivity highlights the importance of the reverse turn for engineering α-toxins with altered selectivity at Nav subtypes.

A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images

PubMed Central

Luo, Yaozhong; Liu, Longzhong; Li, Xuelong

2017-01-01

Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US) image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality. In this paper, we propose a new segmentation scheme to combine both region- and edge-based information into the robust graph-based (RGB) segmentation method. The only interaction required is to select two diagonal points to determine a region of interest (ROI) on the original image. The ROI image is smoothed by a bilateral filter and then contrast-enhanced by histogram equalization. Then, the enhanced image is filtered by pyramid mean shift to improve homogeneity. With the optimization of particle swarm optimization (PSO) algorithm, the RGB segmentation method is performed to segment the filtered image. The segmentation results of our method have been compared with the corresponding results obtained by three existing approaches, and four metrics have been used to measure the segmentation performance. The experimental results show that the method achieves the best overall performance and gets the lowest ARE (10.77%), the second highest TPVF (85.34%), and the second lowest FPVF (4.48%). PMID:28536703

Maximum-likelihood techniques for joint segmentation-classification of multispectral chromosome images.

PubMed

Schwartzkopf, Wade C; Bovik, Alan C; Evans, Brian L

2005-12-01

Traditional chromosome imaging has been limited to grayscale images, but recently a 5-fluorophore combinatorial labeling technique (M-FISH) was developed wherein each class of chromosomes binds with a different combination of fluorophores. This results in a multispectral image, where each class of chromosomes has distinct spectral components. In this paper, we develop new methods for automatic chromosome identification by exploiting the multispectral information in M-FISH chromosome images and by jointly performing chromosome segmentation and classification. We (1) develop a maximum-likelihood hypothesis test that uses multispectral information, together with conventional criteria, to select the best segmentation possibility; (2) use this likelihood function to combine chromosome segmentation and classification into a robust chromosome identification system; and (3) show that the proposed likelihood function can also be used as a reliable indicator of errors in segmentation, errors in classification, and chromosome anomalies, which can be indicators of radiation damage, cancer, and a wide variety of inherited diseases. We show that the proposed multispectral joint segmentation-classification method outperforms past grayscale segmentation methods when decomposing touching chromosomes. We also show that it outperforms past M-FISH classification techniques that do not use segmentation information.

Temperature-dependent plasticity of segment number in an arthropod species: the centipede Strigamia maritima.

PubMed

Vedel, Vincent; Chipman, Ariel D; Akam, Michael; Arthur, Wallace

2008-01-01

The evolution of arthropod segment number provides us with a paradox, because, whereas there is more than 20-fold variation in this character overall, most classes and orders of arthropods are composed of species that lack any variation in the number of segments. So, what is the origin of the higher-level variation? The centipede order Geophilomorpha is unusual because, with the exception of one of its families, all species exhibit intraspecific variation in segment number. Hence it provides an opportunity to investigate how segment number may change in a microevolutionary context. Here, we show that segment number can be directly altered by an environmental factor (temperature)-this is the first such demonstration for any arthropod. The direction of the effect is such that higher temperature during embryogenesis produces more segments. This potentially explains an intraspecific cline in the species concerned, Strigamia maritima, but it does not explain how such a cline is translated into the parallel interspecific pattern of lower-latitude species having more segments. Given the plastic nature of the intraspecific variation, its link with interspecific differences may lie in selection acting on developmental reaction norms.

Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

NASA Astrophysics Data System (ADS)

Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

2018-04-01

Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

[Fixed appliance therapy in patients with impaired short-circuit in the anterior part of the maxilla].

PubMed

Matthews-Brzozowska, Teresa; Pobol-Aidi, Małgorzata; Cudziło, Dorota

2015-03-01

Malocclusion in the anterior segment of maxilla and mandible are easily visible not only for dentists but also for the doctors of other specialties. Early diagnosis and appropriate therapy is important not only for occlusion but also for aesthetic reasons. The aim of the paper is to evaluate the anterior segment of maxilla and mandible in patients with malocclusion in this part and correct occlusion in the lateral segments. Medical documentation, i.e. medical history, extra- and intraoral radiograms, diagnostic casts, panoramic and lateral cephalometric radiograms of patients aged 7-12 diagnosed with malocclusion in the anterior segment of maxilla and mandible and who were treated with a fixed sectional appliance and facemask was analyzed. Descriptive and cephalometric features were analyzed before (T1) and after (T2) the treatment in 25 children. The differences between the status before and after the treatment, and the extent of change between T1 and T2 were analyzed. Statistical analysis of mean values of selected metrical features before (at T1) and after (at T2) the treatment has revealed that all metrical features concerning soft, bony and dental tissues determining the facial profile, the shape of the bony and dental structures have changed and have reached values which are closer to the norm for the population for selected features. The changes were statistically significant (p<0.0001). Treatment with fixed appliances segment facemask resulted in statistically significant improvement in the parameters investigated, which demonstrates the applicability of this therapy in the treatment of anterior maxillary segment in patients with mixed dentition. © 2015 MEDPRESS.

The border-to-border distribution method for analysis of cytoplasmic particles and organelles.

PubMed

Yacovone, Shalane K; Ornelles, David A; Lyles, Douglas S

2016-02-01

Comparing the distribution of cytoplasmic particles and organelles between different experimental conditions can be challenging due to the heterogeneous nature of cell morphologies. The border-to-border distribution method was created to enable the quantitative analysis of fluorescently labeled cytoplasmic particles and organelles of multiple cells from images obtained by confocal microscopy. The method consists of four steps: (1) imaging of fluorescently labeled cells, (2) division of the image of the cytoplasm into radial segments, (3) selection of segments of interest, and (4) population analysis of fluorescence intensities at the pixel level either as a function of distance along the selected radial segments or as a function of angle around an annulus. The method was validated using the well-characterized effect of brefeldin A (BFA) on the distribution of the vesicular stomatitis virus G protein, in which intensely labeled Golgi membranes are redistributed within the cytoplasm. Surprisingly, in untreated cells, the distribution of fluorescence in Golgi membrane-containing radial segments was similar to the distribution of fluorescence in other G protein-containing segments, indicating that the presence of Golgi membranes did not shift the distribution of G protein towards the nucleus compared to the distribution of G protein in other regions of the cell. Treatment with BFA caused only a slight shift in the distribution of the brightest G protein-containing segments which had a distribution similar to that in untreated cells. Instead, the major effect of BFA was to alter the annular distribution of G protein in the perinuclear region.

[Plaque segmentation of intracoronary optical coherence tomography images based on K-means and improved random walk algorithm].

PubMed

Wang, Guanglei; Wang, Pengyu; Han, Yechen; Liu, Xiuling; Li, Yan; Lu, Qian

2017-06-01

In recent years, optical coherence tomography (OCT) has developed into a popular coronary imaging technology at home and abroad. The segmentation of plaque regions in coronary OCT images has great significance for vulnerable plaque recognition and research. In this paper, a new algorithm based on K -means clustering and improved random walk is proposed and Semi-automated segmentation of calcified plaque, fibrotic plaque and lipid pool was achieved. And the weight function of random walk is improved. The distance between the edges of pixels in the image and the seed points is added to the definition of the weight function. It increases the weak edge weights and prevent over-segmentation. Based on the above methods, the OCT images of 9 coronary atherosclerotic patients were selected for plaque segmentation. By contrasting the doctor's manual segmentation results with this method, it was proved that this method had good robustness and accuracy. It is hoped that this method can be helpful for the clinical diagnosis of coronary heart disease.

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.

Carotid stenosis assessment with multi-detector CT angiography: comparison between manual and automatic segmentation methods.

PubMed

Zhu, Chengcheng; Patterson, Andrew J; Thomas, Owen M; Sadat, Umar; Graves, Martin J; Gillard, Jonathan H

2013-04-01

Luminal stenosis is used for selecting the optimal management strategy for patients with carotid artery disease. The aim of this study is to evaluate the reproducibility of carotid stenosis quantification using manual and automated segmentation methods using submillimeter through-plane resolution Multi-Detector CT angiography (MDCTA). 35 patients having carotid artery disease with >30 % luminal stenosis as identified by carotid duplex imaging underwent contrast enhanced MDCTA. Two experienced CT readers quantified carotid stenosis from axial source images, reconstructed maximum intensity projection (MIP) and 3D-carotid geometry which was automatically segmented by an open-source toolkit (Vascular Modelling Toolkit, VMTK) using NASCET criteria. Good agreement among the measurement using axial images, MIP and automatic segmentation was observed. Automatic segmentation methods show better inter-observer agreement between the readers (intra-class correlation coefficient (ICC): 0.99 for diameter stenosis measurement) than manual measurement of axial (ICC = 0.82) and MIP (ICC = 0.86) images. Carotid stenosis quantification using an automatic segmentation method has higher reproducibility compared with manual methods.

Highly CO2-Selective Gas Separation Membranes Based on Segmented Copolymers of Poly(Ethylene oxide) Reinforced with Pentiptycene-Containing Polyimide Hard Segments.

PubMed

Luo, Shuangjiang; Stevens, Kevin A; Park, Jae Sung; Moon, Joshua D; Liu, Qiang; Freeman, Benny D; Guo, Ruilan

2016-01-27

Poly(ethylene oxide) (PEO)-containing polymer membranes are attractive for CO2-related gas separations due to their high selectivity toward CO2. However, the development of PEO-rich membranes is frequently challenged by weak mechanical properties and a high crystallization tendency of PEO that hinders gas transport. Here we report a new series of highly CO2-selective, amorphous PEO-containing segmented copolymers prepared from commercial Jeffamine polyetheramines and pentiptycene-based polyimide. The copolymers are much more mechanically robust than the nonpentiptycene containing counterparts due to the molecular reinforcement mechanism of supramolecular chain threading and interlocking interactions induced by the pentiptycene structures, which also effectively suppresses PEO crystallization leading to a completely amorphous structure even at 60% PEO weight content. Membrane transport properties are sensitively affected by both PEO weight content and PEO chain length. A nonlinear correlation between CO2 permeability with PEO weight content was observed due to the competition between solubility and diffusivity contributions, whereby the copolymers change from being size-selective to solubility-selective when PEO content reaches 40%. CO2 selectivities over H2 and N2 increase monotonically with both PEO content and chain length, indicating strong CO2-philicity of the copolymers. The copolymer film with the longest PEO sequence (PEO2000) and highest PEO weight content (60%) showed a measured CO2 pure gas permeability of 39 Barrer, and ideal CO2/H2 and CO2/N2 selectivities of 4.1 and 46, respectively, at 35 °C and 3 atm, making them attractive for hydrogen purification and carbon capture.

Reproduction in the male honey possum (Tarsipes rostratus: Marsupialia): the epididymis.

PubMed

Cummins, J M; Temple-Smith, P D; Renfree, M B

1986-11-01

The epididymis of the adult honey possum, Tarsipes rostratus, is enclosed by a heavily pigmented tunica vaginalis and lies with the testis in a prominent prepenile scrotum. It is connected to the testis by a single ductus efferentis and is lined by approximately equal numbers of cuboidal ciliated and principal cells. It is unusual for marsupials in having no well-defined compartments or fibrous septae and in having extensive convolutions of the duct only at the caudal flexure. Three principal functional zones (initial, middle, and terminal segments) were identified in the epididymis, based on epithelial type and ultrastructural evidence of sperm maturation. Luminal diameter increases progressively throughout the tract, and epithelial height variations (from about 2 to 20 microns) are greatest in the terminal segment. The epithelium itself is remarkably low (maximum of 21.6 microns) compared with that seen in the epididymis of other mammals. The thickness of the peritubular smooth muscle coat increases close to the junction of the epididymis and ductus deferens. Sperm concentrations were estimated from counts of sperm nuclei and thus can be no more than approximations. The figures are consistent, however, with a rapid increase in concentration in the initial segment, indicating extensive fluid resorption. Sperm concentrations appear to peak in the distal zone of the terminal segment, although sampling problems and wide variations in count make such a conclusion only tentative. Principal and basal cells are the predominant cell types in the epididymal epithelium. Basal cells are most abundant in the initial and distal middle segment. Principal cells show structural evidence of active exchange with the luminal contents and have abundant apical stereocilia, the structure of which depends on the epididymal zone. Other cell types occur less commonly in the epithelium. Lipid-rich and phagocytic principal cells are restricted to the middle and distal zones of the middle segment, respectively. Clear cells, restricted to the terminal segment, and halo cells were found in very low numbers. As in some other marsupials, principal cells (possibly specialized for this function) selectively remove cytoplasmic droplets and probably other cellular debris from the luminal contents. In Tarsipes, however, this process is not very efficient, and many discarded droplets pass through to the terminal segment where they form large masses of debris associated with aggregates of degenerating spermatozoa.

Proviruses with Long-Term Stable Expression Accumulate in Transcriptionally Active Chromatin Close to the Gene Regulatory Elements: Comparison of ASLV-, HIV- and MLV-Derived Vectors

PubMed Central

Miklík, Dalibor; Šenigl, Filip; Hejnar, Jiří

2018-01-01

Individual groups of retroviruses and retroviral vectors differ in their integration site preference and interaction with the host genome. Hence, immediately after infection genome-wide distribution of integrated proviruses is non-random. During long-term in vitro or persistent in vivo infection, the genomic position and chromatin environment of the provirus affects its transcriptional activity. Thus, a selection of long-term stably expressed proviruses and elimination of proviruses, which have been gradually silenced by epigenetic mechanisms, helps in the identification of genomic compartments permissive for proviral transcription. We compare here the extent and time course of provirus silencing in single cell clones of the K562 human myeloid lymphoblastoma cell line that have been infected with retroviral reporter vectors derived from avian sarcoma/leukosis virus (ASLV), human immunodeficiency virus type 1 (HIV) and murine leukaemia virus (MLV). While MLV proviruses remain transcriptionally active, ASLV proviruses are prone to rapid silencing. The HIV provirus displays gradual silencing only after an extended time period in culture. The analysis of integration sites of long-term stably expressed proviruses shows a strong bias for some genomic features—especially integration close to the transcription start sites of active transcription units. Furthermore, complex analysis of histone modifications enriched at the site of integration points to the accumulation of proviruses of all three groups in gene regulatory segments, particularly close to the enhancer loci. We conclude that the proximity to active regulatory chromatin segments correlates with stable provirus expression in various retroviral species. PMID:29517993

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Importance of envelope modulations during consonants and vowels in segmentally interrupted sentencesa)

PubMed Central

Fogerty, Daniel

2014-01-01

The present study investigated the importance of overall segment amplitude and intrinsic segment amplitude modulation of consonants and vowels to sentence intelligibility. Sentences were processed according to three conditions that replaced consonant or vowel segments with noise matched to the long-term average speech spectrum. Segments were replaced with (1) low-level noise that distorted the overall sentence envelope, (2) segment-level noise that restored the overall syllabic amplitude modulation of the sentence, and (3) segment-modulated noise that further restored faster temporal envelope modulations during the vowel. Results from the first experiment demonstrated an incremental benefit with increasing resolution of the vowel temporal envelope. However, amplitude modulations of replaced consonant segments had a comparatively minimal effect on overall sentence intelligibility scores. A second experiment selectively noise-masked preserved vowel segments in order to equate overall performance of consonant-replaced sentences to that of the vowel-replaced sentences. Results demonstrated no significant effect of restoring consonant modulations during the interrupting noise when existing vowel cues were degraded. A third experiment demonstrated greater perceived sentence continuity with the preservation or addition of vowel envelope modulations. Overall, results support previous investigations demonstrating the importance of vowel envelope modulations to the intelligibility of interrupted sentences. PMID:24606291

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

The Effects of Appeal on Children's Comprehension and Recall of Content in Educational Television Programs

ERIC Educational Resources Information Center

Gabrelian, Natalie; Blumberg, Fran C.; Hogan, Tracy M.

2009-01-01

This exploratory study investigated the effects of audience appeal on fourth-graders' (n = 25) and fifth-graders' (n = 24) comprehension of and selective attention to narrative and academic content in educational program segments. Students were shown two program segments that focused on one of two math concepts, perimeter or scale, and that were…

Exterior Decay of Wood-Plastic Composite Boards: Characterization and Magnetic Resonance Imaging

Treesearch

Rebecca Ibach; Grace Sun; Marek Gnatowski; Jessie Glaeser; Mathew Leung; John Haight

2016-01-01

Magnetic resonance imaging (MRI) was used to evaluate free water content and distribution in wood-plastic composite (WPC) materials decayed during exterior exposure near Hilo, Hawaii. Two segments of the same board blend were selected from 6 commercial decking boards that had fungal fruiting bodies. One of the two board segments was exposed in sun, the other in shadow...

Targeting Information to Market Segments: An Action Oriented Study of Attitudes Toward Vocational Education Among Target Populations. Final Report.

ERIC Educational Resources Information Center

Sikorski, Linda A.; And Others

Research was conducted to show how segments of the population of minority and disadvantaged youth might be positively influenced by selective information campaigns to participate in vocational education programs. The first-year effort (stage 1) undertook to measure student attitudes and to develop recommendations for using this information in…