Warping an atlas derived from serial histology to 5 high-resolution MRIs.

PubMed

Tullo, Stephanie; Devenyi, Gabriel A; Patel, Raihaan; Park, Min Tae M; Collins, D Louis; Chakravarty, M Mallar

2018-06-19

Previous work from our group demonstrated the use of multiple input atlases to a modified multi-atlas framework (MAGeT-Brain) to improve subject-based segmentation accuracy. Currently, segmentation of the striatum, globus pallidus and thalamus are generated from a single high-resolution and -contrast MRI atlas derived from annotated serial histological sections. Here, we warp this atlas to five high-resolution MRI templates to create five de novo atlases. The overall goal of this work is to use these newly warped atlases as input to MAGeT-Brain in an effort to consolidate and improve the workflow presented in previous manuscripts from our group, allowing for simultaneous multi-structure segmentation. The work presented details the methodology used for the creation of the atlases using a technique previously proposed, where atlas labels are modified to mimic the intensity and contrast profile of MRI to facilitate atlas-to-template nonlinear transformation estimation. Dice's Kappa metric was used to demonstrate high quality registration and segmentation accuracy of the atlases. The final atlases are available at https://github.com/CobraLab/atlases/tree/master/5-atlas-subcortical.

Ultra High-Resolution Anterior Segment Optical Coherence Tomography in the Diagnosis and Management of Ocular Surface Squamous Neoplasia

PubMed Central

Thomas, Benjamin J.; Galor, Anat; Nanji, Afshan A.; Sayyad, Fouad El; Wang, Jianhua; Dubovy, Sander R.; Joag, Madhura G.; Karp, Carol L.

2014-01-01

The development of optical coherence tomography (OCT) technology has helped to usher in a new era of in vivo diagnostic imaging of the eye. The utilization of OCT for imaging of the anterior segment and ocular surface has evolved from time-domain devices to spectral-domain devices with greater penetrance and resolution, providing novel images of anterior segment pathology to assist in diagnosis and management of disease. Ocular surface squamous neoplasia (OSSN) is one such pathology that has proven demonstrable by certain anterior segment OCT machines, specifically the newer devices capable of performing ultra high-resolution OCT (UHR-OCT). Distinctive features of OSSN on high resolution OCT allow for diagnosis and differentiation from other ocular surface pathologies. Subtle findings on these images help to characterize the OSSN lesions beyond what is apparent with the clinical examination, providing guidance for clinical management. The purpose of this review is to examine the published literature on the utilization of UHR-OCT for the diagnosis and management of OSSN, as well as to report novel uses of this technology and potential directions for its future development. PMID:24439046

Hybrid region merging method for segmentation of high-resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi; Wang, Jiangeng; Wang, Zuo

2014-12-01

Image segmentation remains a challenging problem for object-based image analysis. In this paper, a hybrid region merging (HRM) method is proposed to segment high-resolution remote sensing images. HRM integrates the advantages of global-oriented and local-oriented region merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region, which provides an elegant way to avoid the problem of starting point assignment and to enhance the optimization ability for local-oriented region merging. During the region growing procedure, the merging iterations are constrained within the local vicinity, so that the segmentation is accelerated and can reflect the local context, as compared with the global-oriented method. A set of high-resolution remote sensing images is used to test the effectiveness of the HRM method, and three region-based remote sensing image segmentation methods are adopted for comparison, including the hierarchical stepwise optimization (HSWO) method, the local-mutual best region merging (LMM) method, and the multiresolution segmentation (MRS) method embedded in eCognition Developer software. Both the supervised evaluation and visual assessment show that HRM performs better than HSWO and LMM by combining both their advantages. The segmentation results of HRM and MRS are visually comparable, but HRM can describe objects as single regions better than MRS, and the supervised and unsupervised evaluation results further prove the superiority of HRM.

A high-resolution 3D ultrasonic system for rapid evaluation of the anterior and posterior segment.

PubMed

Peyman, Gholam A; Ingram, Charles P; Montilla, Leonardo G; Witte, Russell S

2012-01-01

Traditional ultrasound imaging systems for ophthalmology employ slow, mechanical scanning of a single-element ultrasound transducer. The goal was to demonstrate rapid examination of the anterior and posterior segment with a three-dimensional (3D) commercial ultrasound system incorporating high-resolution linear probe arrays. The 3D images of the porcine eye were generated in approximately 10 seconds by scanning one of two commercial linear arrays (25- and 50-MHz). Healthy enucleated pig eyes were compared with those with induced injury or placement of a foreign material (eg, metal). Rapid, volumetric imaging was also demonstrated in one human eye in vivo. The 50-MHz probe provided exquisite volumetric images of the anterior segment at a depth up to 15 mm and axial resolution of 30 μm. The 25-MHz probe provided a larger field of view (lateral X depth: 20 × 30 mm), sufficient for capturing the entire anterior and posterior segments of the pig eye, at a resolution of 60 μm. A 50-MHz scan through the human eyelid illustrated detailed structures of the Meibomian glands, cilia, cornea, and anterior segment back to the posterior capsule. The 3D system with its high-frequency ultrasound arrays, fast data acquisition, and volume rendering capability shows promise for investigating anterior and posterior structures of the eye. Copyright 2012, SLACK Incorporated.

Development of High Resolution Mirrors and Cd-Zn-Te Detectors for Hard X-ray Astronomy

NASA Technical Reports Server (NTRS)

Ramsey, Brian D.; Speegle, Chet O.; Gaskin, Jessica; Sharma, Dharma; Engelhaupt, Darell; Six, N. Frank (Technical Monitor)

2002-01-01

We describe the fabrication and implementation of a high-resolution conical, grazing- incidence, hard X-ray (20-70 keV) telescope. When flown aboard stratospheric balloons, these mirrors are used to image cosmic sources such as supernovae, neutron stars, and quasars. The fabrication process involves generating super-polished mandrels, mirror shell electroforming, and mirror testing. The cylindrical mandrels consist of two conical segments; each segment is approximately 305 mm long. These mandrels are first, precision ground to within approx. 1.0 micron straightness along each conical segment and then lapped and polished to less than 0.5 micron straightness. Each mandrel segment is the super-polished to an average surface roughness of approx. 3.25 angstrom rms. By mirror shell replication, this combination of good figure and low surface roughness has enabled us to achieve 15 arcsec, confirmed by X-ray measurements in the Marshall Space Flight Center 102 meter test facility. To image the focused X-rays requires a focal plane detector with appropriate spatial resolution. For 15 arcsec optics of 6 meter focal length, this resolution must be around 200 microns. In addition, the detector must have a high efficiency, relatively high energy resolution, and low background. We are currently developing Cadmium-Zinc-Telluride fine-pixel detectors for this purpose. The detectors under study consist of a 16x16 pixel array with a pixel pitch of 300 microns and are 1 mm and 2 mm thick. At 60 keV, the measured energy resolution is around 2%.

Objects Grouping for Segmentation of Roads Network in High Resolution Images of Urban Areas

NASA Astrophysics Data System (ADS)

Maboudi, M.; Amini, J.; Hahn, M.

2016-06-01

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors - as the main source of large scale mapping applications - was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of "Object-based Image Analysis (OBIA)" as an alternative to pixel-based image analysis methods. Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

High-Resolution Gamma-Ray Imaging Measurements Using Externally Segmented Germanium Detectors

NASA Technical Reports Server (NTRS)

Callas, J.; Mahoney, W.; Skelton, R.; Varnell, L.; Wheaton, W.

1994-01-01

Fully two-dimensional gamma-ray imaging with simultaneous high-resolution spectroscopy has been demonstrated using an externally segmented germanium sensor. The system employs a single high-purity coaxial detector with its outer electrode segmented into 5 distinct charge collection regions and a lead coded aperture with a uniformly redundant array (URA) pattern. A series of one-dimensional responses was collected around 511 keV while the system was rotated in steps through 180 degrees. A non-negative, linear least-squares algorithm was then employed to reconstruct a 2-dimensional image. Corrections for multiple scattering in the detector, and the finite distance of source and detector are made in the reconstruction process.

Automated Solar Flare Detection and Feature Extraction in High-Resolution and Full-Disk Hα Images

NASA Astrophysics Data System (ADS)

Yang, Meng; Tian, Yu; Liu, Yangyi; Rao, Changhui

2018-05-01

In this article, an automated solar flare detection method applied to both full-disk and local high-resolution Hα images is proposed. An adaptive gray threshold and an area threshold are used to segment the flare region. Features of each detected flare event are extracted, e.g. the start, peak, and end time, the importance class, and the brightness class. Experimental results have verified that the proposed method can obtain more stable and accurate segmentation results than previous works on full-disk images from Big Bear Solar Observatory (BBSO) and Kanzelhöhe Observatory for Solar and Environmental Research (KSO), and satisfying segmentation results on high-resolution images from the Goode Solar Telescope (GST). Moreover, the extracted flare features correlate well with the data given by KSO. The method may be able to implement a more complicated statistical analysis of Hα solar flares.

Local X-ray Computed Tomography Imaging for Mineralogical and Pore Characterization

NASA Astrophysics Data System (ADS)

Mills, G.; Willson, C. S.

2015-12-01

Sample size, material properties and image resolution are all tradeoffs that must be considered when imaging porous media samples with X-ray computed tomography. In many natural and engineered samples, pore and throat sizes span several orders of magnitude and are often correlated with the material composition. Local tomography is a nondestructive technique that images a subvolume, within a larger specimen, at high resolution and uses low-resolution tomography data from the larger specimen to reduce reconstruction error. The high-resolution, subvolume data can be used to extract important fine-scale properties but, due to the additional noise associated with the truncated dataset, it makes segmentation of different materials and mineral phases a challenge. The low-resolution data of a larger specimen is typically of much higher-quality making material characterization much easier. In addition, the imaging of a larger domain, allows for mm-scale bulk properties and heterogeneities to be determined. In this research, a 7 mm diameter and ~15 mm in length sandstone core was scanned twice. The first scan was performed to cover the entire diameter and length of the specimen at an image voxel resolution of 4.1 μm. The second scan was performed on a subvolume, ~1.3 mm in length and ~2.1 mm in diameter, at an image voxel resolution of 1.08 μm. After image processing and segmentation, the pore network structure and mineralogical features were extracted from the low-resolution dataset. Due to the noise in the truncated high-resolution dataset, several image processing approaches were applied prior to image segmentation and extraction of the pore network structure and mineralogy. Results from the different truncated tomography segmented data sets are compared to each other to evaluate the potential of each approach in identifying the different solid phases from the original 16 bit data set. The truncated tomography segmented data sets were also compared to the whole-core tomography segmented data set in two ways: (1) assessment of the porosity and pore size distribution at different scales; and (2) comparison of the mineralogical composition and distribution. Finally, registration of the two datasets will be used to show how the pore structure and mineralogy details at the two scales can be used to supplement each other.

High resolution manometry findings in patients with esophageal epiphrenic diverticula.

PubMed

Vicentine, Fernando P P; Herbella, Fernando A M; Silva, Luciana C; Patti, Marco G

2011-12-01

The pathophysiology of esophageal epiphrenic diverticula is still uncertain even though a concomitant motility disorder is found in the majority of patients in different series. High resolution manometry may allow detection of motor abnormalities in a higher number of patients with esophageal epiphrenic diverticula compared with conventional manometry. This study aims to evaluate the high resolution manometry findings in patients with esophageal epiphrenic diverticula. Nine individuals (mean age 63 ± 10 years, 4 females) with esophageal epiphrenic diverticula underwent high resolution manometry. A single diverticulum was observed in eight patients and multiple diverticula in one. Visual analysis of conventional tracings and color pressure plots for identification of segmental abnormalities was performed by two researchers experienced in high resolution manometry. Upper esophageal sphincter was normal in all patients. Esophageal body was abnormal in eight patients; lower esophageal sphincter was abnormal in seven patients. Named esophageal motility disorders were found in seven patients: achalasia in six, diffuse esophageal spasm in one. In one patient, a segmental hypercontractile zone was noticed with pressure of 196 mm Hg. High resolution manometry demonstrated motor abnormalities in all patients with esophageal epiphrenic diverticula.

Fully automatic segmentation of femurs with medullary canal definition in high and in low resolution CT scans.

PubMed

Almeida, Diogo F; Ruben, Rui B; Folgado, João; Fernandes, Paulo R; Audenaert, Emmanuel; Verhegghe, Benedict; De Beule, Matthieu

2016-12-01

Femur segmentation can be an important tool in orthopedic surgical planning. However, in order to overcome the need of an experienced user with extensive knowledge on the techniques, segmentation should be fully automatic. In this paper a new fully automatic femur segmentation method for CT images is presented. This method is also able to define automatically the medullary canal and performs well even in low resolution CT scans. Fully automatic femoral segmentation was performed adapting a template mesh of the femoral volume to medical images. In order to achieve this, an adaptation of the active shape model (ASM) technique based on the statistical shape model (SSM) and local appearance model (LAM) of the femur with a novel initialization method was used, to drive the template mesh deformation in order to fit the in-image femoral shape in a time effective approach. With the proposed method a 98% convergence rate was achieved. For high resolution CT images group the average error is less than 1mm. For the low resolution image group the results are also accurate and the average error is less than 1.5mm. The proposed segmentation pipeline is accurate, robust and completely user free. The method is robust to patient orientation, image artifacts and poorly defined edges. The results excelled even in CT images with a significant slice thickness, i.e., above 5mm. Medullary canal segmentation increases the geometric information that can be used in orthopedic surgical planning or in finite element analysis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

High-resolution imaging gamma-ray spectroscopy with externally segmented germanium detectors

NASA Technical Reports Server (NTRS)

Callas, J. L.; Mahoney, W. A.; Varnell, L. S.; Wheaton, W. A.

1993-01-01

Externally segmented germanium detectors promise a breakthrough in gamma-ray imaging capabilities while retaining the superb energy resolution of germanium spectrometers. An angular resolution of 0.2 deg becomes practical by combining position-sensitive germanium detectors having a segment thickness of a few millimeters with a one-dimensional coded aperture located about a meter from the detectors. Correspondingly higher angular resolutions are possible with larger separations between the detectors and the coded aperture. Two-dimensional images can be obtained by rotating the instrument. Although the basic concept is similar to optical or X-ray coded-aperture imaging techniques, several complicating effects arise because of the penetrating nature of gamma rays. The complications include partial transmission through the coded aperture elements, Compton scattering in the germanium detectors, and high background count rates. Extensive electron-photon Monte Carlo modeling of a realistic detector/coded-aperture/collimator system has been performed. Results show that these complicating effects can be characterized and accounted for with no significant loss in instrument sensitivity.

Fast vessel segmentation in retinal images using multi-scale enhancement and second-order local entropy

NASA Astrophysics Data System (ADS)

Yu, H.; Barriga, S.; Agurto, C.; Zamora, G.; Bauman, W.; Soliz, P.

2012-03-01

Retinal vasculature is one of the most important anatomical structures in digital retinal photographs. Accurate segmentation of retinal blood vessels is an essential task in automated analysis of retinopathy. This paper presents a new and effective vessel segmentation algorithm that features computational simplicity and fast implementation. This method uses morphological pre-processing to decrease the disturbance of bright structures and lesions before vessel extraction. Next, a vessel probability map is generated by computing the eigenvalues of the second derivatives of Gaussian filtered image at multiple scales. Then, the second order local entropy thresholding is applied to segment the vessel map. Lastly, a rule-based decision step, which measures the geometric shape difference between vessels and lesions is applied to reduce false positives. The algorithm is evaluated on the low-resolution DRIVE and STARE databases and the publicly available high-resolution image database from Friedrich-Alexander University Erlangen-Nuremberg, Germany). The proposed method achieved comparable performance to state of the art unsupervised vessel segmentation methods with a competitive faster speed on the DRIVE and STARE databases. For the high resolution fundus image database, the proposed algorithm outperforms an existing approach both on performance and speed. The efficiency and robustness make the blood vessel segmentation method described here suitable for broad application in automated analysis of retinal images.

Development of a Dedicated Radiotherapy Unit with Real-Time Image Guidance and Motion Management for Accelerated Partial Breast Irradiation

DTIC Science & Technology

2012-08-01

respiratory motions using 4D tagged magnetic resonance imaging ( MRI ) data and 4D high-resolution respiratory-gated CT data respectively. Both...dimensional segmented human anatomy. Medical Physics, 1994. 21(2): p. 299-302. 6. Zubal, I.G., et al. High resolution, MRI -based, segmented...the beam direction. T2-weighted images were acquired after 24 hours with a 3T- MRI scanner using a turbo spin-echo sequence. Imaging parameters were

Retinal blood vessel segmentation in high resolution fundus photographs using automated feature parameter estimation

NASA Astrophysics Data System (ADS)

Orlando, José Ignacio; Fracchia, Marcos; del Río, Valeria; del Fresno, Mariana

2017-11-01

Several ophthalmological and systemic diseases are manifested through pathological changes in the properties and the distribution of the retinal blood vessels. The characterization of such alterations requires the segmentation of the vasculature, which is a tedious and time-consuming task that is infeasible to be performed manually. Numerous attempts have been made to propose automated methods for segmenting the retinal vasculature from fundus photographs, although their application in real clinical scenarios is usually limited by their ability to deal with images taken at different resolutions. This is likely due to the large number of parameters that have to be properly calibrated according to each image scale. In this paper we propose to apply a novel strategy for automated feature parameter estimation, combined with a vessel segmentation method based on fully connected conditional random fields. The estimation model is learned by linear regression from structural properties of the images and known optimal configurations, that were previously obtained for low resolution data sets. Our experiments in high resolution images show that this approach is able to estimate appropriate configurations that are suitable for performing the segmentation task without requiring to re-engineer parameters. Furthermore, our combined approach reported state of the art performance on the benchmark data set HRF, as measured in terms of the F1-score and the Matthews correlation coefficient.

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

PubMed

Iglesias, Juan Eugenio; Augustinack, Jean C; Nguyen, Khoa; Player, Christopher M; Player, Allison; Wright, Michelle; Roy, Nicole; Frosch, Matthew P; McKee, Ann C; Wald, Lawrence L; Fischl, Bruce; Van Leemput, Koen

2015-07-15

Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and classification based on whole hippocampal volume (82% accuracy). Copyright © 2015. Published by Elsevier Inc.

High-Resolution Isotropic Three-Dimensional MR Imaging of the Extraforaminal Segments of the Cranial Nerves.

PubMed

Wen, Jessica; Desai, Naman S; Jeffery, Dean; Aygun, Nafi; Blitz, Ari

2018-02-01

High-resolution isotropic 3-dimensional (D) MR imaging with and without contrast is now routinely used for imaging evaluation of cranial nerve anatomy and pathologic conditions. The anatomic details of the extraforaminal segments are well-visualized on these techniques. A wide range of pathologic entities may cause enhancement or displacement of the nerve, which is now visible to an extent not available on standard 2D imaging. This article highlights the anatomy of extraforaminal segments of the cranial nerves and uses select cases to illustrate the utility and power of these sequences, with a focus on constructive interference in steady-state. Copyright © 2017 Elsevier Inc. All rights reserved.

Automated detection, 3D segmentation and analysis of high resolution spine MR images using statistical shape models

NASA Astrophysics Data System (ADS)

Neubert, A.; Fripp, J.; Engstrom, C.; Schwarz, R.; Lauer, L.; Salvado, O.; Crozier, S.

2012-12-01

Recent advances in high resolution magnetic resonance (MR) imaging of the spine provide a basis for the automated assessment of intervertebral disc (IVD) and vertebral body (VB) anatomy. High resolution three-dimensional (3D) morphological information contained in these images may be useful for early detection and monitoring of common spine disorders, such as disc degeneration. This work proposes an automated approach to extract the 3D segmentations of lumbar and thoracic IVDs and VBs from MR images using statistical shape analysis and registration of grey level intensity profiles. The algorithm was validated on a dataset of volumetric scans of the thoracolumbar spine of asymptomatic volunteers obtained on a 3T scanner using the relatively new 3D T2-weighted SPACE pulse sequence. Manual segmentations and expert radiological findings of early signs of disc degeneration were used in the validation. There was good agreement between manual and automated segmentation of the IVD and VB volumes with the mean Dice scores of 0.89 ± 0.04 and 0.91 ± 0.02 and mean absolute surface distances of 0.55 ± 0.18 mm and 0.67 ± 0.17 mm respectively. The method compares favourably to existing 3D MR segmentation techniques for VBs. This is the first time IVDs have been automatically segmented from 3D volumetric scans and shape parameters obtained were used in preliminary analyses to accurately classify (100% sensitivity, 98.3% specificity) disc abnormalities associated with early degenerative changes.

Potential impacts of robust surface roughness indexes on DTM-based segmentation

NASA Astrophysics Data System (ADS)

Trevisani, Sebastiano; Rocca, Michele

2017-04-01

In this study, we explore the impact of robust surface texture indexes based on MAD (median absolute differences), implemented by Trevisani and Rocca (2015), in the unsupervised morphological segmentation of an alpine basin. The area was already object of a geomorphometric analysis, consisting in the roughness-based segmentation of the landscape (Trevisani et al. 2012); the roughness indexes were calculated on a high resolution DTM derived by means of airborne Lidar using the variogram as estimator. The calculated roughness indexes have been then used for the fuzzy clustering (Odeh et al., 1992; Burrough et al., 2000) of the basin, revealing the high informative geomorphometric content of the roughness-based indexes. However, the fuzzy clustering revealed a high fuzziness and a high degree of mixing between textural classes; this was ascribed both to the morphological complexity of the basin and to the high sensitivity of variogram to non-stationarity and signal-noise. Accordingly, we explore how the new implemented roughness indexes based on MAD affect the morphological segmentation of the studied basin. References Burrough, P.A., Van Gaans, P.F.M., MacMillan, R.A., 2000. High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems 113, 37-52. Odeh, I.O.A., McBratney, A.B., Chittleborough, D.J., 1992. Soil pattern recognition with fuzzy-c-means: application to classification and soil-landform interrelationships. Soil Sciences Society of America Journal 56, 505-516. Trevisani, S., Cavalli, M. & Marchi, L. 2012, "Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin", Geomorphology, vol. 161-162, pp. 26-39. Trevisani, S. & Rocca, M. 2015, "MAD: Robust image texture analysis for applications in high resolution geomorphometry", Computers and Geosciences, vol. 81, pp. 78-92.

Three-Dimensional Imaging and Numerical Reconstruction of Graphite/Epoxy Composite Microstructure Based on Ultra-High Resolution X-Ray Computed Tomography

NASA Technical Reports Server (NTRS)

Czabaj, M. W.; Riccio, M. L.; Whitacre, W. W.

2014-01-01

A combined experimental and computational study aimed at high-resolution 3D imaging, visualization, and numerical reconstruction of fiber-reinforced polymer microstructures at the fiber length scale is presented. To this end, a sample of graphite/epoxy composite was imaged at sub-micron resolution using a 3D X-ray computed tomography microscope. Next, a novel segmentation algorithm was developed, based on concepts adopted from computer vision and multi-target tracking, to detect and estimate, with high accuracy, the position of individual fibers in a volume of the imaged composite. In the current implementation, the segmentation algorithm was based on Global Nearest Neighbor data-association architecture, a Kalman filter estimator, and several novel algorithms for virtualfiber stitching, smoothing, and overlap removal. The segmentation algorithm was used on a sub-volume of the imaged composite, detecting 508 individual fibers. The segmentation data were qualitatively compared to the tomographic data, demonstrating high accuracy of the numerical reconstruction. Moreover, the data were used to quantify a) the relative distribution of individual-fiber cross sections within the imaged sub-volume, and b) the local fiber misorientation relative to the global fiber axis. Finally, the segmentation data were converted using commercially available finite element (FE) software to generate a detailed FE mesh of the composite volume. The methodology described herein demonstrates the feasibility of realizing an FE-based, virtual-testing framework for graphite/fiber composites at the constituent level.

Photogrammetric Point Clouds Generation in Urban Areas from Integrated Image Matching and Segmentation

NASA Astrophysics Data System (ADS)

Ye, L.; Wu, B.

2017-09-01

High-resolution imagery is an attractive option for surveying and mapping applications due to the advantages of high quality imaging, short revisit time, and lower cost. Automated reliable and dense image matching is essential for photogrammetric 3D data derivation. Such matching, in urban areas, however, is extremely difficult, owing to the complexity of urban textures and severe occlusion problems on the images caused by tall buildings. Aimed at exploiting high-resolution imagery for 3D urban modelling applications, this paper presents an integrated image matching and segmentation approach for reliable dense matching of high-resolution imagery in urban areas. The approach is based on the framework of our existing self-adaptive triangulation constrained image matching (SATM), but incorporates three novel aspects to tackle the image matching difficulties in urban areas: 1) occlusion filtering based on image segmentation, 2) segment-adaptive similarity correlation to reduce the similarity ambiguity, 3) improved dense matching propagation to provide more reliable matches in urban areas. Experimental analyses were conducted using aerial images of Vaihingen, Germany and high-resolution satellite images in Hong Kong. The photogrammetric point clouds were generated, from which digital surface models (DSMs) were derived. They were compared with the corresponding airborne laser scanning data and the DSMs generated from the Semi-Global matching (SGM) method. The experimental results show that the proposed approach is able to produce dense and reliable matches comparable to SGM in flat areas, while for densely built-up areas, the proposed method performs better than SGM. The proposed method offers an alternative solution for 3D surface reconstruction in urban areas.

Semantic Segmentation of Convolutional Neural Network for Supervised Classification of Multispectral Remote Sensing

NASA Astrophysics Data System (ADS)

Xue, L.; Liu, C.; Wu, Y.; Li, H.

2018-04-01

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.

Residential roof condition assessment system using deep learning

NASA Astrophysics Data System (ADS)

Wang, Fan; Kerekes, John P.; Xu, Zhuoyi; Wang, Yandong

2018-01-01

The emergence of high resolution (HR) and ultra high resolution (UHR) airborne remote sensing imagery is enabling humans to move beyond traditional land cover analysis applications to the detailed characterization of surface objects. A residential roof condition assessment method using techniques from deep learning is presented. The proposed method operates on individual roofs and divides the task into two stages: (1) roof segmentation, followed by (2) condition classification of the segmented roof regions. As the first step in this process, a self-tuning method is proposed to segment the images into small homogeneous areas. The segmentation is initialized with simple linear iterative clustering followed by deep learned feature extraction and region merging, with the optimal result selected by an unsupervised index, Q. After the segmentation, a pretrained residual network is fine-tuned on the augmented roof segments using a proposed k-pixel extension technique for classification. The effectiveness of the proposed algorithm was demonstrated on both HR and UHR imagery collected by EagleView over different study sites. The proposed algorithm has yielded promising results and has outperformed traditional machine learning methods using hand-crafted features.

Generating Ground Reference Data for a Global Impervious Surface Survey

NASA Technical Reports Server (NTRS)

Tilton, James C.; deColstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

We are engaged in 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. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.

Ultrahigh resolution retinal imaging by visible light OCT with longitudinal achromatization

PubMed Central

Chong, Shau Poh; Zhang, Tingwei; Kho, Aaron; Bernucci, Marcel T.; Dubra, Alfredo; Srinivasan, Vivek J.

2018-01-01

Chromatic aberrations are an important design consideration in high resolution, high bandwidth, refractive imaging systems that use visible light. Here, we present a fiber-based spectral/Fourier domain, visible light OCT ophthalmoscope corrected for the average longitudinal chromatic aberration (LCA) of the human eye. Analysis of complex speckles from in vivo retinal images showed that achromatization resulted in a speckle autocorrelation function that was ~20% narrower in the axial direction, but unchanged in the transverse direction. In images from the improved, achromatized system, the separation between Bruch’s membrane (BM), the retinal pigment epithelium (RPE), and the outer segment tips clearly emerged across the entire 6.5 mm field-of-view, enabling segmentation and morphometry of BM and the RPE in a human subject. Finally, cross-sectional images depicted distinct inner retinal layers with high resolution. Thus, with chromatic aberration compensation, visible light OCT can achieve volume resolutions and retinal image quality that matches or exceeds ultrahigh resolution near-infrared OCT systems with no monochromatic aberration compensation. PMID:29675296

Segmentation of High Angular Resolution Diffusion MRI using Sparse Riemannian Manifold Clustering

PubMed Central

Wright, Margaret J.; Thompson, Paul M.; Vidal, René

2015-01-01

We address the problem of segmenting high angular resolution diffusion imaging (HARDI) data into multiple regions (or fiber tracts) with distinct diffusion properties. We use the orientation distribution function (ODF) to represent HARDI data and cast the problem as a clustering problem in the space of ODFs. Our approach integrates tools from sparse representation theory and Riemannian geometry into a graph theoretic segmentation framework. By exploiting the Riemannian properties of the space of ODFs, we learn a sparse representation for each ODF and infer the segmentation by applying spectral clustering to a similarity matrix built from these representations. In cases where regions with similar (resp. distinct) diffusion properties belong to different (resp. same) fiber tracts, we obtain the segmentation by incorporating spatial and user-specified pairwise relationships into the formulation. Experiments on synthetic data evaluate the sensitivity of our method to image noise and the presence of complex fiber configurations, and show its superior performance compared to alternative segmentation methods. Experiments on phantom and real data demonstrate the accuracy of the proposed method in segmenting simulated fibers, as well as white matter fiber tracts of clinical importance in the human brain. PMID:24108748

75 MHz ultrasound biomicroscopy of anterior segment of eye.

PubMed

Silverman, Ronald H; Cannata, Jonathan; Shung, K Kirk; Gal, Omer; Patel, Monica; Lloyd, Harriet O; Feleppa, Ernest J; Coleman, D Jackson

2006-07-01

Very high frequency ultrasound (35-50 MHz) has had a significant impact upon clinical imaging of the anterior segment of the eye, offering an axial resolution as small as 30 microm. Higher frequencies, while potentially offering even finer resolution, are more affected by absorption in ocular tissues and even in the fluid coupling medium. Our aim was to develop and apply improved transducer technology utilizing frequencies beyond those routinely used for ultrasound biomicroscopy of the eye. A 75-MHz lithium niobate transducer with 2 mm aperture and 6 mm focal length was fabricated. We scanned the ciliary body and cornea of a human eye six years post-LASIK. Spectral parameter images were produced from the midband fit to local calibrated power spectra. Images were compared with those produced using a 35 MHz lithium niobate transducer of similar fractional bandwidth and focal ratio. The 75-MHz transducer was found to have a fractional bandwidth (-6 dB) of 61%. Images of the post-LASIK cornea showed higher stromal backscatter at 75 MHz than at 35 MHz. The improved lateral resolution resulted in better visualization of discontinuities in Bowman's layer, indicative of microfolds or breaks occurring at the time of surgery. The LASIK surface was evident as a discontinuity in stromal backscatter between the stromal component of the flap and the residual stroma. The iris and ciliary body were visualized despite attenuation by the overlying sclera. Very high frequency ultrasound imaging of the anterior segment of the eye has been restricted to the 35-50 MHz band for over a decade. We showed that higher frequencies can be used in vivo to image the cornea and anterior segment. This improvement in resolution and high sensitivity to backscatter from the corneal stroma will provide benefits in clinical diagnostic imaging of the anterior segment.

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

PubMed Central

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

2013-01-01

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

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.

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

Brun, E., E-mail: emmanuel.brun@esrf.fr; Grandl, S.; Sztrókay-Gaul, A.

Purpose: Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. Methods: The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer basedmore » phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedure’s possible applications. Results: A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. Conclusions: The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.« less

Segmentation methodology for automated classification and differentiation of soft tissues in multiband images of high-resolution ultrasonic transmission tomography.

PubMed

Jeong, Jeong-Won; Shin, Dae C; Do, Synho; Marmarelis, Vasilis Z

2006-08-01

This paper presents a novel segmentation methodology for automated classification and differentiation of soft tissues using multiband data obtained with the newly developed system of high-resolution ultrasonic transmission tomography (HUTT) for imaging biological organs. This methodology extends and combines two existing approaches: the L-level set active contour (AC) segmentation approach and the agglomerative hierarchical kappa-means approach for unsupervised clustering (UC). To prevent the trapping of the current iterative minimization AC algorithm in a local minimum, we introduce a multiresolution approach that applies the level set functions at successively increasing resolutions of the image data. The resulting AC clusters are subsequently rearranged by the UC algorithm that seeks the optimal set of clusters yielding the minimum within-cluster distances in the feature space. The presented results from Monte Carlo simulations and experimental animal-tissue data demonstrate that the proposed methodology outperforms other existing methods without depending on heuristic parameters and provides a reliable means for soft tissue differentiation in HUTT images.

Recognition and characterization of networks of water bodies in the Arctic ice-wedge polygonal tundra using high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Skurikhin, A. N.; Gangodagamage, C.; Rowland, J. C.; Wilson, C. J.

2013-12-01

Arctic lowland landscapes underlain by permafrost are often characterized by polygon-like patterns such as ice-wedge polygons outlined by networks of ice wedges and complemented with polygon rims, troughs, shallow ponds and thermokarst lakes. Polygonal patterns and corresponding features are relatively easy to recognize in high spatial resolution satellite imagery by a human, but their automated recognition is challenging due to the variability in their spectral appearance, the irregularity of individual trough spacing and orientation within the patterns, and a lack of unique spectral response attributable to troughs with widths commonly between 1 m and 2 m. Accurate identification of fine scale elements of ice-wedge polygonal tundra is important as their imprecise recognition may bias estimates of water, heat and carbon fluxes in large-scale climate models. Our focus is on the problem of identification of Arctic polygonal tundra fine-scale landscape elements (as small as 1 m - 2 m width). The challenge of the considered problem is that while large water bodies (e.g. lakes and rivers) can be recognized based on spectral response, reliable recognition of troughs is more difficult. Troughs do not have unique spectral signature, their appearance is noisy (edges are not strong), their width is small, and they often form connected networks with ponds and lakes, and thus they have overlapping spectral response with other water bodies and surrounding non-water bodies. We present a semi-automated approach to identify and classify Arctic polygonal tundra landscape components across the range of spatial scales, such as troughs, ponds, river- and lake-like objects, using high spatial resolution satellite imagery. The novelty of the approach lies in: (1) the combined use of segmentation and shape-based classification to identify a broad range of water bodies, including troughs, and (2) the use of high-resolution WorldView-2 satellite imagery (with resolution of 0.6 m) for this identification. The approach starts by segmenting water bodies from an image, which are then categorized using shape-based classification. Segmentation uses combination of pan sharpened multispectral bands and is based on the active contours without edges technique. The segmentation is robust to noise and can detect objects with weak boundaries that is important for extraction of troughs. We then categorize the segmented regions via shape based classification. Because segmentation accuracy is the main factor impacting the quality of the shape-based classification, for segmentation accuracy assessment we created reference image using WorldView-2 satellite image of ice-wedge polygonal tundra. Reference image contained manually labelled image regions which cover components of drainage networks, such as troughs, ponds, rivers and lakes. The evaluation has shown that the approach provides a good accuracy of segmentation and reasonable classification results. The overall accuracy of the segmentation is approximately 95%, the segmentation user's and producer's accuracies are approximately 92% and 97% respectively.

Angiographic and structural imaging using high axial resolution fiber-based visible-light OCT

PubMed Central

Pi, Shaohua; Camino, Acner; Zhang, Miao; Cepurna, William; Liu, Gangjun; Huang, David; Morrison, John; Jia, Yali

2017-01-01

Optical coherence tomography using visible-light sources can increase the axial resolution without the need for broader spectral bandwidth. Here, a high-resolution, fiber-based, visible-light optical coherence tomography system is built and used to image normal retina in rats and blood vessels in chicken embryo. In the rat retina, accurate segmentation of retinal layer boundaries and quantification of layer thicknesses are accomplished. Furthermore, three distinct capillary plexuses in the retina and the choriocapillaris are identified and the characteristic pattern of the nerve fiber layer thickness in rats is revealed. In the chicken embryo model, the microvascular network and a venous bifurcation are examined and the ability to identify and segment large vessel walls is demonstrated. PMID:29082087

A deployable telescope for sub-meter resolutions from microsatellite platforms

NASA Astrophysics Data System (ADS)

Dolkens, D.; Kuiper, J. M.

2017-11-01

Sub-meter resolution imagery has become increasingly important for disaster response, defence and security applications. Earth Observation (EO) at these resolutions has long been the realm of large and heavy telescopes, which results in high image costs, limited availability and long revisit times. Using synthetic aperture technology, instruments can now be developed that can reach these resolutions using a substantially smaller launch volume and mass. To obtain a competitive MicroSatellite telescope design, a concept study was performed to develop a deployable instrument that can reach a ground resolution of 25 cm from an orbital altitude of 500 km. Two classes of instruments were analysed: the Fizeau synthetic aperture, a telescope that uses a segmented primary mirror, and a Michelson synthetic aperture, an instrument concept that combines the light of a distributed array of afocal telescopes into a final image. In a trade-off the Fizeau synthetic aperture was selected as the most promising concept for obtaining high resolution imagery from a Low Earth Orbit. The optical design of the Fizeau synthetic aperture is based on a full-field Korsch telescope that has been optimized for compactness and an excellent wavefront quality. It uses three aperture segments in a tri-arm configuration that can be folded alongside the instrument during launch. The secondary mirror is mounted on a deployable boom, further decreasing the launch volume. To maintain a high image quality while operating in the harsh and dynamic space environment, one of the most challenging obstacles that must be addressed is the very tight tolerance on the positioning of the three primary mirror segments and the secondary mirror. Following a sensitivity analysis, systems engineering budgets have been defined. The instrument concept features a robust thermo-mechanical design, aimed at reducing the mechanical uncertainties to a minimum. Silicon Carbide mirror segments, the use of Invar for the deployable arms and a main housing with active thermal control, will guarantee a high thermal stability during operations. Since a robust mechanical design alone is insufficient to ensure a diffraction limited performance, an inorbit calibration system was developed. Post launch, a combination of interferometric measurements and capacitive sensors will be used to characterise the system. Actuators beneath the primary mirror segments will then correct the position of the mirror segments to meet the required operating accuracies. During operations, a passive system will be used. This system relies on a phase diversity algorithm to retrieve residual wavefront aberrations and deconvolve the image data. Using this approach, a good end-to-end imaging performance can be achieved.

High resolution, MRI-based, segmented, computerized head phantom

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

Zubal, I.G.; Harrell, C.R.; Smith, E.O.

1999-01-01

The authors have created a high-resolution software phantom of the human brain which is applicable to voxel-based radiation transport calculations yielding nuclear medicine simulated images and/or internal dose estimates. A software head phantom was created from 124 transverse MRI images of a healthy normal individual. The transverse T2 slices, recorded in a 256x256 matrix from a GE Signa 2 scanner, have isotropic voxel dimensions of 1.5 mm and were manually segmented by the clinical staff. Each voxel of the phantom contains one of 62 index numbers designating anatomical, neurological, and taxonomical structures. The result is stored as a 256x256x128 bytemore » array. Internal volumes compare favorably to those described in the ICRP Reference Man. The computerized array represents a high resolution model of a typical human brain and serves as a voxel-based anthropomorphic head phantom suitable for computer-based modeling and simulation calculations. It offers an improved realism over previous mathematically described software brain phantoms, and creates a reference standard for comparing results of newly emerging voxel-based computations. Such voxel-based computations lead the way to developing diagnostic and dosimetry calculations which can utilize patient-specific diagnostic images. However, such individualized approaches lack fast, automatic segmentation schemes for routine use; therefore, the high resolution, typical head geometry gives the most realistic patient model currently available.« less

Contextually guided very-high-resolution imagery classification with semantic segments

NASA Astrophysics Data System (ADS)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.

PubMed

Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A

2011-04-01

Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.

Employing unmanned aerial vehicle to monitor the health condition of wind turbines

NASA Astrophysics Data System (ADS)

Huang, Yishuo; Chiang, Chih-Hung; Hsu, Keng-Tsang; Cheng, Chia-Chi

2018-04-01

Unmanned aerial vehicle (UAV) can gather the spatial information of huge structures, such as wind turbines, that can be difficult to obtain with traditional approaches. In this paper, the UAV used in the experiments is equipped with high resolution camera and thermal infrared camera. The high resolution camera can provide a series of images with resolution up to 10 Megapixels. Those images can be used to form the 3D model using the digital photogrammetry technique. By comparing the 3D scenes of the same wind turbine at different times, possible displacement of the supporting tower of the wind turbine, caused by ground movement or foundation deterioration may be determined. The recorded thermal images are analyzed by applying the image segmentation methods to the surface temperature distribution. A series of sub-regions are separated by the differences of the surface temperature. The high-resolution optical image and the segmented thermal image are fused such that the surface anomalies are more easily identified for wind turbines.

Optimization of the Performance of Segmented Scintillators for Radiotherapy Imaging through Novel Binning Techniques

PubMed Central

El-Mohri, Youcef; Antonuk, Larry E.; Choroszucha, Richard B.; Zhao, Qihua; Jiang, Hao; Liu, Langechuan

2014-01-01

Thick, segmented crystalline scintillators have shown increasing promise as replacement x-ray converters for the phosphor screens currently used in active matrix flat-panel imagers (AMFPIs) in radiotherapy, by virtue of providing over an order of magnitude improvement in the DQE. However, element-to-element misalignment in current segmented scintillator prototypes creates a challenge for optimal registration with underlying AMFPI arrays, resulting in degradation of spatial resolution. To overcome this challenge, a methodology involving the use of a relatively high resolution AMFPI array in combination with novel binning techniques is presented. The array, which has a pixel pitch of 0.127 mm, was coupled to prototype segmented scintillators based on BGO, LYSO and CsI:Tl materials, each having a nominal element-to-element pitch of 1.016 mm and thickness of ~1 cm. The AMFPI systems incorporating these prototypes were characterized at a radiotherapy energy of 6 MV in terms of MTF, NPS, DQE, and reconstructed images of a resolution phantom acquired using a cone-beam CT geometry. For each prototype, the application of 8×8 pixel binning to achieve a sampling pitch of 1.016 mm was optimized through use of an alignment metric which minimized misregistration and thereby improved spatial resolution. In addition, the application of alternative binning techniques that exclude the collection of signal near septal walls resulted in further significant improvement in spatial resolution for the BGO and LYSO prototypes, though not for the CsI:Tl prototype due to the large amount of optical cross-talk resulting from significant light spread between scintillator elements in that device. The efficacy of these techniques for improving spatial resolution appears to be enhanced for scintillator materials that exhibit mechanical hardness, high density and high refractive index, such as BGO. Moreover, materials that exhibit these properties as well as offer significantly higher light output than BGO, such as CdWO4, should provide the additional benefit of preserving DQE performance. PMID:24487347

Quantitative assessment of rat corneal thickness and morphology during stem cell therapy by high-speed optical coherence tomography

NASA Astrophysics Data System (ADS)

Lal, Cerine; McGrath, James; Subhash, Hrebesh; Rani, Sweta; Ritter, Thomas; Leahy, Martin

2016-03-01

Optical Coherence Tomography (OCT) is a non-invasive 3 dimensional optical imaging modality that enables high resolution cross sectional imaging in biological tissues and materials. Its high axial and lateral resolution combined with high sensitivity, imaging depth and wide field of view makes it suitable for wide variety of high resolution medical imaging applications at clinically relevant speed. With the advent of swept source lasers, the imaging speed of OCT has increased considerably in recent years. OCT has been used in ophthalmology to study dynamic changes occurring in the cornea and iris, thereby providing physiological and pathological changes that occur within the anterior segment structures such as in glaucoma, during refractive surgery, lamellar keratoplasty and corneal diseases. In this study, we assess the changes in corneal thickness in the anterior segment of the eye during wound healing process in a rat corneal burn model following stem cell therapy using high speed swept source OCT.

Small should be the New Big: High-resolution Models with Small Segments have Big Advantages when Modeling Eutrophication in the Great Lakes

EPA Science Inventory

Historical mathematical models, especially Great Lakes eutrophication models, traditionally used course segmentation schemes and relatively simple hydrodynamics to represent system behavior. Although many modelers have claimed success using such models, these representations can ...

A pulse-front-tilt–compensated streaked optical spectrometer with high throughput and picosecond time resolution

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

Katz, J., E-mail: jkat@lle.rochester.edu; Boni, R.; Rivlis, R.

A high-throughput, broadband optical spectrometer coupled to the Rochester optical streak system equipped with a Photonis P820 streak tube was designed to record time-resolved spectra with 1-ps time resolution. Spectral resolution of 0.8 nm is achieved over a wavelength coverage range of 480 to 580 nm, using a 300-groove/mm diffraction grating in conjunction with a pair of 225-mm-focal-length doublets operating at an f/2.9 aperture. Overall pulse-front tilt across the beam diameter generated by the diffraction grating is reduced by preferentially delaying discrete segments of the collimated input beam using a 34-element reflective echelon optic. The introduced delay temporally aligns themore » beam segments and the net pulse-front tilt is limited to the accumulation across an individual sub-element. The resulting spectrometer design balances resolving power and pulse-front tilt while maintaining high throughput.« less

Combining High Spatial Resolution Optical and LIDAR Data for Object-Based Image Classification

NASA Astrophysics Data System (ADS)

Li, R.; Zhang, T.; Geng, R.; Wang, L.

2018-04-01

In order to classify high spatial resolution images more accurately, in this research, a hierarchical rule-based object-based classification framework was developed based on a high-resolution image with airborne Light Detection and Ranging (LiDAR) data. The eCognition software is employed to conduct the whole process. In detail, firstly, the FBSP optimizer (Fuzzy-based Segmentation Parameter) is used to obtain the optimal scale parameters for different land cover types. Then, using the segmented regions as basic units, the classification rules for various land cover types are established according to the spectral, morphological and texture features extracted from the optical images, and the height feature from LiDAR respectively. Thirdly, the object classification results are evaluated by using the confusion matrix, overall accuracy and Kappa coefficients. As a result, a method using the combination of an aerial image and the airborne Lidar data shows higher accuracy.

Meta-shell Approach for Constructing Lightweight and High Resolution X-Ray Optics

NASA Technical Reports Server (NTRS)

McClelland, Ryan S.

2016-01-01

Lightweight and high resolution optics are needed for future space-based x-ray telescopes to achieve advances in high-energy astrophysics. Past missions such as Chandra and XMM-Newton have achieved excellent angular resolution using a full shell mirror approach. Other missions such as Suzaku and NuSTAR have achieved lightweight mirrors using a segmented approach. This paper describes a new approach, called meta-shells, which combines the fabrication advantages of segmented optics with the alignment advantages of full shell optics. Meta-shells are built by layering overlapping mirror segments onto a central structural shell. The resulting optic has the stiffness and rotational symmetry of a full shell, but with an order of magnitude greater collecting area. Several meta-shells so constructed can be integrated into a large x-ray mirror assembly by proven methods used for Chandra and XMM-Newton. The mirror segments are mounted to the meta-shell using a novel four point semi-kinematic mount. The four point mount deterministically locates the segment in its most performance sensitive degrees of freedom. Extensive analysis has been performed to demonstrate the feasibility of the four point mount and meta-shell approach. A mathematical model of a meta-shell constructed with mirror segments bonded at four points and subject to launch loads has been developed to determine the optimal design parameters, namely bond size, mirror segment span, and number of layers per meta-shell. The parameters of an example 1.3 m diameter mirror assembly are given including the predicted effective area. To verify the mathematical model and support opto-mechanical analysis, a detailed finite element model of a meta-shell was created. Finite element analysis predicts low gravity distortion and low thermal distortion. Recent results are discussed including Structural Thermal Optical Performance (STOP) analysis as well as vibration and shock testing of prototype meta-shells.

Embedded Implementation of VHR Satellite Image Segmentation

PubMed Central

Li, Chao; Balla-Arabé, Souleymane; Ginhac, Dominique; Yang, Fan

2016-01-01

Processing and analysis of Very High Resolution (VHR) satellite images provide a mass of crucial information, which can be used for urban planning, security issues or environmental monitoring. However, they are computationally expensive and, thus, time consuming, while some of the applications, such as natural disaster monitoring and prevention, require high efficiency performance. Fortunately, parallel computing techniques and embedded systems have made great progress in recent years, and a series of massively parallel image processing devices, such as digital signal processors or Field Programmable Gate Arrays (FPGAs), have been made available to engineers at a very convenient price and demonstrate significant advantages in terms of running-cost, embeddability, power consumption flexibility, etc. In this work, we designed a texture region segmentation method for very high resolution satellite images by using the level set algorithm and the multi-kernel theory in a high-abstraction C environment and realize its register-transfer level implementation with the help of a new proposed high-level synthesis-based design flow. The evaluation experiments demonstrate that the proposed design can produce high quality image segmentation with a significant running-cost advantage. PMID:27240370

Partial volume correction of brain perfusion estimates using the inherent signal data of time-resolved arterial spin labeling.

PubMed

Ahlgren, André; Wirestam, Ronnie; Petersen, Esben Thade; Ståhlberg, Freddy; Knutsson, Linda

2014-09-01

Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1 -weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1 -based segmentation method, with no spatial priors, and a modified PVC method based on linear regression. The presented approach thus avoids prior assumptions about the spatial distribution of brain compartments, while also avoiding coregistration between different image volumes. Simulations based on a digital phantom as well as in vivo measurements in 10 volunteers were used to assess the performance of the proposed segmentation approach. The simulation results indicated that QUASAR data can be used for robust partial volume estimation, and this was confirmed by the in vivo experiments. The proposed PVC method yielded probable perfusion maps, comparable to a reference method based on segmentation of a high-resolution morphological scan. Corrected gray matter (GM) perfusion was 47% higher than uncorrected values, suggesting a significant amount of PVEs in the data. Whereas the reference method failed to completely eliminate the dependence of perfusion estimates on the volume fraction, the novel approach produced GM perfusion values independent of GM volume fraction. The intra-subject coefficient of variation of corrected perfusion values was lowest for the proposed PVC method. As shown in this work, low-resolution partial volume estimation in connection with ASL perfusion estimation is feasible, and provides a promising tool for decoupling perfusion and tissue volume. Copyright © 2014 John Wiley & Sons, Ltd.

Dense deconvolution net: Multi path fusion and dense deconvolution for high resolution skin lesion segmentation.

PubMed

He, Xinzi; Yu, Zhen; Wang, Tianfu; Lei, Baiying; Shi, Yiyan

2018-01-01

Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated to form the global feature maps using skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s.

75 MHz Ultrasound Biomicroscopy of Anterior Segment of Eye

PubMed Central

Silverman, Ronald H.; Cannata, Jonathan; Shung, K. Kirk; Gal, Omer; Patel, Monica; Lloyd, Harriet O.; Feleppa, Ernest J.; Coleman, D. Jackson

2006-01-01

Very high frequency ultrasound (35–50 MHz) has had a significant impact upon clinical imaging of the anterior segment of the eye, offering an axial resolution as small as 30 μm. Higher frequencies, while potentially offering even finer resolution, are more affected by absorption in ocular tissues and even in the fluid coupling medium. Our aim was to develop and apply improved transducer technology utilizing frequencies beyond those routinely used for ultrasound biomicroscopy of the eye. A 75-MHz lithium niobate transducer with 2 mm aperture and 6 mm focal length was fabricated. We scanned the ciliary body and cornea of a human eye six years post-LASIK. Spectral parameter images were produced from the midband fit to local calibrated power spectra. Images were compared with those produced using a 35 MHz lithium niobate transducer of similar fractional bandwidth and focal ratio. The 75-MHz transducer was found to have a fractional bandwidth (−6 dB) of 61%. Images of the post-LASIK cornea showed higher stromal backscatter at 75 MHz than at 35 MHz. The improved lateral resolution resulted in better visualization of discontinuities in Bowman’s layer, indicative of microfolds or breaks occurring at the time of surgery. The LASIK surface was evident as a discontinuity in stromal backscatter between the stromal component of the flap and the residual stroma. The iris and ciliary body were visualized despite attenuation by the overlying sclera. Very high frequency ultrasound imaging of the anterior segment of the eye has been restricted to the 35–50 MHz band for over a decade. We showed that higher frequencies can be used in vivo to image the cornea and anterior segment. This improvement in resolution and high sensitivity to backscatter from the corneal stroma will provide benefits in clinical diagnostic imaging of the anterior segment. PMID:17147058

Texture analysis of high-resolution FLAIR images for TLE

NASA Astrophysics Data System (ADS)

Jafari-Khouzani, Kourosh; Soltanian-Zadeh, Hamid; Elisevich, Kost

2005-04-01

This paper presents a study of the texture information of high-resolution FLAIR images of the brain with the aim of determining the abnormality and consequently the candidacy of the hippocampus for temporal lobe epilepsy (TLE) surgery. Intensity and volume features of the hippocampus from FLAIR images of the brain have been previously shown to be useful in detecting the abnormal hippocampus in TLE. However, the small size of the hippocampus may limit the texture information. High-resolution FLAIR images show more details of the abnormal intensity variations of the hippocampi and therefore are more suitable for texture analysis. We study and compare the low and high-resolution FLAIR images of six epileptic patients. The hippocampi are segmented manually by an expert from T1-weighted MR images. Then the segmented regions are mapped on the corresponding FLAIR images for texture analysis. The 2-D wavelet transforms of the hippocampi are employed for feature extraction. We compare the ability of the texture features from regular and high-resolution FLAIR images to distinguish normal and abnormal hippocampi. Intracranial EEG results as well as surgery outcome are used as gold standard. The results show that the intensity variations of the hippocampus are related to the abnormalities in the TLE.

Optical imaging modalities: From design to diagnosis of skin cancer

NASA Astrophysics Data System (ADS)

Korde, Vrushali Raj

This study investigates three high resolution optical imaging modalities to better detect and diagnose skin cancer. The ideal high resolution optical imaging system can visualize pre-malignant tissue growth non-invasively with resolution comparable to histology. I examined 3 modalities which approached this goal. The first method examined was high magnification microscopy of thin stained tissue sections, together with a statistical analysis of nuclear chromatin patterns termed Karyometry. This method has subcellular resolution, but it necessitates taking a biopsy at the desired tissue site and imaging the tissue ex-vivo. My part of this study was to develop an automated nuclear segmentation algorithm to segment cell nuclei in skin histology images for karyometric analysis. The results of this algorithm were compared to hand segmented cell nuclei in the same images, and it was concluded that the automated segmentations can be used for karyometric analysis. The second optical imaging modality I investigated was Optical Coherence Tomography (OCT). OCT is analogous to ultrasound, in which sound waves are delivered into the body and the echo time and reflected signal magnitude are measured. Due to the fast speed of light and detector temporal integration times, low coherence interferometry is needed to gate the backscattered light. OCT acquires cross sectional images, and has an axial resolution of 1-15 mum (depending on the source bandwidth) and a lateral resolution of 10-20 mum (depending on the sample arm optics). While it is not capable of achieving subcellular resolution, it is a non-invasive imaging modality. OCT was used in this study to evaluate skin along a continuum from normal to sun damaged to precancer. I developed algorithms to detect statistically significant differences between images of sun protected and sun damaged skin, as well as between undiseased and precancerous skin. An Optical Coherence Microscopy (OCM) endoscope was developed in the third portion of this study. OCM is a high resolution en-face imaging modality. It is a hybrid system that combines the principles of confocal microscopy with coherence gating to provide an increased imaging depth. It can also be described as an OCT system with a high NA objective. Similar to OCT, the axial resolution is determined by the source center wavelength and bandwidth. The NA of the sample arm optics determines the lateral resolution, usually on the order of 1-5 mum. My effort on this system was to develop a handheld endoscope. To my knowledge, an OCM endoscope has not been developed prior to this work. An image of skin was taken as a proof of concept. This rigid handheld OCM endoscope will be useful for applications ranging from minimally invasive surgical imaging to non-invasively assessing dysplasia and sun damage in skin.

High-resolution ultrasound imaging of the eye – a review

PubMed Central

Silverman, Ronald H

2009-01-01

This report summarizes the physics, technology and clinical application of ultrasound biomicroscopy (UBM) of the eye, in which frequencies of 35 MHz and above provide over a threefold improvement in resolution compared with conventional ophthalmic ultrasound systems. UBM allows imaging of anatomy and pathology involving the anterior segment, including regions obscured by overlying optically opaque anatomic or pathologic structures. UBM provides diagnostically significant information in conditions such as glaucoma, cysts and neoplasms, trauma and foreign bodies. UBM also can provide crucial biometric information regarding anterior segment structures, including the cornea and its constituent layers and the anterior and posterior chambers. Although UBM has now been in use for over 15 years, new technologies, including transducer arrays, pulse encoding and combination of ultrasound with light, offer the potential for significant advances in high-resolution diagnostic imaging of the eye. PMID:19138310

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

High-resolution ultrasound imaging of the eye - a review.

PubMed

Silverman, Ronald H

2009-01-01

This report summarizes the physics, technology and clinical application of ultrasound biomicroscopy (UBM) of the eye, in which frequencies of 35 MHz and above provide over a threefold improvement in resolution compared with conventional ophthalmic ultrasound systems. UBM allows imaging of anatomy and pathology involving the anterior segment, including regions obscured by overlying optically opaque anatomic or pathologic structures. UBM provides diagnostically significant information in conditions such as glaucoma, cysts and neoplasms, trauma and foreign bodies. UBM also can provide crucial biometric information regarding anterior segment structures, including the cornea and its constituent layers and the anterior and posterior chambers. Although UBM has now been in use for over 15 years, new technologies, including transducer arrays, pulse encoding and combination of ultrasound with light, offer the potential for significant advances in high-resolution diagnostic imaging of the eye.

IMRT sequencing for a six-bank multi-leaf system.

PubMed

Topolnjak, R; van der Heide, U A; Lagendijk, J J W

2005-05-07

In this study, we present a sequencer for delivering step-and-shoot IMRT using a six-bank multi-leaf system. Such a system was proposed earlier and combines a high-resolution field-shaping ability with a large field size. It consists of three layers of two opposing leaf banks with 1 cm leaves. The layers are rotated relative to each other at 60 degrees . A low-resolution mode of sequencing is achieved by using one layer of leaves as primary MLC, while the other two are used to improve back-up collimation. For high-resolution sequencing, an algorithm is presented that creates segments shaped by all six banks. Compared to a hypothetical mini-MLC with 0.4 cm leaves, a similar performance can be achieved, but a trade-off has to be made between accuracy and the number of segments.

Change detection of polarimetric SAR images based on the KummerU Distribution

NASA Astrophysics Data System (ADS)

Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

2014-11-01

In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

An Improved Unsupervised Image Segmentation Evaluation Approach Based on - and Over-Segmentation Aware

NASA Astrophysics Data System (ADS)

Su, Tengfei

2018-04-01

In this paper, an unsupervised evaluation scheme for remote sensing image segmentation is developed. Based on a method called under- and over-segmentation aware (UOA), the new approach is improved by overcoming the defect in the part of estimating over-segmentation error. Two cases of such error-prone defect are listed, and edge strength is employed to devise a solution to this issue. Two subsets of high resolution remote sensing images were used to test the proposed algorithm, and the experimental results indicate its superior performance, which is attributed to its improved OSE detection model.

Automated segmentation of pulmonary structures in thoracic computed tomography scans: a review

NASA Astrophysics Data System (ADS)

van Rikxoort, Eva M.; van Ginneken, Bram

2013-09-01

Computed tomography (CT) is the modality of choice for imaging the lungs in vivo. Sub-millimeter isotropic images of the lungs can be obtained within seconds, allowing the detection of small lesions and detailed analysis of disease processes. The high resolution of thoracic CT and the high prevalence of lung diseases require a high degree of automation in the analysis pipeline. The automated segmentation of pulmonary structures in thoracic CT has been an important research topic for over a decade now. This systematic review provides an overview of current literature. We discuss segmentation methods for the lungs, the pulmonary vasculature, the airways, including airway tree construction and airway wall segmentation, the fissures, the lobes and the pulmonary segments. For each topic, the current state of the art is summarized, and topics for future research are identified.

A research of road centerline extraction algorithm from high resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhang, Yushan; Xu, Tingfa

2017-09-01

Satellite remote sensing technology has become one of the most effective methods for land surface monitoring in recent years, due to its advantages such as short period, large scale and rich information. Meanwhile, road extraction is an important field in the applications of high resolution remote sensing images. An intelligent and automatic road extraction algorithm with high precision has great significance for transportation, road network updating and urban planning. The fuzzy c-means (FCM) clustering segmentation algorithms have been used in road extraction, but the traditional algorithms did not consider spatial information. An improved fuzzy C-means clustering algorithm combined with spatial information (SFCM) is proposed in this paper, which is proved to be effective for noisy image segmentation. Firstly, the image is segmented using the SFCM. Secondly, the segmentation result is processed by mathematical morphology to remover the joint region. Thirdly, the road centerlines are extracted by morphology thinning and burr trimming. The average integrity of the centerline extraction algorithm is 97.98%, the average accuracy is 95.36% and the average quality is 93.59%. Experimental results show that the proposed method in this paper is effective for road centerline extraction.

3D Segmentation of Maxilla in Cone-beam Computed Tomography Imaging Using Base Invariant Wavelet Active Shape Model on Customized Two-manifold Topology

PubMed Central

Chang, Yu-Bing; Xia, James J.; Yuan, Peng; Kuo, Tai-Hong; Xiong, Zixiang; Gateno, Jaime; Zhou, Xiaobo

2013-01-01

Recent advances in cone-beam computed tomography (CBCT) have rapidly enabled widepsread applications of dentomaxillofacial imaging and orthodontic practices in the past decades due to its low radiation dose, high spatial resolution, and accessibility. However, low contrast resolution in CBCT image has become its major limitation in building skull models. Intensive hand-segmentation is usually required to reconstruct the skull models. One of the regions affected by this limitation the most is the thin bone images. This paper presents a novel segmentation approach based on wavelet density model (WDM) for a particular interest in the outer surface of anterior wall of maxilla. Nineteen CBCT datasets are used to conduct two experiments. This mode-based segmentation approach is validated and compared with three different segmentation approaches. The results show that the performance of this model-based segmentation approach is better than those of the other approaches. It can achieve 0.25 ± 0.2mm of surface error from ground truth of bone surface. PMID:23694914

Object segmentation using graph cuts and active contours in a pyramidal framework

NASA Astrophysics Data System (ADS)

Subudhi, Priyambada; Mukhopadhyay, Susanta

2018-03-01

Graph cuts and active contours are two very popular interactive object segmentation techniques in the field of computer vision and image processing. However, both these approaches have their own well-known limitations. Graph cut methods perform efficiently giving global optimal segmentation result for smaller images. However, for larger images, huge graphs need to be constructed which not only takes an unacceptable amount of memory but also increases the time required for segmentation to a great extent. On the other hand, in case of active contours, initial contour selection plays an important role in the accuracy of the segmentation. So a proper selection of initial contour may improve the complexity as well as the accuracy of the result. In this paper, we have tried to combine these two approaches to overcome their above-mentioned drawbacks and develop a fast technique of object segmentation. Here, we have used a pyramidal framework and applied the mincut/maxflow algorithm on the lowest resolution image with the least number of seed points possible which will be very fast due to the smaller size of the image. Then, the obtained segmentation contour is super-sampled and and worked as the initial contour for the next higher resolution image. As the initial contour is very close to the actual contour, so fewer number of iterations will be required for the convergence of the contour. The process is repeated for all the high-resolution images and experimental results show that our approach is faster as well as memory efficient as compare to both graph cut or active contour segmentation alone.

Visualizing the root-PDL-bone interface using high-resolution microtomography

NASA Astrophysics Data System (ADS)

Dalstra, Michel; Cattaneo, Paolo M.; Herzen, Julia; Beckmann, Felix

2008-08-01

The root/periodontal ligament/bone (RPB) interface is important for a correct understanding of the load transfer mechanism of masticatory forces and orthodontic loads. It is the aim of this study to assess the three-dimensional structure of the RPB interface using high-resolution microtomography. A human posterior jaw segment, obtained at autopsy from a 22-year old male donor was first scanned using a tomograph at the HASYLAB/DESY synchrotron facility (Hamburg, Germany) at 31μm resolution. Afterwards the first molar and its surrounding bone were removed with a 10mm hollow core drill. From this cylindrical sample smaller samples were drilled out in the buccolingual direction with a 1.5mm hollow core drill. These samples were scanned at 4μm resolution. The scans of the entire segment showed alveolar bone with a thin lamina dura, supported by an intricate trabecular network. Although featuring numerous openings between the PDL and the bone marrow on the other side to allow blood vessels to transverse, the lamina dura seems smooth at this resolution. First at high resolution, however, it becomes evident that it is irregular with bony spiculae and pitted surfaces. Therefore the stresses in the bone during physiological or orthodontic loading are much higher than expected from a smooth continuous alveolus.

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.

ST-segment resolution with bivalirudin versus heparin and routine glycoprotein IIb/IIIa inhibitors started in the ambulance in ST-segment elevation myocardial infarction patients transported for primary percutaneous coronary intervention: The EUROMAX ST-segment resolution substudy.

PubMed

Van't Hof, Arnoud; Giannini, Francesco; Ten Berg, Jurrien; Tolsma, Rudolf; Clemmensen, Peter; Bernstein, Debra; Coste, Pierre; Goldstein, Patrick; Zeymer, Uwe; Hamm, Christian; Deliargyris, Efthymios; Steg, Philippe G

2017-08-01

Myocardial reperfusion after primary percutaneous coronary intervention (PCI) can be assessed by the extent of post-procedural ST-segment resolution. The European Ambulance Acute Coronary Syndrome Angiography (EUROMAX) trial compared pre-hospital bivalirudin and pre-hospital heparin or enoxaparin with or without GPIIb/IIIa inhibitors (GPIs) in primary PCI. This nested substudy was performed in centres routinely using pre-hospital GPI in order to compare the impact of randomized treatments on ST-resolution after primary PCI. Residual cumulative ST-segment deviation on the single one hour post-procedure electrocardiogram (ECG) was assessed by an independent core laboratory and was the primary endpoint. It was calculated that 762 evaluable patients were needed to show non-inferiority (85% power, alpha 2.5%) between randomized treatments. A total of 871 participated with electrocardiographic data available in 824 patients (95%). Residual ST-segment deviation one hour after PCI was 3.8±4.9 mm versus 3.9±5.2 mm for bivalirudin and heparin+GPI, respectively ( p=0.0019 for non-inferiority). Overall, there were no differences between randomized treatments in any measures of ST-segment resolution either before or after the index procedure. Pre-hospital treatment with bivalirudin is non-inferior to pre-hospital heparin + GPI with regard to residual ST-segment deviation or ST-segment resolution, reflecting comparable myocardial reperfusion with the two strategies.

Co/Au multisegmented nanowires: a 3D array of magnetostatically coupled nanopillars

NASA Astrophysics Data System (ADS)

Bran, C.; Ivanov, Yu P.; Kosel, J.; Chubykalo-Fesenko, O.; Vazquez, M.

2017-03-01

Arrays of multisegmented Co/Au nanowires with designed segment lengths and diameters have been prepared by electrodeposition into aluminum oxide templates. The high quality of the Co/Au interface and the crystallographic structure of Co segments have determined by high-resolution transmission electron microscopy. Magnetic hysteresis loop measurements show larger coercivity and squareness of multisegmented nanowires as compared to single segment Co nanowires. The complementary micromagnetic simulations are in good agreement with the experimental results, confirming that the magnetic behavior is defined mainly by magnetostatic coupling between different segments. The proposed structure constitutes an innovative route towards a 3D array of synchronized magnetic nano-oscillators with large potential in nanoelectronics.

A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images.

PubMed

Janowczyk, Andrew; Doyle, Scott; Gilmore, Hannah; Madabhushi, Anant

2018-01-01

Deep learning (DL) has recently been successfully applied to a number of image analysis problems. However, DL approaches tend to be inefficient for segmentation on large image data, such as high-resolution digital pathology slide images. For example, typical breast biopsy images scanned at 40× magnification contain billions of pixels, of which usually only a small percentage belong to the class of interest. For a typical naïve deep learning scheme, parsing through and interrogating all the image pixels would represent hundreds if not thousands of hours of compute time using high performance computing environments. In this paper, we present a resolution adaptive deep hierarchical (RADHicaL) learning scheme wherein DL networks at lower resolutions are leveraged to determine if higher levels of magnification, and thus computation, are necessary to provide precise results. We evaluate our approach on a nuclear segmentation task with a cohort of 141 ER+ breast cancer images and show we can reduce computation time on average by about 85%. Expert annotations of 12,000 nuclei across these 141 images were employed for quantitative evaluation of RADHicaL. A head-to-head comparison with a naïve DL approach, operating solely at the highest magnification, yielded the following performance metrics: .9407 vs .9854 Detection Rate, .8218 vs .8489 F -score, .8061 vs .8364 true positive rate and .8822 vs 0.8932 positive predictive value. Our performance indices compare favourably with state of the art nuclear segmentation approaches for digital pathology images.

TU-A-9A-06: Semi-Automatic Segmentation of Skin Cancer in High-Frequency Ultrasound Images: Initial Comparison with Histology

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

Gao, Y; Li, X; Fishman, K

Purpose: In skin-cancer radiotherapy, the assessment of skin lesion is challenging, particularly with important features such as the depth and width hard to determine. The aim of this study is to develop interative segmentation method to delineate tumor boundary using high-frequency ultrasound images and to correlate the segmentation results with the histopathological tumor dimensions. Methods: We analyzed 6 patients who comprised a total of 10 skin lesions involving the face, scalp, and hand. The patient’s various skin lesions were scanned using a high-frequency ultrasound system (Episcan, LONGPORT, INC., PA, U.S.A), with a 30-MHz single-element transducer. The lateral resolution was 14.6more » micron and the axial resolution was 3.85 micron for the ultrasound image. Semiautomatic image segmentation was performed to extract the cancer region, using a robust statistics driven active contour algorithm. The corresponding histology images were also obtained after tumor resection and served as the reference standards in this study. Results: Eight out of the 10 lesions are successfully segmented. The ultrasound tumor delineation correlates well with the histology assessment, in all the measurements such as depth, size, and shape. The depths measured by the ultrasound have an average of 9.3% difference comparing with that in the histology images. The remaining 2 cases suffered from the situation of mismatching between pathology and ultrasound images. Conclusion: High-frequency ultrasound is a noninvasive, accurate and easy-accessible modality to image skin cancer. Our segmentation method, combined with high-frequency ultrasound technology, provides a promising tool to estimate the extent of the tumor to guide the radiotherapy procedure and monitor treatment response.« less

Automated Segmentation of High-Resolution Photospheric Images of Active Regions

NASA Astrophysics Data System (ADS)

Yang, Meng; Tian, Yu; Rao, Changhui

2018-02-01

Due to the development of ground-based, large-aperture solar telescopes with adaptive optics (AO) resulting in increasing resolving ability, more accurate sunspot identifications and characterizations are required. In this article, we have developed a set of automated segmentation methods for high-resolution solar photospheric images. Firstly, a local-intensity-clustering level-set method is applied to roughly separate solar granulation and sunspots. Then reinitialization-free level-set evolution is adopted to adjust the boundaries of the photospheric patch; an adaptive intensity threshold is used to discriminate between umbra and penumbra; light bridges are selected according to their regional properties from candidates produced by morphological operations. The proposed method is applied to the solar high-resolution TiO 705.7-nm images taken by the 151-element AO system and Ground-Layer Adaptive Optics prototype system at the 1-m New Vacuum Solar Telescope of the Yunnan Observatory. Experimental results show that the method achieves satisfactory robustness and efficiency with low computational cost on high-resolution images. The method could also be applied to full-disk images, and the calculated sunspot areas correlate well with the data given by the National Oceanic and Atmospheric Administration (NOAA).

Semantic Segmentation of Forest Stands of Pure Species as a Global Optimization Problem

NASA Astrophysics Data System (ADS)

Dechesne, C.; Mallet, C.; Le Bris, A.; Gouet-Brunet, V.

2017-05-01

Forest stand delineation is a fundamental task for forest management purposes, that is still mainly manually performed through visual inspection of geospatial (very) high spatial resolution images. Stand detection has been barely addressed in the literature which has mainly focused, in forested environments, on individual tree extraction and tree species classification. From a methodological point of view, stand detection can be considered as a semantic segmentation problem. It offers two advantages. First, one can retrieve the dominant tree species per segment. Secondly, one can benefit from existing low-level tree species label maps from the literature as a basis for high-level object extraction. Thus, the semantic segmentation issue becomes a regularization issue in a weakly structured environment and can be formulated in an energetical framework. This papers aims at investigating which regularization strategies of the literature are the most adapted to delineate and classify forest stands of pure species. Both airborne lidar point clouds and multispectral very high spatial resolution images are integrated for that purpose. The local methods (such as filtering and probabilistic relaxation) are not adapted for such problem since the increase of the classification accuracy is below 5%. The global methods, based on an energy model, tend to be more efficient with an accuracy gain up to 15%. The segmentation results using such models have an accuracy ranging from 96% to 99%.

A scalable method to improve gray matter segmentation at ultra high field MRI.

PubMed

Gulban, Omer Faruk; Schneider, Marian; Marquardt, Ingo; Haast, Roy A M; De Martino, Federico

2018-01-01

High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data.

A scalable method to improve gray matter segmentation at ultra high field MRI

PubMed Central

De Martino, Federico

2018-01-01

High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data. PMID:29874295

WCPP-THE WOLF PLOTTING AND CONTOURING PACKAGE

NASA Technical Reports Server (NTRS)

Masaki, G. T.

1994-01-01

The WOLF Contouring and Plotting Package provides the user with a complete general purpose plotting and contouring capability. This package is a complete system for producing line printer, SC4020, Gerber, Calcomp, and SD4060 plots. The package has been designed to be highly flexible and easy to use. Any plot from a quick simple plot (which requires only one call to the package) to highly sophisticated plots (including motion picture plots) can be easily generated with only a basic knowledge of FORTRAN and the plot commands. Anyone designing a software system that requires plotted output will find that this package offers many advantages over the standard hardware support packages available. The WCPP package is divided into a plot segment and a contour segment. The plot segment can produce output for any combination of line printer, SC4020, Gerber, Calcomp, and SD4060 plots. The line printer plots allow the user to have plots available immediately after a job is run at a low cost. Although the resolution of line printer plots is low, the quick results allows the user to judge if a high resolution plot of a particular run is desirable. The SC4020 and SD4060 provide high speed high resolution cathode ray plots with film and hard copy output available. The Gerber and Calcomp plotters provide very high quality (of publishable quality) plots of good resolution. Being bed or drum type plotters, the Gerber and Calcomp plotters are usually slow and not suited for large volume plotting. All output for any or all of the plotters can be produced simultaneously. The types of plots supported are: linear, semi-log, log-log, polar, tabular data using the FORTRAN WRITE statement, 3-D perspective linear, and affine transformations. The labeling facility provides for horizontal labels, vertical labels, diagonal labels, vector characters of a requested size (special character fonts are easily implemented), and rotated letters. The gridding routines label the grid lines according to user specification. Special line features include multiple lines, dashed lines, and tic marks. The contour segment of this package is a collection of subroutines which can be used to produce contour plots and perform related functions. The package can contour any data which can be placed on a grid or data which is regularly spaced, including any general affine or polar grid data. The package includes routines which will grid random data. Contour levels can be specified at any values desired. Input data can be smoothed with undefined points being acceptable where data is unreliable or unknown. Plots which are extremely large or detailed can be automatically output in parts to improve resolution or overcome plotter size limitations. The contouring segment uses the plot segment for actual plotting, thus all the features described for the plotting segment are available to the user of the contouring segment. Included with this package are two data bases for producing world map plots in Mercator projection. One data base provides just continent outlines and another provides continent outlines and national borders in great detail. This package is written in FORTRAN IV and IBM OS ASSEMBLER and has been implemented on an IBM 360 with a central memory requirement of approximately 140K of 8 bit bytes. The ASSEMBLER routines are basic plotter interface routines. The WCPP package was developed in 1972.

Magnetic resonance imaging of water ascent in embolized xylem vessels of grapevine stem segments

Treesearch

Mingtao Wang; Melvin T. Tyree; Roderick E. Wasylishen

2013-01-01

Temporal and spatial information about water refilling of embolized xylem vessels and the rate of water ascent in these vessels is critical for understanding embolism repair in intact living vascular plants. High-resolution 1H magnetic resonance imaging (MRI) experiments have been performed on embolized grapevine stem segments while they were...

Attention Modifies Spatial Resolution According to Task Demands.

PubMed

Barbot, Antoine; Carrasco, Marisa

2017-03-01

How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands.

Attention Modifies Spatial Resolution According to Task Demands

PubMed Central

Barbot, Antoine; Carrasco, Marisa

2017-01-01

How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands. PMID:28118103

Continuous Beam Steering From a Segmented Liquid Crystal Optical Phased Array

NASA Technical Reports Server (NTRS)

Titus, Charles M.; Pouch, John; Nguyen, Hung; Miranda, Felix; Bos, Philip J.

2002-01-01

Optical communications to and from deep space probes will require beams possessing divergence on the order of a microradian, and must be steered with sub-microradian precision. Segmented liquid crystal spatial phase modulators, a type of optical phased array, are considered for this ultra-high resolution beam steering. It is shown here that in an ideal device of this type, there are ultimately no restrictions on the angular resolution. Computer simulations are used to obtain that result, and to analyze the influence of beam truncation and substrate flatness on the performance of this type of device.

Continuous Beam Steering From A Segmented Liquid Crystal Optical Phased Array

NASA Technical Reports Server (NTRS)

Pouch, John; Nguyen, Hung; Miranda, Felix; Titus, Charles M.; Bos, Philip J.

2002-01-01

Optical communications to and from deep space probes will require beams possessing divergence on the order of a microradian, and must be steered with sub-microradian precision. Segmented liquid crystal spatial phase modulators, a type of optical phased array, are considered for this ultra-high resolution beam steering. It is shown here that in an ideal device of this type, there are ultimately no restrictions on the angular resolution. Computer simulations are used to obtain that result, and to analyze the influence of beam truncation and substrate flatness on the performance of this type of device.

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

PubMed

Belgiu, Mariana; Dr Guţ, Lucian

2014-10-01

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

Automated 3D closed surface segmentation: application to vertebral body segmentation in CT images.

PubMed

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

2016-05-01

A fully automated segmentation algorithm, progressive surface resolution (PSR), is presented in this paper to determine the closed surface of approximately convex blob-like structures that are common in biomedical imaging. The PSR algorithm was applied to the cortical surface segmentation of 460 vertebral bodies on 46 low-dose chest CT images, which can be potentially used for automated bone mineral density measurement and compression fracture detection. The target surface is realized by a closed triangular mesh, which thereby guarantees the enclosure. The surface vertices of the triangular mesh representation are constrained along radial trajectories that are uniformly distributed in 3D angle space. The segmentation is accomplished by determining for each radial trajectory the location of its intersection with the target surface. The surface is first initialized based on an input high confidence boundary image and then resolved progressively based on a dynamic attraction map in an order of decreasing degree of evidence regarding the target surface location. For the visual evaluation, the algorithm achieved acceptable segmentation for 99.35 % vertebral bodies. Quantitative evaluation was performed on 46 vertebral bodies and achieved overall mean Dice coefficient of 0.939 (with max [Formula: see text] 0.957, min [Formula: see text] 0.906 and standard deviation [Formula: see text] 0.011) using manual annotations as the ground truth. Both visual and quantitative evaluations demonstrate encouraging performance of the PSR algorithm. This novel surface resolution strategy provides uniform angular resolution for the segmented surface with computation complexity and runtime that are linearly constrained by the total number of vertices of the triangular mesh representation.

Unsupervised motion-based object segmentation refined by color

NASA Astrophysics Data System (ADS)

Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

2003-06-01

For various applications, such as data compression, structure from motion, medical imaging and video enhancement, there is a need for an algorithm that divides video sequences into independently moving objects. Because our focus is on video enhancement and structure from motion for consumer electronics, we strive for a low complexity solution. For still images, several approaches exist based on colour, but these lack in both speed and segmentation quality. For instance, colour-based watershed algorithms produce a so-called oversegmentation with many segments covering each single physical object. Other colour segmentation approaches exist which somehow limit the number of segments to reduce this oversegmentation problem. However, this often results in inaccurate edges or even missed objects. Most likely, colour is an inherently insufficient cue for real world object segmentation, because real world objects can display complex combinations of colours. For video sequences, however, an additional cue is available, namely the motion of objects. When different objects in a scene have different motion, the motion cue alone is often enough to reliably distinguish objects from one another and the background. However, because of the lack of sufficient resolution of efficient motion estimators, like the 3DRS block matcher, the resulting segmentation is not at pixel resolution, but at block resolution. Existing pixel resolution motion estimators are more sensitive to noise, suffer more from aperture problems or have less correspondence to the true motion of objects when compared to block-based approaches or are too computationally expensive. From its tendency to oversegmentation it is apparent that colour segmentation is particularly effective near edges of homogeneously coloured areas. On the other hand, block-based true motion estimation is particularly effective in heterogeneous areas, because heterogeneous areas improve the chance a block is unique and thus decrease the chance of the wrong position producing a good match. Consequently, a number of methods exist which combine motion and colour segmentation. These methods use colour segmentation as a base for the motion segmentation and estimation or perform an independent colour segmentation in parallel which is in some way combined with the motion segmentation. The presented method uses both techniques to complement each other by first segmenting on motion cues and then refining the segmentation with colour. To our knowledge few methods exist which adopt this approach. One example is te{meshrefine}. This method uses an irregular mesh, which hinders its efficient implementation in consumer electronics devices. Furthermore, the method produces a foreground/background segmentation, while our applications call for the segmentation of multiple objects. NEW METHOD As mentioned above we start with motion segmentation and refine the edges of this segmentation with a pixel resolution colour segmentation method afterwards. There are several reasons for this approach: + Motion segmentation does not produce the oversegmentation which colour segmentation methods normally produce, because objects are more likely to have colour discontinuities than motion discontinuities. In this way, the colour segmentation only has to be done at the edges of segments, confining the colour segmentation to a smaller part of the image. In such a part, it is more likely that the colour of an object is homogeneous. + This approach restricts the computationally expensive pixel resolution colour segmentation to a subset of the image. Together with the very efficient 3DRS motion estimation algorithm, this helps to reduce the computational complexity. + The motion cue alone is often enough to reliably distinguish objects from one another and the background. To obtain the motion vector fields, a variant of the 3DRS block-based motion estimator which analyses three frames of input was used. The 3DRS motion estimator is known for its ability to estimate motion vectors which closely resemble the true motion. BLOCK-BASED MOTION SEGMENTATION As mentioned above we start with a block-resolution segmentation based on motion vectors. The presented method is inspired by the well-known K-means segmentation method te{K-means}. Several other methods (e.g. te{kmeansc}) adapt K-means for connectedness by adding a weighted shape-error. This adds the additional difficulty of finding the correct weights for the shape-parameters. Also, these methods often bias one particular pre-defined shape. The presented method, which we call K-regions, encourages connectedness because only blocks at the edges of segments may be assigned to another segment. This constrains the segmentation method to such a degree that it allows the method to use least squares for the robust fitting of affine motion models for each segment. Contrary to te{parmkm}, the segmentation step still operates on vectors instead of model parameters. To make sure the segmentation is temporally consistent, the segmentation of the previous frame will be used as initialisation for every new frame. We also present a scheme which makes the algorithm independent of the initially chosen amount of segments. COLOUR-BASED INTRA-BLOCK SEGMENTATION The block resolution motion-based segmentation forms the starting point for the pixel resolution segmentation. The pixel resolution segmentation is obtained from the block resolution segmentation by reclassifying pixels only at the edges of clusters. We assume that an edge between two objects can be found in either one of two neighbouring blocks that belong to different clusters. This assumption allows us to do the pixel resolution segmentation on each pair of such neighbouring blocks separately. Because of the local nature of the segmentation, it largely avoids problems with heterogeneously coloured areas. Because no new segments are introduced in this step, it also does not suffer from oversegmentation problems. The presented method has no problems with bifurcations. For the pixel resolution segmentation itself we reclassify pixels such that we optimize an error norm which favour similarly coloured regions and straight edges. SEGMENTATION MEASURE To assist in the evaluation of the proposed algorithm we developed a quality metric. Because the problem does not have an exact specification, we decided to define a ground truth output which we find desirable for a given input. We define the measure for the segmentation quality as being how different the segmentation is from the ground truth. Our measure enables us to evaluate oversegmentation and undersegmentation seperately. Also, it allows us to evaluate which parts of a frame suffer from oversegmentation or undersegmentation. The proposed algorithm has been tested on several typical sequences. CONCLUSIONS In this abstract we presented a new video segmentation method which performs well in the segmentation of multiple independently moving foreground objects from each other and the background. It combines the strong points of both colour and motion segmentation in the way we expected. One of the weak points is that the segmentation method suffers from undersegmentation when adjacent objects display similar motion. In sequences with detailed backgrounds the segmentation will sometimes display noisy edges. Apart from these results, we think that some of the techniques, and in particular the K-regions technique, may be useful for other two-dimensional data segmentation problems.

High-resolution, anthropomorphic, computational breast phantom: fusion of rule-based structures with patient-based anatomy

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Gong, Xiaolin; Graff, Christian G.; Santana, Maira; Sturgeon, Gregory M.; Sauer, Thomas J.; Zeng, Rongping; Glick, Stephen J.; Lo, Joseph Y.

2017-03-01

While patient-based breast phantoms are realistic, they are limited by low resolution due to the image acquisition and segmentation process. The purpose of this study is to restore the high frequency components for the patient-based phantoms by adding power law noise (PLN) and breast structures generated based on mathematical models. First, 3D radial symmetric PLN with β=3 was added at the boundary between adipose and glandular tissue to connect broken tissue and create a high frequency contour of the glandular tissue. Next, selected high-frequency features from the FDA rule-based computational phantom (Cooper's ligaments, ductal network, and blood vessels) were fused into the phantom. The effects of enhancement in this study were demonstrated by 2D mammography projections and digital breast tomosynthesis (DBT) reconstruction volumes. The addition of PLN and rule-based models leads to a continuous decrease in β. The new β is 2.76, which is similar to what typically found for reconstructed DBT volumes. The new combined breast phantoms retain the realism from segmentation and gain higher resolution after restoration.

Object-based image analysis for cadastral mapping using satellite images

NASA Astrophysics Data System (ADS)

Kohli, D.; Crommelinck, S.; Bennett, R.; Koeva, M.; Lemmen, C.

2017-10-01

Cadasters together with land registry form a core ingredient of any land administration system. Cadastral maps comprise of the extent, ownership and value of land which are essential for recording and updating land records. Traditional methods for cadastral surveying and mapping often prove to be labor, cost and time intensive: alternative approaches are thus being researched for creating such maps. With the advent of very high resolution (VHR) imagery, satellite remote sensing offers a tremendous opportunity for (semi)-automation of cadastral boundaries detection. In this paper, we explore the potential of object-based image analysis (OBIA) approach for this purpose by applying two segmentation methods, i.e. MRS (multi-resolution segmentation) and ESP (estimation of scale parameter) to identify visible cadastral boundaries. Results show that a balance between high percentage of completeness and correctness is hard to achieve: a low error of commission often comes with a high error of omission. However, we conclude that the resulting segments/land use polygons can potentially be used as a base for further aggregation into tenure polygons using participatory mapping.

Ultrasound biomicroscopy. High-frequency ultrasound imaging of the eye at microscopic resolution.

PubMed

Pavlin, C J; Foster, F S

1998-11-01

UBM presents us with a new method of imaging the anterior segment of the eye at high resolution. Its strengths lie in its ability to produce cross-sections of the living eye at microscopic resolution without violating the integrity of the globe. UBM, although lacking the resolution of optical microscopy, gives us images in living eyes without affecting the internal relationships of the structures imaged. There are many other applications of this new imaging method. Examples of other uses include imaging adnexal pathology, assessing corneal changes with refractive surgery, the assessment of trauma, and determination of intraocular lens position.

Reproducibility of myelin content-based human habenula segmentation at 3 Tesla.

PubMed

Kim, Joo-Won; Naidich, Thomas P; Joseph, Joshmi; Nair, Divya; Glasser, Matthew F; O'halloran, Rafael; Doucet, Gaelle E; Lee, Won Hee; Krinsky, Hannah; Paulino, Alejandro; Glahn, David C; Anticevic, Alan; Frangou, Sophia; Xu, Junqian

2018-03-26

In vivo morphological study of the human habenula, a pair of small epithalamic nuclei adjacent to the dorsomedial thalamus, has recently gained significant interest for its role in reward and aversion processing. However, segmenting the habenula from in vivo magnetic resonance imaging (MRI) is challenging due to the habenula's small size and low anatomical contrast. Although manual and semi-automated habenula segmentation methods have been reported, the test-retest reproducibility of the segmented habenula volume and the consistency of the boundaries of habenula segmentation have not been investigated. In this study, we evaluated the intra- and inter-site reproducibility of in vivo human habenula segmentation from 3T MRI (0.7-0.8 mm isotropic resolution) using our previously proposed semi-automated myelin contrast-based method and its fully-automated version, as well as a previously published manual geometry-based method. The habenula segmentation using our semi-automated method showed consistent boundary definition (high Dice coefficient, low mean distance, and moderate Hausdorff distance) and reproducible volume measurement (low coefficient of variation). Furthermore, the habenula boundary in our semi-automated segmentation from 3T MRI agreed well with that in the manual segmentation from 7T MRI (0.5 mm isotropic resolution) of the same subjects. Overall, our proposed semi-automated habenula segmentation showed reliable and reproducible habenula localization, while its fully-automated version offers an efficient way for large sample analysis. © 2018 Wiley Periodicals, Inc.

Segmented X-Ray Optics for Future Space Telescopes

NASA Technical Reports Server (NTRS)

McClelland, Ryan S.

2013-01-01

Lightweight and high resolution mirrors are needed for future space-based X-ray telescopes to achieve advances in high-energy astrophysics. The slumped glass mirror technology in development at NASA GSFC aims to build X-ray mirror modules with an area to mass ratio of approx.17 sq cm/kg at 1 keV and a resolution of 10 arc-sec Half Power Diameter (HPD) or better at an affordable cost. As the technology nears the performance requirements, additional engineering effort is needed to ensure the modules are compatible with space-flight. This paper describes Flight Mirror Assembly (FMA) designs for several X-ray astrophysics missions studied by NASA and defines generic driving requirements and subsequent verification tests necessary to advance technology readiness for mission implementation. The requirement to perform X-ray testing in a horizontal beam, based on the orientation of existing facilities, is particularly burdensome on the mirror technology, necessitating mechanical over-constraint of the mirror segments and stiffening of the modules in order to prevent self-weight deformation errors from dominating the measured performance. This requirement, in turn, drives the mass and complexity of the system while limiting the testable angular resolution. Design options for a vertical X-ray test facility alleviating these issues are explored. An alternate mirror and module design using kinematic constraint of the mirror segments, enabled by a vertical test facility, is proposed. The kinematic mounting concept has significant advantages including potential for higher angular resolution, simplified mirror integration, and relaxed thermal requirements. However, it presents new challenges including low vibration modes and imperfections in kinematic constraint. Implementation concepts overcoming these challenges are described along with preliminary test and analysis results demonstrating the feasibility of kinematically mounting slumped glass mirror segments.

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid

PubMed Central

González, Martin; Sánchez-Pedraza, Antonio; Marfil, Rebeca; Rodríguez, Juan A.; Bandera, Antonio

2016-01-01

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms. PMID:27898029

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid.

PubMed

González, Martin; Sánchez-Pedraza, Antonio; Marfil, Rebeca; Rodríguez, Juan A; Bandera, Antonio

2016-11-26

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms.

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

PubMed Central

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder.

PubMed

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

Object-based classification of earthquake damage from high-resolution optical imagery using machine learning

NASA Astrophysics Data System (ADS)

Bialas, James; Oommen, Thomas; Rebbapragada, Umaa; Levin, Eugene

2016-07-01

Object-based approaches in the segmentation and classification of remotely sensed images yield more promising results compared to pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods are often used, but yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time-sensitive applications, such as earthquake damage assessment. Herein, we used a systematic approach in evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely sensed imagery. We tested a variety of algorithms and parameters on post-event aerial imagery for the 2011 earthquake in Christchurch, New Zealand. Results were compared against manually selected test cases representing different classes. In doing so, we can evaluate the effectiveness of the segmentation and classification of different classes and compare different levels of multistep image segmentations. Our classifier is compared against recent pixel-based and object-based classification studies for postevent imagery of earthquake damage. Our results show an improvement against both pixel-based and object-based methods for classifying earthquake damage in high resolution, post-event imagery.

Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters

PubMed Central

Dalca, Adrian; Danagoulian, Giovanna; Kikinis, Ron; Schmidt, Ehud; Golland, Polina

2011-01-01

Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation. PMID:22003741

Segmentation of nerve bundles and ganglia in spine MRI using particle filters.

PubMed

Dalca, Adrian; Danagoulian, Giovanna; Kikinis, Ron; Schmidt, Ehud; Golland, Polina

2011-01-01

Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation.

An automated image processing routine for segmentation of cell cytoplasms in high-resolution autofluorescence images

NASA Astrophysics Data System (ADS)

Walsh, Alex J.; Skala, Melissa C.

2014-02-01

The heterogeneity of genotypes and phenotypes within cancers is correlated with disease progression and drug-resistant cellular sub-populations. Therefore, robust techniques capable of probing majority and minority cell populations are important both for cancer diagnostics and therapy monitoring. Herein, we present a modified CellProfiler routine to isolate cytoplasmic fluorescence signal on a single cell level from high resolution auto-fluorescence microscopic images.

Automated segmentation of synchrotron radiation micro-computed tomography biomedical images using Graph Cuts and neural networks

NASA Astrophysics Data System (ADS)

Alvarenga de Moura Meneses, Anderson; Giusti, Alessandro; de Almeida, André Pereira; Parreira Nogueira, Liebert; Braz, Delson; Cely Barroso, Regina; deAlmeida, Carlos Eduardo

2011-12-01

Synchrotron Radiation (SR) X-ray micro-Computed Tomography (μCT) enables magnified images to be used as a non-invasive and non-destructive technique with a high space resolution for the qualitative and quantitative analyses of biomedical samples. The research on applications of segmentation algorithms to SR-μCT is an open problem, due to the interesting and well-known characteristics of SR images for visualization, such as the high resolution and the phase contrast effect. In this article, we describe and assess the application of the Energy Minimization via Graph Cuts (EMvGC) algorithm for the segmentation of SR-μCT biomedical images acquired at the Synchrotron Radiation for MEdical Physics (SYRMEP) beam line at the Elettra Laboratory (Trieste, Italy). We also propose a method using EMvGC with Artificial Neural Networks (EMANNs) for correcting misclassifications due to intensity variation of phase contrast, which are important effects and sometimes indispensable in certain biomedical applications, although they impair the segmentation provided by conventional techniques. Results demonstrate considerable success in the segmentation of SR-μCT biomedical images, with average Dice Similarity Coefficient 99.88% for bony tissue in Wistar Rats rib samples (EMvGC), as well as 98.95% and 98.02% for scans of Rhodnius prolixus insect samples (Chagas's disease vector) with EMANNs, in relation to manual segmentation. The techniques EMvGC and EMANNs cope with the task of performing segmentation in images with the intensity variation due to phase contrast effects, presenting a superior performance in comparison to conventional segmentation techniques based on thresholding and linear/nonlinear image filtering, which is also discussed in the present article.

Advanced Ecosystem Mapping Techniques for Large Arctic Study Domains Using Calibrated High-Resolution Imagery

NASA Astrophysics Data System (ADS)

Macander, M. J.; Frost, G. V., Jr.

2015-12-01

Regional-scale mapping of vegetation and other ecosystem properties has traditionally relied on medium-resolution remote sensing such as Landsat (30 m) and MODIS (250 m). Yet, the burgeoning availability of high-resolution (<=2 m) imagery and ongoing advances in computing power and analysis tools raises the prospect of performing ecosystem mapping at fine spatial scales over large study domains. Here we demonstrate cutting-edge mapping approaches over a ~35,000 km² study area on Alaska's North Slope using calibrated and atmospherically-corrected mosaics of high-resolution WorldView-2 and GeoEye-1 imagery: (1) an a priori spectral approach incorporating the Satellite Imagery Automatic Mapper (SIAM) algorithms; (2) image segmentation techniques; and (3) texture metrics. The SIAM spectral approach classifies radiometrically-calibrated imagery to general vegetation density categories and non-vegetated classes. The SIAM classes were developed globally and their applicability in arctic tundra environments has not been previously evaluated. Image segmentation, or object-based image analysis, automatically partitions high-resolution imagery into homogeneous image regions that can then be analyzed based on spectral, textural, and contextual information. We applied eCognition software to delineate waterbodies and vegetation classes, in combination with other techniques. Texture metrics were evaluated to determine the feasibility of using high-resolution imagery to algorithmically characterize periglacial surface forms (e.g., ice-wedge polygons), which are an important physical characteristic of permafrost-dominated regions but which cannot be distinguished by medium-resolution remote sensing. These advanced mapping techniques provide products which can provide essential information supporting a broad range of ecosystem science and land-use planning applications in northern Alaska and elsewhere in the circumpolar Arctic.

Clinical impact and predictors of complete ST segment resolution after primary percutaneous coronary intervention: A subanalysis of the ATLANTIC Trial.

PubMed

Fabris, Enrico; van 't Hof, Arnoud; Hamm, Christian W; Lapostolle, Frédéric; Lassen, Jens F; Goodman, Shaun G; Ten Berg, Jurriën M; Bolognese, Leonardo; Cequier, Angel; Chettibi, Mohamed; Hammett, Christopher J; Huber, Kurt; Janzon, Magnus; Merkely, Béla; Storey, Robert F; Zeymer, Uwe; Cantor, Warren J; Tsatsaris, Anne; Kerneis, Mathieu; Diallo, Abdourahmane; Vicaut, Eric; Montalescot, Gilles

2017-08-01

In the ATLANTIC (Administration of Ticagrelor in the catheterization laboratory or in the Ambulance for New ST elevation myocardial Infarction to open the Coronary artery) trial the early use of aspirin, anticoagulation, and ticagrelor coupled with very short medical contact-to-balloon times represent good indicators of optimal treatment of ST-elevation myocardial infarction and an ideal setting to explore which factors may influence coronary reperfusion beyond a well-established pre-hospital system. This study sought to evaluate predictors of complete ST-segment resolution after percutaneous coronary intervention in ST-elevation myocardial infarction patients enrolled in the ATLANTIC trial. ST-segment analysis was performed on electrocardiograms recorded at the time of inclusion (pre-hospital electrocardiogram), and one hour after percutaneous coronary intervention (post-percutaneous coronary intervention electrocardiogram) by an independent core laboratory. Complete ST-segment resolution was defined as ≥70% ST-segment resolution. Complete ST-segment resolution occurred post-percutaneous coronary intervention in 54.9% ( n=800/1456) of patients and predicted lower 30-day composite major adverse cardiovascular and cerebrovascular events (odds ratio 0.35, 95% confidence interval 0.19-0.65; p<0.01), definite stent thrombosis (odds ratio 0.18, 95% confidence interval 0.02-0.88; p=0.03), and total mortality (odds ratio 0.43, 95% confidence interval 0.19-0.97; p=0.04). In multivariate analysis, independent negative predictors of complete ST-segment resolution were the time from symptoms to pre-hospital electrocardiogram (odds ratio 0.91, 95% confidence interval 0.85-0.98; p<0.01) and diabetes mellitus (odds ratio 0.6, 95% confidence interval 0.44-0.83; p<0.01); pre-hospital ticagrelor treatment showed a favorable trend for complete ST-segment resolution (odds ratio 1.22, 95% confidence interval 0.99-1.51; p=0.06). This study confirmed that post-percutaneous coronary intervention complete ST-segment resolution is a valid surrogate marker for cardiovascular clinical outcomes. In the current era of ST-elevation myocardial infarction reperfusion, patients' delay and diabetes mellitus are independent predictors of poor reperfusion and need specific attention in the future.

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

PubMed

Liu, Fang; Zhou, Zhaoye; Jang, Hyungseok; Samsonov, Alexey; Zhao, Gengyan; Kijowski, Richard

2018-04-01

To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint. A fully automated segmentation pipeline was built by combining a semantic segmentation CNN and 3D simplex deformable modeling. A CNN technique called SegNet was applied as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification. The 3D simplex deformable modeling refined the output from SegNet to preserve the overall shape and maintain a desirable smooth surface for musculoskeletal structure. The fully automated segmentation method was tested using a publicly available knee image data set to compare with currently used state-of-the-art segmentation methods. The fully automated method was also evaluated on two different data sets, which include morphological and quantitative MR images with different tissue contrasts. The proposed fully automated segmentation method provided good segmentation performance with segmentation accuracy superior to most of state-of-the-art methods in the publicly available knee image data set. The method also demonstrated versatile segmentation performance on both morphological and quantitative musculoskeletal MR images with different tissue contrasts and spatial resolutions. The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Evaluation of a High-Resolution Benchtop Micro-CT Scanner for Application in Porous Media Research

NASA Astrophysics Data System (ADS)

Tuller, M.; Vaz, C. M.; Lasso, P. O.; Kulkarni, R.; Ferre, T. A.

2010-12-01

Recent advances in Micro Computed Tomography (MCT) provided the motivation to thoroughly evaluate and optimize scanning, image reconstruction/segmentation and pore-space analysis capabilities of a new generation benchtop MCT scanner and associated software package. To demonstrate applicability to soil research the project was focused on determination of porosities and pore size distributions of two Brazilian Oxisols from segmented MCT-data. Effects of metal filters and various acquisition parameters (e.g. total rotation, rotation step, and radiograph frame averaging) on image quality and acquisition time are evaluated. Impacts of sample size and scanning resolution on CT-derived porosities and pore-size distributions are illustrated.

Implementation and assessment of diffusion-weighted partial Fourier readout-segmented echo-planar imaging.

PubMed

Frost, Robert; Porter, David A; Miller, Karla L; Jezzard, Peter

2012-08-01

Single-shot echo-planar imaging has been used widely in diffusion magnetic resonance imaging due to the difficulties in correcting motion-induced phase corruption in multishot data. Readout-segmented EPI has addressed the multishot problem by introducing a two-dimensional nonlinear navigator correction with online reacquisition of uncorrectable data to enable acquisition of high-resolution diffusion data with reduced susceptibility artifact and T*(2) blurring. The primary shortcoming of readout-segmented EPI in its current form is its long acquisition time (longer than similar resolution single-shot echo-planar imaging protocols by approximately the number of readout segments), which limits the number of diffusion directions. By omitting readout segments at one side of k-space and using partial Fourier reconstruction, readout-segmented EPI imaging times could be reduced. In this study, the effects of homodyne and projection onto convex sets reconstructions on estimates of the fractional anisotropy, mean diffusivity, and diffusion orientation in fiber tracts and raw T(2)- and trace-weighted signal are compared, along with signal-to-noise ratio results. It is found that projections onto convex sets reconstruction with 3/5 segments in a 2 mm isotropic diffusion tensor image acquisition and 9/13 segments in a 0.9 × 0.9 × 4.0 mm(3) diffusion-weighted image acquisition provide good fidelity relative to the full k-space parameters. This allows application of readout-segmented EPI to tractography studies, and clinical stroke and oncology protocols. Copyright © 2011 Wiley-Liss, Inc.

A super resolution framework for low resolution document image OCR

NASA Astrophysics Data System (ADS)

Ma, Di; Agam, Gady

2013-01-01

Optical character recognition is widely used for converting document images into digital media. Existing OCR algorithms and tools produce good results from high resolution, good quality, document images. In this paper, we propose a machine learning based super resolution framework for low resolution document image OCR. Two main techniques are used in our proposed approach: a document page segmentation algorithm and a modified K-means clustering algorithm. Using this approach, by exploiting coherence in the document, we reconstruct from a low resolution document image a better resolution image and improve OCR results. Experimental results show substantial gain in low resolution documents such as the ones captured from video.

Image feature based GPS trace filtering for road network generation and road segmentation

DOE PAGES

Yuan, Jiangye; Cheriyadat, Anil M.

2015-10-19

We propose a new method to infer road networks from GPS trace data and accurately segment road regions in high-resolution aerial images. Unlike previous efforts that rely on GPS traces alone, we exploit image features to infer road networks from noisy trace data. The inferred road network is used to guide road segmentation. We show that the number of image segments spanned by the traces and the trace orientation validated with image features are important attributes for identifying GPS traces on road regions. Based on filtered traces , we construct road networks and integrate them with image features to segmentmore » road regions. Lastly, our experiments show that the proposed method produces more accurate road networks than the leading method that uses GPS traces alone, and also achieves high accuracy in segmenting road regions even with very noisy GPS data.« less

Image feature based GPS trace filtering for road network generation and road segmentation

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

Yuan, Jiangye; Cheriyadat, Anil M.

We propose a new method to infer road networks from GPS trace data and accurately segment road regions in high-resolution aerial images. Unlike previous efforts that rely on GPS traces alone, we exploit image features to infer road networks from noisy trace data. The inferred road network is used to guide road segmentation. We show that the number of image segments spanned by the traces and the trace orientation validated with image features are important attributes for identifying GPS traces on road regions. Based on filtered traces , we construct road networks and integrate them with image features to segmentmore » road regions. Lastly, our experiments show that the proposed method produces more accurate road networks than the leading method that uses GPS traces alone, and also achieves high accuracy in segmenting road regions even with very noisy GPS data.« less

A multi-scale tensor voting approach for small retinal vessel segmentation in high resolution fundus images.

PubMed

Christodoulidis, Argyrios; Hurtut, Thomas; Tahar, Houssem Ben; Cheriet, Farida

2016-09-01

Segmenting the retinal vessels from fundus images is a prerequisite for many CAD systems for the automatic detection of diabetic retinopathy lesions. So far, research efforts have concentrated mainly on the accurate localization of the large to medium diameter vessels. However, failure to detect the smallest vessels at the segmentation step can lead to false positive lesion detection counts in a subsequent lesion analysis stage. In this study, a new hybrid method for the segmentation of the smallest vessels is proposed. Line detection and perceptual organization techniques are combined in a multi-scale scheme. Small vessels are reconstructed from the perceptual-based approach via tracking and pixel painting. The segmentation was validated in a high resolution fundus image database including healthy and diabetic subjects using pixel-based as well as perceptual-based measures. The proposed method achieves 85.06% sensitivity rate, while the original multi-scale line detection method achieves 81.06% sensitivity rate for the corresponding images (p<0.05). The improvement in the sensitivity rate for the database is 6.47% when only the smallest vessels are considered (p<0.05). For the perceptual-based measure, the proposed method improves the detection of the vasculature by 7.8% against the original multi-scale line detection method (p<0.05). Copyright © 2016 Elsevier Ltd. All rights reserved.

Novel Strategy to Evaluate Infectious Salmon Anemia Virus Variants by High Resolution Melting

PubMed Central

Sepúlveda, Dagoberto; Cárdenas, Constanza; Carmona, Marisela; Marshall, Sergio H.

2012-01-01

Genetic variability is a key problem in the prevention and therapy of RNA-based virus infections. Infectious Salmon Anemia virus (ISAv) is an RNA virus which aggressively attacks salmon producing farms worldwide and in particular in Chile. Just as with most of the Orthomyxovirus, ISAv displays high variability in its genome which is reflected by a wider infection potential, thus hampering management and prevention of the disease. Although a number of widely validated detection procedures exist, in this case there is a need of a more complex approach to the characterization of virus variability. We have adapted a procedure of High Resolution Melting (HRM) as a fine-tuning technique to fully differentiate viral variants detected in Chile and projected to other infective variants reported elsewhere. Out of the eight viral coding segments, the technique was adapted using natural Chilean variants for two of them, namely segments 5 and 6, recognized as virulence-associated factors. Our work demonstrates the versatility of the technique as well as its superior resolution capacity compared with standard techniques currently in use as key diagnostic tools. PMID:22719837

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Texture segmentation of non-cooperative spacecrafts images based on wavelet and fractal dimension

NASA Astrophysics Data System (ADS)

Wu, Kanzhi; Yue, Xiaokui

2011-06-01

With the increase of on-orbit manipulations and space conflictions, missions such as tracking and capturing the target spacecrafts are aroused. Unlike cooperative spacecrafts, fixing beacons or any other marks on the targets is impossible. Due to the unknown shape and geometry features of non-cooperative spacecraft, in order to localize the target and obtain the latitude, we need to segment the target image and recognize the target from the background. The data and errors during the following procedures such as feature extraction and matching can also be reduced. Multi-resolution analysis of wavelet theory reflects human beings' recognition towards images from low resolution to high resolution. In addition, spacecraft is the only man-made object in the image compared to the natural background and the differences will be certainly observed between the fractal dimensions of target and background. Combined wavelet transform and fractal dimension, in this paper, we proposed a new segmentation algorithm for the images which contains complicated background such as the universe and planet surfaces. At first, Daubechies wavelet basis is applied to decompose the image in both x axis and y axis, thus obtain four sub-images. Then, calculate the fractal dimensions in four sub-images using different methods; after analyzed the results of fractal dimensions in sub-images, we choose Differential Box Counting in low resolution image as the principle to segment the texture which has the greatest divergences between different sub-images. This paper also presents the results of experiments by using the algorithm above. It is demonstrated that an accurate texture segmentation result can be obtained using the proposed technique.

Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

NASA Astrophysics Data System (ADS)

Xiao, P.; Kelly, M.; Guo, Q.

2014-12-01

This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree from multispectral image and Lidar data: recall, precision and F-score. This work explores the tradeoff between the expensive Lidar data and inexpensive multispectral image. The conclusion will guide the optimal data selection in different density canopy areas for individual tree segmentation, and contribute to the field of forest remote sensing.

Photovoltaic panel extraction from very high-resolution aerial imagery using region-line primitive association analysis and template matching

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Sun, Yujie; Wang, Qiao

2018-07-01

In object-based image analysis (OBIA), object classification performance is jointly determined by image segmentation, sample or rule setting, and classifiers. Typically, as a crucial step to obtain object primitives, image segmentation quality significantly influences subsequent feature extraction and analyses. By contrast, template matching extracts specific objects from images and prevents shape defects caused by image segmentation. However, creating or editing templates is tedious and sometimes results in incomplete or inaccurate templates. In this study, we combine OBIA and template matching techniques to address these problems and aim for accurate photovoltaic panel (PVP) extraction from very high-resolution (VHR) aerial imagery. The proposed method is based on the previously proposed region-line primitive association framework, in which complementary information between region (segment) and line (straight line) primitives is utilized to achieve a more powerful performance than routine OBIA. Several novel concepts, including the mutual fitting ratio and best-fitting template based on region-line primitive association analyses, are proposed. Automatic template generation and matching method for PVP extraction from VHR imagery are designed for concept and model validation. Results show that the proposed method can successfully extract PVPs without any user-specified matching template or training sample. High user independency and accuracy are the main characteristics of the proposed method in comparison with routine OBIA and template matching techniques.

Fetal brain volumetry through MRI volumetric reconstruction and segmentation

PubMed Central

Estroff, Judy A.; Barnewolt, Carol E.; Connolly, Susan A.; Warfield, Simon K.

2013-01-01

Purpose Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested. Materials and methods The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation. Results Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses. Conclusion The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation. PMID:20625848

Automatic optimization high-speed high-resolution OCT retinal imaging at 1μm

NASA Astrophysics Data System (ADS)

Cua, Michelle; Liu, Xiyun; Miao, Dongkai; Lee, Sujin; Lee, Sieun; Bonora, Stefano; Zawadzki, Robert J.; Mackenzie, Paul J.; Jian, Yifan; Sarunic, Marinko V.

2015-03-01

High-resolution OCT retinal imaging is important in providing visualization of various retinal structures to aid researchers in better understanding the pathogenesis of vision-robbing diseases. However, conventional optical coherence tomography (OCT) systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking optical coherence tomography (OCT) system with automatic optimization for high-resolution, extended-focal-range clinical retinal imaging. A variable-focus liquid lens was added to correct for de-focus in real-time. A GPU-accelerated segmentation and optimization was used to provide real-time layer-specific enface visualization as well as depth-specific focus adjustment. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the ONH, from which we extracted clinically-relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

A system for the analysis of foot and ankle kinematics during gait.

PubMed

Kidder, S M; Abuzzahab, F S; Harris, G F; Johnson, J E

1996-03-01

A five-camera Vicon (Oxford Metrics, Oxford, England) motion analysis system was used to acquire foot and ankle motion data. Static resolution and accuracy were computed as 0.86 +/- 0.13 mm and 98.9%, while dynamic resolution and accuracy were 0.1 +/- 0.89 and 99.4% (sagittal plane). Spectral analysis revealed high frequency noise and the need for a filter (6 Hz Butterworth low-pass) as used in similar clinical situations. A four-segment rigid body model of the foot and ankle was developed. The four rigid body foot model segments were 1) tibia and fibula, 2) calcaneus, talus, and navicular, 3) cuneiforms, cuboid, and metatarsals, and 4) hallux. The Euler method for describing relative foot and ankle segment orientation was utilized in order to maintain accuracy and ease of clinical application. Kinematic data from a single test subject are presented.

The LUVOIR Large Mission Concept

NASA Astrophysics Data System (ADS)

O'Meara, John; LUVOIR Science and Technology Definition Team

2018-01-01

LUVOIR is one of four large mission concepts for which the NASA Astrophysics Division has commissioned studies by Science and Technology Definition Teams (STDTs) drawn from the astronomical community. We are currently developing two architectures: Architecture A with a 15.1 meter segmented primary mirror, and Architecture B with a 9.2 meter segmented primary mirror. Our focus in this presentation is the Architecture A LUVOIR. LUVOIR will operate at the Sun-Earth L2 point. It will be designed to support a broad range of astrophysics and exoplanet studies. The initial instruments developed for LUVOIR Architecture A include 1) a high-performance optical/NIR coronagraph with imaging and spectroscopic capability, 2) a UV imager and spectrograph with high spectral resolution and multi-object capability, 3) a high-definition wide-field optical/NIR camera, and 4) a high resolution UV/optical spectropolarimeter. LUVOIR will be designed for extreme stability to support unprecedented spatial resolution and coronagraphy. It is intended to be a long-lifetime facility that is both serviceable, upgradable, and primarily driven by guest observer science programs. In this presentation, we will describe the observatory, its instruments, and survey the transformative science LUVOIR can accomplish.

Design and Analysis of an X-Ray Mirror Assembly Using the Meta-Shell Approach

NASA Technical Reports Server (NTRS)

McClelland, Ryan S.; Bonafede, Joseph; Saha, Timo T.; Solly, Peter M.; Zhang, William W.

2016-01-01

Lightweight and high resolution optics are needed for future space-based x-ray telescopes to achieve advances in high-energy astrophysics. Past missions such as Chandra and XMM-Newton have achieved excellent angular resolution using a full shell mirror approach. Other missions such as Suzaku and NuSTAR have achieved lightweight mirrors using a segmented approach. This paper describes a new approach, called meta-shells, which combines the fabrication advantages of segmented optics with the alignment advantages of full shell optics. Meta-shells are built by layering overlapping mirror segments onto a central structural shell. The resulting optic has the stiffness and rotational symmetry of a full shell, but with an order of magnitude greater collecting area. Several meta-shells so constructed can be integrated into a large x-ray mirror assembly by proven methods used for Chandra and XMM-Newton. The mirror segments are mounted to the meta-shell using a novel four point semi-kinematic mount. The four point mount deterministically locates the segment in its most performance sensitive degrees of freedom. Extensive analysis has been performed to demonstrate the feasibility of the four point mount and meta-shell approach. A mathematical model of a meta-shell constructed with mirror segments bonded at four points and subject to launch loads has been developed to determine the optimal design parameters, namely bond size, mirror segment span, and number of layers per meta-shell. The parameters of an example 1.3 m diameter mirror assembly are given including the predicted effective area. To verify the mathematical model and support opto-mechanical analysis, a detailed finite element model of a meta-shell was created. Finite element analysis predicts low gravity distortion and low sensitivity to thermal gradients.

Remote sensing image segmentation using local sparse structure constrained latent low rank representation

NASA Astrophysics Data System (ADS)

Tian, Shu; Zhang, Ye; Yan, Yimin; Su, Nan; Zhang, Junping

2016-09-01

Latent low-rank representation (LatLRR) has been attached considerable attention in the field of remote sensing image segmentation, due to its effectiveness in exploring the multiple subspace structures of data. However, the increasingly heterogeneous texture information in the high spatial resolution remote sensing images, leads to more severe interference of pixels in local neighborhood, and the LatLRR fails to capture the local complex structure information. Therefore, we present a local sparse structure constrainted latent low-rank representation (LSSLatLRR) segmentation method, which explicitly imposes the local sparse structure constraint on LatLRR to capture the intrinsic local structure in manifold structure feature subspaces. The whole segmentation framework can be viewed as two stages in cascade. In the first stage, we use the local histogram transform to extract the texture local histogram features (LHOG) at each pixel, which can efficiently capture the complex and micro-texture pattern. In the second stage, a local sparse structure (LSS) formulation is established on LHOG, which aims to preserve the local intrinsic structure and enhance the relationship between pixels having similar local characteristics. Meanwhile, by integrating the LSS and the LatLRR, we can efficiently capture the local sparse and low-rank structure in the mixture of feature subspace, and we adopt the subspace segmentation method to improve the segmentation accuracy. Experimental results on the remote sensing images with different spatial resolution show that, compared with three state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

Precise Alignment and Permanent Mounting of Thin and Lightweight X-ray Segments

NASA Technical Reports Server (NTRS)

Biskach, Michael P.; Chan, Kai-Wing; Hong, Melinda N.; Mazzarella, James R.; McClelland, Ryan S.; Norman, Michael J.; Saha, Timo T.; Zhang, William W.

2012-01-01

To provide observations to support current research efforts in high energy astrophysics. future X-ray telescope designs must provide matching or better angular resolution while significantly increasing the total collecting area. In such a design the permanent mounting of thin and lightweight segments is critical to the overall performance of the complete X-ray optic assembly. The thin and lightweight segments used in the assemhly of the modules are desigued to maintain and/or exceed the resolution of existing X-ray telescopes while providing a substantial increase in collecting area. Such thin and delicate X-ray segments are easily distorted and yet must be aligned to the arcsecond level and retain accurate alignment for many years. The Next Generation X-ray Optic (NGXO) group at NASA Goddard Space Flight Center has designed, assembled. and implemented new hardware and procedures mth the short term goal of aligning three pairs of X-ray segments in a technology demonstration module while maintaining 10 arcsec alignment through environmental testing as part of the eventual design and construction of a full sized module capable of housing hundreds of X-ray segments. The recent attempts at multiple segment pair alignment and permanent mounting is described along with an overview of the procedure used. A look into what the next year mll bring for the alignment and permanent segment mounting effort illustrates some of the challenges left to overcome before an attempt to populate a full sized module can begin.

Hybrid method for building extraction in vegetation-rich urban areas from very high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Jayasekare, Ajith S.; Wickramasuriya, Rohan; Namazi-Rad, Mohammad-Reza; Perez, Pascal; Singh, Gaurav

2017-07-01

A continuous update of building information is necessary in today's urban planning. Digital images acquired by remote sensing platforms at appropriate spatial and temporal resolutions provide an excellent data source to achieve this. In particular, high-resolution satellite images are often used to retrieve objects such as rooftops using feature extraction. However, high-resolution images acquired over built-up areas are associated with noises such as shadows that reduce the accuracy of feature extraction. Feature extraction heavily relies on the reflectance purity of objects, which is difficult to perfect in complex urban landscapes. An attempt was made to increase the reflectance purity of building rooftops affected by shadows. In addition to the multispectral (MS) image, derivatives thereof namely, normalized difference vegetation index and principle component (PC) images were incorporated in generating the probability image. This hybrid probability image generation ensured that the effect of shadows on rooftop extraction, particularly on light-colored roofs, is largely eliminated. The PC image was also used for image segmentation, which further increased the accuracy compared to segmentation performed on an MS image. Results show that the presented method can achieve higher rooftop extraction accuracy (70.4%) in vegetation-rich urban areas compared to traditional methods.

Interleaved segment correction achieves higher improvement factors in using genetic algorithm to optimize light focusing through scattering media

NASA Astrophysics Data System (ADS)

Li, Runze; Peng, Tong; Liang, Yansheng; Yang, Yanlong; Yao, Baoli; Yu, Xianghua; Min, Junwei; Lei, Ming; Yan, Shaohui; Zhang, Chunmin; Ye, Tong

2017-10-01

Focusing and imaging through scattering media has been proved possible with high resolution wavefront shaping. A completely scrambled scattering field can be corrected by applying a correction phase mask on a phase only spatial light modulator (SLM) and thereby the focusing quality can be improved. The correction phase is often found by global searching algorithms, among which Genetic Algorithm (GA) stands out for its parallel optimization process and high performance in noisy environment. However, the convergence of GA slows down gradually with the progression of optimization, causing the improvement factor of optimization to reach a plateau eventually. In this report, we propose an interleaved segment correction (ISC) method that can significantly boost the improvement factor with the same number of iterations comparing with the conventional all segment correction method. In the ISC method, all the phase segments are divided into a number of interleaved groups; GA optimization procedures are performed individually and sequentially among each group of segments. The final correction phase mask is formed by applying correction phases of all interleaved groups together on the SLM. The ISC method has been proved significantly useful in practice because of its ability to achieve better improvement factors when noise is present in the system. We have also demonstrated that the imaging quality is improved as better correction phases are found and applied on the SLM. Additionally, the ISC method lowers the demand of dynamic ranges of detection devices. The proposed method holds potential in applications, such as high-resolution imaging in deep tissue.

Avoiding hard chromatographic segmentation: A moving window approach for the automated resolution of gas chromatography-mass spectrometry-based metabolomics signals by multivariate methods.

PubMed

Domingo-Almenara, Xavier; Perera, Alexandre; Brezmes, Jesus

2016-11-25

Gas chromatography-mass spectrometry (GC-MS) produces large and complex datasets characterized by co-eluted compounds and at trace levels, and with a distinct compound ion-redundancy as a result of the high fragmentation by the electron impact ionization. Compounds in GC-MS can be resolved by taking advantage of the multivariate nature of GC-MS data by applying multivariate resolution methods. However, multivariate methods have to be applied in small regions of the chromatogram, and therefore chromatograms are segmented prior to the application of the algorithms. The automation of this segmentation process is a challenging task as it implies separating between informative data and noise from the chromatogram. This study demonstrates the capabilities of independent component analysis-orthogonal signal deconvolution (ICA-OSD) and multivariate curve resolution-alternating least squares (MCR-ALS) with an overlapping moving window implementation to avoid the typical hard chromatographic segmentation. Also, after being resolved, compounds are aligned across samples by an automated alignment algorithm. We evaluated the proposed methods through a quantitative analysis of GC-qTOF MS data from 25 serum samples. The quantitative performance of both moving window ICA-OSD and MCR-ALS-based implementations was compared with the quantification of 33 compounds by the XCMS package. Results shown that most of the R 2 coefficients of determination exhibited a high correlation (R 2 >0.90) in both ICA-OSD and MCR-ALS moving window-based approaches. Copyright © 2016 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Automatic 3D Segmentation and Quantification of Lenticulostriate Arteries from High-Resolution 7 Tesla MRA Images.

PubMed

Wei Liao; Rohr, Karl; Chang-Ki Kang; Zang-Hee Cho; Worz, Stefan

2016-01-01

We propose a novel hybrid approach for automatic 3D segmentation and quantification of high-resolution 7 Tesla magnetic resonance angiography (MRA) images of the human cerebral vasculature. Our approach consists of two main steps. First, a 3D model-based approach is used to segment and quantify thick vessels and most parts of thin vessels. Second, remaining vessel gaps of the first step in low-contrast and noisy regions are completed using a 3D minimal path approach, which exploits directional information. We present two novel minimal path approaches. The first is an explicit approach based on energy minimization using probabilistic sampling, and the second is an implicit approach based on fast marching with anisotropic directional prior. We conducted an extensive evaluation with over 2300 3D synthetic images and 40 real 3D 7 Tesla MRA images. Quantitative and qualitative evaluation shows that our approach achieves superior results compared with a previous minimal path approach. Furthermore, our approach was successfully used in two clinical studies on stroke and vascular dementia.

Sensitivity field distributions for segmental bioelectrical impedance analysis based on real human anatomy

NASA Astrophysics Data System (ADS)

Danilov, A. A.; Kramarenko, V. K.; Nikolaev, D. V.; Rudnev, S. G.; Salamatova, V. Yu; Smirnov, A. V.; Vassilevski, Yu V.

2013-04-01

In this work, an adaptive unstructured tetrahedral mesh generation technology is applied for simulation of segmental bioimpedance measurements using high-resolution whole-body model of the Visible Human Project man. Sensitivity field distributions for a conventional tetrapolar, as well as eight- and ten-electrode measurement configurations are obtained. Based on the ten-electrode configuration, we suggest an algorithm for monitoring changes in the upper lung area.

Slit-lamp photography and videography with high magnifications

PubMed Central

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

2015-01-01

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

Countering Beam Divergence Effects with Focused Segmented Scintillators for High DQE Megavoltage Active Matrix Imagers

PubMed Central

Liu, Langechuan; Antonuk, Larry E; Zhao, Qihua; El-Mohri, Youcef; Jiang, Hao

2012-01-01

The imaging performance of active matrix flat-panel imagers designed for megavoltage imaging (MV AMFPIs) is severely constrained by relatively low x-ray detection efficiency, which leads to a detective quantum efficiency (DQE) of only ~1%. Previous theoretical and empirical studies by our group have demonstrated the potential for addressing this constraint through utilization of thick, two-dimensional, segmented scintillators with optically isolated crystals. However, this strategy is constrained by degradation of high-frequency DQE resulting from spatial resolution loss at locations away from the central beam axis due to oblique incidence of radiation. To address this challenge, segmented scintillators constructed so that the crystals are individually focused toward the radiation source are proposed and theoretically investigated. The study was performed using Monte Carlo simulations of radiation transport to examine the modulation transfer function and DQE of focused segmented scintillators with thicknesses ranging from 5 to 60 mm. The results demonstrate that, independent of scintillator thickness, the introduction of focusing largely restores spatial resolution and DQE performance otherwise lost in thick, unfocused segmented scintillators. For the case of a 60 mm thick BGO scintillator and at a location 20 cm off the central beam axis, use of focusing improves DQE by up to a factor of ~130 at non-zero spatial frequencies. The results also indicate relatively robust tolerance of such scintillators to positional displacements, of up to 10 cm in the source-to-detector direction and 2 cm in the lateral direction, from their optimal focusing position, which could potentially enhance practical clinical use of focused segmented scintillators in MV AMFPIs. PMID:22854009

Improved high-resolution ultrasonic imaging of the eye.

PubMed

Silverman, Ronald H; Ketterling, Jeffrey A; Mamou, Jonathan; Coleman, D Jackson

2008-01-01

Currently, virtually all clinical diagnostic ultrasound systems used in ophthalmology are based on fixed-focus, single-element transducers. High-frequency (> or = 20-MHz) transducers introduced to ophthalmology during the last decade have led to improved resolution and diagnostic capabilities for assessment of the anterior segment and the retina. However, single-element transducers are restricted to a small depth of field, limiting their capacity to image the eye as a whole. We fabricated a 20-MHz annular array probe prototype consisting of 5 concentric transducer elements and scanned an ex vivo human eye. Synthetically focused images of the bank eye showed improved depth of field and sensitivity, allowing simultaneous display of the anterior and posterior segments and the full lens contour. This capability may be useful in assessment of vitreoretinal pathologies and investigation of the accommodative mechanism.

An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

PubMed

Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

2016-01-01

The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

A high-resolution gamma-ray and hard X-ray spectrometer for solar flare observations in Max 1991

NASA Technical Reports Server (NTRS)

Lin, R. P.; Curtis, D. W.; Harvey, P.; Hurley, K.; Primbsch, J. H.; Smith, D. M.; Pelling, R. M.; Duttweiler, F.

1988-01-01

A long duration balloon flight instrument for Max 1991 designed to study the acceleration of greater than 10 MeV ions and greater than 15 keV electrons in solar flares through high resolution spectroscopy of the gamma ray lines and hard X-ray and gamma ray continuum is described. The instrument, HIREGS, consists of an array of high-purity, n-type coaxial germanium detectors (HPGe) cooled to less than 90 K and surrounded by a bismuth germanate (BGO) anticoincidence shield. It will cover the energy range 15 keV to 20 MeV with keV spectral resolution, sufficient for accurate measurement of all parameters of the expected gamma ray lines with the exception of the neutron capture deuterium line. Electrical segmentation of the HPGe detector into a thin front segment and a thick rear segment, together with pulse-shape discrimination, provides optimal dynamic range and signal-to-background characteristics for flare measurements. Neutrons and gamma rays up to approximately 0.1 to 1 GeV can be detected and identified with the combination of the HPGe detectors and rear BGO shield. The HIREGS is planned for long duration balloon flights (LDBF) for solar flare studies during Max 1991. The two exploratory LDBFs carried out at mid-latitudes in 1987 to 1988 are described, and the LDBFs in Antarctica, which could in principle provide 24 hour/day solar coverage and very long flight durations (20 to 30 days) because of minimal ballast requirements are discussed.

MRI Superresolution Using Self-Similarity and Image Priors

PubMed Central

Manjón, José V.; Coupé, Pierrick; Buades, Antonio; Collins, D. Louis; Robles, Montserrat

2010-01-01

In Magnetic Resonance Imaging typical clinical settings, both low- and high-resolution images of different types are routinarily acquired. In some cases, the acquired low-resolution images have to be upsampled to match with other high-resolution images for posterior analysis or postprocessing such as registration or multimodal segmentation. However, classical interpolation techniques are not able to recover the high-frequency information lost during the acquisition process. In the present paper, a new superresolution method is proposed to reconstruct high-resolution images from the low-resolution ones using information from coplanar high resolution images acquired of the same subject. Furthermore, the reconstruction process is constrained to be physically plausible with the MR acquisition model that allows a meaningful interpretation of the results. Experiments on synthetic and real data are supplied to show the effectiveness of the proposed approach. A comparison with classical state-of-the-art interpolation techniques is presented to demonstrate the improved performance of the proposed methodology. PMID:21197094

Real-time image sequence segmentation using curve evolution

NASA Astrophysics Data System (ADS)

Zhang, Jun; Liu, Weisong

2001-04-01

In this paper, we describe a novel approach to image sequence segmentation and its real-time implementation. This approach uses the 3D structure tensor to produce a more robust frame difference signal and uses curve evolution to extract whole objects. Our algorithm is implemented on a standard PC running the Windows operating system with video capture from a USB camera that is a standard Windows video capture device. Using the Windows standard video I/O functionalities, our segmentation software is highly portable and easy to maintain and upgrade. In its current implementation on a Pentium 400, the system can perform segmentation at 5 frames/sec with a frame resolution of 160 by 120.

Imaging hydrothermal roots along the Endeavour segment of the Juan de Fuca ridge using elastic full waveform inversion.

NASA Astrophysics Data System (ADS)

Arnulf, A. F.; Harding, A. J.; Kent, G. M.

2016-12-01

The Endeavour segment is a 90 km-long, medium-spreading-rate, oceanic spreading center located on the northern Juan de Fuca ridge (JDFR). The central part of this segment forms a 25-km-long volcanic high that hosts five of the most hydrothermally active vent fields on the MOR system, namely (from north to south): Sasquatch, Salty Dawg, High Rise, Main Endeavour and Mothra. Mass, heat and chemical fluxes associated to vigorous hydrothermal venting are large, however the geometry of the fluid circulation system through the oceanic crust remains almost completely undefined. To produce high-resolution velocity/reflectivity structures along the axis of the Endeavour segment, here, we combined a synthetic ocean bottom experiment (SOBE), 2-D traveltime tomography, 2D elastic full waveform and reverse time migration (RTM). We present velocity and reflectivity sections along Endeavour segment at unprecedented spatial resolutions. We clearly image a set of independent, geometrically complex, elongated low-velocity regions linking the top of the magma chamber at depth to the hydrothermal vent fields on the seafloor. We interpret these narrow pipe-like units as focused regions of hydrothermal fluid up-flow, where acidic and corrosive fluids form pipe-like alteration zones as previously observed in Cyprus ophiolites. Furthermore, the amplitude of these low-velocity channels is shown to be highly variable, with the strongest velocity drops observed at Main Endeavour, Mothra and Salty Dawg hydrothermal vent fields, possibly suggesting more mature hydrothermal cells. Interestingly, the near-seafloor structure beneath those three sites is very similar and highlights a sharp lateral transition in velocity (north to south). On the other hand, the High-Rise hydrothermal vent field is characterized by several lower amplitudes up-flow zones and relatively slow near-surface velocities. Last, Sasquatch vent field is located in an area of high near-surface velocities and is not characterized by an obvious low-velocity up-flow region, in good agreement with an extinct vent field.

Multiplexing curvature sensors using fibre segment interferometry for lateral vibration measurements

NASA Astrophysics Data System (ADS)

Kissinger, Thomas; Chehura, Edmon; James, Stephen W.; Tatam, Ralph P.

2017-04-01

Dynamic fibre-optic curvature sensing is demonstrated by interrogating chains of fibre segments, separated by broadband Bragg grating reflectors, using range-resolved interferometry (RRI). Four fibre strings, containing four fibre segments each of gauge length 20 cm, are attached to the opposing sides of a support structure and the resulting differential strain measurements allow inference of lateral displacements of a cantilever test object. Dynamic tip displacement resolutions in the micrometre range at an interferometric bandwidth of 21 kHz demonstrate the suitability of this approach for highly sensitive and cost-effective fibre-optic directional vibration measurements of smart structures.

High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas.

PubMed

Saygin, Z M; Kliemann, D; Iglesias, J E; van der Kouwe, A J W; Boyd, E; Reuter, M; Stevens, A; Van Leemput, K; McKee, A; Frosch, M P; Fischl, B; Augustinack, J C

2017-07-15

The amygdala is composed of multiple nuclei with unique functions and connections in the limbic system and to the rest of the brain. However, standard in vivo neuroimaging tools to automatically delineate the amygdala into its multiple nuclei are still rare. By scanning postmortem specimens at high resolution (100-150µm) at 7T field strength (n = 10), we were able to visualize and label nine amygdala nuclei (anterior amygdaloid, cortico-amygdaloid transition area; basal, lateral, accessory basal, central, cortical medial, paralaminar nuclei). We created an atlas from these labels using a recently developed atlas building algorithm based on Bayesian inference. This atlas, which will be released as part of FreeSurfer, can be used to automatically segment nine amygdala nuclei from a standard resolution structural MR image. We applied this atlas to two publicly available datasets (ADNI and ABIDE) with standard resolution T1 data, used individual volumetric data of the amygdala nuclei as the measure and found that our atlas i) discriminates between Alzheimer's disease participants and age-matched control participants with 84% accuracy (AUC=0.915), and ii) discriminates between individuals with autism and age-, sex- and IQ-matched neurotypically developed control participants with 59.5% accuracy (AUC=0.59). For both datasets, the new ex vivo atlas significantly outperformed (all p < .05) estimations of the whole amygdala derived from the segmentation in FreeSurfer 5.1 (ADNI: 75%, ABIDE: 54% accuracy), as well as classification based on whole amygdala volume (using the sum of all amygdala nuclei volumes; ADNI: 81%, ABIDE: 55% accuracy). This new atlas and the segmentation tools that utilize it will provide neuroimaging researchers with the ability to explore the function and connectivity of the human amygdala nuclei with unprecedented detail in healthy adults as well as those with neurodevelopmental and neurodegenerative disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2016-01-01

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

Automated MRI segmentation for individualized modeling of current flow in the human head.

PubMed

Huang, Yu; Dmochowski, Jacek P; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C

2013-12-01

High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.

Automatic lung lobe segmentation using particles, thin plate splines, and maximum a posteriori estimation.

PubMed

Ross, James C; San José Estépar, Rail; Kindlmann, Gordon; Díaz, Alejandro; Westin, Carl-Fredrik; Silverman, Edwin K; Washko, George R

2010-01-01

We present a fully automatic lung lobe segmentation algorithm that is effective in high resolution computed tomography (CT) datasets in the presence of confounding factors such as incomplete fissures (anatomical structures indicating lobe boundaries), advanced disease states, high body mass index (BMI), and low-dose scanning protocols. In contrast to other algorithms that leverage segmentations of auxiliary structures (esp. vessels and airways), we rely only upon image features indicating fissure locations. We employ a particle system that samples the image domain and provides a set of candidate fissure locations. We follow this stage with maximum a posteriori (MAP) estimation to eliminate poor candidates and then perform a post-processing operation to remove remaining noise particles. We then fit a thin plate spline (TPS) interpolating surface to the fissure particles to form the final lung lobe segmentation. Results indicate that our algorithm performs comparably to pulmonologist-generated lung lobe segmentations on a set of challenging cases.

Automatic Lung Lobe Segmentation Using Particles, Thin Plate Splines, and Maximum a Posteriori Estimation

PubMed Central

Ross, James C.; Estépar, Raúl San José; Kindlmann, Gordon; Díaz, Alejandro; Westin, Carl-Fredrik; Silverman, Edwin K.; Washko, George R.

2011-01-01

We present a fully automatic lung lobe segmentation algorithm that is effective in high resolution computed tomography (CT) datasets in the presence of confounding factors such as incomplete fissures (anatomical structures indicating lobe boundaries), advanced disease states, high body mass index (BMI), and low-dose scanning protocols. In contrast to other algorithms that leverage segmentations of auxiliary structures (esp. vessels and airways), we rely only upon image features indicating fissure locations. We employ a particle system that samples the image domain and provides a set of candidate fissure locations. We follow this stage with maximum a posteriori (MAP) estimation to eliminate poor candidates and then perform a post-processing operation to remove remaining noise particles. We then fit a thin plate spline (TPS) interpolating surface to the fissure particles to form the final lung lobe segmentation. Results indicate that our algorithm performs comparably to pulmonologist-generated lung lobe segmentations on a set of challenging cases. PMID:20879396

Global Land Survey Impervious Mapping Project Web Site

NASA Technical Reports Server (NTRS)

DeColstoun, Eric Brown; Phillips, Jacqueline

2014-01-01

The Global Land Survey Impervious Mapping Project (GLS-IMP) aims to produce the first global maps of impervious cover at the 30m spatial resolution of Landsat. The project uses Global Land Survey (GLS) Landsat data as its base but incorporates training data generated from very high resolution commercial satellite data and using a Hierarchical segmentation program called Hseg. The web site contains general project information, a high level description of the science, examples of input and output data, as well as links to other relevant projects.

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas

PubMed Central

Liu, Bo; Wu, Huayi; Wang, Yandong; Liu, Wenming

2015-01-01

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background. We present a new method for extracting main roads from high-resolution grayscale imagery based on directional mathematical morphology and prior knowledge obtained from the Volunteered Geographic Information found in the OpenStreetMap. The two salient steps in this strategy are: (1) using directional mathematical morphology to enhance the contrast between roads and non-roads; (2) using OpenStreetMap roads as prior knowledge to segment the remotely sensed imagery. Experiments were conducted on two ZiYuan-3 images and one QuickBird high-resolution grayscale image to compare our proposed method to other commonly used techniques for road feature extraction. The results demonstrated the validity and better performance of the proposed method for urban main road feature extraction. PMID:26397832

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.

Vessel segmentation in 3D spectral OCT scans of the retina

NASA Astrophysics Data System (ADS)

Niemeijer, Meindert; Garvin, Mona K.; van Ginneken, Bram; Sonka, Milan; Abràmoff, Michael D.

2008-03-01

The latest generation of spectral optical coherence tomography (OCT) scanners is able to image 3D cross-sectional volumes of the retina at a high resolution and high speed. These scans offer a detailed view of the structure of the retina. Automated segmentation of the vessels in these volumes may lead to more objective diagnosis of retinal vascular disease including hypertensive retinopathy, retinopathy of prematurity. Additionally, vessel segmentation can allow color fundus images to be registered to these 3D volumes, possibly leading to a better understanding of the structure and localization of retinal structures and lesions. In this paper we present a method for automatically segmenting the vessels in a 3D OCT volume. First, the retina is automatically segmented into multiple layers, using simultaneous segmentation of their boundary surfaces in 3D. Next, a 2D projection of the vessels is produced by only using information from certain segmented layers. Finally, a supervised, pixel classification based vessel segmentation approach is applied to the projection image. We compared the influence of two methods for the projection on the performance of the vessel segmentation on 10 optic nerve head centered 3D OCT scans. The method was trained on 5 independent scans. Using ROC analysis, our proposed vessel segmentation system obtains an area under the curve of 0.970 when compared with the segmentation of a human observer.

SMART-X: Square Meter, Arcsecond Resolution Telescope for X-rays

NASA Astrophysics Data System (ADS)

Vikhlinin, Alexey; SMART-X Collaboration

2013-04-01

SMART-X is a concept for a next-generation X-ray observatory with large-area, 0.5" angular resolution grazing incidence adjustable X-ray mirrors, high-throughput critical angle transmission gratings, and X-ray microcalorimeter and CMOS-based imager in the focal plane. High angular resolution is enabled by new technology based on controlling the shape of mirror segments using thin film piezo actuators deposited on the back surface. Science applications include observations of growth of supermassive black holes since redshifts of ~10, ultra-deep surveys over 10's of square degrees, galaxy assembly at z=2-3, as well as new opportunities in the high-resolution X-ray spectroscopy and time domains. We also review the progress in technology development, tests, and mission design over the past year.

a New Approach for Subway Tunnel Deformation Monitoring: High-Resolution Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Li, J.; Wan, Y.; Gao, X.

2012-07-01

With the improvement of the accuracy and efficiency of laser scanning technology, high-resolution terrestrial laser scanning (TLS) technology can obtain high precise points-cloud and density distribution and can be applied to high-precision deformation monitoring of subway tunnels and high-speed railway bridges and other fields. In this paper, a new approach using a points-cloud segmentation method based on vectors of neighbor points and surface fitting method based on moving least squares was proposed and applied to subway tunnel deformation monitoring in Tianjin combined with a new high-resolution terrestrial laser scanner (Riegl VZ-400). There were three main procedures. Firstly, a points-cloud consisted of several scanning was registered by linearized iterative least squares approach to improve the accuracy of registration, and several control points were acquired by total stations (TS) and then adjusted. Secondly, the registered points-cloud was resampled and segmented based on vectors of neighbor points to select suitable points. Thirdly, the selected points were used to fit the subway tunnel surface with moving least squares algorithm. Then a series of parallel sections obtained from temporal series of fitting tunnel surfaces were compared to analysis the deformation. Finally, the results of the approach in z direction were compared with the fiber optical displacement sensor approach and the results in x, y directions were compared with TS respectively, and comparison results showed the accuracy errors of x, y, z directions were respectively about 1.5 mm, 2 mm, 1 mm. Therefore the new approach using high-resolution TLS can meet the demand of subway tunnel deformation monitoring.

Manual segmentation of the fornix, fimbria, and alveus on high-resolution 3T MRI: Application via fully-automated mapping of the human memory circuit white and grey matter in healthy and pathological aging.

PubMed

Amaral, Robert S C; Park, Min Tae M; Devenyi, Gabriel A; Lynn, Vivian; Pipitone, Jon; Winterburn, Julie; Chavez, Sofia; Schira, Mark; Lobaugh, Nancy J; Voineskos, Aristotle N; Pruessner, Jens C; Chakravarty, M Mallar

2018-04-15

Recently, much attention has been focused on the definition and structure of the hippocampus and its subfields, while the projections from the hippocampus have been relatively understudied. Here, we derive a reliable protocol for manual segmentation of hippocampal white matter regions (alveus, fimbria, and fornix) using high-resolution magnetic resonance images that are complementary to our previous definitions of the hippocampal subfields, both of which are freely available at https://github.com/cobralab/atlases. Our segmentation methods demonstrated high inter- and intra-rater reliability, were validated as inputs in automated segmentation, and were used to analyze the trajectory of these regions in both healthy aging (OASIS), and Alzheimer's disease (AD) and mild cognitive impairment (MCI; using ADNI). We observed significant bilateral decreases in the fornix in healthy aging while the alveus and cornu ammonis (CA) 1 were well preserved (all p's<0.006). MCI and AD demonstrated significant decreases in fimbriae and fornices. Many hippocampal subfields exhibited decreased volume in both MCI and AD, yet no significant differences were found between MCI and AD cohorts themselves. Our results suggest a neuroprotective or compensatory role for the alveus and CA1 in healthy aging and suggest that an improved understanding of the volumetric trajectories of these structures is required. Copyright © 2016 Elsevier Inc. All rights reserved.

Cochlea segmentation using iterated random walks with shape prior

NASA Astrophysics Data System (ADS)

Ruiz Pujadas, Esmeralda; Kjer, Hans Martin; Vera, Sergio; Ceresa, Mario; González Ballester, Miguel Ángel

2016-03-01

Cochlear implants can restore hearing to deaf or partially deaf patients. In order to plan the intervention, a model from high resolution µCT images is to be built from accurate cochlea segmentations and then, adapted to a patient-specific model. Thus, a precise segmentation is required to build such a model. We propose a new framework for segmentation of µCT cochlear images using random walks where a region term is combined with a distance shape prior weighted by a confidence map to adjust its influence according to the strength of the image contour. Then, the region term can take advantage of the high contrast between the background and foreground and the distance prior guides the segmentation to the exterior of the cochlea as well as to less contrasted regions inside the cochlea. Finally, a refinement is performed preserving the topology using a topological method and an error control map to prevent boundary leakage. We tested the proposed approach with 10 datasets and compared it with the latest techniques with random walks and priors. The experiments suggest that this method gives promising results for cochlea segmentation.

Semantic Image Segmentation with Contextual Hierarchical Models.

PubMed

Seyedhosseini, Mojtaba; Tasdizen, Tolga

2016-05-01

Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

Evolution of fine scale segmentation at intermediate ridges: example of Alarcon Rise and Endeavour Segment.

NASA Astrophysics Data System (ADS)

Le Saout, M.; Clague, D. A.; Paduan, J. B.; Caress, D. W.

2016-12-01

Mid-ocean ridges are marked by a segmentation of the axis and underlying magmatic system. Fine-scale segmentation is mainly studied along fast spreading ridges. Here we analyze the evolution of the 3rd and 4th order segmentation along two intermediate spreading centers, characterized by contrasting morphologies. Alarcon Rise, with a full spreading rate of 49 mm/yr, is characterized by an axial high and a relatively narrow axial summit trough. Endeavour segment has a spreading rate of 52.5 mm/yr and is represented by a wide axial valley affected by numerous faults. These two ridges are characterized by high and low volcanic periods, respectively. The segmentation is analyzed using high-resolution bathymetric cross-sections perpendicular to the axes. These profiles are 1200-m-long for Alarcon Rise and 2400-m-long at Endeavour Segment and are 100 m apart. The discontinuity order is based on variations, from either side of each offset, in: 1/the geometry and orientation of the axial summit trough or graben 2/ the lava morphology, and 3/ the distribution of hydrothermal vents. Alarcon Rise is marked by a recent southeast jump in volcanic activity. The comparison between actual and previous segmentation reveals a rapid evolution of the 3rd order segmentation in the most active part of the ridge, with a lengthening of the central 3rd segment of 8 km over 3-4 ky. However, no relation is observed in the 4th order segmentation before and after the axis jump. Along Endeavour, traces of the previous 3rd order discontinuities are still perceptible on the walls of the graben. This 3rd order segmentation has persisted at least during the last 4.5 ky. Indeed, it is visible in the distribution of the recent hydrothermal vents observed in the axial valley as well as in the segmentation of the axial magma lens. Analysis of the two ridges suggests that small-scale segmentation varies primarily during high magmatic phases.

Investigation of spatial resolution improvement by use of a mouth-insert detector in the helmet PET scanner.

PubMed

Ahmed, Abdella M; Tashima, Hideaki; Yamaya, Taiga

2018-03-01

The dominant factor limiting the intrinsic spatial resolution of a positron emission tomography (PET) system is the size of the crystal elements in the detector. To increase sensitivity and achieve high spatial resolution, it is essential to use advanced depth-of-interaction (DOI) detectors and arrange them close to the subject. The DOI detectors help maintain high spatial resolution by mitigating the parallax error caused by the thickness of the scintillator near the peripheral regions of the field-of-view. As an optimal geometry for a brain PET scanner, with high sensitivity and spatial resolution, we proposed and developed the helmet-chin PET scanner using 54 four-layered DOI detectors consisting of a 16 × 16 × 4 array of GSOZ scintillator crystals with dimensions of 2.8 × 2.8 × 7.5 mm 3 . All the detectors used in the helmet-chin PET scanner had the same spatial resolution. In this study, we conducted a feasibility study of a new add-on detector arrangement for the helmet PET scanner by replacing the chin detector with a segmented crystal cube, having high spatial resolution in all directions, which can be placed inside the mouth. The crystal cube (which we have named the mouth-insert detector) has an array of 20 × 20 × 20 LYSO crystal segments with dimensions of 1 × 1 × 1 mm 3 . Thus, the scanner is formed by the combination of the helmet and mouth-insert detectors, and is referred to as the helmet-mouth-insert PET scanner. The results show that the helmet-mouth-insert PET scanner has comparable sensitivity and improved spatial resolution near the center of the hemisphere, compared to the helmet-chin PET scanner.

Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.

PubMed

Babin, D; Pižurica, A; Bellens, R; De Bock, J; Shang, Y; Goossens, B; Vansteenkiste, E; Philips, W

2012-07-01

Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure. Copyright © 2012 Elsevier B.V. All rights reserved.

Protection of Distal Embolization in High-Risk Patients with Acute ST-Segment Elevation Myocardial Infarction (PREMIAR).

PubMed

Cura, Fernando A; Escudero, Alejandro Garcia; Berrocal, Daniel; Mendiz, Oscar; Trivi, Marcelo S; Fernandez, Juan; Palacios, Alejandro; Albertal, Mariano; Piraino, Ruben; Riccitelli, Miguel Angel; Gruberg, Luis; Ballarino, Miguel; Milei, Jose; Baeza, Ricardo; Thierer, Jorge; Grinfeld, Liliana; Krucoff, Mitchell; O'Neill, William; Belardi, Jorge

2007-02-01

Distal embolization may decrease myocardial reperfusion after primary percutaneous coronary intervention (PCI). Nonetheless, results of previous trials assessing the role of distal protection during primary PCI have been controversial. The Protection of Distal Embolization in High-Risk Patients with Acute ST-Segment Elevation Myocardial Infarction Trial (PREMIAR) was a prospective, randomized, controlled study designed to evaluate the role of filter-based distal protection during PCI in patients with acute ST-segment elevation myocardial infarction at high risk of embolic events (including only baseline Thrombolysis In Myocardial Infarction grade 0 to 2 flow). The primary end point was continuous monitoring of ST-segment resolution. Secondary end points included core laboratory analysis of angiographic myocardial blush, ejection fraction measured by cardiac ultrasound, and adverse cardiac events at 6 months. From a total of 194 enrolled patients, 140 subjects were randomized to PCI with or without embolic protection, and 54 were included in a registry arm due to the presence of angiographic exclusion criteria. Baseline characteristics were comparable between arms. The rate of complete ST-segment resolution (>or=70%) at 60 minutes was similar in patients treated with or without distal protection (61.2% vs 60.3%, respectively, p = 0.85). Angiographic myocardial blush (67% vs 70.7%, p = 0.73), in-hospital ejection fraction (47.4 +/- 9.9% vs 45.3 +/- 7.3%, p = 0.29), and combined end point of death, heart failure, or reinfarction at 6 months (14.3% vs 15.7%, p = 0.81) were consistently achieved in a similar proportion in the 2 groups. In conclusion, the use of filter-based distal protection is safe and effectively retrieves debris; however, such use does not translate into an improvement of myocardial reperfusion, left ventricular performance, or clinical outcomes.

Slip-accumulation patterns and earthquake recurrences along the Talas-Fergana Fault - Contributions of high-resolution geomorphic offsets.

NASA Astrophysics Data System (ADS)

Rizza, M.; Dubois, C.; Fleury, J.; Abdrakhmatov, K.; Pousse, L.; Baikulov, S.; Vezinet, A.

2017-12-01

In the western Tien-Shan Range, the largest intracontinental strike-slip fault is the Karatau-Talas Fergana Fault system. This dextral fault system is subdivided into two main segments: the Karatau fault to the north and the Talas-Fergana fault (TFF) to the south. Kinematics and rates of deformation for the TFF during the Quaternary period are still debated and are poorly constrained. Only a few paleoseismological investigations are availabe along the TFF (Burtman et al., 1996; Korjenkov et al., 2010) and no systematic quantifications of the dextral displacements along the TFF has been undertaken. As such, the appraisal of the TFF behavior demands new tectonic information. In this study, we present the first detailed analysis of the morphology and the segmentation of the TFF and an offset inventory of morphological markers along the TFF. To discuss temporal and spatial recurrence patterns of slip accumulated over multiple seismic events, our study focused on a 60 km-long section of the TFF (Chatkal segment). Using tri-stereo Pleiades satellite images, high-resolution DEMs (1*1 m pixel size) have been generated in order to (i) analyze the fine-scale fault geometry and (ii) thoroughly measure geomorphic offsets. Photogrammetry data obtained from our drone survey on high interest sites, provide higher-resolution DEMs of 0.5 * 0.5 m pixel size.Our remote sensing mapping allows an unprecedented subdivision - into five distinct segments - of the study area. About 215 geomorphic markers have been measured and offsets range from 4.5m to 180 m. More than 80% of these offsets are smaller than 60 m, suggesting landscape reset during glacial maximum. Calculations of Cumulative Offset Probability Density (COPD) for the whole 60 km-long section as well as for each segments support distinct behavior from a segment to another and thus variability in slip-accumulation patterns. Our data argue for uniform slip model behavior along this section of the TFF. Moreover, we excavated a trench and found evidence for two earthquakes. Analysis of radiocarbon and OSL samples collected in the excavation will provide constraints on the timing of those two events. We also collected some surficial samples for cosmogenic dating to determine the geological slip-rate at two sites and to discuss some spatial slip-rate variations along the TFF.

Resonant inelastic X-ray scattering spectrometer with 25meV resolution at the Cu K -edge

DOE PAGES

Ketenoglu, Didem; Harder, Manuel; Klementiev, Konstantin; ...

2015-06-27

An unparalleled resolution is reported with an inelastic X-ray scattering instrument at the CuK-edge. Based on a segmented concave analyzer, featuring single-crystal quartz (SiO 2) pixels, the spectrometer delivers a resolution near 25meV (FWHM) at 8981eV. Besides the quartz analyzer, the performance of the spectrometer relies on a four-bounce Si(553) high-resolution monochromator and focusing Kirkpatrick–Baez optics. The measured resolution agrees with the ray-tracing simulation of an ideal spectrometer. The performance of the spectrometer is demonstrated by reproducing the phonon dispersion curve of a beryllium single-crystal.

Detection of Aspens Using High Resolution Aerial Laser Scanning Data and Digital Aerial Images

PubMed Central

Säynäjoki, Raita; Packalén, Petteri; Maltamo, Matti; Vehmas, Mikko; Eerikäinen, Kalle

2008-01-01

The aim was to use high resolution Aerial Laser Scanning (ALS) data and aerial images to detect European aspen (Populus tremula L.) from among other deciduous trees. The field data consisted of 14 sample plots of 30 m × 30 m size located in the Koli National Park in the North Karelia, Eastern Finland. A Canopy Height Model (CHM) was interpolated from the ALS data with a pulse density of 3.86/m2, low-pass filtered using Height-Based Filtering (HBF) and binarized to create the mask needed to separate the ground pixels from the canopy pixels within individual areas. Watershed segmentation was applied to the low-pass filtered CHM in order to create preliminary canopy segments, from which the non-canopy elements were extracted to obtain the final canopy segmentation, i.e. the ground mask was analysed against the canopy mask. A manual classification of aerial images was employed to separate the canopy segments of deciduous trees from those of coniferous trees. Finally, linear discriminant analysis was applied to the correctly classified canopy segments of deciduous trees to classify them into segments belonging to aspen and those belonging to other deciduous trees. The independent variables used in the classification were obtained from the first pulse ALS point data. The accuracy of discrimination between aspen and other deciduous trees was 78.6%. The independent variables in the classification function were the proportion of vegetation hits, the standard deviation of in pulse heights, accumulated intensity at the 90th percentile and the proportion of laser points reflected at the 60th height percentile. The accuracy of classification corresponded to the validation results of earlier ALS-based studies on the classification of individual deciduous trees to tree species. PMID:27873799

Three-dimensional high-resolution ultrasonic imaging of the eye

NASA Astrophysics Data System (ADS)

Silverman, Ronald H.; Lizzi, Frederick L.; Kalisz, Andrew; Coleman, D. J.

2000-04-01

Very high frequency (50 MHz) ultrasound provides spatial resolution on the order of 30 microns axially by 60 microns laterally. Our aim was to reconstruct the three-dimensional anatomy of the eye in the full detail permitted by this fine- scale transducer resolution. We scanned the eyes of human subjects and anesthetized rabbits in a sequence of parallel planes 50 microns apart. Within each scan plane, vectors were also spaced 50 microns apart. Radio-frequency data were digitized at a rate of 250 MHz or higher. A series of spectrum analysis and segmentation algorithms was applied to data acquired in each plane; the outputs of these procedures were used to produce color-coded 3-D representations of the sclera, iris and ciliary processes to enhance 3-D volume rendered presentation. We visualized the radial pattern of individual ciliary processes in humans and rabbits and the geodetic web of supporting connections between the ciliary processes and iris that exist only in the rabbit. By acquiring data such that adjacent vectors and planes are separated by less than the transducer's lateral resolution, we were able to visualize structures, such as the ciliary web, that had not been seen before in-vivo. Our techniques offer the possibility of high- precision imaging and measurement of anterior segment structures. This would be relevant in monitoring of glaucoma, tumors, foreign bodies and other clinical conditions.

High resolution melting analysis: rapid and precise characterisation of recombinant influenza A genomes

PubMed Central

2013-01-01

Background High resolution melting analysis (HRM) is a rapid and cost-effective technique for the characterisation of PCR amplicons. Because the reverse genetics of segmented influenza A viruses allows the generation of numerous influenza A virus reassortants within a short time, methods for the rapid selection of the correct recombinants are very useful. Methods PCR primer pairs covering the single nucleotide polymorphism (SNP) positions of two different influenza A H5N1 strains were designed. Reassortants of the two different H5N1 isolates were used as a model to prove the suitability of HRM for the selection of the correct recombinants. Furthermore, two different cycler instruments were compared. Results Both cycler instruments generated comparable average melting peaks, which allowed the easy identification and selection of the correct cloned segments or reassorted viruses. Conclusions HRM is a highly suitable method for the rapid and precise characterisation of cloned influenza A genomes. PMID:24028349

A harmonized segmentation protocol for hippocampal and parahippocampal subregions: why do we need one and what are the key goals?

PubMed Central

Olsen, Rosanna K.; Berron, David; Carr, Valerie A.; Stark, Craig E.L.; Amaral, Robert S.C.; Amunts, Katrin; Augustinack, Jean C.; Bender, Andrew R.; Bernstein, Jeffrey D.; Boccardi, Marina; Bocchetta, Martina; Burggren, Alison; Chakravarty, M. Mallar; Chupin, Marie; Ekstrom, Arne; de Flores, Robin; Insausti, Ricardo; Kanel, Prabesh; Kedo, Olga; Kennedy, Kristen M.; Kerchner, Geoffrey A.; LaRocque, Karen F.; Liu, Xiuwen; Maass, Anne; Malykhin, Nicolai; Mueller, Susanne G.; Ofen, Noa; Palombo, Daniela J.; Parekh, Mansi B.; Pluta, John B.; Pruessner, Jens C.; Raz, Naftali; Rodrigue, Karen M.; Schoemaker, Dorothee; Shafer, Andrea T.; Steve, Trevor A.; Suthana, Nanthia; Wang, Lei; Winterburn, Julie L.; Yassa, Michael A.; Yushkevich, Paul A.; la Joie, Renaud

2016-01-01

The advent of high-resolution magnetic resonance imaging (MRI) has enabled in vivo research in a variety of populations and diseases on the structure and function of hippocampal subfields and subdivisions of the parahippocampal gyrus. Due to the many extant and highly discrepant segmentation protocols, comparing results across studies is difficult. To overcome this barrier, the Hippocampal Subfields Group was formed as an international collaboration with the aim of developing a harmonized protocol for manual segmentation of hippocampal and parahippocampal subregions on high-resolution MRI. In this commentary we discuss the goals for this protocol and the associated key challenges involved in its development. These include differences among existing anatomical reference materials, striking the right balance between reliability of measurements and anatomical validity, and the development of a versatile protocol that can be adopted for the study of populations varying in age and health. The commentary outlines these key challenges, as well as the proposed solution of each, with concrete examples from our working plan. Finally, with two examples, we illustrate how the harmonized protocol, once completed, is expected to impact the field by producing measurements that are quantitatively comparable across labs and by facilitating the synthesis of findings across different studies. PMID:27862600

TIGRESS highly-segmented high-purity germanium clover detector

NASA Astrophysics Data System (ADS)

Scraggs, H. C.; Pearson, C. J.; Hackman, G.; Smith, M. B.; Austin, R. A. E.; Ball, G. C.; Boston, A. J.; Bricault, P.; Chakrawarthy, R. S.; Churchman, R.; Cowan, N.; Cronkhite, G.; Cunningham, E. S.; Drake, T. E.; Finlay, P.; Garrett, P. E.; Grinyer, G. F.; Hyland, B.; Jones, B.; Leslie, J. R.; Martin, J.-P.; Morris, D.; Morton, A. C.; Phillips, A. A.; Sarazin, F.; Schumaker, M. A.; Svensson, C. E.; Valiente-Dobón, J. J.; Waddington, J. C.; Watters, L. M.; Zimmerman, L.

2005-05-01

The TRIUMF-ISAC Gamma-Ray Escape-Suppressed Spectrometer (TIGRESS) will consist of twelve units of four high-purity germanium (HPGe) crystals in a common cryostat. The outer contacts of each crystal will be divided into four quadrants and two lateral segments for a total of eight outer contacts. The performance of a prototype HPGe four-crystal unit has been investigated. Integrated noise spectra for all contacts were measured. Energy resolutions, relative efficiencies for both individual crystals and for the entire unit, and peak-to-total ratios were measured with point-like sources. Position-dependent performance was measured by moving a collimated source across the face of the detector.

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.

Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high resolution imagery and Lidar ancillary data for classification of urban land cover.

Multi-resolution cell orientation congruence descriptors for epithelium segmentation in endometrial histology images.

PubMed

Li, Guannan; Raza, Shan E Ahmed; Rajpoot, Nasir M

2017-04-01

It has been recently shown that recurrent miscarriage can be caused by abnormally high ratio of number of uterine natural killer (UNK) cells to the number of stromal cells in human female uterus lining. Due to high workload, the counting of UNK and stromal cells needs to be automated using computer algorithms. However, stromal cells are very similar in appearance to epithelial cells which must be excluded in the counting process. To exclude the epithelial cells from the counting process it is necessary to identify epithelial regions. There are two types of epithelial layers that can be encountered in the endometrium: luminal epithelium and glandular epithelium. To the best of our knowledge, there is no existing method that addresses the segmentation of both types of epithelium simultaneously in endometrial histology images. In this paper, we propose a multi-resolution Cell Orientation Congruence (COCo) descriptor which exploits the fact that neighbouring epithelial cells exhibit similarity in terms of their orientations. Our experimental results show that the proposed descriptors yield accurate results in simultaneously segmenting both luminal and glandular epithelium. Copyright © 2017 Elsevier B.V. All rights reserved.

Pupil-segmentation-based adaptive optical correction of a high-numerical-aperture gradient refractive index lens for two-photon fluorescence endoscopy.

PubMed

Wang, Chen; Ji, Na

2012-06-01

The intrinsic aberrations of high-NA gradient refractive index (GRIN) lenses limit their image quality as well as field of view. Here we used a pupil-segmentation-based adaptive optical approach to correct the inherent aberrations in a two-photon fluorescence endoscope utilizing a 0.8 NA GRIN lens. By correcting the field-dependent aberrations, we recovered diffraction-limited performance across a large imaging field. The consequent improvements in imaging signal and resolution allowed us to detect fine structures that were otherwise invisible inside mouse brain slices.

The Analysis of Image Segmentation Hierarchies with a Graph-based Knowledge Discovery System

NASA Technical Reports Server (NTRS)

Tilton, James C.; Cooke, diane J.; Ketkar, Nikhil; Aksoy, Selim

2008-01-01

Currently available pixel-based analysis techniques do not effectively extract the information content from the increasingly available high spatial resolution remotely sensed imagery data. A general consensus is that object-based image analysis (OBIA) is required to effectively analyze this type of data. OBIA is usually a two-stage process; image segmentation followed by an analysis of the segmented objects. We are exploring an approach to OBIA in which hierarchical image segmentations provided by the Recursive Hierarchical Segmentation (RHSEG) software developed at NASA GSFC are analyzed by the Subdue graph-based knowledge discovery system developed by a team at Washington State University. In this paper we discuss out initial approach to representing the RHSEG-produced hierarchical image segmentations in a graphical form understandable by Subdue, and provide results on real and simulated data. We also discuss planned improvements designed to more effectively and completely convey the hierarchical segmentation information to Subdue and to improve processing efficiency.

A scale self-adapting segmentation approach and knowledge transfer for automatically updating land use/cover change databases using high spatial resolution images

NASA Astrophysics Data System (ADS)

Wang, Zhihua; Yang, Xiaomei; Lu, Chen; Yang, Fengshuo

2018-07-01

Automatic updating of land use/cover change (LUCC) databases using high spatial resolution images (HSRI) is important for environmental monitoring and policy making, especially for coastal areas that connect the land and coast and that tend to change frequently. Many object-based change detection methods are proposed, especially those combining historical LUCC with HSRI. However, the scale parameter(s) segmenting the serial temporal images, which directly determines the average object size, is hard to choose without experts' intervention. And the samples transferred from historical LUCC also need experts' intervention to avoid insufficient or wrong samples. With respect to the scale parameter(s) choosing, a Scale Self-Adapting Segmentation (SSAS) approach based on the exponential sampling of a scale parameter and location of the local maximum of a weighted local variance was proposed to determine the scale selection problem when segmenting images constrained by LUCC for detecting changes. With respect to the samples transferring, Knowledge Transfer (KT), a classifier trained on historical images with LUCC and applied in the classification of updated images, was also proposed. Comparison experiments were conducted in a coastal area of Zhujiang, China, using SPOT 5 images acquired in 2005 and 2010. The results reveal that (1) SSAS can segment images more effectively without intervention of experts. (2) KT can also reach the maximum accuracy of samples transfer without experts' intervention. Strategy SSAS + KT would be a good choice if the temporal historical image and LUCC match, and the historical image and updated image are obtained from the same resource.

Real-time myocardium segmentation for the assessment of cardiac function variation

NASA Astrophysics Data System (ADS)

Zoehrer, Fabian; Huellebrand, Markus; Chitiboi, Teodora; Oechtering, Thekla; Sieren, Malte; Frahm, Jens; Hahn, Horst K.; Hennemuth, Anja

2017-03-01

Recent developments in MRI enable the acquisition of image sequences with high spatio-temporal resolution. Cardiac motion can be captured without gating and triggering. Image size and contrast relations differ from conventional cardiac MRI cine sequences requiring new adapted analysis methods. We suggest a novel segmentation approach utilizing contrast invariant polar scanning techniques. It has been tested with 20 datasets of arrhythmia patients. The results do not differ significantly more between automatic and manual segmentations than between observers. This indicates that the presented solution could enable clinical applications of real-time MRI for the examination of arrhythmic cardiac motion in the future.

Synthetic aperture imaging in ultrasound calibration

NASA Astrophysics Data System (ADS)

Ameri, Golafsoun; Baxter, John S. H.; McLeod, A. Jonathan; Jayaranthe, Uditha L.; Chen, Elvis C. S.; Peters, Terry M.

2014-03-01

Ultrasound calibration allows for ultrasound images to be incorporated into a variety of interventional applica­ tions. Traditional Z- bar calibration procedures rely on wired phantoms with an a priori known geometry. The line fiducials produce small, localized echoes which are then segmented from an array of ultrasound images from different tracked probe positions. In conventional B-mode ultrasound, the wires at greater depths appear blurred and are difficult to segment accurately, limiting the accuracy of ultrasound calibration. This paper presents a novel ultrasound calibration procedure that takes advantage of synthetic aperture imaging to reconstruct high resolution ultrasound images at arbitrary depths. In these images, line fiducials are much more readily and accu­ rately segmented, leading to decreased calibration error. The proposed calibration technique is compared to one based on B-mode ultrasound. The fiducial localization error was improved from 0.21mm in conventional B-mode images to 0.15mm in synthetic aperture images corresponding to an improvement of 29%. This resulted in an overall reduction of calibration error from a target registration error of 2.00mm to 1.78mm, an improvement of 11%. Synthetic aperture images display greatly improved segmentation capabilities due to their improved resolution and interpretability resulting in improved calibration.

Object-based methods for individual tree identification and tree species classification from high-spatial resolution imagery

NASA Astrophysics Data System (ADS)

Wang, Le

2003-10-01

Modern forest management poses an increasing need for detailed knowledge of forest information at different spatial scales. At the forest level, the information for tree species assemblage is desired whereas at or below the stand level, individual tree related information is preferred. Remote Sensing provides an effective tool to extract the above information at multiple spatial scales in the continuous time domain. To date, the increasing volume and readily availability of high-spatial-resolution data have lead to a much wider application of remotely sensed products. Nevertheless, to make effective use of the improving spatial resolution, conventional pixel-based classification methods are far from satisfactory. Correspondingly, developing object-based methods becomes a central challenge for researchers in the field of Remote Sensing. This thesis focuses on the development of methods for accurate individual tree identification and tree species classification. We develop a method in which individual tree crown boundaries and treetop locations are derived under a unified framework. We apply a two-stage approach with edge detection followed by marker-controlled watershed segmentation. Treetops are modeled from radiometry and geometry aspects. Specifically, treetops are assumed to be represented by local radiation maxima and to be located near the center of the tree-crown. As a result, a marker image was created from the derived treetop to guide a watershed segmentation to further differentiate overlapping trees and to produce a segmented image comprised of individual tree crowns. The image segmentation method developed achieves a promising result for a 256 x 256 CASI image. Then further effort is made to extend our methods to the multiscales which are constructed from a wavelet decomposition. A scale consistency and geometric consistency are designed to examine the gradients along the scale-space for the purpose of separating true crown boundary from unwanted textures occurring due to branches and twigs. As a result from the inverse wavelet transform, the tree crown boundary is enhanced while the unwanted textures are suppressed. Based on the enhanced image, an improvement is achieved when applying the two-stage methods to a high resolution aerial photograph. To improve tree species classification, we develop a new method to choose the optimal scale parameter with the aid of Bhattacharya Distance (BD), a well-known index of class separability in traditional pixel-based classification. The optimal scale parameter is then fed in the process of a region-growing-based segmentation as a break-off value. Our object classification achieves a better accuracy in separating tree species when compared to the conventional Maximum Likelihood Classification (MLC). In summary, we develop two object-based methods for identifying individual trees and classifying tree species from high-spatial resolution imagery. Both methods achieve promising results and will promote integration of Remote Sensing and GIS in forest applications.

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

PubMed

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

2011-03-01

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

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

En-face Flying Spot OCT/Ophthalmoscope

NASA Astrophysics Data System (ADS)

Rosen, Richard B.; Garcia, Patricia; Podoleanu, Adrian Gh.; Cucu, Radu; Dobre, George; Trifanov, Irina; van Velthoven, Mirjam E. J.; de Smet, Marc D.; Rogers, John A.; Hathaway, Mark; Pedro, Justin; Weitz, Rishard

This is a review of a technique for high-resolution imaging of the eye that allows multiple sample sectioning perspectives with different axial resolutions. The technique involves the flying spot approach employed in confocal scanning laser ophthalmoscopy which is extended to OCT imaging via time domain en face fast lateral scanning. The ability of imaging with multiple axial resolutions stimulated the development of the dual en face OCT-confocal imaging technology. Dual imaging also allows various other imaging combinations, such as OCT with confocal microscopy for imaging the eye anterior segment and OCT with fluorescence angiography imaging.

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods

PubMed Central

de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C. W.; Petersen, Esben T.; De Vis, Jill B.

2018-01-01

Objective In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T1-based brain segmentation methods. Materials and methods Ten healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice with repositioning in between. The scan protocol consisted of a low resolution (LR) CSF sequence (0:57min), a high resolution (HR) CSF sequence (3:21min) and a 3D T1-weighted sequence (6:47min). Data of the HR 3D-T1-weighted images were downsampled to obtain LR T1-weighted images (reconstructed imaging time: 1:59 min). Data of the CSF MRI sequences was automatically segmented using in-house software. The 3D T1-weighted images were segmented using FSL (5.0), SPM12 and FreeSurfer (5.3.0). Results The mean absolute differences for BPV and ICV between the first and second scan for CSF LR (BPV/ICV: 12±9/7±4cc) and CSF HR (5±5/4±2cc) were comparable to FSL HR (9±11/19±23cc), FSL LR (7±4, 6±5cc), FreeSurfer HR (5±3/14±8cc), FreeSurfer LR (9±8, 12±10cc), and SPM HR (5±3/4±7cc), and SPM LR (5±4, 5±3cc). The correlation between the measured volumes of the CSF sequences and that measured by FSL, FreeSurfer and SPM HR and LR was very good (all Pearson’s correlation coefficients >0.83, R2 .67–.97). The results from the downsampled data and the high-resolution data were similar. Conclusion Both CSF MRI sequences have a precision comparable to, and a very good correlation with established 3D T1-based automated segmentations methods for the segmentation of BPV and ICV. However, the short imaging time of the fast CSF MRI sequence is superior to the 3D T1 sequence on which segmentation with established methods is performed. PMID:29672584

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods.

PubMed

van der Kleij, Lisa A; de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C W; Petersen, Esben T; De Vis, Jill B

2018-01-01

In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T1-based brain segmentation methods. Ten healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice with repositioning in between. The scan protocol consisted of a low resolution (LR) CSF sequence (0:57min), a high resolution (HR) CSF sequence (3:21min) and a 3D T1-weighted sequence (6:47min). Data of the HR 3D-T1-weighted images were downsampled to obtain LR T1-weighted images (reconstructed imaging time: 1:59 min). Data of the CSF MRI sequences was automatically segmented using in-house software. The 3D T1-weighted images were segmented using FSL (5.0), SPM12 and FreeSurfer (5.3.0). The mean absolute differences for BPV and ICV between the first and second scan for CSF LR (BPV/ICV: 12±9/7±4cc) and CSF HR (5±5/4±2cc) were comparable to FSL HR (9±11/19±23cc), FSL LR (7±4, 6±5cc), FreeSurfer HR (5±3/14±8cc), FreeSurfer LR (9±8, 12±10cc), and SPM HR (5±3/4±7cc), and SPM LR (5±4, 5±3cc). The correlation between the measured volumes of the CSF sequences and that measured by FSL, FreeSurfer and SPM HR and LR was very good (all Pearson's correlation coefficients >0.83, R2 .67-.97). The results from the downsampled data and the high-resolution data were similar. Both CSF MRI sequences have a precision comparable to, and a very good correlation with established 3D T1-based automated segmentations methods for the segmentation of BPV and ICV. However, the short imaging time of the fast CSF MRI sequence is superior to the 3D T1 sequence on which segmentation with established methods is performed.

Temporal and spatial neural dynamics in the perception of basic emotions from complex scenes

PubMed Central

Costa, Tommaso; Cauda, Franco; Crini, Manuella; Tatu, Mona-Karina; Celeghin, Alessia; de Gelder, Beatrice

2014-01-01

The different temporal dynamics of emotions are critical to understand their evolutionary role in the regulation of interactions with the surrounding environment. Here, we investigated the temporal dynamics underlying the perception of four basic emotions from complex scenes varying in valence and arousal (fear, disgust, happiness and sadness) with the millisecond time resolution of Electroencephalography (EEG). Event-related potentials were computed and each emotion showed a specific temporal profile, as revealed by distinct time segments of significant differences from the neutral scenes. Fear perception elicited significant activity at the earliest time segments, followed by disgust, happiness and sadness. Moreover, fear, disgust and happiness were characterized by two time segments of significant activity, whereas sadness showed only one long-latency time segment of activity. Multidimensional scaling was used to assess the correspondence between neural temporal dynamics and the subjective experience elicited by the four emotions in a subsequent behavioral task. We found a high coherence between these two classes of data, indicating that psychological categories defining emotions have a close correspondence at the brain level in terms of neural temporal dynamics. Finally, we localized the brain regions of time-dependent activity for each emotion and time segment with the low-resolution brain electromagnetic tomography. Fear and disgust showed widely distributed activations, predominantly in the right hemisphere. Happiness activated a number of areas mostly in the left hemisphere, whereas sadness showed a limited number of active areas at late latency. The present findings indicate that the neural signature of basic emotions can emerge as the byproduct of dynamic spatiotemporal brain networks as investigated with millisecond-range resolution, rather than in time-independent areas involved uniquely in the processing one specific emotion. PMID:24214921

High-resolution, time-resolved MRA provides superior definition of lower-extremity arterial segments compared to 2D time-of-flight imaging.

PubMed

Thornton, F J; Du, J; Suleiman, S A; Dieter, R; Tefera, G; Pillai, K R; Korosec, F R; Mistretta, C A; Grist, T M

2006-08-01

To evaluate a novel time-resolved contrast-enhanced (CE) projection reconstruction (PR) magnetic resonance angiography (MRA) method for identifying potential bypass graft target vessels in patients with Class II-IV peripheral vascular disease. Twenty patients (M:F = 15:5, mean age = 58 years, range = 48-83 years), were recruited from routine MRA referrals. All imaging was performed on a 1.5 T MRI system with fast gradients (Signa LX; GE Healthcare, Waukesha, WI). Images were acquired with a novel technique that combined undersampled PR with a time-resolved acquisition to yield an MRA method with high temporal and spatial resolution. The method is called PR hyper time-resolved imaging of contrast kinetics (PR-hyperTRICKS). Quantitative and qualitative analyses were used to compare two-dimensional (2D) time-of-flight (TOF) and PR-hyperTRICKS in 13 arterial segments per lower extremity. Statistical analysis was performed with the Wilcoxon signed-rank test. Fifteen percent (77/517) of the vessels were scored as missing or nondiagnostic with 2D TOF, but were scored as diagnostic with PR-hyperTRICKS. Image quality was superior with PR-hyperTRICKS vs. 2D TOF (on a four-point scale, mean rank = 3.3 +/- 1.2 vs. 2.9 +/- 1.2, P < 0.0001). PR-hyperTRICKS produced images with high contrast-to-noise ratios (CNR) and high spatial and temporal resolution. 2D TOF images were of inferior quality due to moderate spatial resolution, inferior CNR, greater flow-related artifacts, and absence of temporal resolution. PR-hyperTRICKS provides superior preoperative assessment of lower limb ischemia compared to 2D TOF.

Three-dimensional anterior segment imaging in patients with type 1 Boston Keratoprosthesis with switchable full depth range swept source optical coherence tomography

PubMed Central

Poddar, Raju; Cortés, Dennis E.; Werner, John S.; Mannis, Mark J.

2013-01-01

Abstract. A high-speed (100 kHz A-scans/s) complex conjugate resolved 1 μm swept source optical coherence tomography (SS-OCT) system using coherence revival of the light source is suitable for dense three-dimensional (3-D) imaging of the anterior segment. The short acquisition time helps to minimize the influence of motion artifacts. The extended depth range of the SS-OCT system allows topographic analysis of clinically relevant images of the entire depth of the anterior segment of the eye. Patients with the type 1 Boston Keratoprosthesis (KPro) require evaluation of the full anterior segment depth. Current commercially available OCT systems are not suitable for this application due to limited acquisition speed, resolution, and axial imaging range. Moreover, most commonly used research grade and some clinical OCT systems implement a commercially available SS (Axsun) that offers only 3.7 mm imaging range (in air) in its standard configuration. We describe implementation of a common swept laser with built-in k-clock to allow phase stable imaging in both low range and high range, 3.7 and 11.5 mm in air, respectively, without the need to build an external MZI k-clock. As a result, 3-D morphology of the KPro position with respect to the surrounding tissue could be investigated in vivo both at high resolution and with large depth range to achieve noninvasive and precise evaluation of success of the surgical procedure. PMID:23912759

Intact figure-ground segmentation in schizophrenia.

PubMed

Herzog, Michael H; Kopmann, Sabine; Brand, Andreas

2004-11-30

As revealed by backward masking studies, schizophrenic patients show strong impairments of early visual processing. However, the underlying temporal mechanisms are not yet well understood. To shed light on the exact timing of these deficits, we employed a paradigm in which two masks follow each other. We investigated 16 medicated schizophrenic patients and a matched group of 14 controls with a new backward masking technique, shine-through. In accordance with other masking studies, schizophrenic patients require a dramatically longer processing time to reach a predefined performance level compared with healthy subjects. However, patients are surprisingly sensitive to subtle differences in the timing of the two masks, revealing good temporal resolution. This good temporal resolution indicates intact and fast perceptual grouping and figure-ground segmentation in spite of high susceptibility to masking procedures in schizophrenia.

A fully convolutional networks (FCN) based image segmentation algorithm in binocular imaging system

NASA Astrophysics Data System (ADS)

Long, Zourong; Wei, Biao; Feng, Peng; Yu, Pengwei; Liu, Yuanyuan

2018-01-01

This paper proposes an image segmentation algorithm with fully convolutional networks (FCN) in binocular imaging system under various circumstance. Image segmentation is perfectly solved by semantic segmentation. FCN classifies the pixels, so as to achieve the level of image semantic segmentation. Different from the classical convolutional neural networks (CNN), FCN uses convolution layers instead of the fully connected layers. So it can accept image of arbitrary size. In this paper, we combine the convolutional neural network and scale invariant feature matching to solve the problem of visual positioning under different scenarios. All high-resolution images are captured with our calibrated binocular imaging system and several groups of test data are collected to verify this method. The experimental results show that the binocular images are effectively segmented without over-segmentation. With these segmented images, feature matching via SURF method is implemented to obtain regional information for further image processing. The final positioning procedure shows that the results are acceptable in the range of 1.4 1.6 m, the distance error is less than 10mm.

Volumetric multimodality neural network for brain tumor segmentation

NASA Astrophysics Data System (ADS)

Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

2017-11-01

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

CERES: A new cerebellum lobule segmentation method.

PubMed

Romero, Jose E; Coupé, Pierrick; Giraud, Rémi; Ta, Vinh-Thong; Fonov, Vladimir; Park, Min Tae M; Chakravarty, M Mallar; Voineskos, Aristotle N; Manjón, Jose V

2017-02-15

The human cerebellum is involved in language, motor tasks and cognitive processes such as attention or emotional processing. Therefore, an automatic and accurate segmentation method is highly desirable to measure and understand the cerebellum role in normal and pathological brain development. In this work, we propose a patch-based multi-atlas segmentation tool called CERES (CEREbellum Segmentation) that is able to automatically parcellate the cerebellum lobules. The proposed method works with standard resolution magnetic resonance T1-weighted images and uses the Optimized PatchMatch algorithm to speed up the patch matching process. The proposed method was compared with related recent state-of-the-art methods showing competitive results in both accuracy (average DICE of 0.7729) and execution time (around 5 minutes). Copyright © 2016 Elsevier Inc. All rights reserved.

Classification with an edge: Improving semantic image segmentation with boundary detection

NASA Astrophysics Data System (ADS)

Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

2018-01-01

We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

Semantic Building FAÇADE Segmentation from Airborne Oblique Images

NASA Astrophysics Data System (ADS)

Lin, Y.; Nex, F.; Yang, M. Y.

2018-05-01

With the introduction of airborne oblique camera systems and the improvement of photogrammetric techniques, high-resolution 2D and 3D data can be acquired in urban areas. This high-resolution data allows us to perform detailed investigations on building roofs and façades which can contribute to LoD3 city modeling. Normally, façade segmentation is achieved from terrestrial views. In this paper, we address the problem from aerial views by using high resolution oblique aerial images as the data source in urban areas. In addition to traditional image features, such as RGB and SIFT, normal vector and planarity are also extracted from dense matching point clouds. Then, these 3D geometrical features are projected back to 2D space to assist façade interpretation. Random forest is trained and applied to label façade pixels. Fully connected conditional random field (CRF), capturing long-range spatial interactions, is used as a post-processing to refine our classification results. Its pairwise potential is defined by a linear combination of Gaussian kernels and the CRF model is efficiently solved by mean field approximation. Experiments show that 3D features can significantly improve classification results. Also, fully connected CRF performs well in correcting noisy pixels.

SEGMENTATION OF MITOCHONDRIA IN ELECTRON MICROSCOPY IMAGES USING ALGEBRAIC CURVES.

PubMed

Seyedhosseini, Mojtaba; Ellisman, Mark H; Tasdizen, Tolga

2013-01-01

High-resolution microscopy techniques have been used to generate large volumes of data with enough details for understanding the complex structure of the nervous system. However, automatic techniques are required to segment cells and intracellular structures in these multi-terabyte datasets and make anatomical analysis possible on a large scale. We propose a fully automated method that exploits both shape information and regional statistics to segment irregularly shaped intracellular structures such as mitochondria in electron microscopy (EM) images. The main idea is to use algebraic curves to extract shape features together with texture features from image patches. Then, these powerful features are used to learn a random forest classifier, which can predict mitochondria locations precisely. Finally, the algebraic curves together with regional information are used to segment the mitochondria at the predicted locations. We demonstrate that our method outperforms the state-of-the-art algorithms in segmentation of mitochondria in EM images.

Texture-adaptive hyperspectral video acquisition system with a spatial light modulator

NASA Astrophysics Data System (ADS)

Fang, Xiaojing; Feng, Jiao; Wang, Yongjin

2014-10-01

We present a new hybrid camera system based on spatial light modulator (SLM) to capture texture-adaptive high-resolution hyperspectral video. The hybrid camera system records a hyperspectral video with low spatial resolution using a gray camera and a high-spatial resolution video using a RGB camera. The hyperspectral video is subsampled by the SLM. The subsampled points can be adaptively selected according to the texture characteristic of the scene by combining with digital imaging analysis and computational processing. In this paper, we propose an adaptive sampling method utilizing texture segmentation and wavelet transform (WT). We also demonstrate the effectiveness of the sampled pattern on the SLM with the proposed method.

A Segmented Neutron Detector with a High Position Resolution for the (p,pn) Reactions

NASA Astrophysics Data System (ADS)

Kubota, Yuki; Sasano, Masaki; Uesaka, Tomohiro; Dozono, Masanori; Itoh, Masatoshi; Kawase, Shoichiro; Kobayashi, Motoki; Lee, CheongSoo; Matsubara, Hiroaki; Miki, Kenjiro; Miya, Hiroyuki; Ota, Shinsuke; Sekiguchi, Kimiko; Shima, Tatsushi; Taguchi, Takahiro; Tamii, Atsushi; Tang, Tsz Leung; Tokieda, Hiroshi; Wakasa, Tomotsugu; Wakui, Takashi; Yasuda, Jumpei; Zenihiro, Juzo

We are developing a neutron detector with a high position resolution to study the single particle properties of nuclei by the knockout (p,pn) reaction at intermediate energies. We constructed a prototype detector consisting of plastic scintillating fibers and multi-anode photomultiplier tubes (PMTs). Test experiments using 200- and 70-MeV proton and 199-, 188-, 68-, and 50-MeV neutron were performed for characterizing its performance. Preliminary results show that a position resolution of about 3 mm at full-width at half-maximum (FWHM) is realized as designed. The resulting separation-energy resolution to be obtained for (p,pn) measurement would be 1 MeV in FWHM, when the detector is used at a distance of 2 m from the target for measuring the neutron momentum.

Design and fabrication of a large vertical travel silicon inchworm microactuator for advanced segmented silicon space telescope (ASSIST)

NASA Technical Reports Server (NTRS)

Yang, E.; Dekany, R.; Padin, S.

2003-01-01

The goal of this research is to develop inchworm motor systems capable of simultaneously providing nanometer resolution, high stiffness, large output force, long travel range, and compactness for ultraprecision positioning applications in space.

Automated MRI Segmentation for Individualized Modeling of Current Flow in the Human Head

PubMed Central

Huang, Yu; Dmochowski, Jacek P.; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C.

2013-01-01

Objective High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography (HD-EEG) require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images (MRI) requires labor-intensive manual segmentation, even when leveraging available automated segmentation tools. Also, accurate placement of many high-density electrodes on individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. Approach A fully automated segmentation technique based on Statical Parametric Mapping 8 (SPM8), including an improved tissue probability map (TPM) and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on 4 healthy subjects and 7 stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. Main results The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view (FOV) extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Significance Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials. PMID:24099977

Automated MRI segmentation for individualized modeling of current flow in the human head

NASA Astrophysics Data System (ADS)

Huang, Yu; Dmochowski, Jacek P.; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C.

2013-12-01

Objective. High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. Approach. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets.Main results. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly.Significance. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.

A method for evaluating the murine pulmonary vasculature using micro-computed tomography.

PubMed

Phillips, Michael R; Moore, Scott M; Shah, Mansi; Lee, Clara; Lee, Yueh Z; Faber, James E; McLean, Sean E

2017-01-01

Significant mortality and morbidity are associated with alterations in the pulmonary vasculature. While techniques have been described for quantitative morphometry of whole-lung arterial trees in larger animals, no methods have been described in mice. We report a method for the quantitative assessment of murine pulmonary arterial vasculature using high-resolution computed tomography scanning. Mice were harvested at 2 weeks, 4 weeks, and 3 months of age. The pulmonary artery vascular tree was pressure perfused to maximal dilation with a radio-opaque casting material with viscosity and pressure set to prevent capillary transit and venous filling. The lungs were fixed and scanned on a specimen computed tomography scanner at 8-μm resolution, and the vessels were segmented. Vessels were grouped into categories based on lumen diameter and branch generation. Robust high-resolution segmentation was achieved, permitting detailed quantitation of pulmonary vascular morphometrics. As expected, postnatal lung development was associated with progressive increase in small-vessel number and arterial branching complexity. These methods for quantitative analysis of the pulmonary vasculature in postnatal and adult mice provide a useful tool for the evaluation of mouse models of disease that affect the pulmonary vasculature. Copyright © 2016 Elsevier Inc. All rights reserved.

A Semi-Automated Machine Learning Algorithm for Tree Cover Delineation from 1-m Naip Imagery Using a High Performance Computing Architecture

NASA Astrophysics Data System (ADS)

Basu, S.; Ganguly, S.; Nemani, R. R.; Mukhopadhyay, S.; Milesi, C.; Votava, P.; Michaelis, A.; Zhang, G.; Cook, B. D.; Saatchi, S. S.; Boyda, E.

2014-12-01

Accurate tree cover delineation is a useful instrument in the derivation of Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) satellite imagery data. Numerous algorithms have been designed to perform tree cover delineation in high to coarse resolution satellite imagery, but most of them do not scale to terabytes of data, typical in these VHR datasets. In this paper, we present an automated probabilistic framework for the segmentation and classification of 1-m VHR data as obtained from the National Agriculture Imagery Program (NAIP) for deriving tree cover estimates for the whole of Continental United States, using a High Performance Computing Architecture. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field (CRF), which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by incorporating expert knowledge through the relabeling of misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the state of California, which covers a total of 11,095 NAIP tiles and spans a total geographical area of 163,696 sq. miles. Our framework produced correct detection rates of around 85% for fragmented forests and 70% for urban tree cover areas, with false positive rates lower than 3% for both regions. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR high-resolution canopy height model shows the effectiveness of our algorithm in generating accurate high-resolution tree cover maps.

Detecting phase-amplitude coupling with high frequency resolution using adaptive decompositions

PubMed Central

Pittman-Polletta, Benjamin; Hsieh, Wan-Hsin; Kaur, Satvinder; Lo, Men-Tzung; Hu, Kun

2014-01-01

Background Phase-amplitude coupling (PAC) – the dependence of the amplitude of one rhythm on the phase of another, lower-frequency rhythm – has recently been used to illuminate cross-frequency coordination in neurophysiological activity. An essential step in measuring PAC is decomposing data to obtain rhythmic components of interest. Current methods of PAC assessment employ narrowband Fourier-based filters, which assume that biological rhythms are stationary, harmonic oscillations. However, biological signals frequently contain irregular and nonstationary features, which may contaminate rhythms of interest and complicate comodulogram interpretation, especially when frequency resolution is limited by short data segments. New method To better account for nonstationarities while maintaining sharp frequency resolution in PAC measurement, even for short data segments, we introduce a new method of PAC assessment which utilizes adaptive and more generally broadband decomposition techniques – such as the empirical mode decomposition (EMD). To obtain high frequency resolution PAC measurements, our method distributes the PAC associated with pairs of broadband oscillations over frequency space according to the time-local frequencies of these oscillations. Comparison with existing methods We compare our novel adaptive approach to a narrowband comodulogram approach on a variety of simulated signals of short duration, studying systematically how different types of nonstationarities affect these methods, as well as on EEG data. Conclusions Our results show: (1) narrowband filtering can lead to poor PAC frequency resolution, and inaccuracy and false negatives in PAC assessment; (2) our adaptive approach attains better PAC frequency resolution and is more resistant to nonstationarities and artifacts than traditional comodulograms. PMID:24452055

A rapid extraction of landslide disaster information research based on GF-1 image

NASA Astrophysics Data System (ADS)

Wang, Sai; Xu, Suning; Peng, Ling; Wang, Zhiyi; Wang, Na

2015-08-01

In recent years, the landslide disasters occurred frequently because of the seismic activity. It brings great harm to people's life. It has caused high attention of the state and the extensive concern of society. In the field of geological disaster, landslide information extraction based on remote sensing has been controversial, but high resolution remote sensing image can improve the accuracy of information extraction effectively with its rich texture and geometry information. Therefore, it is feasible to extract the information of earthquake- triggered landslides with serious surface damage and large scale. Taking the Wenchuan county as the study area, this paper uses multi-scale segmentation method to extract the landslide image object through domestic GF-1 images and DEM data, which uses the estimation of scale parameter tool to determine the optimal segmentation scale; After analyzing the characteristics of landslide high-resolution image comprehensively and selecting spectrum feature, texture feature, geometric features and landform characteristics of the image, we can establish the extracting rules to extract landslide disaster information. The extraction results show that there are 20 landslide whose total area is 521279.31 .Compared with visual interpretation results, the extraction accuracy is 72.22%. This study indicates its efficient and feasible to extract earthquake landslide disaster information based on high resolution remote sensing and it provides important technical support for post-disaster emergency investigation and disaster assessment.

Unsupervised segmentation of low-contrast multichannel images: discrimination of tissue components in microscopic images of unstained specimens

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Popović Hadžija, Marijana; Hadžija, Mirko; Aralica, Gorana

2015-06-01

Low-contrast images, such as color microscopic images of unstained histological specimens, are composed of objects with highly correlated spectral profiles. Such images are very hard to segment. Here, we present a method that nonlinearly maps low-contrast color image into an image with an increased number of non-physical channels and a decreased correlation between spectral profiles. The method is a proof-of-concept validated on the unsupervised segmentation of color images of unstained specimens, in which case the tissue components appear colorless when viewed under the light microscope. Specimens of human hepatocellular carcinoma, human liver with metastasis from colon and gastric cancer and mouse fatty liver were used for validation. The average correlation between the spectral profiles of the tissue components was greater than 0.9985, and the worst case correlation was greater than 0.9997. The proposed method can potentially be applied to the segmentation of low-contrast multichannel images with high spatial resolution that arise in other imaging modalities.

A harmonized segmentation protocol for hippocampal and parahippocampal subregions: Why do we need one and what are the key goals?

PubMed

Wisse, Laura E M; Daugherty, Ana M; Olsen, Rosanna K; Berron, David; Carr, Valerie A; Stark, Craig E L; Amaral, Robert S C; Amunts, Katrin; Augustinack, Jean C; Bender, Andrew R; Bernstein, Jeffrey D; Boccardi, Marina; Bocchetta, Martina; Burggren, Alison; Chakravarty, M Mallar; Chupin, Marie; Ekstrom, Arne; de Flores, Robin; Insausti, Ricardo; Kanel, Prabesh; Kedo, Olga; Kennedy, Kristen M; Kerchner, Geoffrey A; LaRocque, Karen F; Liu, Xiuwen; Maass, Anne; Malykhin, Nicolai; Mueller, Susanne G; Ofen, Noa; Palombo, Daniela J; Parekh, Mansi B; Pluta, John B; Pruessner, Jens C; Raz, Naftali; Rodrigue, Karen M; Schoemaker, Dorothee; Shafer, Andrea T; Steve, Trevor A; Suthana, Nanthia; Wang, Lei; Winterburn, Julie L; Yassa, Michael A; Yushkevich, Paul A; la Joie, Renaud

2017-01-01

The advent of high-resolution magnetic resonance imaging (MRI) has enabled in vivo research in a variety of populations and diseases on the structure and function of hippocampal subfields and subdivisions of the parahippocampal gyrus. Because of the many extant and highly discrepant segmentation protocols, comparing results across studies is difficult. To overcome this barrier, the Hippocampal Subfields Group was formed as an international collaboration with the aim of developing a harmonized protocol for manual segmentation of hippocampal and parahippocampal subregions on high-resolution MRI. In this commentary we discuss the goals for this protocol and the associated key challenges involved in its development. These include differences among existing anatomical reference materials, striking the right balance between reliability of measurements and anatomical validity, and the development of a versatile protocol that can be adopted for the study of populations varying in age and health. The commentary outlines these key challenges, as well as the proposed solution of each, with concrete examples from our working plan. Finally, with two examples, we illustrate how the harmonized protocol, once completed, is expected to impact the field by producing measurements that are quantitatively comparable across labs and by facilitating the synthesis of findings across different studies. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

X-Ray Optics for the 2020's

NASA Technical Reports Server (NTRS)

Zhang, Will

2010-01-01

X-ray optics is an essential and enabling technology for x-ray astronomy. This slide presentation presents the authors views on the requirements for x-ray optics as progress is made toward building IXO and preparing for the 2020's. The presentation reviews the status of several technologies that are being developed and outlines the steps that we as a community needs to take to move toward x-ray optics meeting the five key requirements: (1) high angular resolution, (2) large effective area, (3) low mass, (4) fast production, and (5) low cost. There is discussion of segmentation vs full shell, size of the mirror segment, mirror segment frabrication, post-slumping figure improvement, and characterization of coating quality.

Development of a dual-ended readout detector with segmented crystal bars made using a subsurface laser engraving technique

NASA Astrophysics Data System (ADS)

Mohammadi, Akram; Yoshida, Eiji; Nishikido, Fumihiko; Nitta, Munetaka; Shimizu, Keiji; Sakai, Toshiaki; Yamaya, Taiga

2018-01-01

Depth of interaction (DOI) information is indispensable to improving the sensitivity and spatial resolution of positron emission tomography (PET) systems, especially for small field-of-view PET such as small animal PET and human brain PET. We have already developed a series of X’tal cube detectors for isotropic spatial resolution and we obtained the best isotropic resolution of 0.77 mm for detectors with six-sided readout. However, it is still challenging to apply the detector for PET systems due to the high cost of six-sided readout electronics and carrying out segmentation of a monolithic cubic scintillator in three dimensions using the subsurface laser engraving (SSLE) technique. In this work, we propose a more practical X’tal cube with a two-sided readout detector, which is made of crystal bars segmented in the height direction only by using the SSLE technique. We developed two types of prototype detectors with a 3 mm cubic segment and a 1.5 mm cubic segment by using 3  ×  3  ×  20 mm3 and 1.5  ×  1.5  ×  20 mm3 crystal bars segmented into 7 and 13 DOI segments, respectively, using the SSLE technique. First, the performance of the detector, composed of one crystal bar with different DOI segments and two thorough silicon via (TSV) multi-pixel photon counters (MPPCs) as readout at both ends of the crystal bar, were evaluated in order to demonstrate the capability of the segmented crystal bars as a DOI detector. Then, performance evaluation was carried out for a 4  ×  4 crystal array of 3  ×  3  ×  20 mm3 with 7 DOI segments and an 8  ×  8 crystal array of 1.5  ×  1.5  ×  20 mm3 with 13 DOI segments. Each readout included a 4  ×  4 channel of the 3  ×  3 mm2 active area of the TSV MPPCs. The three-dimensional position maps of the detectors were obtained by the Anger-type calculation. All the segments in the 4  ×  4 array were identified very clearly when there was air between the crystal bars, as each crystal bar was coupled to one channel of the MPPCs; however, it was necessary to optimize optical conditions between crystal bars for the 8  ×  8 array because of light sharing between crystal bars coupled to one channel of the MPPCs. The optimization was performed for the 8  ×  8 array by inserting reflectors fully or partially between the crystal bars and the best crystal identification performance was obtained with the partial reflectors between the crystal bars. The mean energy resolutions at the 511 keV photo peak for the 4  ×  4 array with air between the crystal bars and for the 8  ×  8 array with partial reflectors between the crystal bars were 10.1%  ±  0.3% and 10.8%  ±  0.8%, respectively. Timing resolutions of 783  ±  36 ps and 1.14  ±  0.22 ns were obtained for the detectors composed of the 4  ×  4 array and the 8  ×  8 array with partial reflectors, respectively. These values correspond to single photon timing resolutions. Practical X’tal cubes with 3 mm and 1.5 mm DOI resolutions and two-sided readout were developed.

Development of a dual-ended readout detector with segmented crystal bars made using a subsurface laser engraving technique.

PubMed

Mohammadi, Akram; Yoshida, Eiji; Nishikido, Fumihiko; Nitta, Munetaka; Shimizu, Keiji; Sakai, Toshiaki; Yamaya, Taiga

2018-01-11

Depth of interaction (DOI) information is indispensable to improving the sensitivity and spatial resolution of positron emission tomography (PET) systems, especially for small field-of-view PET such as small animal PET and human brain PET. We have already developed a series of X'tal cube detectors for isotropic spatial resolution and we obtained the best isotropic resolution of 0.77 mm for detectors with six-sided readout. However, it is still challenging to apply the detector for PET systems due to the high cost of six-sided readout electronics and carrying out segmentation of a monolithic cubic scintillator in three dimensions using the subsurface laser engraving (SSLE) technique. In this work, we propose a more practical X'tal cube with a two-sided readout detector, which is made of crystal bars segmented in the height direction only by using the SSLE technique. We developed two types of prototype detectors with a 3 mm cubic segment and a 1.5 mm cubic segment by using 3  ×  3  ×  20 mm 3 and 1.5  ×  1.5  ×  20 mm 3 crystal bars segmented into 7 and 13 DOI segments, respectively, using the SSLE technique. First, the performance of the detector, composed of one crystal bar with different DOI segments and two thorough silicon via (TSV) multi-pixel photon counters (MPPCs) as readout at both ends of the crystal bar, were evaluated in order to demonstrate the capability of the segmented crystal bars as a DOI detector. Then, performance evaluation was carried out for a 4  ×  4 crystal array of 3  ×  3  ×  20 mm 3 with 7 DOI segments and an 8  ×  8 crystal array of 1.5  ×  1.5  ×  20 mm 3 with 13 DOI segments. Each readout included a 4  ×  4 channel of the 3  ×  3 mm 2 active area of the TSV MPPCs. The three-dimensional position maps of the detectors were obtained by the Anger-type calculation. All the segments in the 4  ×  4 array were identified very clearly when there was air between the crystal bars, as each crystal bar was coupled to one channel of the MPPCs; however, it was necessary to optimize optical conditions between crystal bars for the 8  ×  8 array because of light sharing between crystal bars coupled to one channel of the MPPCs. The optimization was performed for the 8  ×  8 array by inserting reflectors fully or partially between the crystal bars and the best crystal identification performance was obtained with the partial reflectors between the crystal bars. The mean energy resolutions at the 511 keV photo peak for the 4  ×  4 array with air between the crystal bars and for the 8  ×  8 array with partial reflectors between the crystal bars were 10.1%  ±  0.3% and 10.8%  ±  0.8%, respectively. Timing resolutions of 783  ±  36 ps and 1.14  ±  0.22 ns were obtained for the detectors composed of the 4  ×  4 array and the 8  ×  8 array with partial reflectors, respectively. These values correspond to single photon timing resolutions. Practical X'tal cubes with 3 mm and 1.5 mm DOI resolutions and two-sided readout were developed.

Multiview boosting digital pathology analysis of prostate cancer.

PubMed

Kwak, Jin Tae; Hewitt, Stephen M

2017-04-01

Various digital pathology tools have been developed to aid in analyzing tissues and improving cancer pathology. The multi-resolution nature of cancer pathology, however, has not been fully analyzed and utilized. Here, we develop an automated, cooperative, and multi-resolution method for improving prostate cancer diagnosis. Digitized tissue specimen images are obtained from 5 tissue microarrays (TMAs). The TMAs include 70 benign and 135 cancer samples (TMA1), 74 benign and 89 cancer samples (TMA2), 70 benign and 115 cancer samples (TMA3), 79 benign and 82 cancer samples (TMA4), and 72 benign and 86 cancer samples (TMA5). The tissue specimen images are segmented using intensity- and texture-based features. Using the segmentation results, a number of morphological features from lumens and epithelial nuclei are computed to characterize tissues at different resolutions. Applying a multiview boosting algorithm, tissue characteristics, obtained from differing resolutions, are cooperatively combined to achieve accurate cancer detection. In segmenting prostate tissues, the multiview boosting method achieved≥ 0.97 AUC using TMA1. For detecting cancers, the multiview boosting method achieved an AUC of 0.98 (95% CI: 0.97-0.99) as trained on TMA2 and tested on TMA3, TMA4, and TMA5. The proposed method was superior to single-view approaches, utilizing features from a single resolution or merging features from all the resolutions. Moreover, the performance of the proposed method was insensitive to the choice of the training dataset. Trained on TMA3, TMA4, and TMA5, the proposed method obtained an AUC of 0.97 (95% CI: 0.96-0.98), 0.98 (95% CI: 0.96-0.99), and 0.97 (95% CI: 0.96-0.98), respectively. The multiview boosting method is capable of integrating information from multiple resolutions in an effective and efficient fashion and identifying cancers with high accuracy. The multiview boosting method holds a great potential for improving digital pathology tools and research. Copyright © 2017 Elsevier B.V. All rights reserved.

Local and global evaluation for remote sensing image segmentation

NASA Astrophysics Data System (ADS)

Su, Tengfei; Zhang, Shengwei

2017-08-01

In object-based image analysis, how to produce accurate segmentation is usually a very important issue that needs to be solved before image classification or target recognition. The study for segmentation evaluation method is key to solving this issue. Almost all of the existent evaluation strategies only focus on the global performance assessment. However, these methods are ineffective for the situation that two segmentation results with very similar overall performance have very different local error distributions. To overcome this problem, this paper presents an approach that can both locally and globally quantify segmentation incorrectness. In doing so, region-overlapping metrics are utilized to quantify each reference geo-object's over and under-segmentation error. These quantified error values are used to produce segmentation error maps which have effective illustrative power to delineate local segmentation error patterns. The error values for all of the reference geo-objects are aggregated through using area-weighted summation, so that global indicators can be derived. An experiment using two scenes of very different high resolution images showed that the global evaluation part of the proposed approach was almost as effective as other two global evaluation methods, and the local part was a useful complement to comparing different segmentation results.

SeeGH--a software tool for visualization of whole genome array comparative genomic hybridization data.

PubMed

Chi, Bryan; DeLeeuw, Ronald J; Coe, Bradley P; MacAulay, Calum; Lam, Wan L

2004-02-09

Array comparative genomic hybridization (CGH) is a technique which detects copy number differences in DNA segments. Complete sequencing of the human genome and the development of an array representing a tiling set of tens of thousands of DNA segments spanning the entire human genome has made high resolution copy number analysis throughout the genome possible. Since array CGH provides signal ratio for each DNA segment, visualization would require the reassembly of individual data points into chromosome profiles. We have developed a visualization tool for displaying whole genome array CGH data in the context of chromosomal location. SeeGH is an application that translates spot signal ratio data from array CGH experiments to displays of high resolution chromosome profiles. Data is imported from a simple tab delimited text file obtained from standard microarray image analysis software. SeeGH processes the signal ratio data and graphically displays it in a conventional CGH karyotype diagram with the added features of magnification and DNA segment annotation. In this process, SeeGH imports the data into a database, calculates the average ratio and standard deviation for each replicate spot, and links them to chromosome regions for graphical display. Once the data is displayed, users have the option of hiding or flagging DNA segments based on user defined criteria, and retrieve annotation information such as clone name, NCBI sequence accession number, ratio, base pair position on the chromosome, and standard deviation. SeeGH represents a novel software tool used to view and analyze array CGH data. The software gives users the ability to view the data in an overall genomic view as well as magnify specific chromosomal regions facilitating the precise localization of genetic alterations. SeeGH is easily installed and runs on Microsoft Windows 2000 or later environments.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

PubMed

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-09-11

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

Simultaneous 3D segmentation of three bone compartments on high resolution knee MR images from osteoarthritis initiative (OAI) using graph cuts

NASA Astrophysics Data System (ADS)

Shim, Hackjoon; Kwoh, C. Kent; Yun, Il Dong; Lee, Sang Uk; Bae, Kyongtae

2009-02-01

Osteoarthritis (OA) is associated with degradation of cartilage and related changes in the underlying bone. Quantitative measurement of those changes from MR images is an important biomarker to study the progression of OA and it requires a reliable segmentation of knee bone and cartilage. As the most popular method, manual segmentation of knee joint structures by boundary delineation is highly laborious and subject to user-variation. To overcome these difficulties, we have developed a semi-automated method for segmentation of knee bones, which consisted of two steps: placement of seeds and computation of segmentation. In the first step, seeds were placed by the user on a number of slices and then were propagated automatically to neighboring images. The seed placement could be performed on any of sagittal, coronal, and axial planes. The second step, computation of segmentation, was based on a graph-cuts algorithm where the optimal segmentation is the one that minimizes a cost function, which integrated the seeds specified by the user and both the regional and boundary properties of the regions to be segmented. The algorithm also allows simultaneous segmentation of three compartments of the knee bone (femur, tibia, patella). Our method was tested on the knee MR images of six subjects from the osteoarthritis initiative (OAI). The segmentation processing time (mean+/-SD) was (22+/-4)min, which is much shorter than that by the manual boundary delineation method (typically several hours). With this improved efficiency, our segmentation method will facilitate the quantitative morphologic analysis of changes in knee bones associated with osteoarthritis.

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

Multi-segment detector array for hybrid reflection-mode ultrasound and optoacoustic tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Merčep, Elena; Burton, Neal C.; Deán-Ben, Xosé Luís.; Razansky, Daniel

2017-02-01

The complementary contrast of the optoacoustic (OA) and pulse-echo ultrasound (US) modalities makes the combined usage of these imaging technologies highly advantageous. Due to the different physical contrast mechanisms development of a detector array optimally suited for both modalities is one of the challenges to efficient implementation of a single OA-US imaging device. We demonstrate imaging performance of the first hybrid detector array whose novel design, incorporating array segments of linear and concave geometry, optimally supports image acquisition in both reflection-mode ultrasonography and optoacoustic tomography modes. Hybrid detector array has a total number of 256 elements and three segments of different geometry and variable pitch size: a central 128-element linear segment with pitch of 0.25mm, ideally suited for pulse-echo US imaging, and two external 64-elements segments with concave geometry and 0.6mm pitch optimized for OA image acquisition. Interleaved OA and US image acquisition with up to 25 fps is facilitated through a custom-made multiplexer unit. Spatial resolution of the transducer was characterized in numerical simulations and validated in phantom experiments and comprises 230 and 300 μm in the respective OA and US imaging modes. Imaging performance of the multi-segment detector array was experimentally shown in a series of imaging sessions with healthy volunteers. Employing mixed array geometries allows at the same time achieving excellent OA contrast with a large field of view, and US contrast for complementary structural features with reduced side-lobes and improved resolution. The newly designed hybrid detector array that comprises segments of linear and concave geometries optimally fulfills requirements for efficient US and OA imaging and may expand the applicability of the developed hybrid OPUS imaging technology and accelerate its clinical translation.

DEIMOS-2: cost-effective, very-high resolution multispectral imagery

NASA Astrophysics Data System (ADS)

Pirondini, Fabrizio; López, Julio; González, Enrique; González, José Antonio

2014-10-01

ELECNOR DEIMOS is a private Spanish company, part of the Elecnor industrial group, which owns and operates DEIMOS-1, the first Spanish Earth Observation satellite. DEIMOS-1, launched in 2009, is among the world leading sources of high resolution data. On June 19th, 2014 ELECNOR DEIMOS launched its second satellite, DEIMOS-2, which is a very-high resolution, agile satellite capable of providing 75-cm pan-sharpened imagery, with a 12kmwide swath. The DEIMOS-2 camera delivers multispectral imagery in 5 bands: Panchromatic, G, R, B and NIR. DEIMOS-2 is the first European satellite completely owned by private capital, which is capable of providing submetric multispectral imagery. The whole end-to-end DEIMOS-2 system is designed to provide a cost-effective, dependable and highly responsive service to cope with the increasing need of fast access to very-high resolution imagery. The same 24/7 commercial service which is now available for DEIMOS-1, including tasking, download, processing and delivery, will become available for DEIMOS-2 as well, as soon as the satellite enters into commercial operations, at the end of its in-orbit commissioning. The DEIMOS-2 satellite has been co-developed by ELECNOR DEIMOS and SATREC-I (South Korea), and it has been integrated and tested in the new ELECNOR DEIMOS Satellite Systems premises in Puertollano (Spain). The DEIMOS-2 ground segment, which includes four receiving/commanding ground stations in Spain, Sweden and Canada, has been completely developed in-house by ELECNOR DEIMOS, based on its Ground Segment for Earth Observation (gs4EO®) suite. In this paper we describe the main features of the DEIMOS-2 system, with emphasis on its initial operations and the quality of the initial imagery, and provide updated information on its mission status.

Temporal Resolution Needed for Auditory Communication: Measurement With Mosaic Speech

PubMed Central

Nakajima, Yoshitaka; Matsuda, Mizuki; Ueda, Kazuo; Remijn, Gerard B.

2018-01-01

Temporal resolution needed for Japanese speech communication was measured. A new experimental paradigm that can reflect the spectro-temporal resolution necessary for healthy listeners to perceive speech is introduced. As a first step, we report listeners' intelligibility scores of Japanese speech with a systematically degraded temporal resolution, so-called “mosaic speech”: speech mosaicized in the coordinates of time and frequency. The results of two experiments show that mosaic speech cut into short static segments was almost perfectly intelligible with a temporal resolution of 40 ms or finer. Intelligibility dropped for a temporal resolution of 80 ms, but was still around 50%-correct level. The data are in line with previous results showing that speech signals separated into short temporal segments of <100 ms can be remarkably robust in terms of linguistic-content perception against drastic manipulations in each segment, such as partial signal omission or temporal reversal. The human perceptual system thus can extract meaning from unexpectedly rough temporal information in speech. The process resembles that of the visual system stringing together static movie frames of ~40 ms into vivid motion. PMID:29740295

Design of a High Resolution Hexapod Positioning Mechanism

NASA Technical Reports Server (NTRS)

Britt, Jamie

2001-01-01

This paper describes the development of a high resolution, six-degree of freedom positioning mechanism. This mechanism, based on the Stewart platform concept, was designed for use with the Developmental Comparative Active Optics Telescope Testbed (DCATT), a ground-based technology testbed for the Next Generation Space Telescope (NGST). The mechanism provides active control to the DCATT telescope's segmented primary mirror. Emphasis is on design decisions and technical challenges. Significant issues include undesirable motion properties of PZT-inchworm actuators, testing difficulties, dimensional stability, and use of advanced composite materials. Supporting test data from prototype mechanisms is presented.

Design of a High Resolution Hexapod Positioning Mechanism

NASA Technical Reports Server (NTRS)

Britt, Jamie; Brodeur, Stephen J. (Technical Monitor)

2001-01-01

This paper describes the development of a high resolution, six-degree of freedom positioning mechanism. This mechanism, based on the Stewart platform concept, was designed for use with the Developmental Comparative Active Optics Telescope Testbed (DCATT), a ground-based technology testbed for the Next Generation Space Telescope (NGST). The mechanism provides active control to the DCATT telescope's segmented primary mirror. Emphasis is on design decisions and technical challenges. Significant issues include undesirable motion properties of PZT-inchworm actuators, testing difficulties, dimensional stability and use of advanced composite materials. Supporting test data from prototype mechanisms is presented.

A high resolution computer tomography scoring system to predict culture-positive pulmonary tuberculosis in the emergency department.

PubMed

Yeh, Jun-Jun; Neoh, Choo-Aun; Chen, Cheng-Ren; Chou, Christine Yi-Ting; Wu, Ming-Ting

2014-01-01

This study evaluated the use of high-resolution computed tomography (HRCT) to predict the presence of culture-positive pulmonary tuberculosis (PTB) in adult patients with pulmonary lesions in the emergency department (ED). The study included a derivation phase and validation phase with a total of 8,245 patients with pulmonary disease. There were 132 patients with culture-positive PTB in the derivation phase and 147 patients with culture-positive PTB in the validation phase. Imaging evaluation of pulmonary lesions included morphology and segmental distribution. The post-test probability ratios between both phases in three prevalence areas were analyzed. In the derivation phase, a multivariate analysis model identified cavitation, consolidation, and clusters/nodules in right or left upper lobe (except anterior segment) and consolidation of the superior segment of the right or left lower lobe as independent positive factors for culture-positive PTB, while consolidation of the right or left lower lobe (except superior segment) were independent negative factors. An ideal cutoff point based on the receiver operating characteristic (ROC) curve analysis was obtained at a score of 1. The sensitivity, specificity, positivity predictive value, and negative predictive value from derivation phase were 98.5% (130/132), 99.7% (3997/4008), 92.2% (130/141), and 99.9% (3997/3999). Based on the predicted positive likelihood ratio value of 328.33 in derivation phase, the post-test probability was observed to be 91.5% in the derivation phase, 92.5% in the validation phase, 94.5% in a high TB prevalence area, 91.0% in a moderate prevalence area, and 76.8% in moderate-to-low prevalence area. Our model using HRCT, which is feasible to perform in the ED, can promptly diagnose culture-positive PTB in moderate and moderate-to-low prevalence areas.

Individual tree crown delineation using localized contour tree method and airborne LiDAR data in coniferous forests

NASA Astrophysics Data System (ADS)

Wu, Bin; Yu, Bailang; Wu, Qiusheng; Huang, Yan; Chen, Zuoqi; Wu, Jianping

2016-10-01

Individual tree crown delineation is of great importance for forest inventory and management. The increasing availability of high-resolution airborne light detection and ranging (LiDAR) data makes it possible to delineate the crown structure of individual trees and deduce their geometric properties with high accuracy. In this study, we developed an automated segmentation method that is able to fully utilize high-resolution LiDAR data for detecting, extracting, and characterizing individual tree crowns with a multitude of geometric and topological properties. The proposed approach captures topological structure of forest and quantifies topological relationships of tree crowns by using a graph theory-based localized contour tree method, and finally segments individual tree crowns by analogy of recognizing hills from a topographic map. This approach consists of five key technical components: (1) derivation of canopy height model from airborne LiDAR data; (2) generation of contours based on the canopy height model; (3) extraction of hierarchical structures of tree crowns using the localized contour tree method; (4) delineation of individual tree crowns by segmenting hierarchical crown structure; and (5) calculation of geometric and topological properties of individual trees. We applied our new method to the Medicine Bow National Forest in the southwest of Laramie, Wyoming and the HJ Andrews Experimental Forest in the central portion of the Cascade Range of Oregon, U.S. The results reveal that the overall accuracy of individual tree crown delineation for the two study areas achieved 94.21% and 75.07%, respectively. Our method holds great potential for segmenting individual tree crowns under various forest conditions. Furthermore, the geometric and topological attributes derived from our method provide comprehensive and essential information for forest management.

Association of admission testosterone level with ST-segment resolution in male patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention.

PubMed

Separham, Ahmad; Ghaffari, Samad; Sohrabi, Bahram; Aslanabadi, Naser; Hadavi Bavil, Mozhgan; Lotfollahi, Hasanali

2017-01-01

Low level of testosterone may be associated with cardiovascular diseases in men, as some evidence suggests a protective role for testosterone in cardiovascular system. Little is known about the possible role of serum testosterone in response to reperfusion therapy in ST-elevation myocardial infarction (STEMI) and its relationship with ST-segment recovery. The present study was conducted to evaluate the association of serum testosterone levels with ST-segment resolution following primary percutaneous coronary intervention (PPCI) in male patients with acute STEMI. Forty-eight men (mean age 54.55 ± 12.20) with STEMI undergoing PPCI were enrolled prospectively. Single-lead ST segment resolution in the lead with maximum baseline ST-elevation was measured and patients were divided into two groups according to the degree of ST-segment resolution: complete (> or =50%) or incomplete (<50%). The basic and demographic data of all patients, their left ventricular ejection fraction (LVEF) and laboratory findings including serum levels of free testosterone and cardiac enzymes were recorded along with angiographic finding and baseline TIMI (Thrombolysis in Myocardial Infarction) flow and also in-hospital complications and then these variables were compared between two groups. A complete ST-resolution (≥50%) was observed in 72.9% of the patients. The serum levels of free testosterone ( P  = 0.04), peak cardiac troponin ( P  = 0.03) were significantly higher and hs-CRP ( P  = 0.02) were lower in patients with complete ST-resolution compared to those with incomplete ST-resolution. In-hospital complications were observed in 31.2% of patients. The patients with a lower baseline TIMI flow ( P  = 0.03) and those who developed complications ( P  = 0.04) had lower levels of free testosterone. A significant positive correlation was observed between the left ventricular function and serum levels of free testosterone ( P  = 0.01 and r = +0.362). This study suggests that in men with STEMI undergoing PPCI, higher serum levels of testosterone are associated with a better reperfusion response, fewer complications and a better left ventricular function.

Reliability of Semi-Automated Segmentations in Glioblastoma.

PubMed

Huber, T; Alber, G; Bette, S; Boeckh-Behrens, T; Gempt, J; Ringel, F; Alberts, E; Zimmer, C; Bauer, J S

2017-06-01

In glioblastoma, quantitative volumetric measurements of contrast-enhancing or fluid-attenuated inversion recovery (FLAIR) hyperintense tumor compartments are needed for an objective assessment of therapy response. The aim of this study was to evaluate the reliability of a semi-automated, region-growing segmentation tool for determining tumor volume in patients with glioblastoma among different users of the software. A total of 320 segmentations of tumor-associated FLAIR changes and contrast-enhancing tumor tissue were performed by different raters (neuroradiologists, medical students, and volunteers). All patients underwent high-resolution magnetic resonance imaging including a 3D-FLAIR and a 3D-MPRage sequence. Segmentations were done using a semi-automated, region-growing segmentation tool. Intra- and inter-rater-reliability were addressed by intra-class-correlation (ICC). Root-mean-square error (RMSE) was used to determine the precision error. Dice score was calculated to measure the overlap between segmentations. Semi-automated segmentation showed a high ICC (> 0.985) for all groups indicating an excellent intra- and inter-rater-reliability. Significant smaller precision errors and higher Dice scores were observed for FLAIR segmentations compared with segmentations of contrast-enhancement. Single rater segmentations showed the lowest RMSE for FLAIR of 3.3 % (MPRage: 8.2 %). Both, single raters and neuroradiologists had the lowest precision error for longitudinal evaluation of FLAIR changes. Semi-automated volumetry of glioblastoma was reliably performed by all groups of raters, even without neuroradiologic expertise. Interestingly, segmentations of tumor-associated FLAIR changes were more reliable than segmentations of contrast enhancement. In longitudinal evaluations, an experienced rater can detect progressive FLAIR changes of less than 15 % reliably in a quantitative way which could help to detect progressive disease earlier.

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

Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data

PubMed Central

Huang, Huabing; Gong, Peng; Cheng, Xiao; Clinton, Nick; Li, Zengyuan

2009-01-01

Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data. PMID:22573971

Automated road network extraction from high spatial resolution multi-spectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a road network. The extracted road network is evaluated against a reference dataset using a line segment matching algorithm. The entire process is unsupervised and fully automated. Based on extensive experimentation on a variety of remotely-sensed multi-spectral images, the proposed methodology achieves a moderate success in automating road network extraction from high spatial resolution multi-spectral imagery.

Shallow seismic imaging of folds above the Puente Hills blind-thrust fault, Los Angeles, California

USGS Publications Warehouse

Pratt, T.L.; Shaw, J.H.; Dolan, J.F.; Christofferson, S.A.; Williams, R.A.; Odum, J.K.; Plesch, A.

2002-01-01

High-resolution seismic reflection profiles image discrete folds in the shallow subsurface (<600 m) above two segments of the Puente Hills blind-thrust fault system, Los Angeles basin, California. The profiles demonstrate late Quaternary activity at the fault tip, precisely locate the axial surfaces of folds within the upper 100 m, and constrain the geometry and kinematics of recent folding. The Santa Fe Springs segment of the Puente Hills fault zone shows an upward-narrowing kink band with an active anticlinal axial surface, consistent with fault-bend folding above an active thrust ramp. The Coyote Hills segment shows an active synclinal axial surface that coincides with the base of a 9-m-high scarp, consistent with tip-line folding or the presence of a backthrust. The seismic profiles pinpoint targets for future geologic work to constrain slip rates and ages of past events on this important fault system.

Identification of Extracellular Segments by Mass Spectrometry Improves Topology Prediction of Transmembrane Proteins.

PubMed

Langó, Tamás; Róna, Gergely; Hunyadi-Gulyás, Éva; Turiák, Lilla; Varga, Julia; Dobson, László; Várady, György; Drahos, László; Vértessy, Beáta G; Medzihradszky, Katalin F; Szakács, Gergely; Tusnády, Gábor E

2017-02-13

Transmembrane proteins play crucial role in signaling, ion transport, nutrient uptake, as well as in maintaining the dynamic equilibrium between the internal and external environment of cells. Despite their important biological functions and abundance, less than 2% of all determined structures are transmembrane proteins. Given the persisting technical difficulties associated with high resolution structure determination of transmembrane proteins, additional methods, including computational and experimental techniques remain vital in promoting our understanding of their topologies, 3D structures, functions and interactions. Here we report a method for the high-throughput determination of extracellular segments of transmembrane proteins based on the identification of surface labeled and biotin captured peptide fragments by LC/MS/MS. We show that reliable identification of extracellular protein segments increases the accuracy and reliability of existing topology prediction algorithms. Using the experimental topology data as constraints, our improved prediction tool provides accurate and reliable topology models for hundreds of human transmembrane proteins.

High Bolus Tirofiban vs Abciximab in Acute STEMI Patients Undergoing Primary PCI – The Tamip Study

PubMed Central

Balghith, Mohammed A.

2012-01-01

Background: Primary percutaneous coronary intervention (PCI) has been shown to be an effective therapy for patients with acute myocardial infarction (MI). Glycoprotein (GP) IIb/IIIa receptor blockers reduce thrombotic complications in patients undergoing PCI. Most available data relate to Reopro, which has been registered for this indication. GP IIb/IIIa reduce unfavorable outcome in U/A and non ST-elevation myocardial infarction (STEMI) patients. Only few studies focused on high dose Aggrastat for STEMI patients in the emergency department (ED) before PCI. The aim is to increase the patency during the time awaiting coronary angioplasty in patients with acute MI. Objectives: To study the effect of upfront high bolus dose (HDR) of tirofiban on the extent of residual ST segment deviation 1 hour after primary PCI and the incidence of TIMI 3 flow of the infarct-related artery (IRA). Materials and Methods: A randomized, open label, single center study in the ED. A total of 90 patients with acute ST-elevation MI, diagnosed clinically by ECG criteria (ST segment elevation of >2 mm in two adjacent ECG leads), and with an expectation that a patient will undergo primary PCI. Patients were aged 21-85 years and all received heparin 5000 u, aspirin 160 mg, and Plavix 600 mg. Patients were divided in two groups (group I: triofiban high bolus vs group II: Reopro) with 45 patients in each group. In group I, high bolus triofiban 25 mcg/kg over 3 min was started in the ED with maintenance infusion of 0.15 mcg/ kg/min continued for 12 hours and transferred to cath lab for PCI. Patients in group II were transferred to cath lab, where a standard dose of Reopro was given with a bolus of 0.25 mcg/kg and maintenance infusion of 0.125 mcg/kg/min over 12 hours. Results: ST segment resolution and TIMI flow were evaluated in both groups before and after PCI. Thirty-five patients (78%) enrolled in group I and 29 patients (64%) in group II had resolution of ST segment (P-value 0.24). Twenty-one patients (47% group I) vs 23 patients (51% group II) with P-value 0.83 achieved TIMI 0 flow. Twenty-four patients (53% group I) compared with 22 patients (49% group II) with P-value 0.83 had TIMI 1 to 3 flow before PCI. TIMI 3 flow was achieved in 40 patients (89% group I) compared with 38 patients (84% group II) with P-value 0.76. Conclusion: In this study there was a trend toward better ST segment resolution and patency of IRA (i.e., improved TIMI flow) in patients given high bolus dose Aggrastat in the ED. Larger studies are needed to confirm this finding. PMID:23181175

Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging

PubMed Central

Reishofer, Gernot; Koschutnig, Karl; Langkammer, Christian; Porter, David; Jehna, Margit; Enzinger, Christian; Keeling, Stephen; Ebner, Franz

2013-01-01

Readout-segmented echo planar imaging with 2D navigator-based reacquisition is an uprising technique enabling the sampling of high-resolution diffusion images with reduced susceptibility artifacts. However, low signal from the small voxels and long scan times hamper the clinical applicability. Therefore, we introduce a regularization algorithm based on total variation that is applied directly on the entire diffusion tensor. The spatially varying regularization parameter is determined automatically dependent on spatial variations in signal-to-noise ratio thus, avoiding over- or under-regularization. Information about the noise distribution in the diffusion tensor is extracted from the diffusion weighted images by means of complex independent component analysis. Moreover, the combination of those features enables processing of the diffusion data absolutely user independent. Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking such as Mean Fiber Length, Track Count, Volume and Voxel Count. Specifically, for in vivo data findings suggest that tractography results from the regularized diffusion tensor based on one measurement (16 min) generates results comparable to the un-regularized data with three averages (48 min). This significant reduction in scan time renders high resolution (1×1×2.5 mm3) diffusion tensor imaging of the entire brain applicable in a clinical context. PMID:24019951

Conditions that influence the accuracy of anthropometric parameter estimation for human body segments using shape-from-silhouette

NASA Astrophysics Data System (ADS)

Mundermann, Lars; Mundermann, Annegret; Chaudhari, Ajit M.; Andriacchi, Thomas P.

2005-01-01

Anthropometric parameters are fundamental for a wide variety of applications in biomechanics, anthropology, medicine and sports. Recent technological advancements provide methods for constructing 3D surfaces directly. Of these new technologies, visual hull construction may be the most cost-effective yet sufficiently accurate method. However, the conditions influencing the accuracy of anthropometric measurements based on visual hull reconstruction are unknown. The purpose of this study was to evaluate the conditions that influence the accuracy of 3D shape-from-silhouette reconstruction of body segments dependent on number of cameras, camera resolution and object contours. The results demonstrate that the visual hulls lacked accuracy in concave regions and narrow spaces, but setups with a high number of cameras reconstructed a human form with an average accuracy of 1.0 mm. In general, setups with less than 8 cameras yielded largely inaccurate visual hull constructions, while setups with 16 and more cameras provided good volume estimations. Body segment volumes were obtained with an average error of 10% at a 640x480 resolution using 8 cameras. Changes in resolution did not significantly affect the average error. However, substantial decreases in error were observed with increasing number of cameras (33.3% using 4 cameras; 10.5% using 8 cameras; 4.1% using 16 cameras; 1.2% using 64 cameras).

Revealing misassembled segments in the bovine reference genome by high resolution linkage disequilibrium scan

USDA-ARS?s Scientific Manuscript database

Misassembly signatures, created by shuffling the order of sequences while assembling a genome, can be easily seen by analyzing the unexpected behaviour of the linkage disequilibrium (LD) decay. A heuristic process was proposed to identify those misassembly signatures and presented the ones found in ...

Particle swarm optimization method for small retinal vessels detection on multiresolution fundus images.

PubMed

Khomri, Bilal; Christodoulidis, Argyrios; Djerou, Leila; Babahenini, Mohamed Chaouki; Cheriet, Farida

2018-05-01

Retinal vessel segmentation plays an important role in the diagnosis of eye diseases and is considered as one of the most challenging tasks in computer-aided diagnosis (CAD) systems. The main goal of this study was to propose a method for blood-vessel segmentation that could deal with the problem of detecting vessels of varying diameters in high- and low-resolution fundus images. We proposed to use the particle swarm optimization (PSO) algorithm to improve the multiscale line detection (MSLD) method. The PSO algorithm was applied to find the best arrangement of scales in the MSLD method and to handle the problem of multiscale response recombination. The performance of the proposed method was evaluated on two low-resolution (DRIVE and STARE) and one high-resolution fundus (HRF) image datasets. The data include healthy (H) and diabetic retinopathy (DR) cases. The proposed approach improved the sensitivity rate against the MSLD by 4.7% for the DRIVE dataset and by 1.8% for the STARE dataset. For the high-resolution dataset, the proposed approach achieved 87.09% sensitivity rate, whereas the MSLD method achieves 82.58% sensitivity rate at the same specificity level. When only the smallest vessels were considered, the proposed approach improved the sensitivity rate by 11.02% and by 4.42% for the healthy and the diabetic cases, respectively. Integrating the proposed method in a comprehensive CAD system for DR screening would allow the reduction of false positives due to missed small vessels, misclassified as red lesions. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

PubMed Central

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-01-01

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543

A novel fiber Bragg grating wavelength demodulation system based on F-P etalon

NASA Astrophysics Data System (ADS)

Yang, Gang; Guo, Jinghong; Xu, Guoliang; Lv, Lidong; Tu, Guojie; Xia, Lan

2014-10-01

This paper designs and implies a high precision FBG demodulation system which based on F-P etalon. In order to reduce the influence of the temperature drift effect, the peristaltic effect, and the nonlinear effect of F-P filter in traditional tunable filter method, F-P etalon is added as dynamical calibration and wavelength reference. Meanwhile segmentation demodulation which uses ASE spectral characteristics is applied to achieve high accuracy of the center wavelength of FBG. The experiment shows that the stability, resolution are 0.65pm, 0.23pm, respectively. Key words: fiber optics; fiber Bragg grating sensor system; tunable Fabry-Perot filter; F-P etalon; spectrum segmentation demodulation

A Marked Poisson Process Driven Latent Shape Model for 3D Segmentation of Reflectance Confocal Microscopy Image Stacks of Human Skin.

PubMed

Ghanta, Sindhu; Jordan, Michael I; Kose, Kivanc; Brooks, Dana H; Rajadhyaksha, Milind; Dy, Jennifer G

2017-01-01

Segmenting objects of interest from 3D data sets is a common problem encountered in biological data. Small field of view and intrinsic biological variability combined with optically subtle changes of intensity, resolution, and low contrast in images make the task of segmentation difficult, especially for microscopy of unstained living or freshly excised thick tissues. Incorporating shape information in addition to the appearance of the object of interest can often help improve segmentation performance. However, the shapes of objects in tissue can be highly variable and design of a flexible shape model that encompasses these variations is challenging. To address such complex segmentation problems, we propose a unified probabilistic framework that can incorporate the uncertainty associated with complex shapes, variable appearance, and unknown locations. The driving application that inspired the development of this framework is a biologically important segmentation problem: the task of automatically detecting and segmenting the dermal-epidermal junction (DEJ) in 3D reflectance confocal microscopy (RCM) images of human skin. RCM imaging allows noninvasive observation of cellular, nuclear, and morphological detail. The DEJ is an important morphological feature as it is where disorder, disease, and cancer usually start. Detecting the DEJ is challenging, because it is a 2D surface in a 3D volume which has strong but highly variable number of irregularly spaced and variably shaped "peaks and valleys." In addition, RCM imaging resolution, contrast, and intensity vary with depth. Thus, a prior model needs to incorporate the intrinsic structure while allowing variability in essentially all its parameters. We propose a model which can incorporate objects of interest with complex shapes and variable appearance in an unsupervised setting by utilizing domain knowledge to build appropriate priors of the model. Our novel strategy to model this structure combines a spatial Poisson process with shape priors and performs inference using Gibbs sampling. Experimental results show that the proposed unsupervised model is able to automatically detect the DEJ with physiologically relevant accuracy in the range 10- 20 μm .

A Marked Poisson Process Driven Latent Shape Model for 3D Segmentation of Reflectance Confocal Microscopy Image Stacks of Human Skin

PubMed Central

Ghanta, Sindhu; Jordan, Michael I.; Kose, Kivanc; Brooks, Dana H.; Rajadhyaksha, Milind; Dy, Jennifer G.

2016-01-01

Segmenting objects of interest from 3D datasets is a common problem encountered in biological data. Small field of view and intrinsic biological variability combined with optically subtle changes of intensity, resolution and low contrast in images make the task of segmentation difficult, especially for microscopy of unstained living or freshly excised thick tissues. Incorporating shape information in addition to the appearance of the object of interest can often help improve segmentation performance. However, shapes of objects in tissue can be highly variable and design of a flexible shape model that encompasses these variations is challenging. To address such complex segmentation problems, we propose a unified probabilistic framework that can incorporate the uncertainty associated with complex shapes, variable appearance and unknown locations. The driving application which inspired the development of this framework is a biologically important segmentation problem: the task of automatically detecting and segmenting the dermal-epidermal junction (DEJ) in 3D reflectance confocal microscopy (RCM) images of human skin. RCM imaging allows noninvasive observation of cellular, nuclear and morphological detail. The DEJ is an important morphological feature as it is where disorder, disease and cancer usually start. Detecting the DEJ is challenging because it is a 2D surface in a 3D volume which has strong but highly variable number of irregularly spaced and variably shaped “peaks and valleys”. In addition, RCM imaging resolution, contrast and intensity vary with depth. Thus a prior model needs to incorporate the intrinsic structure while allowing variability in essentially all its parameters. We propose a model which can incorporate objects of interest with complex shapes and variable appearance in an unsupervised setting by utilizing domain knowledge to build appropriate priors of the model. Our novel strategy to model this structure combines a spatial Poisson process with shape priors and performs inference using Gibbs sampling. Experimental results show that the proposed unsupervised model is able to automatically detect the DEJ with physiologically relevant accuracy in the range 10 – 20µm. PMID:27723590

(Un)targeted Scanning of Locks of Hair for Drugs of Abuse by Direct Analysis in Real Time-High-Resolution Mass Spectrometry.

PubMed

Duvivier, Wilco F; van Putten, Marc R; van Beek, Teris A; Nielen, Michel W F

2016-02-16

Forensic hair evidence can be used to obtain retrospective timelines of drug use by analysis of hair segments. However, this is a laborious and time-consuming process, and mass spectrometric (MS) imaging techniques, which show great potential for single-hair targeted analysis, are less useful due to differences in hair growth rate between individual hairs. As an alternative, a fast untargeted analysis method was developed that uses direct analysis in real time-high-resolution mass spectrometry (DART-HRMS) to longitudinally scan intact locks of hair without extensive sample preparation or segmentation. The hair scan method was validated for cocaine against an accredited liquid chromatography/tandem mass spectrometry (LC/MS/MS) method. The detection limit for cocaine in hair was found to comply with the cutoff value of 0.5 ng/mg recommended by the Society of Hair Testing; that is, the DART hair scan method is amenable to forensic cases. Under DART conditions, no significant thermal degradation of cocaine occurred. The standard DART spot size of 5.1 ± 1.1 mm could be improved to 3.3 ± 1.0 mm, corresponding to approximately 10 days of hair growth, by using a high spatial resolution exit cone. By use of data-dependent product ion scans, multiple drugs of abuse could be detected in a single drug user hair scan with confirmation of identity by both exact mass and MS/HRMS fragmentation patterns. Furthermore, full-scan high-resolution data were retrospectively interrogated versus a list of more than 100 compounds and revealed additional hits and temporal profiles in good correlation with reported drug use.

Respiratory-gated segment reconstruction for radiation treatment planning using 256-slice CT-scanner during free breathing

NASA Astrophysics Data System (ADS)

Mori, Shinichiro; Endo, Masahiro; Kohno, Ryosuke; Minohara, Shinichi; Kohno, Kazutoshi; Asakura, Hiroshi; Fujiwara, Hideaki; Murase, Kenya

2005-04-01

The conventional respiratory-gated CT scan technique includes anatomic motion induced artifacts due to the low temporal resolution. They are a significant source of error in radiotherapy treatment planning for the thorax and upper abdomen. Temporal resolution and image quality are important factors to minimize planning target volume margin due to the respiratory motion. To achieve high temporal resolution and high signal-to-noise ratio, we developed a respiratory gated segment reconstruction algorithm and adapted it to Feldkamp-Davis-Kress algorithm (FDK) with a 256-detector row CT. The 256-detector row CT could scan approximately 100 mm in the cranio-caudal direction with 0.5 mm slice thickness in one rotation. Data acquisition for the RS-FDK relies on the assistance of the respiratory sensing system by a cine scan mode (table remains stationary). We evaluated RS-FDK in phantom study with the 256-detector row CT and compared it with full scan (FS-FDK) and HS-FDK results with regard to volume accuracy and image noise, and finally adapted the RS-FDK to an animal study. The RS-FDK gave a more accurate volume than the others and it had the same signal-to-noise ratio as the FS-FDK. In the animal study, the RS-FDK visualized the clearest edges of the liver and pulmonary vessels of all the algorithms. In conclusion, the RS-FDK algorithm has a capability of high temporal resolution and high signal-to-noise ratio. Therefore it will be useful when combined with new radiotherapy techniques including image guided radiation therapy (IGRT) and 4D radiation therapy.

Lung segmentation from HRCT using united geometric active contours

NASA Astrophysics Data System (ADS)

Liu, Junwei; Li, Chuanfu; Xiong, Jin; Feng, Huanqing

2007-12-01

Accurate lung segmentation from high resolution CT images is a challenging task due to various detail tracheal structures, missing boundary segments and complex lung anatomy. One popular method is based on gray-level threshold, however its results are usually rough. A united geometric active contours model based on level set is proposed for lung segmentation in this paper. Particularly, this method combines local boundary information and region statistical-based model synchronously: 1) Boundary term ensures the integrality of lung tissue.2) Region term makes the level set function evolve with global characteristic and independent on initial settings. A penalizing energy term is introduced into the model, which forces the level set function evolving without re-initialization. The method is found to be much more efficient in lung segmentation than other methods that are only based on boundary or region. Results are shown by 3D lung surface reconstruction, which indicates that the method will play an important role in the design of computer-aided diagnostic (CAD) system.

Globally optimal tumor segmentation in PET-CT images: a graph-based co-segmentation method.

PubMed

Han, Dongfeng; Bayouth, John; Song, Qi; Taurani, Aakant; Sonka, Milan; Buatti, John; Wu, Xiaodong

2011-01-01

Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET and low contrast in CT images. In this paper, we have proposed a general framework to use both PET and CT images simultaneously for tumor segmentation. Our method utilizes the strength of each imaging modality: the superior contrast of PET and the superior spatial resolution of CT. We formulate this problem as a Markov Random Field (MRF) based segmentation of the image pair with a regularized term that penalizes the segmentation difference between PET and CT. Our method simulates the clinical practice of delineating tumor simultaneously using both PET and CT, and is able to concurrently segment tumor from both modalities, achieving globally optimal solutions in low-order polynomial time by a single maximum flow computation. The method was evaluated on clinically relevant tumor segmentation problems. The results showed that our method can effectively make use of both PET and CT image information, yielding segmentation accuracy of 0.85 in Dice similarity coefficient and the average median hausdorff distance (HD) of 6.4 mm, which is 10% (resp., 16%) improvement compared to the graph cuts method solely using the PET (resp., CT) images.

Comparison of performance of object-based image analysis techniques available in open source software (Spring and Orfeo Toolbox/Monteverdi) considering very high spatial resolution data

NASA Astrophysics Data System (ADS)

Teodoro, Ana C.; Araujo, Ricardo

2016-01-01

The use of unmanned aerial vehicles (UAVs) for remote sensing applications is becoming more frequent. However, this type of information can result in several software problems related to the huge amount of data available. Object-based image analysis (OBIA) has proven to be superior to pixel-based analysis for very high-resolution images. The main objective of this work was to explore the potentialities of the OBIA methods available in two different open source software applications, Spring and OTB/Monteverdi, in order to generate an urban land cover map. An orthomosaic derived from UAVs was considered, 10 different regions of interest were selected, and two different approaches were followed. The first one (Spring) uses the region growing segmentation algorithm followed by the Bhattacharya classifier. The second approach (OTB/Monteverdi) uses the mean shift segmentation algorithm followed by the support vector machine (SVM) classifier. Two strategies were followed: four classes were considered using Spring and thereafter seven classes were considered for OTB/Monteverdi. The SVM classifier produces slightly better results and presents a shorter processing time. However, the poor spectral resolution of the data (only RGB bands) is an important factor that limits the performance of the classifiers applied.

High-Frequency Ultrasonic Imaging of the Anterior Segment Using an Annular Array Transducer

PubMed Central

Silverman, Ronald H.; Ketterling, Jeffrey A.; Coleman, D. Jackson

2006-01-01

Objective Very-high-frequency (>35 MHz) ultrasound (VHFU) allows imaging of anterior segment structures of the eye with a resolution of less than 40-μm. The low focal ratio of VHFU transducers, however, results in a depth-of-field (DOF) of less than 1-mm. Our aim was to develop a high-frequency annular array transducer for ocular imaging with improved DOF, sensitivity and resolution compared to conventional transducers. Design Experimental Study Participants Cadaver eyes, ex vivo cow eyes, in vivo rabbit eyes. Methods A spherically curved annular array ultrasound transducer was fabricated. The array consisted of five concentric rings of equal area, had an overall aperture of 6 mm and a geometric focus of 12 mm. The nominal center frequency of all array elements was 40 MHz. An experimental system was designed in which a single array element was pulsed and echo data recorded from all elements. By sequentially pulsing each element, echo data were acquired for all 25 transmit/receive annuli combinations. The echo data were then synthetically focused and composite images produced. Transducer operation was tested by scanning a test object consisting of a series of 25-μm diameter wires spaced at increasing range from the transducer. Imaging capabilities of the annular array were demonstrated in ex vivo bovine, in vivo rabbit and human cadaver eyes. Main Outcome Measures Depth of field, resolution and sensitivity. Results The wire scans verified the operation of the array and demonstrated a 6.0 mm DOF compared to the 1.0 mm DOF of a conventional single-element transducer of comparable frequency, aperture and focal length. B-mode images of ex vivo bovine, in vivo rabbit and cadaver eyes showed that while the single-element transducer had high sensitivity and resolution within 1–2 mm of its focus, the array with synthetic focusing maintained this quality over a 6 mm DOF. Conclusion An annular array for high-resolution ocular imaging has been demonstrated. This technology offers improved depth-of-field, sensitivity and lateral resolution compared to single-element fixed focus transducers currently used for VHFU imaging of the eye. PMID:17141314

High-frequency ultrasonic imaging of the anterior segment using an annular array transducer.

PubMed

Silverman, Ronald H; Ketterling, Jeffrey A; Coleman, D Jackson

2007-04-01

Very high-frequency ultrasound (VHFU; >35 megahertz [MHz]) allows imaging of anterior segment structures of the eye with a resolution of less than 40 microm. The low focal ratio of VHFU transducers, however, results in a depth of field (DOF) of less than 1 mm. The aim was to develop a high-frequency annular array transducer for ocular imaging with improved DOF, sensitivity, and resolution compared with conventional transducers. Experimental study. Cadaver eyes, ex vivo cow eyes, in vivo rabbit eyes. A spherically curved annular array ultrasound transducer was fabricated. The array consisted of 5 concentric rings of equal area, had an overall aperture of 6 mm, and a geometric focus of 12 mm. The nominal center frequency of all array elements was 40 MHz. An experimental system was designed in which a single array element was pulsed and echo data were recorded from all elements. By sequentially pulsing each element, echo data were acquired for all 25 transmit-and-receive annuli combinations. The echo data then were focused synthetically and composite images were produced. Transducer operation was tested by scanning a test object consisting of a series of 25-microm diameter wires spaced at increasing range from the transducer. Imaging capabilities of the annular array were demonstrated in ex vivo bovine, in vivo rabbit, and human cadaver eyes. Depth of field, resolution, and sensitivity. The wire scans verified the operation of the array and demonstrated a 6.0-mm DOF, compared with the 1.0-mm DOF of a conventional single-element transducer of comparable frequency, aperture, and focal length. B-mode images of ex vivo bovine, in vivo rabbit, and cadaver eyes showed that although the single-element transducer had high sensitivity and resolution within 1 to 2 mm of its focus, the array with synthetic focusing maintained this quality over a 6-mm DOF. An annular array for high-resolution ocular imaging has been demonstrated. This technology offers improved DOF, sensitivity, and lateral resolution compared with single-element fixed focus transducers currently used for VHFU imaging of the eye.

Assessment of Multiresolution Segmentation for Extracting Greenhouses from WORLDVIEW-2 Imagery

NASA Astrophysics Data System (ADS)

Aguilar, M. A.; Aguilar, F. J.; García Lorca, A.; Guirado, E.; Betlej, M.; Cichon, P.; Nemmaoui, A.; Vallario, A.; Parente, C.

2016-06-01

The latest breed of very high resolution (VHR) commercial satellites opens new possibilities for cartographic and remote sensing applications. In this way, object based image analysis (OBIA) approach has been proved as the best option when working with VHR satellite imagery. OBIA considers spectral, geometric, textural and topological attributes associated with meaningful image objects. Thus, the first step of OBIA, referred to as segmentation, is to delineate objects of interest. Determination of an optimal segmentation is crucial for a good performance of the second stage in OBIA, the classification process. The main goal of this work is to assess the multiresolution segmentation algorithm provided by eCognition software for delineating greenhouses from WorldView- 2 multispectral orthoimages. Specifically, the focus is on finding the optimal parameters of the multiresolution segmentation approach (i.e., Scale, Shape and Compactness) for plastic greenhouses. The optimum Scale parameter estimation was based on the idea of local variance of object heterogeneity within a scene (ESP2 tool). Moreover, different segmentation results were attained by using different combinations of Shape and Compactness values. Assessment of segmentation quality based on the discrepancy between reference polygons and corresponding image segments was carried out to identify the optimal setting of multiresolution segmentation parameters. Three discrepancy indices were used: Potential Segmentation Error (PSE), Number-of-Segments Ratio (NSR) and Euclidean Distance 2 (ED2).

Cell lineage and cell cycling analyses of the 4d micromere using live imaging in the marine annelid Platynereis dumerilii

PubMed Central

Handberg-Thorsager, Mette; Vervoort, Michel

2017-01-01

Cell lineage, cell cycle, and cell fate are tightly associated in developmental processes, but in vivo studies at single-cell resolution showing the intricacies of these associations are rare due to technical limitations. In this study on the marine annelid Platynereis dumerilii, we investigated the lineage of the 4d micromere, using high-resolution long-term live imaging complemented with a live-cell cycle reporter. 4d is the origin of mesodermal lineages and the germline in many spiralians. We traced lineages at single-cell resolution within 4d and demonstrate that embryonic segmental mesoderm forms via teloblastic divisions, as in clitellate annelids. We also identified the precise cellular origins of the larval mesodermal posterior growth zone. We found that differentially-fated progeny of 4d (germline, segmental mesoderm, growth zone) display significantly different cell cycling. This work has evolutionary implications, sets up the foundation for functional studies in annelid stem cells, and presents newly established techniques for live imaging marine embryos. PMID:29231816

Angular resolution of the gaseous micro-pixel detector Gossip

NASA Astrophysics Data System (ADS)

Bilevych, Y.; Blanco Carballo, V.; van Dijk, M.; Fransen, M.; van der Graaf, H.; Hartjes, F.; Hessey, N.; Koppert, W.; Nauta, S.; Rogers, M.; Romaniouk, A.; Veenhof, R.

2011-06-01

Gossip is a gaseous micro-pixel detector with a very thin drift gap intended for a high rate environment like at the pixel layers of ATLAS at the sLHC. The detector outputs not only the crossing point of a traversing MIP, but also the angle of the track, thus greatly simplifying track reconstruction. In this paper we describe a testbeam experiment to examine the angular resolution of the reconstructed track segments in Gossip. We used here the low diffusion gas mixture DME/CO 2 50/50. An angular resolution of 20 mrad for perpendicular tracks could be obtained from a 1.5 mm thin drift volume. However, for the prototype detector used at the testbeam experiment, the resolution of slanting tracks was worsened by poor time resolution of the pixel chip used.

T1-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250 μm.

PubMed

Lüsebrink, Falk; Sciarra, Alessandro; Mattern, Hendrik; Yakupov, Renat; Speck, Oliver

2017-03-14

We present an ultrahigh resolution in vivo human brain magnetic resonance imaging (MRI) dataset. It consists of T 1 -weighted whole brain anatomical data acquired at 7 Tesla with a nominal isotropic resolution of 250 μm of a single young healthy Caucasian subject and was recorded using prospective motion correction. The raw data amounts to approximately 1.2 TB and was acquired in eight hours total scan time. The resolution of this dataset is far beyond any previously published in vivo structural whole brain dataset. Its potential use is to build an in vivo MR brain atlas. Methods for image reconstruction and image restoration can be improved as the raw data is made available. Pre-processing and segmentation procedures can possibly be enhanced for high magnetic field strength and ultrahigh resolution data. Furthermore, potential resolution induced changes in quantitative data analysis can be assessed, e.g., cortical thickness or volumetric measures, as high quality images with an isotropic resolution of 1 and 0.5 mm of the same subject are included in the repository as well.

T1-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250 μm

NASA Astrophysics Data System (ADS)

Lüsebrink, Falk; Sciarra, Alessandro; Mattern, Hendrik; Yakupov, Renat; Speck, Oliver

2017-03-01

We present an ultrahigh resolution in vivo human brain magnetic resonance imaging (MRI) dataset. It consists of T1-weighted whole brain anatomical data acquired at 7 Tesla with a nominal isotropic resolution of 250 μm of a single young healthy Caucasian subject and was recorded using prospective motion correction. The raw data amounts to approximately 1.2 TB and was acquired in eight hours total scan time. The resolution of this dataset is far beyond any previously published in vivo structural whole brain dataset. Its potential use is to build an in vivo MR brain atlas. Methods for image reconstruction and image restoration can be improved as the raw data is made available. Pre-processing and segmentation procedures can possibly be enhanced for high magnetic field strength and ultrahigh resolution data. Furthermore, potential resolution induced changes in quantitative data analysis can be assessed, e.g., cortical thickness or volumetric measures, as high quality images with an isotropic resolution of 1 and 0.5 mm of the same subject are included in the repository as well.

Retinal Structure of Birds of Prey Revealed by Ultra-High Resolution Spectral-Domain Optical Coherence Tomography

PubMed Central

Ruggeri, Marco; Major, James C.; McKeown, Craig; Knighton, Robert W.; Puliafito, Carmen A.

2010-01-01

Purpose. To reveal three-dimensional (3-D) information about the retinal structures of birds of prey in vivo. Methods. An ultra-high resolution spectral-domain optical coherence tomography (SD-OCT) system was built for in vivo imaging of retinas of birds of prey. The calibrated imaging depth and axial resolution of the system were 3.1 mm and 2.8 μm (in tissue), respectively. 3-D segmentation was performed for calculation of the retinal nerve fiber layer (RNFL) map. Results. High-resolution OCT images were obtained of the retinas of four species of birds of prey: two diurnal hawks (Buteo platypterus and Buteo brachyurus) and two nocturnal owls (Bubo virginianus and Strix varia). These images showed the detailed retinal anatomy, including the retinal layers and the structure of the deep and shallow foveae. The calculated thickness map showed the RNFL distribution. Traumatic injury to one bird's retina was also successfully imaged. Conclusions. Ultra-high resolution SD-OCT provides unprecedented high-quality 2-D and 3-D in vivo visualization of the retinal structures of birds of prey. SD-OCT is a powerful imaging tool for vision research in birds of prey. PMID:20554605

Kinematic Alignment and Bonding of Silicon Mirrors for High-Resolution Astronomical X-Ray Optics

NASA Technical Reports Server (NTRS)

Chan, Kai-Wing; Mazzarella, James R.; Saha, Timo T.; Zhang, William W.; Mcclelland, Ryan S.; Biskack, Michael P.; Riveros, Raul E.; Allgood, Kim D.; Kearney, John D.; Sharpe, Marton V.;

Automated tumor volumetry using computer-aided image segmentation.

PubMed

Gaonkar, Bilwaj; Macyszyn, Luke; Bilello, Michel; Sadaghiani, Mohammed Salehi; Akbari, Hamed; Atthiah, Mark A; Ali, Zarina S; Da, Xiao; Zhan, Yiqang; O'Rourke, Donald; Grady, Sean M; Davatzikos, Christos

2015-05-01

Accurate segmentation of brain tumors, and quantification of tumor volume, is important for diagnosis, monitoring, and planning therapeutic intervention. Manual segmentation is not widely used because of time constraints. Previous efforts have mainly produced methods that are tailored to a particular type of tumor or acquisition protocol and have mostly failed to produce a method that functions on different tumor types and is robust to changes in scanning parameters, resolution, and image quality, thereby limiting their clinical value. Herein, we present a semiautomatic method for tumor segmentation that is fast, accurate, and robust to a wide variation in image quality and resolution. A semiautomatic segmentation method based on the geodesic distance transform was developed and validated by using it to segment 54 brain tumors. Glioblastomas, meningiomas, and brain metastases were segmented. Qualitative validation was based on physician ratings provided by three clinical experts. Quantitative validation was based on comparing semiautomatic and manual segmentations. Tumor segmentations obtained using manual and automatic methods were compared quantitatively using the Dice measure of overlap. Subjective evaluation was performed by having human experts rate the computerized segmentations on a 0-5 rating scale where 5 indicated perfect segmentation. The proposed method addresses a significant, unmet need in the field of neuro-oncology. Specifically, this method enables clinicians to obtain accurate and reproducible tumor volumes without the need for manual segmentation. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Automated Tumor Volumetry Using Computer-Aided Image Segmentation

PubMed Central

Bilello, Michel; Sadaghiani, Mohammed Salehi; Akbari, Hamed; Atthiah, Mark A.; Ali, Zarina S.; Da, Xiao; Zhan, Yiqang; O'Rourke, Donald; Grady, Sean M.; Davatzikos, Christos

2015-01-01

Rationale and Objectives Accurate segmentation of brain tumors, and quantification of tumor volume, is important for diagnosis, monitoring, and planning therapeutic intervention. Manual segmentation is not widely used because of time constraints. Previous efforts have mainly produced methods that are tailored to a particular type of tumor or acquisition protocol and have mostly failed to produce a method that functions on different tumor types and is robust to changes in scanning parameters, resolution, and image quality, thereby limiting their clinical value. Herein, we present a semiautomatic method for tumor segmentation that is fast, accurate, and robust to a wide variation in image quality and resolution. Materials and Methods A semiautomatic segmentation method based on the geodesic distance transform was developed and validated by using it to segment 54 brain tumors. Glioblastomas, meningiomas, and brain metastases were segmented. Qualitative validation was based on physician ratings provided by three clinical experts. Quantitative validation was based on comparing semiautomatic and manual segmentations. Results Tumor segmentations obtained using manual and automatic methods were compared quantitatively using the Dice measure of overlap. Subjective evaluation was performed by having human experts rate the computerized segmentations on a 0–5 rating scale where 5 indicated perfect segmentation. Conclusions The proposed method addresses a significant, unmet need in the field of neuro-oncology. Specifically, this method enables clinicians to obtain accurate and reproducible tumor volumes without the need for manual segmentation. PMID:25770633

A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Rosen, Mark; Madabhushi, Anant

2008-03-01

Current techniques for localization of prostatic adenocarcinoma (CaP) via blinded trans-rectal ultrasound biopsy are associated with a high false negative detection rate. While high resolution endorectal in vivo Magnetic Resonance (MR) prostate imaging has been shown to have improved contrast and resolution for CaP detection over ultrasound, similarity in intensity characteristics between benign and cancerous regions on MR images contribute to a high false positive detection rate. In this paper, we present a novel unsupervised segmentation method that employs manifold learning via consensus schemes for detection of cancerous regions from high resolution 1.5 Tesla (T) endorectal in vivo prostate MRI. A significant contribution of this paper is a method to combine multiple weak, lower-dimensional representations of high dimensional feature data in a way analogous to classifier ensemble schemes, and hence create a stable and accurate reduced dimensional representation. After correcting for MR image intensity artifacts, such as bias field inhomogeneity and intensity non-standardness, our algorithm extracts over 350 3D texture features at every spatial location in the MR scene at multiple scales and orientations. Non-linear dimensionality reduction schemes such as Locally Linear Embedding (LLE) and Graph Embedding (GE) are employed to create multiple low dimensional data representations of this high dimensional texture feature space. Our novel consensus embedding method is used to average object adjacencies from within the multiple low dimensional projections so that class relationships are preserved. Unsupervised consensus clustering is then used to partition the objects in this consensus embedding space into distinct classes. Quantitative evaluation on 18 1.5 T prostate MR data against corresponding histology obtained from the multi-site ACRIN trials show a sensitivity of 92.65% and a specificity of 82.06%, which suggests that our method is successfully able to detect suspicious regions in the prostate.

Comparison of an adaptive local thresholding method on CBCT and µCT endodontic images

NASA Astrophysics Data System (ADS)

Michetti, Jérôme; Basarab, Adrian; Diemer, Franck; Kouame, Denis

2018-01-01

Root canal segmentation on cone beam computed tomography (CBCT) images is difficult because of the noise level, resolution limitations, beam hardening and dental morphological variations. An image processing framework, based on an adaptive local threshold method, was evaluated on CBCT images acquired on extracted teeth. A comparison with high quality segmented endodontic images on micro computed tomography (µCT) images acquired from the same teeth was carried out using a dedicated registration process. Each segmented tooth was evaluated according to volume and root canal sections through the area and the Feret’s diameter. The proposed method is shown to overcome the limitations of CBCT and to provide an automated and adaptive complete endodontic segmentation. Despite a slight underestimation (-4, 08%), the local threshold segmentation method based on edge-detection was shown to be fast and accurate. Strong correlations between CBCT and µCT segmentations were found both for the root canal area and diameter (respectively 0.98 and 0.88). Our findings suggest that combining CBCT imaging with this image processing framework may benefit experimental endodontology, teaching and could represent a first development step towards the clinical use of endodontic CBCT segmentation during pulp cavity treatment.

Restoring Wood-Rich Hotspots in Mountain Stream Networks

NASA Astrophysics Data System (ADS)

Wohl, E.; Scott, D.

2016-12-01

Mountain streams commonly include substantial longitudinal variability in valley and channel geometry, alternating repeatedly between steep, narrow and relatively wide, low gradient segments. Segments that are wider and lower gradient than neighboring steeper sections are hotspots with respect to: retention of large wood (LW) and finer sediment and organic matter; uptake of nutrients; and biomass and biodiversity of aquatic and riparian organisms. These segments are also more likely to be transport-limited with respect to floodplain and instream LW. Management designed to protect and restore riverine LW and the physical and ecological processes facilitated by the presence of LW is likely to be most effective if focused on relatively low-gradient stream segments. These segments can be identified using a simple, reach-scale gradient analysis based on high-resolution DEMs, with field visits to identify factors that potentially limit or facilitate LW recruitment and retention, such as forest disturbance history or land use. Drawing on field data from the western US, this presentation outlines a procedure for mapping relatively low-gradient segments in a stream network and for identifying those segments where LW reintroduction or retention is most likely to balance maximizing environmental benefits derived from the presence of LW while minimizing hazards associated with LW.

Design and end-to-end modelling of a deployable telescope

NASA Astrophysics Data System (ADS)

Dolkens, Dennis; Kuiper, Hans

2017-09-01

Deployable optics have the potential of revolutionizing the field of high resolution Earth Observation. By offering the same resolutions as a conventional telescope, while using a much smaller launch volume and mass, the costs of high resolution image data can be brought down drastically. In addition, the technology will ultimately enable resolutions that are currently unattainable due to limitations imposed by the size of launcher fairings. To explore the possibilities and system complexities of a deployable telescope, a concept study was done to design a competitive deployable imager. A deployable telescope was designed for a ground sampling distance of 25 cm from an orbital altitude of 550 km. It offers an angular field of view of 0.6° and has a panchromatic channel as well as four multispectral bands in the visible and near infrared spectrum. The optical design of the telescope is based on an off-axis Korsch Three Mirror Anastigmat. A freeform tertiary mirror is used to ensure a diffraction limited image quality for all channels, while maintaining a compact design. The segmented primary mirror consists of four tapered aperture segments, which can be folded down during launch, while the secondary mirror is mounted on a deployable boom. In its stowed configuration, the telescope fits within a quarter of the volume of a conventional telescope reaching the same resolution. To reach a diffraction limited performance while operating in orbit, the relative position of each individual mirror segment must be controlled to a fraction of a wavelength. Reaching such tolerances with deployable telescope challenging, due to inherent uncertainties in the deployment mechanisms. Adding to the complexity is the fact that the telescope will be operating in a Low Earth Orbit (LEO) where it will be exposed to very dynamic thermal conditions. Therefore, the telescope will be equipped with a robust calibration system. Actuators underneath the primary mirror will be controlled using a closed-loop system based on measurements of the image sharpness as well as measurements obtained with edge sensors placed between the mirror segments. In addition, a phase diversity system will be used to recover residual wavefront aberrations. To aid the design of the deployable telescope, an end-to-end performance model was developed. The model is built around a dedicated ray-trace program written in Matlab. This program was built from the ground up for the purpose of modelling segmented telescope systems and allows for surface data computed with Finite Element Models (FEM) to be imported in the model. The program also contains modules which can simulate the closed-loop calibration of the telescope and it can use simulated images as an input for phase diversity and image processing algorithms. For a given thermo-mechanical state, the end-to-end model can predict the image quality that will be obtained after the calibration has been completed and the image has been processed. As such, the model is a powerful systems engineering tool, which can be used to optimize the in-orbit performance of a segmented, deployable telescope.

Detecting the Reconnection Electron Diffusion Regions in Magnetospheric MultiScale mission high resolution data

NASA Astrophysics Data System (ADS)

Shimoda, E.; Eriksson, S.; Ahmadi, N.; Ergun, R.; Wilder, F. D.; Goodrich, K.

2017-12-01

The Magnetospheric Multi-Scale (MMS) mission resolves the small-scale structure of the Reconnection Electron Diffusion Regions (EDRs) using four spacecraft. We have surveyed two years of MMS data to find the candidates for the EDRs. We searched all the high-resolution segments when Fast Plasma Investigation (FPI) instrument was on. The search criteria are based on measuring the dissipation rate, agyrotropy, a reversal in jet velocity and magnetic field. Once these events were found for MMS1 data, the burst period for the other spacecraft was analyzed. We present our results of the best possible EDR candidates.

Steroid-responsive polyradiculopathy in association with focal segmental glomerulosclerosis

PubMed Central

Chapman, Andrew R.; Gamble, Paul; Pollock, Anne Marie; Joss, Nicola

2013-01-01

An 80-year-old woman presented with simultaneous increasing muscle weakness and nephrotic syndrome. A renal biopsy confirmed focal segmental glomerulosclerosis (FSGS). Her neurological diagnosis best fitted with a Guillain–Barre-like syndrome. There have been several cases of FSGS in combination with both conventional and atypical Guillain–Barre syndrome (GBS). Our patient was treated with high-dose steroids and resolution of both nephrotic syndrome and neurological symptoms occurred over 6 months. This article reviews all previously published presentations of this nature and discusses putative mechanisms for the development of concurrent FSGS and GBS. PMID:26069832

Plexus structure imaging with thin slab MR neurography: rotating frames, fly-throughs, and composite projections

NASA Astrophysics Data System (ADS)

Raphael, David T.; McIntee, Diane; Tsuruda, Jay S.; Colletti, Patrick; Tatevossian, Raymond; Frazier, James

2006-03-01

We explored multiple image processing approaches by which to display the segmented adult brachial plexus in a three-dimensional manner. Magnetic resonance neurography (MRN) 1.5-Tesla scans with STIR sequences, which preferentially highlight nerves, were performed in adult volunteers to generate high-resolution raw images. Using multiple software programs, the raw MRN images were then manipulated so as to achieve segmentation of plexus neurovascular structures, which were incorporated into three different visualization schemes: rotating upper thoracic girdle skeletal frames, dynamic fly-throughs parallel to the clavicle, and thin slab volume-rendered composite projections.

Interferometric fibre-optic curvature sensing for structural, directional vibration measurements

NASA Astrophysics Data System (ADS)

Kissinger, Thomas; Chehura, Edmon; James, Stephen W.; Tatam, Ralph P.

2017-06-01

Dynamic fibre-optic curvature sensing using fibre segment interferometry is demonstrated using a cost-effective rangeresolved interferometry interrogation system. Differential strain measurements from four fibre strings, each containing four fibre segments of gauge length 20 cm, allow the inference of lateral vibrations as well as the direction of the vibration of a cantilever test object. Dynamic tip displacement resolutions in the micrometre range over a 21 kHz interferometric bandwidth demonstrate the suitability of this approach for highly sensitive fibre-optic directional vibration measurements, complementing existing laser vibrometry techniques by removing the need for side access to the structure under test.

Intelligent image processing for vegetation classification using multispectral LANDSAT data

NASA Astrophysics Data System (ADS)

Santos, Stewart R.; Flores, Jorge L.; Garcia-Torales, G.

2015-09-01

We propose an intelligent computational technique for analysis of vegetation imaging, which are acquired with multispectral scanner (MSS) sensor. This work focuses on intelligent and adaptive artificial neural network (ANN) methodologies that allow segmentation and classification of spectral remote sensing (RS) signatures, in order to obtain a high resolution map, in which we can delimit the wooded areas and quantify the amount of combustible materials present into these areas. This could provide important information to prevent fires and deforestation of wooded areas. The spectral RS input data, acquired by the MSS sensor, are considered in a random propagation remotely sensed scene with unknown statistics for each Thematic Mapper (TM) band. Performing high-resolution reconstruction and adding these spectral values with neighbor pixels information from each TM band, we can include contextual information into an ANN. The biggest challenge in conventional classifiers is how to reduce the number of components in the feature vector, while preserving the major information contained in the data, especially when the dimensionality of the feature space is high. Preliminary results show that the Adaptive Modified Neural Network method is a promising and effective spectral method for segmentation and classification in RS images acquired with MSS sensor.

A novel single-ended readout depth-of-interaction PET detector fabricated using sub-surface laser engraving.

PubMed

Uchida, H; Sakai, T; Yamauchi, H; Hakamata, K; Shimizu, K; Yamashita, T

2016-09-21

We propose a novel scintillation detector design for positron emission tomography (PET), which has depth of interaction (DOI) capability and uses a single-ended readout scheme. The DOI detector contains a pair of crystal bars segmented using sub-surface laser engraving (SSLE). The two crystal bars are optically coupled to each other at their top segments and are coupled to two photo-sensors at their bottom segments. Initially, we evaluated the performance of different designs of single crystal bars coupled to photomultiplier tubes at both ends. We found that segmentation by SSLE results in superior performance compared to the conventional method. As the next step, we constructed a crystal unit composed of a 3  ×  3  ×  20 mm 3 crystal bar pair, with each bar containing four layers segmented using the SSLE. We measured the DOI performance by changing the optical conditions for the crystal unit. Based on the experimental results, we then assessed the detector performance in terms of the DOI capability by evaluating the position error, energy resolution, and light collection efficiency for various crystal unit designs with different bar sizes and a different number of layers (four to seven layers). DOI encoding with small position error was achieved for crystal units composed of a 3  ×  3  ×  20 mm 3 LYSO bar pair having up to seven layers, and with those composed of a 2  ×  2  ×  20 mm 3 LYSO bar pair having up to six layers. The energy resolution of the segment in the seven-layer 3  ×  3  ×  20 mm 3 crystal bar pair was 9.3%-15.5% for 662 keV gamma-rays, where the segments closer to the photo-sensors provided better energy resolution. SSLE provides high geometrical accuracy at low production cost due to the simplicity of the crystal assembly. Therefore, the proposed DOI detector is expected to be an attractive choice for practical small-bore PET systems dedicated to imaging of the brain, breast, and small animals.

In vivo imaging of raptor retina with ultra high resolution spectral domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Ruggeri, Marco; Major, James C., Jr.; McKeown, Craig; Wehbe, Hassan; Jiao, Shuliang; Puliafito, Carmen A.

2008-02-01

Among birds, raptors are well known for their exceptional eyesight, which is partly due to the unique structure of their retina. Because the raptor retina is the most advanced of any animal species, in vivo examination of its structure would be remarkable. Furthermore, a noticeable percentage of traumatic ocular injuries are identified in birds of prey presented to rehabilitation facilities. Injuries affecting the posterior segment have been considered as a major impact on raptor vision. Hence, in vivo examination of the structure of the posterior segment of the raptors would be helpful for the diagnosis of traumatized birds. The purpose of this study is to demonstrate the application of ultrahigh-resolution Spectral Domain Optical Coherence Tomography (SD-OCT) for non contact in vivo imaging of the retina of birds of prey, which to the best of our knowledge has never been attempted. For the first time we present high quality OCT images of the retina of two species of bird of prey, one diurnal hawk and one nocturnal owl.

Genetically targeted 3D visualisation of Drosophila neurons under Electron Microscopy and X-Ray Microscopy using miniSOG

PubMed Central

Ng, Julian; Browning, Alyssa; Lechner, Lorenz; Terada, Masako; Howard, Gillian; Jefferis, Gregory S. X. E.

2016-01-01

Large dimension, high-resolution imaging is important for neural circuit visualisation as neurons have both long- and short-range patterns: from axons and dendrites to the numerous synapses at terminal endings. Electron Microscopy (EM) is the favoured approach for synaptic resolution imaging but how such structures can be segmented from high-density images within large volume datasets remains challenging. Fluorescent probes are widely used to localise synapses, identify cell-types and in tracing studies. The equivalent EM approach would benefit visualising such labelled structures from within sub-cellular, cellular, tissue and neuroanatomical contexts. Here we developed genetically-encoded, electron-dense markers using miniSOG. We demonstrate their ability in 1) labelling cellular sub-compartments of genetically-targeted neurons, 2) generating contrast under different EM modalities, and 3) segmenting labelled structures from EM volumes using computer-assisted strategies. We also tested non-destructive X-ray imaging on whole Drosophila brains to evaluate contrast staining. This enabled us to target specific regions for EM volume acquisition. PMID:27958322

Production of primary mirror segments for the Giant Magellan Telescope

NASA Astrophysics Data System (ADS)

Martin, H. M.; Allen, R. G.; Burge, J. H.; Davis, J. M.; Davison, W. B.; Johns, M.; Kim, D. W.; Kingsley, J. S.; Law, K.; Lutz, R. D.; Strittmatter, P. A.; Su, P.; Tuell, M. T.; West, S. C.; Zhou, P.

2014-07-01

Segment production for the Giant Magellan Telescope is well underway, with the off-axis Segment 1 completed, off-axis Segments 2 and 3 already cast, and mold construction in progress for the casting of Segment 4, the center segment. All equipment and techniques required for segment fabrication and testing have been demonstrated in the manufacture of Segment 1. The equipment includes a 28 m test tower that incorporates four independent measurements of the segment's figure and geometry. The interferometric test uses a large asymmetric null corrector with three elements including a 3.75 m spherical mirror and a computer-generated hologram. For independent verification of the large-scale segment shape, we use a scanning pentaprism test that exploits the natural geometry of the telescope to focus collimated light to a point. The Software Configurable Optical Test System, loosely based on the Hartmann test, measures slope errors to submicroradian accuracy at high resolution over the full aperture. An enhanced laser tracker system guides the figuring through grinding and initial polishing. All measurements agree within the expected uncertainties, including three independent measurements of radius of curvature that agree within 0.3 mm. Segment 1 was polished using a 1.2 m stressed lap for smoothing and large-scale figuring, and a set of smaller passive rigid-conformal laps on an orbital polisher for deterministic small-scale figuring. For the remaining segments, the Mirror Lab is building a smaller, orbital stressed lap to combine the smoothing capability with deterministic figuring.

Multi-class segmentation of neuronal electron microscopy images using deep learning

NASA Astrophysics Data System (ADS)

Khobragade, Nivedita; Agarwal, Chirag

2018-03-01

Study of connectivity of neural circuits is an essential step towards a better understanding of functioning of the nervous system. With the recent improvement in imaging techniques, high-resolution and high-volume images are being generated requiring automated segmentation techniques. We present a pixel-wise classification method based on Bayesian SegNet architecture. We carried out multi-class segmentation on serial section Transmission Electron Microscopy (ssTEM) images of Drosophila third instar larva ventral nerve cord, labeling the four classes of neuron membranes, neuron intracellular space, mitochondria and glia / extracellular space. Bayesian SegNet was trained using 256 ssTEM images of 256 x 256 pixels and tested on 64 different ssTEM images of the same size, from the same serial stack. Due to high class imbalance, we used a class-balanced version of Bayesian SegNet by re-weighting each class based on their relative frequency. We achieved an overall accuracy of 93% and a mean class accuracy of 88% for pixel-wise segmentation using this encoder-decoder approach. On evaluating the segmentation results using similarity metrics like SSIM and Dice Coefficient, we obtained scores of 0.994 and 0.886 respectively. Additionally, we used the network trained using the 256 ssTEM images of Drosophila third instar larva for multi-class labeling of ISBI 2012 challenge ssTEM dataset.

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

PubMed

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

2018-07-01

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

The use of the Kalman filter in the automated segmentation of EIT lung images.

PubMed

Zifan, A; Liatsis, P; Chapman, B E

2013-06-01

In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging.

Ultrahigh-Resolution Optical Coherence Tomography in Glaucoma

PubMed Central

Wollstein, Gadi; Paunescu, Leila A.; Ko, Tony H.; Fujimoto, James G.; Kowalevicz, Andrew; Hartl, Ingmar; Beaton, Siobahn; Ishikawa, Hiroshi; Mattox, Cynthia; Singh, Omah; Duker, Jay; Drexler, Wolfgang; Schuman, Joel S.

2007-01-01

Objective Optical coherence tomography (OCT) has been shown to be a valuable tool in glaucoma assessment. We investigated a new ultrahigh-resolution OCT (UHR-OCT) imaging system in glaucoma patients and compared the findings with those obtained by conventional-resolution OCT. Design Retrospective comparative case series. Participants A normal subject and 4 glaucoma patients representing various stages of glaucomatous damage. Testing All participants were scanned with StratusOCT (axial resolution of ~10 μm) and UHR-OCT (axial resolution of ~3 μm) at the same visit. Main Outcome Measure Comparison of OCT findings detected with StratusOCT and UHR-OCT. Results Ultrahigh-resolution OCT provides a detailed cross-sectional view of the scanned retinal area that allows differentiation between retinal layers. These UHR images were markedly better than those obtained by the conventional-resolution OCT. Conclusions Ultrahigh-resolution OCT provides high-resolution images of the ocular posterior segment, which improves the ability to detect retinal abnormalities due to glaucoma. PMID:15691556

A Pulse Coupled Neural Network Segmentation Algorithm for Reflectance Confocal Images of Epithelial Tissue

PubMed Central

Malik, Bilal H.; Jabbour, Joey M.; Maitland, Kristen C.

2015-01-01

Automatic segmentation of nuclei in reflectance confocal microscopy images is critical for visualization and rapid quantification of nuclear-to-cytoplasmic ratio, a useful indicator of epithelial precancer. Reflectance confocal microscopy can provide three-dimensional imaging of epithelial tissue in vivo with sub-cellular resolution. Changes in nuclear density or nuclear-to-cytoplasmic ratio as a function of depth obtained from confocal images can be used to determine the presence or stage of epithelial cancers. However, low nuclear to background contrast, low resolution at greater imaging depths, and significant variation in reflectance signal of nuclei complicate segmentation required for quantification of nuclear-to-cytoplasmic ratio. Here, we present an automated segmentation method to segment nuclei in reflectance confocal images using a pulse coupled neural network algorithm, specifically a spiking cortical model, and an artificial neural network classifier. The segmentation algorithm was applied to an image model of nuclei with varying nuclear to background contrast. Greater than 90% of simulated nuclei were detected for contrast of 2.0 or greater. Confocal images of porcine and human oral mucosa were used to evaluate application to epithelial tissue. Segmentation accuracy was assessed using manual segmentation of nuclei as the gold standard. PMID:25816131

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells.

PubMed

Stylianidou, Stella; Brennan, Connor; Nissen, Silas B; Kuwada, Nathan J; Wiggins, Paul A

2016-11-01

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution. © 2016 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships.

PubMed

Hatipoglu, Nuh; Bilgin, Gokhan

2017-10-01

In many computerized methods for cell detection, segmentation, and classification in digital histopathology that have recently emerged, the task of cell segmentation remains a chief problem for image processing in designing computer-aided diagnosis (CAD) systems. In research and diagnostic studies on cancer, pathologists can use CAD systems as second readers to analyze high-resolution histopathological images. Since cell detection and segmentation are critical for cancer grade assessments, cellular and extracellular structures should primarily be extracted from histopathological images. In response, we sought to identify a useful cell segmentation approach with histopathological images that uses not only prominent deep learning algorithms (i.e., convolutional neural networks, stacked autoencoders, and deep belief networks), but also spatial relationships, information of which is critical for achieving better cell segmentation results. To that end, we collected cellular and extracellular samples from histopathological images by windowing in small patches with various sizes. In experiments, the segmentation accuracies of the methods used improved as the window sizes increased due to the addition of local spatial and contextual information. Once we compared the effects of training sample size and influence of window size, results revealed that the deep learning algorithms, especially convolutional neural networks and partly stacked autoencoders, performed better than conventional methods in cell segmentation.

National Hydrography Dataset (NHD)

USGS Publications Warehouse

,

2001-01-01

The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000 scale and exists at that scale for the whole country. High resolution NHD adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Like the 1:100,000-scale NHD, high resolution NHD contains reach codes for networked features and isolated lakes, flow direction, names, stream level, and centerline representations for areal water bodies. Reaches are also defined to represent waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria set out by the Federal Geographic Data Committee.

Patterns of Emphysema Heterogeneity

PubMed Central

Valipour, Arschang; Shah, Pallav L.; Gesierich, Wolfgang; Eberhardt, Ralf; Snell, Greg; Strange, Charlie; Barry, Robert; Gupta, Avina; Henne, Erik; Bandyopadhyay, Sourish; Raffy, Philippe; Yin, Youbing; Tschirren, Juerg; Herth, Felix J.F.

2016-01-01

Background Although lobar patterns of emphysema heterogeneity are indicative of optimal target sites for lung volume reduction (LVR) strategies, the presence of segmental, or sublobar, heterogeneity is often underappreciated. Objective The aim of this study was to understand lobar and segmental patterns of emphysema heterogeneity, which may more precisely indicate optimal target sites for LVR procedures. Methods Patterns of emphysema heterogeneity were evaluated in a representative cohort of 150 severe (GOLD stage III/IV) chronic obstructive pulmonary disease (COPD) patients from the COPDGene study. High-resolution computerized tomography analysis software was used to measure tissue destruction throughout the lungs to compute heterogeneity (≥ 15% difference in tissue destruction) between (inter-) and within (intra-) lobes for each patient. Emphysema tissue destruction was characterized segmentally to define patterns of heterogeneity. Results Segmental tissue destruction revealed interlobar heterogeneity in the left lung (57%) and right lung (52%). Intralobar heterogeneity was observed in at least one lobe of all patients. No patient presented true homogeneity at a segmental level. There was true homogeneity across both lungs in 3% of the cohort when defining heterogeneity as ≥ 30% difference in tissue destruction. Conclusion Many LVR technologies for treatment of emphysema have focused on interlobar heterogeneity and target an entire lobe per procedure. Our observations suggest that a high proportion of patients with emphysema are affected by interlobar as well as intralobar heterogeneity. These findings prompt the need for a segmental approach to LVR in the majority of patients to treat only the most diseased segments and preserve healthier ones. PMID:26430783

Along-strike slab segmentation under Greece from a 500 km long teleseismic receiver-function swath profile : control on large earthquakes, upper plate motion, and surface morphology

NASA Astrophysics Data System (ADS)

Sachpazi, M.; Laigle, M.; Diaz, J.; Gesret, A.; Charalampakis, M.; Kissling, E. H.; Hirn, A.

2010-12-01

Observations from teleseismic converted waves recorded at 100 sites in Greece from Crete to North Aegean in a 500 km swath along the slab strike during the EU project “Thales was right” allow imaging its top in 3D. Multiscale analysis brings high-resolution to interface imaging at depth which resolved for the first time a thin, oceanic, crust for the slab under southern Greece. This first indication of its large negative buoyancy suggests its roll-back and is consistent with the upper plate trenchward motion with the highest velocities there, as shown by GPS. With respect to up to now subduction zone surveys with receivers deployed along the presumed dip to get a cross-section of the downgoing slab, our swath was instead perpendicular, that is along strike. This was in order to track down lateral changes in slab attitude along the subduction zone, that is a possible segmentation. The expected subduction strike at shallow depth, as approximated by a line from SW of Crete to W of the Ionian Islands is about N 135°E. Instead, the slab top is found along an almost N-S line at several places, at 60-70 km depth. However the slab depth contours deviate from it in-between. Their broad correspondance with the Aegean coastline or extensional domain suggests a possible control on surface morphology, and on upper plate deformation as mirrored in the topography of its crust-mantle boundary. Indeed, this first image recovered with such a high lateral resolution reveals that several slab segments can be defined dipping N 60°E, that is with a N 160 °E strike, and that these are juxtaposed through domains of strong localized variations along-strike that suggest warping or tearing of the slab. Apart their strong bearing on geodynamic reconstructions, and the continental/oceanic nature of the slab fragments, these 3D images reach the high-resolution for their discussion with respect to major earthquakes. The attitude of the slab, the dip of its upper part and its buoyancy force enter the balance controlling the degree of seismic coupling, of the seismogenic interplate fault, as well as its along dip extent as discussed earlier for the Ionian Islands. The segmented nature revealed at depth suggests a possible segmentation of the shallower interplate seismogenic zone. The precise location of the stronger intermediate-depth earthquakes occurred during the deployment appears also related to this deep structural and tectonic control.

High-resolution imaging of craniofacial sutures: new tools for understanding the origins of craniosynostoses.

PubMed

Khonsari, R H; Di Rocco, F; Arnaud, E; Sanchez, S; Tafforeau, P

2012-09-01

The developmental genetics and the biomechanics of sutures are well-studied topics, while their microanatomy is still imperfectly known. Here, we aim to investigate the structure of skull vault sutures using a high-resolution imaging device. We used synchrotron X-ray microtomography in order to obtain high-resolution images of skull vault sutures from an extant mammal (the mouse Mus musculus) and from an extinct fish (the placoderm Compagopiscis croucheri). We used segmentation and 3D reconstruction softwares in order to reveal the microanatomy of sutures in these species. The high-resolution images allowed us to study the distribution of osteocytes, the organisation of vascular canals, the shapes of the suture borders, the insertion of Sharpey's fibres, the bone growth lines and the structure of the soft tissues surrounding the sutures. Synchrotron imaging provides new perspectives for the study of the normal microanatomy of sutures. The submicronic resolution of the synchrotron scans gives access to the 3D organisation of structures that were previously only known in 2D, even in normal sutures. The description of anatomical entities such as vascular canals and Sharpey's fibres in abnormally fused sutures would be of interest in the understanding of craniosynostoses.

Photon-triggered nanowire transistors

NASA Astrophysics Data System (ADS)

Kim, Jungkil; Lee, Hoo-Cheol; Kim, Kyoung-Ho; Hwang, Min-Soo; Park, Jin-Sung; Lee, Jung Min; So, Jae-Pil; Choi, Jae-Hyuck; Kwon, Soon-Hong; Barrelet, Carl J.; Park, Hong-Gyu

2017-10-01

Photon-triggered electronic circuits have been a long-standing goal of photonics. Recent demonstrations include either all-optical transistors in which photons control other photons or phototransistors with the gate response tuned or enhanced by photons. However, only a few studies report on devices in which electronic currents are optically switched and amplified without an electrical gate. Here we show photon-triggered nanowire (NW) transistors, photon-triggered NW logic gates and a single NW photodetection system. NWs are synthesized with long crystalline silicon (CSi) segments connected by short porous silicon (PSi) segments. In a fabricated device, the electrical contacts on both ends of the NW are connected to a single PSi segment in the middle. Exposing the PSi segment to light triggers a current in the NW with a high on/off ratio of >8 × 106. A device that contains two PSi segments along the NW can be triggered using two independent optical input signals. Using localized pump lasers, we demonstrate photon-triggered logic gates including AND, OR and NAND gates. A photon-triggered NW transistor of diameter 25 nm with a single 100 nm PSi segment requires less than 300 pW of power. Furthermore, we take advantage of the high photosensitivity and fabricate a submicrometre-resolution photodetection system. Photon-triggered transistors offer a new venue towards multifunctional device applications such as programmable logic elements and ultrasensitive photodetectors.

Photon-triggered nanowire transistors.

PubMed

Kim, Jungkil; Lee, Hoo-Cheol; Kim, Kyoung-Ho; Hwang, Min-Soo; Park, Jin-Sung; Lee, Jung Min; So, Jae-Pil; Choi, Jae-Hyuck; Kwon, Soon-Hong; Barrelet, Carl J; Park, Hong-Gyu

2017-10-01

Photon-triggered electronic circuits have been a long-standing goal of photonics. Recent demonstrations include either all-optical transistors in which photons control other photons or phototransistors with the gate response tuned or enhanced by photons. However, only a few studies report on devices in which electronic currents are optically switched and amplified without an electrical gate. Here we show photon-triggered nanowire (NW) transistors, photon-triggered NW logic gates and a single NW photodetection system. NWs are synthesized with long crystalline silicon (CSi) segments connected by short porous silicon (PSi) segments. In a fabricated device, the electrical contacts on both ends of the NW are connected to a single PSi segment in the middle. Exposing the PSi segment to light triggers a current in the NW with a high on/off ratio of >8 × 10 6 . A device that contains two PSi segments along the NW can be triggered using two independent optical input signals. Using localized pump lasers, we demonstrate photon-triggered logic gates including AND, OR and NAND gates. A photon-triggered NW transistor of diameter 25 nm with a single 100 nm PSi segment requires less than 300 pW of power. Furthermore, we take advantage of the high photosensitivity and fabricate a submicrometre-resolution photodetection system. Photon-triggered transistors offer a new venue towards multifunctional device applications such as programmable logic elements and ultrasensitive photodetectors.

Clinical evaluation of single-shot and readout-segmented diffusion-weighted imaging in stroke patients at 3 T.

PubMed

Morelli, John; Porter, David; Ai, Fei; Gerdes, Clint; Saettele, Megan; Feiweier, Thorsten; Padua, Abraham; Dix, James; Marra, Michael; Rangaswamy, Rajesh; Runge, Val

2013-04-01

Diffusion-weighted imaging (DWI) magnetic resonance imaging (MRI) is most commonly performed utilizing a single-shot echo-planar imaging technique (ss-EPI). Susceptibility artifact and image blur are severe when this sequence is utilized at 3 T. To evaluate a readout-segmented approach to DWI MR in comparison with single-shot echo planar imaging for brain MRI. Eleven healthy volunteers and 14 patients with acute and early subacute infarctions underwent DWI MR examinations at 1.5 and 3T with ss-EPI and readout-segmented echo-planar (rs-EPI) DWI at equal nominal spatial resolutions. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) calculations were made, and two blinded readers ranked the scans in terms of high signal intensity bulk susceptibility artifact, spatial distortions, image blur, overall preference, and motion artifact. SNR and CNR were greatest with rs-EPI (8.1 ± 0.2 SNR vs. 6.0 ± 0.2; P <10(-4) at 3T). Spatial distortions were greater with single-shot (0.23 ± 0.03 at 3T; P <0.001) than with rs-EPI (0.12 ± 0.02 at 3T). Combined with blur and artifact reduction, this resulted in a qualitative preference for the readout-segmented scans overall. Substantial image quality improvements are possible with readout-segmented vs. single-shot EPI - the current clinical standard for DWI - regardless of field strength (1.5 or 3 T). This results in improved image quality secondary to greater real spatial resolution and reduced artifacts from susceptibility in MR imaging of the brain.

A new method for detection and discrimination of Pepino mosaic virus isolates using high resolution melting analysis of the triple gene block 3.

PubMed

Hasiów-Jaroszewska, Beata; Komorowska, Beata

2013-10-01

Diagnostic methods distinguished different Pepino mosaic virus (PepMV) genotypes but the methods do not detect sequence variation in particular gene segments. The necrotic and non-necrotic isolates (pathotypes) of PepMV share a 99% sequence similarity. These isolates differ from each other at one nucleotide site in the triple gene block 3. In this study, a combination of real-time reverse transcription polymerase chain reaction and high resolution melting curve analysis of triple gene block 3 was developed for simultaneous detection and differentiation of PepMV pathotypes. The triple gene block 3 region carrying a transition A → G was amplified using two primer pairs from twelve virus isolates, and was subjected to high resolution melting curve analysis. The results showed two distinct melting curve profiles related to each pathotype. The results also indicated that the high resolution melting method could readily differentiate between necrotic and non-necrotic PepMV pathotypes. Copyright © 2013 Elsevier B.V. All rights reserved.

Measurements of OH(X2pi) in the stratosphere by high resolution UV spectroscopy

NASA Technical Reports Server (NTRS)

Torr, D. G.; Swift, W.; Fennelly, J.; Liu, G.; Torr, M. R.

1987-01-01

This paper reports the first results obtained using high spectral resolution imaging ultraviolet spectroscopy to observe multiple rotational lines of OH A2 Sigma-X2pi (0-0) band. A 9.2 A spectral segment from 3075.8 A to 3085.0 A is imaged at 0.08 A FWHM spectral resolution, allowing the simultaneous acquisition of six of the brightest OH resonance fluorescence emission lines. The high spectral resolution and low scattered light design of the instrument allows these lines to be detected above the Rayleigh scattered sunlight background. The technique permits remote sensing of stratospheric OH from a high altitude instrument. The instrument was flown to an altitude of 40 km on Aug. 25, 1983, and again on June 12, 1986, on scientific balloons from Palestine, TX. The OH profiles inverted from the limb scans made during these flights are reported here. These profiles represent the first measurements of the temporal variation of OH over an extended height range. The results demonstrate that the technique can be used to monitor OH from orbit.

Development of sampling calorimeter with segmented lead glass absorber

NASA Astrophysics Data System (ADS)

Terada, R.; Takeshita, T.; Itoh, H.; Kanzaki, I.

2018-02-01

Sampling calorimeter is indispensable for physics measurement at collider experiment with PFA. Uncertainty of deposit energy at absorber layer degrades energy resolution. This problem will be solved by using lead glass as absorber, which is clear and heavy. High energy particles produce Cherenkov lights whose light yield corresponds to the track length in the lead glass. This information from the absorber will improve the energy resolution of the calorimeter. Performance of this calorimeter prototype tested for electrons at ELPH beam at Tohoku University has been described. We discuss the problems and its capabilities.

A segmented, enriched N-type germanium detector for neutrinoless double beta-decay experiments

NASA Astrophysics Data System (ADS)

Leviner, L. E.; Aalseth, C. E.; Ahmed, M. W.; Avignone, F. T.; Back, H. O.; Barabash, A. S.; Boswell, M.; De Braeckeleer, L.; Brudanin, V. B.; Chan, Y.-D.; Egorov, V. G.; Elliott, S. R.; Gehman, V. M.; Hossbach, T. W.; Kephart, J. D.; Kidd, M. F.; Konovalov, S. I.; Lesko, K. T.; Li, Jingyi; Mei, D.-M.; Mikhailov, S.; Miley, H.; Radford, D. C.; Reeves, J.; Sandukovsky, V. G.; Umatov, V. I.; Underwood, T. A.; Tornow, W.; Wu, Y. K.; Young, A. R.

2014-01-01

We present data characterizing the performance of the first segmented, N-type Ge detector, isotopically enriched to 85% 76Ge. This detector, based on the Ortec PT6×2 design and referred to as SEGA (Segmented, Enriched Germanium Assembly), was developed as a possible prototype for neutrinoless double beta-decay measurements by the MAJORANA collaboration. We present some of the general characteristics (including bias potential, efficiency, leakage current, and integral cross-talk) for this detector in its temporary cryostat. We also present an analysis of the resolution of the detector, and demonstrate that for all but two segments there is at least one channel that reaches the MAJORANA resolution goal below 4 keV FWHM at 2039 keV, and all channels are below 4.5 keV FWHM.

Segmentation of nuclear images in automated cervical cancer screening

NASA Astrophysics Data System (ADS)

Dadeshidze, Vladimir; Olsson, Lars J.; Domanik, Richard A.

1995-08-01

This paper describes an efficient method of segmenting cell nuclei from complex scenes based upon the use of adaptive region growing in conjuction with nucleus-specific filters. Results of segmenting potentially abnormal (cancer or neoplastic) cell nuclei in Papanicolaou smears from 0.8 square micrometers resolution images are also presented.

Riparian Land Use/Land Cover Data for Five Study Units in the Nutrient Enrichment Effects Topical Study of the National Water-Quality Assessment Program

USGS Publications Warehouse

Johnson, Michaela R.; Buell, Gary R.; Kim, Moon H.; Nardi, Mark R.

2007-01-01

This dataset was developed as part of the National Water-Quality Assessment (NAWQA) Program, Nutrient Enrichment Effects Topical (NEET) study for five study units distributed across the United States: Apalachicola-Chattahoochee-Flint River Basin, Central Columbia Plateau-Yakima River Basin, Central Nebraska Basins, Potomac River Basin and Delmarva Peninsula, and White, Great and Little Miami River Basins. One hundred forty-three stream reaches were examined as part of the NEET study conducted 2003-04. Stream segments, with lengths equal to the logarithm of the basin area, were delineated upstream from the downstream ends of the stream reaches with the use of digital orthophoto quarter quadrangles (DOQQ) or selected from the high-resolution National Hydrography Dataset (NHD). Use of the NHD was necessary when the stream was not distinguishable in the DOQQ because of dense tree canopy. The analysis area for each stream segment was defined by a buffer beginning at the segment extending to 250 meters lateral to the stream segment. Delineation of land use/land cover (LULC) map units within stream segment buffers was conducted using on-screen digitizing of riparian LULC classes interpreted from the DOQQ. LULC units were mapped using a classification strategy consisting of nine classes. National Wetlands Inventory (NWI) data were used to aid in wetland classification. Longitudinal transect sampling lines offset from the stream segments were generated and partitioned into the underlying LULC types. These longitudinal samples yielded the relative linear extent and sequence of each LULC type within the riparian zone at the segment scale. The resulting areal and linear LULC data filled in the spatial-scale gap between the 30-meter resolution of the National Land Cover Dataset and the reach-level habitat assessment data collected onsite routinely for NAWQA ecological sampling. The final data consisted of 12 geospatial datasets: LULC within 25 meters of the stream reach (polygon); LULC within 50 meters of the stream reach (polygon); LULC within 50 meters of the stream segment (polygon); LULC within 100 meters of the stream segment (polygon); LULC within 150 meters of the stream segment (polygon); LULC within 250 meters of the stream segment (polygon); frequency of gaps in woody vegetation LULC at the reach scale (arc); stream reaches (arc); longitudinal LULC at the reach scale (arc); frequency of gaps in woody vegetation LULC at the segment scale (arc); stream segments (arc); and longitudinal LULC at the segment scale (arc).

Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue

NASA Astrophysics Data System (ADS)

Sawyer, Travis W.; Rice, Photini F. S.; Sawyer, David M.; Koevary, Jennifer W.; Barton, Jennifer K.

2018-02-01

Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depthresolved, high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must rst be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluated a set of algorithms to segment OCT images of mouse ovaries. We examined ve preprocessing techniques and six segmentation algorithms. While all pre-processing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of 32% +/- 1.2%. Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 0.948 +/- 0.012 compared with manual segmentation (1.0 being identical). Nonetheless, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.

Automated Segmentation and Classification of Coral using Fluid Lensing from Unmanned Airborne Platforms

NASA Technical Reports Server (NTRS)

Instrella, Ron; Chirayath, Ved

2016-01-01

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the world's coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85%. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

Automated Segmentation and Classification of Coral using Fluid Lensing from Unmanned Airborne Platforms

NASA Astrophysics Data System (ADS)

Instrella, R.; Chirayath, V.

2015-12-01

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the world's coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85%. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

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

PubMed

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

2013-01-01

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

Automatic determination of the artery vein ratio in retinal images

NASA Astrophysics Data System (ADS)

Niemeijer, Meindert; van Ginneken, Bram; Abràmoff, Michael D.

2010-03-01

A lower ratio between the width of the arteries and veins (Arteriolar-to-Venular diameter Ratio, AVR) on the retina, is well established to be predictive of stroke and other cardiovascular events in adults, as well as an increased risk of retinopathy of prematurity in premature infants. This work presents an automatic method that detects the location of the optic disc, determines the appropriate region of interest (ROI), classifies the vessels in the ROI into arteries and veins, measures their widths and calculates the AVR. After vessel segmentation and vessel width determination the optic disc is located and the system eliminates all vessels outside the AVR measurement ROI. The remaining vessels are thinned, vessel crossing and bifurcation points are removed leaving a set of vessel segments containing centerline pixels. Features are extracted from each centerline pixel that are used to assign them a soft label indicating the likelihood the pixel is part of a vein. As all centerline pixels in a connected segment should be the same type, the median soft label is assigned to each centerline pixel in the segment. Next artery vein pairs are matched using an iterative algorithm and the widths of the vessels is used to calculate the AVR. We train and test the algorithm using a set of 25 high resolution digital color fundus photographs a reference standard that indicates for the major vessels in the images whether they are an artery or a vein. We compared the AVR values produced by our system with those determined using a computer assisted method in 15 high resolution digital color fundus photographs and obtained a correlation coefficient of 0.881.

Forest Stand Segmentation Using Airborne LIDAR Data and Very High Resolution Multispectral Imagery

NASA Astrophysics Data System (ADS)

Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet, Valérie; Hervieu, Alexandre

2016-06-01

Forest stands are the basic units for forest inventory and mapping. Stands are large forested areas (e.g., ≥ 2 ha) of homogeneous tree species composition. The accurate delineation of forest stands is usually performed by visual analysis of human operators on very high resolution (VHR) optical images. This work is highly time consuming and should be automated for scalability purposes. In this paper, a method based on the fusion of airborne laser scanning data (or lidar) and very high resolution multispectral imagery for automatic forest stand delineation and forest land-cover database update is proposed. The multispectral images give access to the tree species whereas 3D lidar point clouds provide geometric information on the trees. Therefore, multi-modal features are computed, both at pixel and object levels. The objects are individual trees extracted from lidar data. A supervised classification is performed at the object level on the computed features in order to coarsely discriminate the existing tree species in the area of interest. The analysis at tree level is particularly relevant since it significantly improves the tree species classification. A probability map is generated through the tree species classification and inserted with the pixel-based features map in an energetical framework. The proposed energy is then minimized using a standard graph-cut method (namely QPBO with α-expansion) in order to produce a segmentation map with a controlled level of details. Comparison with an existing forest land cover database shows that our method provides satisfactory results both in terms of stand labelling and delineation (matching ranges between 94% and 99%).

A systematic comparison of different object-based classification techniques using high spatial resolution imagery in agricultural environments

NASA Astrophysics Data System (ADS)

Li, Manchun; Ma, Lei; Blaschke, Thomas; Cheng, Liang; Tiede, Dirk

2016-07-01

Geographic Object-Based Image Analysis (GEOBIA) is becoming more prevalent in remote sensing classification, especially for high-resolution imagery. Many supervised classification approaches are applied to objects rather than pixels, and several studies have been conducted to evaluate the performance of such supervised classification techniques in GEOBIA. However, these studies did not systematically investigate all relevant factors affecting the classification (segmentation scale, training set size, feature selection and mixed objects). In this study, statistical methods and visual inspection were used to compare these factors systematically in two agricultural case studies in China. The results indicate that Random Forest (RF) and Support Vector Machines (SVM) are highly suitable for GEOBIA classifications in agricultural areas and confirm the expected general tendency, namely that the overall accuracies decline with increasing segmentation scale. All other investigated methods except for RF and SVM are more prone to obtain a lower accuracy due to the broken objects at fine scales. In contrast to some previous studies, the RF classifiers yielded the best results and the k-nearest neighbor classifier were the worst results, in most cases. Likewise, the RF and Decision Tree classifiers are the most robust with or without feature selection. The results of training sample analyses indicated that the RF and adaboost. M1 possess a superior generalization capability, except when dealing with small training sample sizes. Furthermore, the classification accuracies were directly related to the homogeneity/heterogeneity of the segmented objects for all classifiers. Finally, it was suggested that RF should be considered in most cases for agricultural mapping.

Exact analytical modeling of magnetic vector potential in surface inset permanent magnet DC machines considering magnet segmentation

NASA Astrophysics Data System (ADS)

Jabbari, Ali

2018-01-01

Surface inset permanent magnet DC machine can be used as an alternative in automation systems due to their high efficiency and robustness. Magnet segmentation is a common technique in order to mitigate pulsating torque components in permanent magnet machines. An accurate computation of air-gap magnetic field distribution is necessary in order to calculate machine performance. An exact analytical method for magnetic vector potential calculation in surface inset permanent magnet machines considering magnet segmentation has been proposed in this paper. The analytical method is based on the resolution of Laplace and Poisson equations as well as Maxwell equation in polar coordinate by using sub-domain method. One of the main contributions of the paper is to derive an expression for the magnetic vector potential in the segmented PM region by using hyperbolic functions. The developed method is applied on the performance computation of two prototype surface inset magnet segmented motors with open circuit and on load conditions. The results of these models are validated through FEM method.

Graph-based active learning of agglomeration (GALA): a Python library to segment 2D and 3D neuroimages

PubMed Central

Nunez-Iglesias, Juan; Kennedy, Ryan; Plaza, Stephen M.; Chakraborty, Anirban; Katz, William T.

2014-01-01

The aim in high-resolution connectomics is to reconstruct complete neuronal connectivity in a tissue. Currently, the only technology capable of resolving the smallest neuronal processes is electron microscopy (EM). Thus, a common approach to network reconstruction is to perform (error-prone) automatic segmentation of EM images, followed by manual proofreading by experts to fix errors. We have developed an algorithm and software library to not only improve the accuracy of the initial automatic segmentation, but also point out the image coordinates where it is likely to have made errors. Our software, called gala (graph-based active learning of agglomeration), improves the state of the art in agglomerative image segmentation. It is implemented in Python and makes extensive use of the scientific Python stack (numpy, scipy, networkx, scikit-learn, scikit-image, and others). We present here the software architecture of the gala library, and discuss several designs that we consider would be generally useful for other segmentation packages. We also discuss the current limitations of the gala library and how we intend to address them. PMID:24772079

Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets

PubMed Central

Jeong, Won-Ki; Beyer, Johanna; Hadwiger, Markus; Vazquez, Amelio; Pfister, Hanspeter; Whitaker, Ross T.

2011-01-01

Recent advances in scanning technology provide high resolution EM (Electron Microscopy) datasets that allow neuroscientists to reconstruct complex neural connections in a nervous system. However, due to the enormous size and complexity of the resulting data, segmentation and visualization of neural processes in EM data is usually a difficult and very time-consuming task. In this paper, we present NeuroTrace, a novel EM volume segmentation and visualization system that consists of two parts: a semi-automatic multiphase level set segmentation with 3D tracking for reconstruction of neural processes, and a specialized volume rendering approach for visualization of EM volumes. It employs view-dependent on-demand filtering and evaluation of a local histogram edge metric, as well as on-the-fly interpolation and ray-casting of implicit surfaces for segmented neural structures. Both methods are implemented on the GPU for interactive performance. NeuroTrace is designed to be scalable to large datasets and data-parallel hardware architectures. A comparison of NeuroTrace with a commonly used manual EM segmentation tool shows that our interactive workflow is faster and easier to use for the reconstruction of complex neural processes. PMID:19834227

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

NASA Technical Reports Server (NTRS)

Basu, Saikat; Ganguly, Sangram; Michaelis, Andrew; Votava, Petr; Roy, Anshuman; Mukhopadhyay, Supratik; Nemani, Ramakrishna

2015-01-01

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery using a Probabilistic Learning Framework

NASA Astrophysics Data System (ADS)

Basu, S.; Ganguly, S.; Michaelis, A.; Votava, P.; Roy, A.; Mukhopadhyay, S.; Nemani, R. R.

2015-12-01

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

Energy reconstruction of an n-type segmented inverted coaxial point-contact HPGe detector

DOE PAGES

Salathe, M.; Cooper, R. J.; Crawford, H. L.; ...

2017-06-27

We have characterized, for the rst time, an n-type segmented Inverted Coaxial Point-Contact detector. This novel detector technology relys on a large variation in drift time of the majority charge carriers, as well as image and net charges observed on the segments, to achieve a potential -ray interaction position resolution of better than 1 mm. However, the intrinsic energy resolution in such a detector is poor (more than 20 keV at 1332 keV) because of charge (electron) trapping e ects. We propose an algorithm that enables restoration of the resolution to a value of 3.44 0.03 keV at 1332 keVmore » for events with a single interaction. The algorithm is based on a measurement of the azimuthal angle and the electron drift time of a given event; the energy of the event is corrected as a function of these two values.« less

HGCAL: A High-Granularity Calorimeter for the Endcaps of CMS at HL-LHC

NASA Astrophysics Data System (ADS)

Ochando, Christophe; CMS Collaboration

2017-11-01

Calorimetry at the High Luminosity LHC (HL-LHC) faces two enormous challenges, particularly in the forward direction: radiation tolerance and unprecedented in-time event pileup. To meet these challenges, the CMS experiment has decided to construct a High Granularity Calorimeter (HGCAL), featuring a previously unrealized transverse and longitudinal segmentation, for both electromagnetic and hadronic compartments. This will facilitate particle-flow-type calorimetry, where the fine structure of showers can be measured and used to enhance particle identification, energy resolution and pileup rejection. The majority of the HGCAL will be based on robust and cost-effective hexagonal silicon sensors with about 1cm2 or 0.5cm2 hexagonal cell size, with the final 5 interaction lengths of the hadronic compartment being based on highly segmented plastic scintillator with on-scintillator SiPM readout. We present an overview of the HGCAL project, including the motivation, engineering design, readout concept and simulated performance.

HGCAL: a High-Granularity Calorimeter for the endcaps of CMS at HL-LHC

NASA Astrophysics Data System (ADS)

Magnan, A.-M.

2017-01-01

Calorimetry at the High Luminosity LHC (HL-LHC) faces two enormous challenges, particularly in the forward direction: radiation tolerance and unprecedented in-time event pileup. To meet these challenges, the CMS experiment has decided to construct a High Granularity Calorimeter (HGCAL), featuring a previously unrealized transverse and longitudinal segmentation, for both electromagnetic and hadronic compartments. This will facilitate particle-flow-type calorimetry, where the fine structure of showers can be measured and used to enhance particle identification, energy resolution and pileup rejection. The majority of the HGCAL will be based on robust and cost-effective hexagonal silicon sensors with simeq 1 cm2 or 0.5 cm2 hexagonal cell size, with the final five interaction lengths of the hadronic compartment being based on highly segmented plastic scintillator with on-scintillator SiPM readout. We present an overview of the HGCAL project, including the motivation, engineering design, readout/trigger concept and simulated performance.

High resolution wavenumber analysis for investigation of arterial pulse wave propagation

NASA Astrophysics Data System (ADS)

Hasegawa, Hideyuki; Sato, Masakazu; Irie, Takasuke

2016-07-01

The propagation of the pulse wave along the artery is relatively fast (several m/s), and a high-temporal resolution is required to measure pulse wave velocity (PWV) in a regional segment of the artery. High-frame-rate ultrasound enables the measurement of the regional PWV. In analyses of wave propagation phenomena, the direction and propagation speed are generally identified in the frequency-wavenumber space using the two-dimensional Fourier transform. However, the wavelength of the pulse wave is very long (1 m at a propagation velocity of 10 m/s and a temporal frequency of 10 Hz) compared with a typical lateral field of view of 40 mm in ultrasound imaging. Therefore, PWV cannot be identified in the frequency-wavenumber space owing to the low resolution of the two-dimensional Fourier transform. In the present study, PWV was visualized in the wavenumber domain using phases of arterial wall acceleration waveforms measured by high-frame-rate ultrasound.

High resolution projection X-ray microscope equipped with fluorescent X-ray analyzer and its applications

NASA Astrophysics Data System (ADS)

Minami, K.; Saito, Y.; Kai, H.; Shirota, K.; Yada, K.

2009-09-01

We have newly developed an open type fine-focus X-ray tube "TX-510" to realize a spatial resolution of 50nm and to radiate low energy characteristic X-rays for giving high absorption contrast to images of microscopic organisms. The "TX-510" employs a ZrO/W(100) Schottky emitter and an "In-Lens Field Emission Gun". The key points of the improvements are (1) reduced spherical aberration coefficient of magnetic objective lens, (2) easy and accurate focusing, (3) newly designed astigmatism compensator, (4) segmented thin film target for interchanging the target materials by electron beam shift and (5) fluorescent X-ray analysis system.

Fluid Lensing based Machine Learning for Augmenting Earth Science Coral Datasets

NASA Astrophysics Data System (ADS)

Li, A.; Instrella, R.; Chirayath, V.

2016-12-01

Recently, there has been increased interest in monitoring the effects of climate change upon the world's marine ecosystems, particularly coral reefs. These delicate ecosystems are especially threatened due to their sensitivity to ocean warming and acidification, leading to unprecedented levels of coral bleaching and die-off in recent years. However, current global aquatic remote sensing datasets are unable to quantify changes in marine ecosystems at spatial and temporal scales relevant to their growth. In this project, we employ various supervised and unsupervised machine learning algorithms to augment existing datasets from NASA's Earth Observing System (EOS), using high resolution airborne imagery. This method utilizes NASA's ongoing airborne campaigns as well as its spaceborne assets to collect remote sensing data over these afflicted regions, and employs Fluid Lensing algorithms to resolve optical distortions caused by the fluid surface, producing cm-scale resolution imagery of these diverse ecosystems from airborne platforms. Support Vector Machines (SVMs) and K-mean clustering methods were applied to satellite imagery at 0.5m resolution, producing segmented maps classifying coral based on percent cover and morphology. Compared to a previous study using multidimensional maximum a posteriori (MAP) estimation to separate these features in high resolution airborne datasets, SVMs are able to achieve above 75% accuracy when augmented with existing MAP estimates, while unsupervised methods such as K-means achieve roughly 68% accuracy, verified by manually segmented reference data provided by a marine biologist. This effort thus has broad applications for coastal remote sensing, by helping marine biologists quantify behavioral trends spanning large areas and over longer timescales, and to assess the health of coral reefs worldwide.

MIA-Clustering: a novel method for segmentation of paleontological material.

PubMed

Dunmore, Christopher J; Wollny, Gert; Skinner, Matthew M

2018-01-01

Paleontological research increasingly uses high-resolution micro-computed tomography (μCT) to study the inner architecture of modern and fossil bone material to answer important questions regarding vertebrate evolution. This non-destructive method allows for the measurement of otherwise inaccessible morphology. Digital measurement is predicated on the accurate segmentation of modern or fossilized bone from other structures imaged in μCT scans, as errors in segmentation can result in inaccurate calculations of structural parameters. Several approaches to image segmentation have been proposed with varying degrees of automation, ranging from completely manual segmentation, to the selection of input parameters required for computational algorithms. Many of these segmentation algorithms provide speed and reproducibility at the cost of flexibility that manual segmentation provides. In particular, the segmentation of modern and fossil bone in the presence of materials such as desiccated soft tissue, soil matrix or precipitated crystalline material can be difficult. Here we present a free open-source segmentation algorithm application capable of segmenting modern and fossil bone, which also reduces subjective user decisions to a minimum. We compare the effectiveness of this algorithm with another leading method by using both to measure the parameters of a known dimension reference object, as well as to segment an example problematic fossil scan. The results demonstrate that the medical image analysis-clustering method produces accurate segmentations and offers more flexibility than those of equivalent precision. Its free availability, flexibility to deal with non-bone inclusions and limited need for user input give it broad applicability in anthropological, anatomical, and paleontological contexts.

Segmentation of cortical bone using fast level sets

NASA Astrophysics Data System (ADS)

Chowdhury, Manish; Jörgens, Daniel; Wang, Chunliang; Smedby, Årjan; Moreno, Rodrigo

2017-02-01

Cortical bone plays a big role in the mechanical competence of bone. The analysis of cortical bone requires accurate segmentation methods. Level set methods are usually in the state-of-the-art for segmenting medical images. However, traditional implementations of this method are computationally expensive. This drawback was recently tackled through the so-called coherent propagation extension of the classical algorithm which has decreased computation times dramatically. In this study, we assess the potential of this technique for segmenting cortical bone in interactive time in 3D images acquired through High Resolution peripheral Quantitative Computed Tomography (HR-pQCT). The obtained segmentations are used to estimate cortical thickness and cortical porosity of the investigated images. Cortical thickness and Cortical porosity is computed using sphere fitting and mathematical morphological operations respectively. Qualitative comparison between the segmentations of our proposed algorithm and a previously published approach on six images volumes reveals superior smoothness properties of the level set approach. While the proposed method yields similar results to previous approaches in regions where the boundary between trabecular and cortical bone is well defined, it yields more stable segmentations in challenging regions. This results in more stable estimation of parameters of cortical bone. The proposed technique takes few seconds to compute, which makes it suitable for clinical settings.

Design and manufacture of 8.4 m primary mirror segments and supports for the GMT

NASA Astrophysics Data System (ADS)

Martin, H. M.; Angel, J. R. P.; Burge, J. H.; Cuerden, B.; Davison, W. B.; Johns, M.; Kingsley, J. S.; Kot, L. B.; Lutz, R. D.; Miller, S. M.; Shectman, S. A.; Strittmatter, P. A.; Zhao, C.

2006-06-01

The design, manufacture and support of the primary mirror segments for the GMT build on the successful primary mirror systems of the MMT, Magellan and Large Binocular telescopes. The mirror segment and its support system are based on a proven design, and the experience gained in the existing telescopes has led to significant refinements that will provide even better performance in the GMT. The first 8.4 m segment has been cast at the Steward Observatory Mirror Lab, and optical processing is underway. Measurement of the off-axis surface is the greatest challenge in the manufacture of the segments. A set of tests that meets the requirements has been defined and the concepts have been developed in some detail. The most critical parts of the tests have been demonstrated in the measurement of a 1.7 m off-axis prototype. The principal optical test is a full-aperture, high-resolution null test in which a hybrid reflective-diffractive null corrector compensates for the 14 mm aspheric departure of the off-axis segment. The mirror support uses the same synthetic floatation principle as the MMT, Magellan, and LBT mirrors. Refinements for GMT include 3-axis actuators to accommodate the varying orientations of segments in the telescope.

Segmental lichen aureus: a report of two cases treated with methylprednisolone aceponate.

PubMed

Moche, John; Glassman, Steven; Modi, Deepak; Grayson, Wayne

2011-05-01

Two cases of segmental lichen aureus with a response to topical 0.1% methylprednisolone aceponate ointment are reported. A 9-year-old child and a 23-year-old man showed complete resolution of their lesions following treatment with the latter after 7 months and 4 months, respectively. Lichen aureus is a rare form of the pigmented purpuric dermatoses characterized by golden-brown and lichenoid macules and papules, most often on the lower extremities. Segmental presentations have seldom been described. Histology showed a lichenoid infiltrate with extravasation of red blood cells and haemosiderin deposition. The aetiology is unclear and treatment is disappointing. We report an uncommon segmental presentation of lichen aureus with resolution of the lesions after treatment with a topical corticosteroid. © 2010 The Authors. Australasian Journal of Dermatology © 2010 The Australasian College of Dermatologists.

Automated segmentations of skin, soft-tissue, and skeleton, from torso CT images

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kiryu, Takuji; Hoshi, Hiroaki

2004-05-01

We have been developing a computer-aided diagnosis (CAD) scheme for automatically recognizing human tissue and organ regions from high-resolution torso CT images. We show some initial results for extracting skin, soft-tissue and skeleton regions. 139 patient cases of torso CT images (male 92, female 47; age: 12-88) were used in this study. Each case was imaged with a common protocol (120kV/320mA) and covered the whole torso with isotopic spatial resolution of about 0.63 mm and density resolution of 12 bits. A gray-level thresholding based procedure was applied to separate the human body from background. The density and distance features to body surface were used to determine the skin, and separate soft-tissue from the others. A 3-D region growing based method was used to extract the skeleton. We applied this system to the 139 cases and found that the skin, soft-tissue and skeleton regions were recognized correctly for 93% of the patient cases. The accuracy of segmentation results was acceptable by evaluating the results slice by slice. This scheme will be included in CAD systems for detecting and diagnosing the abnormal lesions in multi-slice torso CT images.

Automatic and hierarchical segmentation of the human skeleton in CT images.

PubMed

Fu, Yabo; Liu, Shi; Li, Harold; Yang, Deshan

2017-04-07

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.

Automatic and hierarchical segmentation of the human skeleton in CT images

NASA Astrophysics Data System (ADS)

Fu, Yabo; Liu, Shi; Li, H. Harold; Yang, Deshan

2017-04-01

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.

Translation-aware semantic segmentation via conditional least-square generative adversarial networks

NASA Astrophysics Data System (ADS)

Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min

2017-10-01

Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.

Atom Resolved Electron Microscpe Images of Polyvinylidene Fluoride Nanofibers for Water Desalination

NASA Astrophysics Data System (ADS)

Liu, Suqi; Reneker, Darrell

Ultra-thin nanofibers of polyvinylidene fluoride (PVDF), observed with an aberration corrected transmission electron microscope, in a through focus series of 50 images, revealed three-dimensional positions and motions of some molecular segments. The x,y positions of fluorine atoms in the PVDF segments were observed at high resolution as described in (DOI: 10.1039/c5nr01619c). The methods described in (DOI:10.1038/nature11074) were used to measure the positions of fluorine atoms along the observation direction of the microscope. PVDF is widely used to separate salt ions from water in reverse osmosis systems. The observed separation depends on the atomic scale positions and motions of segments of the PVDF molecules. Conformational changes and the associated changes in the directions of the dipole moments of PVDF segments distinguish the diffusion of dipolar water molecules from diffusion of salt ions to accomplish desalination. Authors thank Coalescence Filtration Nanofibers Consortium at The University of Akron for support.

Nerve ultrasound shows subclinical peripheral nerve involvement in neurofibromatosis type 2.

PubMed

Telleman, Johan A; Stellingwerff, Menno D; Brekelmans, Geert J; Visser, Leo H

2018-02-01

Neurofibromatosis type 2 (NF2) is mainly associated with central nervous system (CNS) tumors. Peripheral nerve involvement is described in symptomatic patients, but evidence of subclinical peripheral nerve involvement is scarce. We conducted a cross-sectional pilot study in 2 asymptomatic and 3 minimally symptomatic patients with NF2 to detect subclinical peripheral nerve involvement. Patients underwent clinical examination, nerve conduction studies (NCS), and high-resolution ultrasonography (HRUS). A total of 30 schwannomas were found, divided over 20 nerve segments (33.9% of all investigated nerve segments). All patients had at least 1 schwannoma. Schwannomas were identified with HRUS in 37% of clinically unaffected nerve segments and 50% of nerve segments with normal NCS findings. HRUS shows frequent subclinical peripheral nerve involvement in NF2. Clinicians should consider peripheral nerve involvement as a cause of weakness and sensory loss in the extremities in patients with this disease. Muscle Nerve 57: 312-316, 2018. © 2017 Wiley Periodicals, Inc.

Multi-frame super-resolution with quality self-assessment for retinal fundus videos.

PubMed

Köhler, Thomas; Brost, Alexander; Mogalle, Katja; Zhang, Qianyi; Köhler, Christiane; Michelson, Georg; Hornegger, Joachim; Tornow, Ralf P

2014-01-01

This paper proposes a novel super-resolution framework to reconstruct high-resolution fundus images from multiple low-resolution video frames in retinal fundus imaging. Natural eye movements during an examination are used as a cue for super-resolution in a robust maximum a-posteriori scheme. In order to compensate heterogeneous illumination on the fundus, we integrate retrospective illumination correction for photometric registration to the underlying imaging model. Our method utilizes quality self-assessment to provide objective quality scores for reconstructed images as well as to select regularization parameters automatically. In our evaluation on real data acquired from six human subjects with a low-cost video camera, the proposed method achieved considerable enhancements of low-resolution frames and improved noise and sharpness characteristics by 74%. In terms of image analysis, we demonstrate the importance of our method for the improvement of automatic blood vessel segmentation as an example application, where the sensitivity was increased by 13% using super-resolution reconstruction.

Wavelet-based adaptive thresholding method for image segmentation

NASA Astrophysics Data System (ADS)

Chen, Zikuan; Tao, Yang; Chen, Xin; Griffis, Carl

2001-05-01

A nonuniform background distribution may cause a global thresholding method to fail to segment objects. One solution is using a local thresholding method that adapts to local surroundings. In this paper, we propose a novel local thresholding method for image segmentation, using multiscale threshold functions obtained by wavelet synthesis with weighted detail coefficients. In particular, the coarse-to- fine synthesis with attenuated detail coefficients produces a threshold function corresponding to a high-frequency- reduced signal. This wavelet-based local thresholding method adapts to both local size and local surroundings, and its implementation can take advantage of the fast wavelet algorithm. We applied this technique to physical contaminant detection for poultry meat inspection using x-ray imaging. Experiments showed that inclusion objects in deboned poultry could be extracted at multiple resolutions despite their irregular sizes and uneven backgrounds.

MRI helps depict clinically undetectable risk factors in advanced stage retinoblastomas.

PubMed

Galluzzi, Paolo; Hadjistilianou, Theodora; Cerase, Alfonso; Toti, Paolo; Leonini, Sara; Bracco, Sandra; de Francesco, Sonia; Galimberti, Daniela; Balducci, Donatella; Piu, Pietro; Monti, Lucia; Bellini, Matteo; Caini, Mauro; Rossi, Alessandro

2015-02-01

This study compared high-resolution MRI with histology in advanced stage retinoblastomas in which ophthalmoscopy and ultrasonography did not give an exhaustive depiction of the tumour and/or its extension. MRI of orbits and head in 28 retinoblastoma patients (28 eyes) treated with primary enucleation were evaluated. Iris neoangiogenesis, infiltrations of optic nerve, choroid, anterior segment and sclera suspected at MR and histology were compared. Abnormal anterior segment enhancement (AASE) was also correlated with histologically proven infiltrations. Brain images were also evaluated. Significant values were obtained for: prelaminar optic nerve (ON) sensitivity (0.88), positive predictive value (PPV) (0.75) and negative predictive value (NPV) (0.71); post-laminar ON sensitivity (0.50), specificity (0.83), PPV (0.50) and NPV (0.83); overall choroid sensitivity (0.82), and massive choroid NPV (0.69); scleral specificity (1), and NPV (1). AASE correlated with iris neoangiogenesis in 14 out of 19 eyes, and showed significant values for: overall ON PPV (0.65), prelaminar ON sensitivity (0.65), and PPV (0.61), post-laminar ON NPV (0.64); overall choroid sensitivity (0.77), PPV (0.59) and NPV (0.73); scleral NPV (0.83); anterior segment sensitivity (1), and NPV (1). Odds ratios (OR) and accuracy were significant in scleral and prelaminar optic nerve infiltration. Brain examination was unremarkable in all cases. High-resolution MRI may add important findings to clinical evaluation of advanced stage retinoblastomas. © The Author(s) 2015 Reprints and permissions:]br]sagepub.co.uk/journalsPermissions.nav.

Cest Analysis: Automated Change Detection from Very-High Remote Sensing Images

NASA Astrophysics Data System (ADS)

Ehlers, M.; Klonus, S.; Jarmer, T.; Sofina, N.; Michel, U.; Reinartz, P.; Sirmacek, B.

2012-08-01

A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye) new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST) analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT) and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment) with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST) of the change algorithms is applied to calculate the probability of change for a particular location. CEST was tested with high-resolution satellite images of the crisis areas of Darfur (Sudan). CEST results are compared with a number of standard algorithms for automated change detection such as image difference, image ratioe, principal component analysis, delta cue technique and post classification change detection. The new combined method shows superior results averaging between 45% and 15% improvement in accuracy.

Hierarchical layered and semantic-based image segmentation using ergodicity map

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects/regions with contextual topological relationships.

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

Improving the accuracy of macromolecular structure refinement at 7 Å resolution.

PubMed

Brunger, Axel T; Adams, Paul D; Fromme, Petra; Fromme, Raimund; Levitt, Michael; Schröder, Gunnar F

2012-06-06

In X-ray crystallography, molecular replacement and subsequent refinement is challenging at low resolution. We compared refinement methods using synchrotron diffraction data of photosystem I at 7.4 Å resolution, starting from different initial models with increasing deviations from the known high-resolution structure. Standard refinement spoiled the initial models, moving them further away from the true structure and leading to high R(free)-values. In contrast, DEN refinement improved even the most distant starting model as judged by R(free), atomic root-mean-square differences to the true structure, significance of features not included in the initial model, and connectivity of electron density. The best protocol was DEN refinement with initial segmented rigid-body refinement. For the most distant initial model, the fraction of atoms within 2 Å of the true structure improved from 24% to 60%. We also found a significant correlation between R(free) values and the accuracy of the model, suggesting that R(free) is useful even at low resolution. Copyright © 2012 Elsevier Ltd. All rights reserved.

Seeing tobacco mosaic virus through direct electron detectors

PubMed Central

Fromm, Simon A.; Bharat, Tanmay A.M.; Jakobi, Arjen J.; Hagen, Wim J.H.; Sachse, Carsten

2015-01-01

With the introduction of direct electron detectors (DED) to the field of electron cryo-microscopy, a wave of atomic-resolution structures has become available. As the new detectors still require comparative characterization, we have used tobacco mosaic virus (TMV) as a test specimen to study the quality of 3D image reconstructions from data recorded on the two direct electron detector cameras, K2 Summit and Falcon II. Using DED movie frames, we explored related image-processing aspects and compared the performance of micrograph-based and segment-based motion correction approaches. In addition, we investigated the effect of dose deposition on the atomic-resolution structure of TMV and show that radiation damage affects negative carboxyl chains first in a side-chain specific manner. Finally, using 450,000 asymmetric units and limiting the effects of radiation damage, we determined a high-resolution cryo-EM map at 3.35 Å resolution. Here, we provide a comparative case study of highly ordered TMV recorded on different direct electron detectors to establish recording and processing conditions that enable structure determination up to 3.2 Å in resolution using cryo-EM. PMID:25528571

Nonrigid registration-based coronary artery motion correction for cardiac computed tomography

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

Bhagalia, Roshni; Pack, Jed D.; Miller, James V.

2012-07-15

Purpose: X-ray computed tomography angiography (CTA) is the modality of choice to noninvasively monitor and diagnose heart disease with coronary artery health and stenosis detection being of particular interest. Reliable, clinically relevant coronary artery imaging mandates high spatiotemporal resolution. However, advances in intrinsic scanner spatial resolution (CT scanners are available which combine nearly 900 detector columns with focal spot oversampling) can be tempered by motion blurring, particularly in patients with unstable heartbeats. As a result, recently numerous methods have been devised to improve coronary CTA imaging. Solutions involving hardware, multisector algorithms, or {beta}-blockers are limited by cost, oversimplifying assumptions aboutmore » cardiac motion, and populations showing contraindications to drugs, respectively. This work introduces an inexpensive algorithmic solution that retrospectively improves the temporal resolution of coronary CTA without significantly affecting spatial resolution. Methods: Given the goal of ruling out coronary stenosis, the method focuses on 'deblurring' the coronary arteries. The approach makes no assumptions about cardiac motion, can be used on exams acquired at high heart rates (even over 75 beats/min), and draws on a fast and accurate three-dimensional (3D) nonrigid bidirectional labeled point matching approach to estimate the trajectories of the coronary arteries during image acquisition. Motion compensation is achieved by employing a 3D warping of a series of partial reconstructions based on the estimated motion fields. Each of these partial reconstructions is created from data acquired over a short time interval. For brevity, the algorithm 'Subphasic Warp and Add' (SWA) reconstruction. Results: The performance of the new motion estimation-compensation approach was evaluated by a systematic observer study conducted using nine human cardiac CTA exams acquired over a range of average heart rates between 68 and 86 beats/min. Algorithm performance was based-lined against exams reconstructed using standard filtered-backprojection (FBP). The study was performed by three experienced reviewers using the American Heart Association's 15-segment model. All vessel segments were evaluated to quantify their viability to allow a clinical diagnosis before and after motion estimation-compensation using SWA. To the best of the authors' knowledge this is the first such observer study to show that an image processing-based software approach can improve the clinical diagnostic value of CTA for coronary artery evaluation. Conclusions: Results from the observer study show that the SWA method described here can dramatically reduce coronary artery motion and preserve real pathology, without affecting spatial resolution. In particular, the method successfully mitigated motion artifacts in 75% of all initially nondiagnostic coronary artery segments, and in over 45% of the cases this improvement was enough to make a previously nondiagnostic vessel segment clinically diagnostic.« less

Analysing fault growth at the continental break up zone in Afar, Ethiopia

NASA Astrophysics Data System (ADS)

Hofmann, Barbara; Wright, Tim; Rowland, Julie; Hautot, Sophie; Paton, Douglas; Kidane, Tesfaye; Abebe, Bekele

2010-05-01

Continental break up, the formation of new oceans still holds many unanswered questions. The continental rift of Afar, Ethiopia is the only place on Earth today where the final stages of continental rupture and the beginning of seafloor spreading are occurring above sea level. In September 2005 a new rifting episode started at the Dabbahu segment with the intrusion of about 2-2.5 km^ 3 of magma into a 60-km-long dyke (Wright et. al., 2006; Grandin et. al., 2009), causing horizontal opening of up to 8m. Faults within the research area show fresh slip of up to 3m along fault segments of about 10km (Rowland et. al., 2007). Since then 13 further dyke intrusions showing surface deformation have been detected and analysed using InSAR data. However, how faults grow remains a key question. To establish fault growth models, distribution of displacement along surface tracks as well as scaling relationships of faults of different order of magnitudes within a similar lithological setting are essential (eg. Walsh and Watterson, 1988; Cowie and Scholz, 1992). Set in Pliocene flood basalts the highly faulted Dabbahu segment forms an ideal study case. We used 6 pairs of SPOT5 images with a pixel size of 2.5m to create a relative DEM of 6m resolution covering the whole of the 60km x 30km Dabbahu segment. By tying the relative DEM to the georeferenced 90m resolution DEM from SRTM data and applying linear and bi-quadratic polynomial transformations we were able to georeference the DEM. During October 2009 a LiDAR survey took place over the central rift segment with additional cross profiles. The additional data has enhanced the DEM spatial resolution to 1m in the centre. Using this large, precise dataset we have developed an automated method to systematically derive the distribution of displacement along the surface expression of the faults. This enables us to determine whether scaling relationships derived in other areas are valid for magmatically-driven faults. Here we present first results of these statistical analyses.

In vivo imaging of coin-shaped lesions in cytomegalovirus corneal endotheliitis by anterior segment optical coherence tomography.

PubMed

Yokogawa, Hideaki; Kobayashi, Akira; Yamazaki, Natsuko; Sugiyama, Kazuhisa

2014-12-01

The aim of this study was to investigate in vivo corneal changes of coin-shaped lesions in cytomegalovirus corneal endotheliitis using anterior segment optical coherence tomography (AS-OCT). Two eyes of 2 patients (69- and 71-year-old men), with polymerase chain reaction-proven CMV corneal endotheliitis presenting coin-shaped lesions, were included in this study. AS-OCT examination was performed on the initial visit and at follow-up visits by paying special attention to the coin-shaped lesions. Selected AS-OCT images of the cornea were evaluated qualitatively for changes in the shape and degree of light reflection. In both cases, coin-shaped lesions were observed at the corneal endothelial surface as clusters of fine precipitates using slit-lamp biomicroscopy. Using AS-OCT, high-resolution images of the putative coin-shaped lesions were successfully obtained in both patients as an irregularly thickened highly reflective endothelial cell layer. After anti-CMV treatment, the coin-shaped lesions were resolved as assessed by slit-lamp biomicroscopy and AS-OCT in both patients. High-resolution AS-OCT provides novel and detailed visual information of coin-shaped lesions in patients with CMV corneal endotheliitis. Visualization of coin-shaped lesions by AS-OCT may be a useful adjunct to the diagnosis and follow-up of CMV corneal endotheliitis.

Automated segmentation of the lungs from high resolution CT images for quantitative study of chronic obstructive pulmonary diseases

NASA Astrophysics Data System (ADS)

Garg, Ishita; Karwoski, Ronald A.; Camp, Jon J.; Bartholmai, Brian J.; Robb, Richard A.

2005-04-01

Chronic obstructive pulmonary diseases (COPD) are debilitating conditions of the lung and are the fourth leading cause of death in the United States. Early diagnosis is critical for timely intervention and effective treatment. The ability to quantify particular imaging features of specific pathology and accurately assess progression or response to treatment with current imaging tools is relatively poor. The goal of this project was to develop automated segmentation techniques that would be clinically useful as computer assisted diagnostic tools for COPD. The lungs were segmented using an optimized segmentation threshold and the trachea was segmented using a fixed threshold characteristic of air. The segmented images were smoothed by a morphological close operation using spherical elements of different sizes. The results were compared to other segmentation approaches using an optimized threshold to segment the trachea. Comparison of the segmentation results from 10 datasets showed that the method of trachea segmentation using a fixed air threshold followed by morphological closing with spherical element of size 23x23x5 yielded the best results. Inclusion of greater number of pulmonary vessels in the lung volume is important for the development of computer assisted diagnostic tools because the physiological changes of COPD can result in quantifiable anatomic changes in pulmonary vessels. Using a fixed threshold to segment the trachea removed airways from the lungs to a better extent as compared to using an optimized threshold. Preliminary measurements gathered from patient"s CT scans suggest that segmented images can be used for accurate analysis of total lung volume and volumes of regional lung parenchyma. Additionally, reproducible segmentation allows for quantification of specific pathologic features, such as lower intensity pixels, which are characteristic of abnormal air spaces in diseases like emphysema.

Arrays of Segmented, Tapered Light Guides for Use With Large, Planar Scintillation Detectors

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Vaigneur, Keith; Stolin, Alexander V.; Jaliparthi, Gangadhar

2015-06-01

Metabolic imaging techniques can potentially improve detection and diagnosis of cancer in women with radiodense and/or fibrocystic breasts. Our group has previously developed a high-resolution positron emission tomography imaging and biopsy device (PEM-PET) to detect and guide the biopsy of suspicious breast lesions. Initial testing revealed that the imaging field-of-view (FOV) of the scanner was smaller than the physical size of the detector's active area, which could hinder sampling of breast areas close to the chest wall. The purpose of this work was to utilize segmented, tapered light guides for optically coupling the scintillator arrays to arrays of position-sensitive photomultipliers to increase both the active FOV and identification of individual scintillator elements. Testing of the new system revealed that the optics of these structures made it possible to discern detector elements from the complete active area of the detector face. In the previous system the top and bottom rows and left and right columns were not identifiable. Additionally, use of the new light guides increased the contrast of individual detector elements by up to 129%. Improved element identification led to a spatial resolution increase by approximately 12%. Due to attenuation of light in the light guides the detector energy resolution decreased from 18.5% to 19.1%. Overall, these improvements should increase the field-of-view and spatial resolution of the dedicated breast-PET system.

Formation Flying: The Future of Remote Sensing from Space

NASA Technical Reports Server (NTRS)

Leitner, Jesse

2004-01-01

Over the next two decades a revolution is likely to occur in how remote sensing of Earth, other planets or bodies, and a range of phenomena in the universe is performed from space. In particular, current launch vehicle fairing volume and mass constraints will continue to restrict the size of monolithic telescope apertures which can be launched to accommodate only slightly more performance capability than is achievable today, such as by the Hubble Space Telescope. Systems under formulation today, such as the James Webb Space Telescope will be able to increase aperture size and, hence, imaging resolution, by deploying segmented optics. However, this approach is limited as well, by ow ability to control such segments to optical tolerances over long distances with highly uncertain structural dynamics connecting them. Consequently, for orders of magnitude improved resolution as required for imaging black holes, imaging planets, or performing asteroseismology, the only viable approach will be to fly a collection of spacecraft in formation to synthesize a virtual segmented telescope or interferometer with very large baselines. This presentation describes some of the strategic science missions planned in the National Aeronautics and Space Administration, and identifies some of the critical technologies needed to enable some of the most challenging space missions ever conceived which have realistic hopes of flying.

Spacecraft Formation Flying: An Overview of Missions and Technologies

NASA Technical Reports Server (NTRS)

Leitner, Jesse

2007-01-01

Over the next two decades a revolution is likely to occur in how remote sensing of Earth, other planets or bodies, and a range of phenomena in the universe is performed from space. In particular, current launch vehicle fairing volume and mass constraints will continue to restrict the size of monolithic telescope apertures which can be launched to accommodate only slightly more performance capability than is achievable today, such as by the Hubble Space Telescope. Systems under formulation today, such as the James Webb Space Telescope, will be able to increase aperture size and, hence, imaging resolution, by deploying segmented optics. However, this approach is limited as well, by our ability to control such segments to optical tolerances over long distances with highly uncertain structural dynamics connecting them. Consequently, for orders of magnitude improved resolution as required for imaging black holes, imaging planets, or performing asteroseismology, the only viable approach will be to fly a collection of spacecraft in formation to synthesize a virtual segmented telescope or interferometer with very large baselines. This presentation highlights some of the strategic science missions planned in the National Aeronautics and Space Administration, and identifies some of the critical technologies needed to enable some of the most challenging space missions ever conceived which have realistic hopes of flying.

Extracting built-up areas from TerraSAR-X data using object-oriented classification method

NASA Astrophysics Data System (ADS)

Wang, SuYun; Sun, Z. C.

2017-02-01

Based on single-polarized TerraSAR-X, the approach generates homogeneous segments on an arbitrary number of scale levels by applying a region-growing algorithm which takes the intensity of backscatter and shape-related properties into account. The object-oriented procedure consists of three main steps: firstly, the analysis of the local speckle behavior in the SAR intensity data, leading to the generation of a texture image; secondly, a segmentation based on the intensity image; thirdly, the classification of each segment using the derived texture file and intensity information in order to identify and extract build-up areas. In our research, the distribution of BAs in Dongying City is derived from single-polarized TSX SM image (acquired on 17th June 2013) with average ground resolution of 3m using our proposed approach. By cross-validating the random selected validation points with geo-referenced field sites, Quick Bird high-resolution imagery, confusion matrices with statistical indicators are calculated and used for assessing the classification results. The results demonstrate that an overall accuracy 92.89 and a kappa coefficient of 0.85 could be achieved. We have shown that connect texture information with the analysis of the local speckle divergence, combining texture and intensity of construction extraction is feasible, efficient and rapid.

Large-Scale Propagation of Ultrasound in a 3-D Breast Model Based on High-Resolution MRI Data

PubMed Central

Tillett, Jason C.; Metlay, Leon A.; Waag, Robert C.

2010-01-01

A 40 × 35 × 25-mm3 specimen of human breast consisting mostly of fat and connective tissue was imaged using a 3-T magnetic resonance scanner. The resolutions in the image plane and in the orthogonal direction were 130 μm and 150 μm, respectively. Initial processing to prepare the data for segmentation consisted of contrast inversion, interpolation, and noise reduction. Noise reduction used a multilevel bidirectional median filter to preserve edges. The volume of data was segmented into regions of fat and connective tissue by using a combination of local and global thresholding. Local thresholding was performed to preserve fine detail, while global thresholding was performed to minimize the interclass variance between voxels classified as background and voxels classified as object. After smoothing the data to avoid aliasing artifacts, the segmented data volume was visualized using iso-surfaces. The isosurfaces were enhanced using transparency, lighting, shading, reflectance, and animation. Computations of pulse propagation through the model illustrate its utility for the study of ultrasound aberration. The results show the feasibility of using the described combination of methods to demonstrate tissue morphology in a form that provides insight about the way ultrasound beams are aberrated in three dimensions by tissue. PMID:20172794

Large-scale propagation of ultrasound in a 3-D breast model based on high-resolution MRI data.

PubMed

Salahura, Gheorghe; Tillett, Jason C; Metlay, Leon A; Waag, Robert C

2010-06-01

A 40 x 35 x 25-mm(3) specimen of human breast consisting mostly of fat and connective tissue was imaged using a 3-T magnetic resonance scanner. The resolutions in the image plane and in the orthogonal direction were 130 microm and 150 microm, respectively. Initial processing to prepare the data for segmentation consisted of contrast inversion, interpolation, and noise reduction. Noise reduction used a multilevel bidirectional median filter to preserve edges. The volume of data was segmented into regions of fat and connective tissue by using a combination of local and global thresholding. Local thresholding was performed to preserve fine detail, while global thresholding was performed to minimize the interclass variance between voxels classified as background and voxels classified as object. After smoothing the data to avoid aliasing artifacts, the segmented data volume was visualized using isosurfaces. The isosurfaces were enhanced using transparency, lighting, shading, reflectance, and animation. Computations of pulse propagation through the model illustrate its utility for the study of ultrasound aberration. The results show the feasibility of using the described combination of methods to demonstrate tissue morphology in a form that provides insight about the way ultrasound beams are aberrated in three dimensions by tissue.

Automated Detection of Synapses in Serial Section Transmission Electron Microscopy Image Stacks

PubMed Central

Kreshuk, Anna; Koethe, Ullrich; Pax, Elizabeth; Bock, Davi D.; Hamprecht, Fred A.

2014-01-01

We describe a method for fully automated detection of chemical synapses in serial electron microscopy images with highly anisotropic axial and lateral resolution, such as images taken on transmission electron microscopes. Our pipeline starts from classification of the pixels based on 3D pixel features, which is followed by segmentation with an Ising model MRF and another classification step, based on object-level features. Classifiers are learned on sparse user labels; a fully annotated data subvolume is not required for training. The algorithm was validated on a set of 238 synapses in 20 serial 7197×7351 pixel images (4.5×4.5×45 nm resolution) of mouse visual cortex, manually labeled by three independent human annotators and additionally re-verified by an expert neuroscientist. The error rate of the algorithm (12% false negative, 7% false positive detections) is better than state-of-the-art, even though, unlike the state-of-the-art method, our algorithm does not require a prior segmentation of the image volume into cells. The software is based on the ilastik learning and segmentation toolkit and the vigra image processing library and is freely available on our website, along with the test data and gold standard annotations (http://www.ilastik.org/synapse-detection/sstem). PMID:24516550

Three-dimensional estimates of tree canopies: Scaling from high-resolution UAV data to satellite observations

NASA Astrophysics Data System (ADS)

Sankey, T.; Donald, J.; McVay, J.

2015-12-01

High resolution remote sensing images and datasets are typically acquired at a large cost, which poses big a challenge for many scientists. Northern Arizona University recently acquired a custom-engineered, cutting-edge UAV and we can now generate our own images with the instrument. The UAV has a unique capability to carry a large payload including a hyperspectral sensor, which images the Earth surface in over 350 spectral bands at 5 cm resolution, and a lidar scanner, which images the land surface and vegetation in 3-dimensions. Both sensors represent the newest available technology with very high resolution, precision, and accuracy. Using the UAV sensors, we are monitoring the effects of regional forest restoration treatment efforts. Individual tree canopy width and height are measured in the field and via the UAV sensors. The high-resolution UAV images are then used to segment individual tree canopies and to derive 3-dimensional estimates. The UAV image-derived variables are then correlated to the field-based measurements and scaled to satellite-derived tree canopy measurements. The relationships between the field-based and UAV-derived estimates are then extrapolated to a larger area to scale the tree canopy dimensions and to estimate tree density within restored and control forest sites.

The CMS High Granularity Calorimeter for the High Luminosity LHC

NASA Astrophysics Data System (ADS)

Sauvan, J.-B.

2018-02-01

The High Luminosity LHC (HL-LHC) will integrate 10 times more luminosity than the LHC, posing significant challenges for radiation tolerance and event pileup on detectors, especially for forward calorimetry, and hallmarks the issue for future colliders. As part of its HL-LHC upgrade program, the CMS collaboration is designing a High Granularity Calorimeter to replace the existing endcap calorimeters. It features unprecedented transverse and longitudinal segmentation for both electromagnetic (ECAL) and hadronic (HCAL) compartments. This will facilitate particle-flow calorimetry, where the fine structure of showers can be measured and used to enhance pileup rejection and particle identification, whilst still achieving good energy resolution. The ECAL and a large fraction of HCAL will be based on hexagonal silicon sensors of 0.5-1 cm2 cell size, with the remainder of the HCAL based on highly-segmented scintillators with silicon photomultiplier (SiPM) readout. The intrinsic high-precision timing capabilities of the silicon sensors will add an extra dimension to event reconstruction, especially in terms of pileup rejection.

Hippocampal Structure and Human Cognition: Key Role of Spatial Processing and Evidence Supporting the Efficiency Hypothesis in Females

ERIC Educational Resources Information Center

Colom, Roberto; Stein, Jason L.; Rajagopalan, Priya; Martinez, Kenia; Hermel, David; Wang, Yalin; Alvarez-Linera, Juan; Burgaleta, Miguel; Quiroga, Ma. Angeles; Shih, Pei Chun; Thompson, Paul M.

2013-01-01

Here we apply a method for automated segmentation of the hippocampus in 3D high-resolution structural brain MRI scans. One hundred and four healthy young adults completed twenty one tasks measuring abstract, verbal, and spatial intelligence, along with working memory, executive control, attention, and processing speed. After permutation tests…

High-Resolution Patterns of Meiotic Recombination across the Human Major Histocompatibility Complex

PubMed Central

Cullen, Michael; Perfetto, Stephen P.; Klitz, William; Nelson, George; Carrington, Mary

2002-01-01

Definitive characteristics of meiotic recombination events over large (i.e., >1 Mb) segments of the human genome remain obscure, yet they are essential for establishing the haplotypic structure of the genome and for efficient mapping of complex traits. We present a high-resolution map of recombination at the kilobase level across a 3.3-Mb interval encompassing the major histocompatibility complex (MHC). Genotyping of 20,031 single sperm from 12 individuals resulted in the identification and fine mapping of 325 recombinant chromosomes within genomic intervals as small as 7 kb. Several principal characteristics of recombination in this region were observed: (1) rates of recombination can differ significantly between individuals; (2) intense hot spots of recombination occur at least every 0.8 Mb but are not necessarily evenly spaced; (3) distribution in the location of recombination events can differ significantly among individuals; (4) between hot spots, low levels of recombination occur fairly evenly across 100-kb segments, suggesting the presence of warm spots of recombination; and (5) specific sequence motifs associate significantly with recombination distribution. These data provide a plausible model for recombination patterns of the human genome overall. PMID:12297984

Electric field imaging of single atoms

PubMed Central

Shibata, Naoya; Seki, Takehito; Sánchez-Santolino, Gabriel; Findlay, Scott D.; Kohno, Yuji; Matsumoto, Takao; Ishikawa, Ryo; Ikuhara, Yuichi

2017-01-01

In scanning transmission electron microscopy (STEM), single atoms can be imaged by detecting electrons scattered through high angles using post-specimen, annular-type detectors. Recently, it has been shown that the atomic-scale electric field of both the positive atomic nuclei and the surrounding negative electrons within crystalline materials can be probed by atomic-resolution differential phase contrast STEM. Here we demonstrate the real-space imaging of the (projected) atomic electric field distribution inside single Au atoms, using sub-Å spatial resolution STEM combined with a high-speed segmented detector. We directly visualize that the electric field distribution (blurred by the sub-Å size electron probe) drastically changes within the single Au atom in a shape that relates to the spatial variation of total charge density within the atom. Atomic-resolution electric field mapping with single-atom sensitivity enables us to examine their detailed internal and boundary structures. PMID:28555629

Status of ADRIANO R&D in T1015 Collaboration

DOE PAGES

Gatto, Corrado; Di Benedetto, V.; Mazzacane, A.

2015-02-13

The physics program for future High Energy and High Intensity experiments requires an energy resolution of the calorimetric component of detectors at limits of traditional techniques and an excellent particle identification. The novel ADRIANO technology (A Dualreadout Integrally Active Non-segmented Option), currently under development at Fermilab, is showing excellent performance on those respects. Results from detailed Monte Carlo studies on the performance with respect to energy resolution, linear response and transverse containment and a preliminary optimization of the layout are presented. A baseline configuration is chosen with an estimated energy resolution of σ(E)/E ≈ 30%/√E , to support an extensivemore » R&D program recently started by T1015 Collaboration at Fermilab. Furthermore, preliminary results from several test beams at the Fermilab Test Beam Facility (FTBF) of a ~ 1λI prototype are presented. Future prospects with ultra-heavy glass are, also, summarized.« less

Bonding Thin Mirror Segments Without Distortion for the International X-Ray Observatory

NASA Technical Reports Server (NTRS)

Evans, Tyler C.; Chan, Kai-Wing; Saha, Timo T.

2011-01-01

The International X-Ray Observatory (IXO) uses thin glass optics to maximize large effective area and precise low angular resolution. The thin glass mirror segments must be transferred from their fabricated state to a permanent structure without imparting distortion. IXO will incorporate about fourteen thousand thin mirror segments to achieve the mission goal of 3.0 square meters of effective area at 1.25 keV with an angular resolution of five arcseconds. To preserve figure and alignment, the mirror segment must be bonded with sub-micron movement at each corner. Recent advances in technology development have produced significant x-ray test results of a bonded pair of mirrors. Three specific bonding cycles will be described highlighting the improvements in procedure, temperature control, and precision bonding. This paper will highlight the recent advances in alignment and permanent bonding as well as the results they have produced.

The relationship between oceanic transform fault segmentation, seismicity, and thermal structure

NASA Astrophysics Data System (ADS)

Wolfson-Schwehr, Monica

Mid-ocean ridge transform faults (RTFs) are typically viewed as geometrically simple, with fault lengths readily constrained by the ridge-transform intersections. This relative simplicity, combined with well-constrained slip rates, make them an ideal environment for studying strike-slip earthquake behavior. As the resolution of available bathymetric data over oceanic transform faults continues to improve, however, it is being revealed that the geometry and structure of these faults can be complex, including such features as intra-transform pull-apart basins, intra-transform spreading centers, and cross-transform ridges. To better determine the resolution of structural complexity on RTFs, as well as the prevalence of RTF segmentation, fault structure is delineated on a global scale. Segmentation breaks the fault system up into a series of subparallel fault strands separated by an extensional basin, intra-transform spreading center, or fault step. RTF segmentation occurs across the full range of spreading rates, from faults on the ultraslow portion of the Southwest Indian Ridge to faults on the ultrafast portion of the East Pacific Rise (EPR). It is most prevalent along the EPR, which hosts the fastest spreading rates in the world and has undergone multiple changes in relative plate motion over the last couple of million years. Earthquakes on RTFs are known to be small, to scale with the area above the 600°C isotherm, and to exhibit some of the most predictable behaviors in seismology. In order to determine whether segmentation affects the global RTF scaling relations, the scalings are recomputed using an updated seismic catalog and fault database in which RTF systems are broken up according to their degree of segmentation (as delineated from available bathymetric datasets). No statistically significant differences between the new computed scaling relations and the current scaling relations were found, though a few faults were identified as outliers. Finite element analysis is used to model 3-D RTF fault geometry assuming a viscoplastic rheology in order to determine how segmentation affects the underlying thermal structure of the fault. In the models, fault segment length, length and location along fault of the intra-transform spreading center, and slip rate are varied. A new scaling relation is developed for the critical fault offset length (OC) that significantly reduces the thermal area of adjacent fault segments, such that adjacent segments are fully decoupled at ~4 OC . On moderate to fast slipping RTFs, offsets ≥ 5 km are sufficient to significantly reduce the thermal influence between two adjacent transform fault segments. The relationship between fault structure and seismic behavior was directly addressed on the Discovery transform fault, located at 4°S on the East Pacific Rise. One year of microseismicity recorded on an OBS array, and 24 years of Mw ≥ 5.4 earthquakes obtained from the Global Centroid Moment Tensor catalog, were correlated with surface fault structure delineated from high-resolution multibeam bathymetry. Each of the 15 Mw ≥ 5.4 earthquakes was relocated into one of five distinct repeating rupture patches, while microseismicity was found to be reduced within these patches. While the endpoints of these patches appeared to correlate with structural features on the western segment of Discovery, small step-overs in the primary fault trace were not observed at patch boundaries. This indicates that physical segmentation of the fault is not the primary control on the size and location of large earthquakes on Discovery, and that along-strike heterogeneity in fault zone properties must play an important role.

High Resolution Observations of Escaping Ions in the Martian Magnetotail

NASA Astrophysics Data System (ADS)

Halekas, J. S.; Raman, C.; Brain, D.; DiBraccio, G. A.; Harada, Y.; McFadden, J. P.; Mitchell, D. L.; Connerney, J. E. P.; Jakosky, B. M.

2016-12-01

Ions escape from the Martian upper atmosphere via a number of channels, including the central plasmasheet of the magnetotail. Mars Express observations show that the heavy ions O+ and O2+ escaping through the central tail often have approximately the same energy, suggesting acceleration in a quasi-static electric field, which has been interpreted as a Hall electric field. The Solar Wind Ion Analyzer (SWIA) on MAVEN was designed to measure the upstream solar wind. However, during orbit segments with appropriate spacecraft attitude, SWIA can also make high resolution measurements of escaping ions in the tail. During the prime mission, these observations were only returned sporadically, during periods of intense escaping fluxes that fortuitously triggered a mode switch. Now, in the extended mission, we return high resolution observations from SWIA routinely. Some of these high resolution measurements reveal slight differences in both the direction and energy of escaping O+ and O2+ ions, which may help determine the acceleration process(es). We investigate the location and solar wind conditions for which the escaping ions separate in energy and angle and the systematics of their energies and flow vectors, and discuss the implications for ion acceleration and the overall picture of Martian atmospheric escape.

Mapping the distribution of mangrove species in the Core Zone of Mai Po Marshes Nature Reserve, Hong Kong, using hyperspectral data and high-resolution data

NASA Astrophysics Data System (ADS)

Jia, Mingming; Zhang, Yuanzhi; Wang, Zongming; Song, Kaishan; Ren, Chunying

2014-12-01

Mangrove species compositions and distributions are essential for conservation and restoration efforts. In this study, hyperspectral data of EO-1 HYPERION sensor and high spatial resolution data of SPOT-5 sensor were used in Mai Po mangrove species mapping. Objected-oriented method was used in mangrove species classification processing. Firstly, mangrove objects were obtained via segmenting high spatial resolution data of SPOT-5. Then the objects were classified into different mangrove species based on the spectral differences of HYPERION image. The classification result showed that in the top canopy, Kandelia obovata and Avicennia marina dominated Mai Po Marshes Natural Reserve, with area of 196.8 ha and 110.8 ha, respectively, Acanthus ilicifolius and Aegiceras corniculatum were mixed together and living at the edge of channels with an area of 11.7 ha. Additionally, mangrove species shows clearly zonations and associations in the Mai Po Core Zone. The overall accuracy of our mangrove map was 88% and the Kappa confidence was 0.83, which indicated great potential of using hyperspectral and high-resolution data for distinguishing and mapping mangrove species.

Performance evaluation of a high-resolution brain PET scanner using four-layer MPPC DOI detectors.

PubMed

Watanabe, Mitsuo; Saito, Akinori; Isobe, Takashi; Ote, Kibo; Yamada, Ryoko; Moriya, Takahiro; Omura, Tomohide

2017-08-18

A high-resolution positron emission tomography (PET) scanner, dedicated to brain studies, was developed and its performance was evaluated. A four-layer depth of interaction detector was designed containing five detector units axially lined up per layer board. Each of the detector units consists of a finely segmented (1.2 mm) LYSO scintillator array and an 8  ×  8 array of multi-pixel photon counters. Each detector layer has independent front-end and signal processing circuits, and the four detector layers are assembled as a detector module. The new scanner was designed to form a detector ring of 430 mm diameter with 32 detector modules and 168 detector rings with a 1.2 mm pitch. The total crystal number is 655 360. The transaxial and axial field of views (FOVs) are 330 mm in diameter and 201.6 mm, respectively, which are sufficient to measure a whole human brain. The single-event data generated at each detector module were transferred to the data acquisition servers through optical fiber cables. The single-event data from all detector modules were merged and processed to create coincidence event data in on-the-fly software in the data acquisition servers. For image reconstruction, the high-resolution mode (HR-mode) used a 1.2 mm 2 crystal segment size and the high-speed mode (HS-mode) used a 4.8 mm 2 size by collecting 16 crystal segments of 1.2 mm each to reduce the computational cost. The performance of the brain PET scanner was evaluated. For the intrinsic spatial resolution of the detector module, coincidence response functions of the detector module pair, which faced each other at various angles, were measured by scanning a 0.25 mm diameter 22 Na point source. The intrinsic resolutions were obtained with 1.08 mm full width at half-maximum (FWHM) and 1.25 mm FWHM on average at 0 and 22.5 degrees in the first layer pair, respectively. The system spatial resolutions were less than 1.0 mm FWHM throughout the whole FOV, using a list-mode dynamic RAMLA (LM-DRAMA). The system sensitivity was 21.4 cps kBq -1 as measured using an 18 F line source aligned with the center of the transaxial FOV. High count rate capability was evaluated using a cylindrical phantom (20 cm diameter  ×  70 cm length), resulting in 249 kcps in true and 27.9 kcps at 11.9 kBq ml -1 at the peak count in a noise equivalent count rate (NECR_2R). Single-event data acquisition and on-the-fly software coincidence detection performed well, exceeding 25 Mcps and 2.3 Mcps for single and coincidence count rates, respectively. Using phantom studies, we also demonstrated its imaging capabilities by means of a 3D Hoffman brain phantom and an ultra-micro hot-spot phantom. The images obtained were of acceptable quality for high-resolution determination. As clinical and pre-clinical studies, we imaged brains of a human and of small animals.

Performance evaluation of a high-resolution brain PET scanner using four-layer MPPC DOI detectors

NASA Astrophysics Data System (ADS)

Watanabe, Mitsuo; Saito, Akinori; Isobe, Takashi; Ote, Kibo; Yamada, Ryoko; Moriya, Takahiro; Omura, Tomohide

2017-09-01

A high-resolution positron emission tomography (PET) scanner, dedicated to brain studies, was developed and its performance was evaluated. A four-layer depth of interaction detector was designed containing five detector units axially lined up per layer board. Each of the detector units consists of a finely segmented (1.2 mm) LYSO scintillator array and an 8  ×  8 array of multi-pixel photon counters. Each detector layer has independent front-end and signal processing circuits, and the four detector layers are assembled as a detector module. The new scanner was designed to form a detector ring of 430 mm diameter with 32 detector modules and 168 detector rings with a 1.2 mm pitch. The total crystal number is 655 360. The transaxial and axial field of views (FOVs) are 330 mm in diameter and 201.6 mm, respectively, which are sufficient to measure a whole human brain. The single-event data generated at each detector module were transferred to the data acquisition servers through optical fiber cables. The single-event data from all detector modules were merged and processed to create coincidence event data in on-the-fly software in the data acquisition servers. For image reconstruction, the high-resolution mode (HR-mode) used a 1.2 mm2 crystal segment size and the high-speed mode (HS-mode) used a 4.8 mm2 size by collecting 16 crystal segments of 1.2 mm each to reduce the computational cost. The performance of the brain PET scanner was evaluated. For the intrinsic spatial resolution of the detector module, coincidence response functions of the detector module pair, which faced each other at various angles, were measured by scanning a 0.25 mm diameter 22Na point source. The intrinsic resolutions were obtained with 1.08 mm full width at half-maximum (FWHM) and 1.25 mm FWHM on average at 0 and 22.5 degrees in the first layer pair, respectively. The system spatial resolutions were less than 1.0 mm FWHM throughout the whole FOV, using a list-mode dynamic RAMLA (LM-DRAMA). The system sensitivity was 21.4 cps kBq-1 as measured using an 18F line source aligned with the center of the transaxial FOV. High count rate capability was evaluated using a cylindrical phantom (20 cm diameter  ×  70 cm length), resulting in 249 kcps in true and 27.9 kcps at 11.9 kBq ml-1 at the peak count in a noise equivalent count rate (NECR_2R). Single-event data acquisition and on-the-fly software coincidence detection performed well, exceeding 25 Mcps and 2.3 Mcps for single and coincidence count rates, respectively. Using phantom studies, we also demonstrated its imaging capabilities by means of a 3D Hoffman brain phantom and an ultra-micro hot-spot phantom. The images obtained were of acceptable quality for high-resolution determination. As clinical and pre-clinical studies, we imaged brains of a human and of small animals.

The effects of tirofiban infusion on clinical and angiographic outcomes of patients with STEMI undergoing primary PCI.

PubMed

Kaymaz, Cihangir; Keleş, Nurşen; Özdemir, Nihal; Tanboğa, İbrahim Halil; Demircan, Hacer C; Can, Mehmet M; Koca, Fatih; İzgi, İbrahim Akın; Özkan, Alper; Türkmen, Muhsin; Kırma, Cevat; Esen, Ali M

2015-11-01

The present study was designed to determine the effects of tirofiban (Tiro) infusion on angiographic measures, ST-segment resolution, and clinical outcomes in patients with STEMI undergoing PCI. Glycoprotein (GP) IIb/IIIa inhibitors are beneficial in ST-segment elevation myocardial infarction (STEMI) patients undergoing percutaneous coronary intervention (PCI), while the most effective timing of administration is still under investigation. A total of 1242 patients (83.0% males, mean (standard deviation; SD) age: 54.7 (10.9) years) with STEMI who underwent primary PCI were included in this retrospective non-randomized study in four groups, composed of no tirofiban infusion [Tiro (-); n=248], tirofiban infusion before PCI (pre-Tiro; n=720), tirofiban infusion during PCI (peri-Tiro; n=50), and tirofiban infusion after PCI (post-Tiro; n=224). In all Tiro (+) patients, bolus administration of Tiro (10 µg/kg) was followed by infusion (0.15 µg/kg/min) for a mean (SD) duration of 22.4±6.8 hours. The pre-PCI Tiro group was associated with the highest percentage of patients with TIMI 3 flow (99.4%; p<0.001), the lowest corrected TIMI frame count [21(18-23.4); p<0.001], the highest percentage of patients with >75% ST-segment resolution (78.1%; p<0.001), and the lowest rate of in-hospital sudden cardiac death and in-hospital all-cause mortality (3.2%, p<0.05, 3.3%, p=0.01). Major bleeding was reported in 18 (1.8%) patients who received tirofiban. Use of standard-dose bolus tirofiban in addition to aspirin, high-dose clopidogrel, and unfractionated heparin prior to primary PCI significantly improves myocardial reperfusion, ST-segment resolution, in-hospital mortality rate, and in-hospital sudden cardiac death in patients with STEMI with no increased risk of major bleeding.

Non-enhanced, ECG-gated MR angiography of the pedal vasculature: comparison with contrast-enhanced MR angiography and digital subtraction angiography in peripheral arterial occlusive disease.

PubMed

Schubert, Tilman; Takes, Martin; Aschwanden, Markus; Klarhoefer, Markus; Haas, Tanja; Jacob, Augustinus L; Liu, David; Gutzeit, Andreas; Kos, Sebastian

2016-08-01

This study was conducted in order to compare a high resolution, non-contrast-enhanced MRA (NATIVE SPACE, NE-MRA) of the pedal vasculature with contrast-enhanced MRA (CE-MRA) and digital subtraction angiography (DSA) in patients with peripheral arterial occlusive disease (PAOD). The prospective study consists of 20 PAOD patients. All patients underwent percutaneous transluminal angioplasty or stenting and received MR angiographies the following day. With CE-MRA, 75.7 % of vessel segments showed good, 16.4 % suboptimal and 7.9 % not usable image quality. With NE-MRA, 64.6 % showed good, 18.6 % suboptimal and 16.8 % not usable image quality. CE-MRA showed a sensitivity and negative predictive value of 90 %/95 % regarding significant stenosis (greater than 50 %), and specificity and positive predictive value were 88 %/77 %. Accordingly, sensitivity and negative predictive value for the NE-MRA were 96 %/97 % and specificity and positive predictive value were 80 %/69 % for stenoses greater than 50 %. The applied NE-MRA technique achieves high diagnostic accuracy even in very small distal arteries of the foot. However, the rate of non-diagnostic vessel segments is considerably higher for NE-MRA than for CE-MRA. NE-MRA is a valuable alternative to CE-MRA in selected patients. • Comparison of non-enhanced MRA with contrast-enhanced MRA and DSA as gold standard. • High resolution MRA at 3 T for the depiction of small pedal vessels. • Evaluation of high resolution non-enhanced MRA in PAOD patients.

A comparison of needle tip localization accuracy using 2D and 3D trans-rectal ultrasound for high-dose-rate prostate cancer brachytherapy treatment planning

NASA Astrophysics Data System (ADS)

Hrinivich, W. Thomas; Hoover, Douglas A.; Surry, Kathleen; Edirisinghe, Chandima; Montreuil, Jacques; D'Souza, David; Fenster, Aaron; Wong, Eugene

2016-03-01

Background: High-dose-rate brachytherapy (HDR-BT) is a prostate cancer treatment option involving the insertion of hollow needles into the gland through the perineum to deliver a radioactive source. Conventional needle imaging involves indexing a trans-rectal ultrasound (TRUS) probe in the superior/inferior (S/I) direction, using the axial transducer to produce an image set for organ segmentation. These images have limited resolution in the needle insertion direction (S/I), so the sagittal transducer is used to identify needle tips, requiring a manual registration with the axial view. This registration introduces a source of uncertainty in the final segmentations and subsequent treatment plan. Our lab has developed a device enabling 3D-TRUS guided insertions with high S/I spatial resolution, eliminating the need to align axial and sagittal views. Purpose: To compare HDR-BT needle tip localization accuracy between 2D and 3D-TRUS. Methods: 5 prostate cancer patients underwent conventional 2D TRUS guided HDR-BT, during which 3D images were also acquired for post-operative registration and segmentation. Needle end-length measurements were taken, providing a gold standard for insertion depths. Results: 73 needles were analyzed from all 5 patients. Needle tip position differences between imaging techniques was found to be largest in the S/I direction with mean+/-SD of -2.5+/-4.0 mm. End-length measurements indicated that 3D TRUS provided statistically significantly lower mean+/-SD insertion depth error of -0.2+/-3.4 mm versus 2.3+/-3.7 mm with 2D guidance (p < .001). Conclusions: 3D TRUS may provide more accurate HDR-BT needle localization than conventional 2D TRUS guidance for the majority of HDR-BT needles.

Large aperture segmented optics for space-to-ground communications.

PubMed

Lucy, R F

1968-08-01

A large aperture, moderate quality segmented optical array for use in noncoherent space-to-ground laser communications is determined as a function of resolution, diameter, focal length, and number of segments in the array. Secondary optics and construction tolerances are also discussed. Performance predictions show a typical receiver to be capable of megahertz communications at Mars distances during daylight operation.

Feasibility of creating a high-resolution 3D diffusion tensor imaging based atlas of the human brainstem: A case study at 11.7T

PubMed Central

Aggarwal, Manisha; Zhang, Jiangyang; Pletnikova, Olga; Crain, Barbara; Troncoso, Juan; Mori, Susumu

2013-01-01

A three-dimensional stereotaxic atlas of the human brainstem based on high resolution ex vivo diffusion tensor imaging (DTI) is introduced. The atlas consists of high resolution (125–255 μm isotropic) three-dimensional DT images of the formalin-fixed brainstem acquired at 11.7T. The DTI data revealed microscopic neuroanatomical details, allowing three-dimensional visualization and reconstruction of fiber pathways including the decussation of the pyramidal tract fibers, and interdigitating fascicles of the corticospinal and transverse pontine fibers. Additionally, strong grey-white matter contrasts in the apparent diffusion coefficient (ADC) maps enabled precise delineation of grey matter nuclei in the brainstem, including the cranial nerve and the inferior olivary nuclei. Comparison with myelin-stained histology shows that at the level of resolution achieved in this study, the structural details resolved with DTI contrasts in the brainstem were comparable to anatomical delineation obtained with histological sectioning. Major neural structures delineated from DTI contrasts in the brainstem are segmented and three-dimensionally reconstructed. Further, the ex vivo DTI data are nonlinearly mapped to a widely-used in vivo human brain atlas, to construct a high-resolution atlas of the brainstem in the Montreal Neurological Institute (MNI) stereotaxic coordinate space. The results demonstrate the feasibility of developing a 3D DTI based atlas for detailed characterization of brainstem neuroanatomy with high resolution and contrasts, which will be a useful resource for research and clinical applications. PMID:23384518

A state-of-the-art review on segmentation algorithms in intravascular ultrasound (IVUS) images.

PubMed

Katouzian, Amin; Angelini, Elsa D; Carlier, Stéphane G; Suri, Jasjit S; Navab, Nassir; Laine, Andrew F

2012-09-01

Over the past two decades, intravascular ultrasound (IVUS) image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in catheterization procedures and in research studies. IVUS provides cross-sectional grayscale images of the arterial wall and the extent of atherosclerotic plaques with high spatial resolution in real time. In this paper, we review recently developed image processing methods for the detection of media-adventitia and luminal borders in IVUS images acquired with different transducers operating at frequencies ranging from 20 to 45 MHz. We discuss methodological challenges, lack of diversity in reported datasets, and weaknesses of quantification metrics that make IVUS segmentation still an open problem despite all efforts. In conclusion, we call for a common reference database, validation metrics, and ground-truth definition with which new and existing algorithms could be benchmarked.

[Three-dimensional 3D modeling: First applications in radioanatomy and interventional radiology under CT guidance].

PubMed

Aubry, S; Pousse, A; Sarliève, P; Laborie, L; Delabrousse, E; Kastler, B

2006-11-01

To model vertebrae in 3D to improve radioanatomic knowledge of the spine with the vascular and nerve environment and simulate CT-guided interventions. Vertebra acquisitions were made with multidetector CT. We developed segmentation software and specific viewer software using the Delphi programming environment. This segmentation software makes it possible to model 3D high-resolution segments of vertebrae and their environment from multidetector CT acquisitions. Then the specific viewer software provides multiplanar reconstructions of the CT volume and the possibility to select different 3D objects of interest. This software package improves radiologists' radioanatomic knowledge through a new 3D anatomy presentation. Furthermore, the possibility of inserting virtual 3D objects in the volume can simulate CT-guided intervention. The first volumetric radioanatomic software has been born. Furthermore, it simulates CT-guided intervention and consequently has the potential to facilitate learning interventions using CT guidance.

Instantaneous Coastline Extraction from LIDAR Point Cloud and High Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Li, Y.; Zhoing, L.; Lai, Z.; Gan, Z.

2018-04-01

A new method was proposed for instantaneous waterline extraction in this paper, which combines point cloud geometry features and image spectral characteristics of the coastal zone. The proposed method consists of follow steps: Mean Shift algorithm is used to segment the coastal zone of high resolution remote sensing images into small regions containing semantic information;Region features are extracted by integrating LiDAR data and the surface area of the image; initial waterlines are extracted by α-shape algorithm; a region growing algorithm with is taking into coastline refinement, with a growth rule integrating the intensity and topography of LiDAR data; moothing the coastline. Experiments are conducted to demonstrate the efficiency of the proposed method.

a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

2015-12-01

In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

A von Hamos x-ray spectrometer based on a segmented-type diffraction crystal for single-shot x-ray emission spectroscopy and time-resolved resonant inelastic x-ray scattering studies

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

Szlachetko, J.; Institute of Physics, Jan Kochanowski University, 25-406 Kielce; Nachtegaal, M.

2012-10-15

We report on the design and performance of a wavelength-dispersive type spectrometer based on the von Hamos geometry. The spectrometer is equipped with a segmented-type crystal for x-ray diffraction and provides an energy resolution in the order of 0.25 eV and 1 eV over an energy range of 8000 eV-9600 eV. The use of a segmented crystal results in a simple and straightforward crystal preparation that allows to preserve the spectrometer resolution and spectrometer efficiency. Application of the spectrometer for time-resolved resonant inelastic x-ray scattering and single-shot x-ray emission spectroscopy is demonstrated.

Development of a channel classification to evaluate potential for cottonwood restoration, lower segments of the Middle Missouri River, South Dakota and Nebraska

USGS Publications Warehouse

Jacobson, Robert B.; Elliott, Caroline M.; Huhmann, Brittany L.

2010-01-01

This report documents development of a spatially explicit river and flood-plain classification to evaluate potential for cottonwood restoration along the Sharpe and Fort Randall segments of the Middle Missouri River. This project involved evaluating existing topographic, water-surface elevation, and soils data to determine if they were sufficient to create a classification similar to the Land Capability Potential Index (LCPI) developed by Jacobson and others (U.S. Geological Survey Scientific Investigations Report 2007–5256) and developing a geomorphically based classification to apply to evaluating restoration potential.Existing topographic, water-surface elevation, and soils data for the Middle Missouri River were not sufficient to replicate the LCPI. The 1/3-arc-second National Elevation Dataset delineated most of the topographic complexity and produced cumulative frequency distributions similar to a high-resolution 5-meter topographic dataset developed for the Lower Missouri River. However, lack of bathymetry in the National Elevation Dataset produces a potentially critical bias in evaluation of frequently flooded surfaces close to the river. High-resolution soils data alone were insufficient to replace the information content of the LCPI. In test reaches in the Lower Missouri River, soil drainage classes from the Soil Survey Geographic Database database correctly classified 0.8–98.9 percent of the flood-plain area at or below the 5-year return interval flood stage depending on state of channel incision; on average for river miles 423–811, soil drainage class correctly classified only 30.2 percent of the flood-plain area at or below the 5-year return interval flood stage. Lack of congruence between soil characteristics and present-day hydrology results from relatively rapid incision and aggradation of segments of the Missouri River resulting from impoundments and engineering. The most sparsely available data in the Middle Missouri River were water-surface elevations. Whereas hydraulically modeled water-surface elevations were available at 1.6-kilometer intervals in the Lower Missouri River, water-surface elevations in the Middle Missouri River had to be interpolated between streamflow-gaging stations spaced 3–116 kilometers. Lack of high-resolution water-surface elevation data precludes development of LCPI-like classification maps.An hierarchical river classification framework is proposed to provide structure for a multiscale river classification. The segment-scale classification presented in this report is deductive and based on presumed effects of dams, significant tributaries, and geological (and engineered) channel constraints. An inductive reach-scale classification, nested within the segment scale, is based on multivariate statistical clustering of geomorphic data collected at 500-meter intervals along the river. Cluster-based classifications delineate reaches of the river with similar channel and flood-plain geomorphology, and presumably, similar geomorphic and hydrologic processes. The dominant variables in the clustering process were channel width (Fort Randall) and valley width (Sharpe), followed by braiding index (both segments).Clusters with multithread and highly sinuous channels are likely to be associated with dynamic channel migration and deposition of fresh, bare sediment conducive to natural cottonwood germination. However, restoration potential within these reaches is likely to be mitigated by interaction of cottonwood life stages with the highly altered flow regime.

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.

Loosely coupled level sets for retinal layers and drusen segmentation in subjects with dry age-related macular degeneration

NASA Astrophysics Data System (ADS)

Novosel, Jelena; Wang, Ziyuan; de Jong, Henk; Vermeer, Koenraad A.; van Vliet, Lucas J.

2016-03-01

Optical coherence tomography (OCT) is used to produce high-resolution three-dimensional images of the retina, which permit the investigation of retinal irregularities. In dry age-related macular degeneration (AMD), a chronic eye disease that causes central vision loss, disruptions such as drusen and changes in retinal layer thicknesses occur which could be used as biomarkers for disease monitoring and diagnosis. Due to the topology disrupting pathology, existing segmentation methods often fail. Here, we present a solution for the segmentation of retinal layers in dry AMD subjects by extending our previously presented loosely coupled level sets framework which operates on attenuation coefficients. In eyes affected by AMD, Bruch's membrane becomes visible only below the drusen and our segmentation framework is adapted to delineate such a partially discernible interface. Furthermore, the initialization stage, which tentatively segments five interfaces, is modified to accommodate the appearance of drusen. This stage is based on Dijkstra's algorithm and combines prior knowledge on the shape of the interface, gradient and attenuation coefficient in the newly proposed cost function. This prior knowledge is incorporated by varying the weights for horizontal, diagonal and vertical edges. Finally, quantitative evaluation of the accuracy shows a good agreement between manual and automated segmentation.

A Multi-Contact, Low Capacitance HPGe Detector for High Rate Gamma Spectroscopy

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

Cox, Christopher

2014-12-04

The detection, identification and non-destructive assay of special nuclear materials and nuclear fission by-products are critically important activities in support of nuclear non-proliferation programs. Both national and international nuclear safeguard agencies recognize that current accounting methods for spent nuclear fuel are inadequate from a safeguards perspective. Radiation detection and analysis by gamma-ray spectroscopy is a key tool in this field, but no instrument exists that can deliver the required performance (energy resolution and detection sensitivity) in the presence of very high background count rates encountered in the nuclear safeguards arena. The work of this project addresses this critical need bymore » developing a unique gamma-ray detector based on high purity germanium that has the previously unachievable property of operating in the 1 million counts-per-second range while achieving state-of-the-art energy resolution necessary to identify and analyze the isotopes of interest. The technical approach was to design and fabricate a germanium detector with multiple segmented electrodes coupled to multi-channel high rate spectroscopy electronics. Dividing the germanium detector’s signal electrode into smaller sections offers two advantages; firstly, the energy resolution of the detector is potentially improved, and secondly, the detector is able to operate at higher count rates. The design challenges included the following; determining the optimum electrode configuration to meet the stringent energy resolution and count rate requirements; determining the electronic noise (and therefore energy resolution) of the completed system after multiple signals are recombined; designing the germanium crystal housing and vacuum cryostat; and customizing electronics to perform the signal recombination function in real time. In this phase I work, commercial off-the-shelf electrostatic modeling software was used to develop the segmented germanium crystal geometry, which underwent several iterations before an optimal electrode configuration was found. The model was tested and validated against real-world measurements with existing germanium detectors. Extensive modeling of electronic noise was conducted using established formulae, and real-world measurements were performed on candidate front-end electronic components. This initial work proved the feasibility of the design with respect to expected high count rate and energy resolution performance. Phase I also delivered the mechanical design of the detector housing and vacuum cryostat to be built in Phase II. Finally, a Monte Carlo simulation was created to show the response of the complete design to a Cs-137 source. This development presents a significant advance for nuclear safeguards instrumentation with increased speed and accuracy of detection and identification of special nuclear materials. Other significant applications are foreseen for a gamma-ray detector that delivers high energy resolution (1keV FWHM noise) at high count rate (1 Mcps), especially in the areas of physics research and materials analysis.« less

Using Paleoseismic Trenching and LiDAR Analysis to Evaluate Rupture Propagation Through Segment Boundaries of the Central Wasatch Fault Zone, Utah

NASA Astrophysics Data System (ADS)

Bennett, S. E. K.; DuRoss, C. B.; Reitman, N. G.; Devore, J. R.; Hiscock, A.; Gold, R. D.; Briggs, R. W.; Personius, S. F.

2014-12-01

Paleoseismic data near fault segment boundaries constrain the extent of past surface ruptures and the persistence of rupture termination at segment boundaries. Paleoseismic evidence for large (M≥7.0) earthquakes on the central Holocene-active fault segments of the 350-km-long Wasatch fault zone (WFZ) generally supports single-segment ruptures but also permits multi-segment rupture scenarios. The extent and frequency of ruptures that span segment boundaries remains poorly known, adding uncertainty to seismic hazard models for this populated region of Utah. To address these uncertainties we conducted four paleoseismic investigations near the Salt Lake City-Provo and Provo-Nephi segment boundaries of the WFZ. We examined an exposure of the WFZ at Maple Canyon (Woodland Hills, UT) and excavated the Flat Canyon trench (Salem, UT), 7 and 11 km, respectively, from the southern tip of the Provo segment. We document evidence for at least five earthquakes at Maple Canyon and four to seven earthquakes that post-date mid-Holocene fan deposits at Flat Canyon. These earthquake chronologies will be compared to seven earthquakes observed in previous trenches on the northern Nephi segment to assess rupture correlation across the Provo-Nephi segment boundary. To assess rupture correlation across the Salt Lake City-Provo segment boundary we excavated the Alpine trench (Alpine, UT), 1 km from the northern tip of the Provo segment, and the Corner Canyon trench (Draper, UT) 1 km from the southern tip of the Salt Lake City segment. We document evidence for six earthquakes at both sites. Ongoing geochronologic analysis (14C, optically stimulated luminescence) will constrain earthquake chronologies and help identify through-going ruptures across these segment boundaries. Analysis of new high-resolution (0.5m) airborne LiDAR along the entire WFZ will quantify latest Quaternary displacements and slip rates and document spatial and temporal slip patterns near fault segment boundaries.

Effects of voxelization on dose volume histogram accuracy

NASA Astrophysics Data System (ADS)

Sunderland, Kyle; Pinter, Csaba; Lasso, Andras; Fichtinger, Gabor

2016-03-01

PURPOSE: In radiotherapy treatment planning systems, structures of interest such as targets and organs at risk are stored as 2D contours on evenly spaced planes. In order to be used in various algorithms, contours must be converted into binary labelmap volumes using voxelization. The voxelization process results in lost information, which has little effect on the volume of large structures, but has significant impact on small structures, which contain few voxels. Volume differences for segmented structures affects metrics such as dose volume histograms (DVH), which are used for treatment planning. Our goal is to evaluate the impact of voxelization on segmented structures, as well as how factors like voxel size affects metrics, such as DVH. METHODS: We create a series of implicit functions, which represent simulated structures. These structures are sampled at varying resolutions, and compared to labelmaps with high sub-millimeter resolutions. We generate DVH and evaluate voxelization error for the same structures at different resolutions by calculating the agreement acceptance percentage between the DVH. RESULTS: We implemented tools for analysis as modules in the SlicerRT toolkit based on the 3D Slicer platform. We found that there were large DVH variation from the baseline for small structures or for structures located in regions with a high dose gradient, potentially leading to the creation of suboptimal treatment plans. CONCLUSION: This work demonstrates that labelmap and dose volume voxel size is an important factor in DVH accuracy, which must be accounted for in order to ensure the development of accurate treatment plans.

Three-dimensional representation of the human cochlea using micro-computed tomography data: presenting an anatomical model for further numerical calculations.

PubMed

Braun, Katharina; Böhnke, Frank; Stark, Thomas

2012-06-01

We present a complete geometric model of the human cochlea, including the segmentation and reconstruction of the fluid-filled chambers scala tympani and scala vestibuli, the lamina spiralis ossea and the vibrating structure (cochlear partition). Future fluid-structure coupled simulations require a reliable geometric model of the cochlea. The aim of this study was to present an anatomical model of the human cochlea, which can be used for further numerical calculations. Using high resolution micro-computed tomography (µCT), we obtained images of a cut human temporal bone with a spatial resolution of 5.9 µm. Images were manually segmented to obtain the three-dimensional reconstruction of the cochlea. Due to the high resolution of the µCT data, a detailed examination of the geometry of the twisted cochlear partition near the oval and the round window as well as the precise illustration of the helicotrema was possible. After reconstruction of the lamina spiralis ossea, the cochlear partition and the curved geometry of the scala vestibuli and the scala tympani were presented. The obtained data sets were exported as standard lithography (stl) files. These files represented a complete framework for future numerical simulations of mechanical (acoustic) wave propagation on the cochlear partition in the form of mathematical mechanical cochlea models. Additional quantitative information concerning heights, lengths and volumes of the scalae was found and compared with previous results.

Use of Binary Partition Tree and energy minimization for object-based classification of urban land cover

NASA Astrophysics Data System (ADS)

Li, Mengmeng; Bijker, Wietske; Stein, Alfred

2015-04-01

Two main challenges are faced when classifying urban land cover from very high resolution satellite images: obtaining an optimal image segmentation and distinguishing buildings from other man-made objects. For optimal segmentation, this work proposes a hierarchical representation of an image by means of a Binary Partition Tree (BPT) and an unsupervised evaluation of image segmentations by energy minimization. For building extraction, we apply fuzzy sets to create a fuzzy landscape of shadows which in turn involves a two-step procedure. The first step is a preliminarily image classification at a fine segmentation level to generate vegetation and shadow information. The second step models the directional relationship between building and shadow objects to extract building information at the optimal segmentation level. We conducted the experiments on two datasets of Pléiades images from Wuhan City, China. To demonstrate its performance, the proposed classification is compared at the optimal segmentation level with Maximum Likelihood Classification and Support Vector Machine classification. The results show that the proposed classification produced the highest overall accuracies and kappa coefficients, and the smallest over-classification and under-classification geometric errors. We conclude first that integrating BPT with energy minimization offers an effective means for image segmentation. Second, we conclude that the directional relationship between building and shadow objects represented by a fuzzy landscape is important for building extraction.

Precision Linear Actuators for the Spherical Primary Optical Telescope Demonstration Mirror

NASA Technical Reports Server (NTRS)

Budinoff, Jason; Pfenning, David

2006-01-01

The Spherical Primary Optical Telescope (SPOT) is an ongoing research effort at Goddard Space Flight Center developing wavefront sensing and control architectures for future space telescopes. The 03.5-m SPOT telescope primary mirror is comprise9 of six 0.86-m hexagonal mirror segments arranged in a single ring, with the central segment missing. The mirror segments are designed for laboratory use and are not lightweighted to reduce cost. Each primary mirror segment is actuated and has tip, tilt, and piston rigid-body motions. Additionally, the radius of curvature of each mirror segment may be varied mechanically. To provide these degrees of freedom, the SPOT mirror segment assembly requires linear actuators capable of

The origins and impact of primate segmental duplications.

PubMed

Marques-Bonet, Tomas; Girirajan, Santhosh; Eichler, Evan E

2009-10-01

Duplicated sequences are substrates for the emergence of new genes and are an important source of genetic instability associated with rare and common diseases. Analyses of primate genomes have shown an increase in the proportion of interspersed segmental duplications (SDs) within the genomes of humans and great apes. This contrasts with other mammalian genomes that seem to have their recently duplicated sequences organized in a tandem configuration. In this review, we focus on the mechanistic origin and impact of this difference with respect to evolution, genetic diversity and primate phenotype. Although many genomes will be sequenced in the future, resolution of this aspect of genomic architecture still requires high quality sequences and detailed analyses.

Forest Roadidentification and Extractionof Through Advanced Log Matching Techniques

NASA Astrophysics Data System (ADS)

Zhang, W.; Hu, B.; Quist, L.

2017-10-01

A novel algorithm for forest road identification and extraction was developed. The algorithm utilized Laplacian of Gaussian (LoG) filter and slope calculation on high resolution multispectral imagery and LiDAR data respectively to extract both primary road and secondary road segments in the forest area. The proposed method used road shape feature to extract the road segments, which have been further processed as objects with orientation preserved. The road network was generated after post processing with tensor voting. The proposed method was tested on Hearst forest, located in central Ontario, Canada. Based on visual examination against manually digitized roads, the majority of roads from the test area have been identified and extracted from the process.

Recent Advances in High-Resolution MEMS DM Fabrication and Integration

NASA Astrophysics Data System (ADS)

Bifano, T.; Cornelissen, S.; Bierden, P.

2010-09-01

Deformable mirrors fabricated using microelectromechanical systems technology (MEMS-DMs) have been studied at Boston University (BU) and developed/commercialized by Boston Micromachines Corporation (BMC) over the past decade. Recent advances that might have an impact on surveillance telescopes include demonstration of 4092 actuator DMs with continuous mirror face-sheets, and segmented DMs capable of frame rates of greater than 20kHz for devices with up to 1020 independent segments. The 4092 actuator DM, developed by BMC for the Gemini Planet Imaging GPI instrument, was recently delivered to the GPI instrument development team. Its packaging and platform development are described, and the performance results for the latest prototype devices are presented.

Retinal layer segmentation of macular OCT images using boundary classification

PubMed Central

Lang, Andrew; Carass, Aaron; Hauser, Matthew; Sotirchos, Elias S.; Calabresi, Peter A.; Ying, Howard S.; Prince, Jerry L.

2013-01-01

Optical coherence tomography (OCT) has proven to be an essential imaging modality for ophthalmology and is proving to be very important in neurology. OCT enables high resolution imaging of the retina, both at the optic nerve head and the macula. Macular retinal layer thicknesses provide useful diagnostic information and have been shown to correlate well with measures of disease severity in several diseases. Since manual segmentation of these layers is time consuming and prone to bias, automatic segmentation methods are critical for full utilization of this technology. In this work, we build a random forest classifier to segment eight retinal layers in macular cube images acquired by OCT. The random forest classifier learns the boundary pixels between layers, producing an accurate probability map for each boundary, which is then processed to finalize the boundaries. Using this algorithm, we can accurately segment the entire retina contained in the macular cube to an accuracy of at least 4.3 microns for any of the nine boundaries. Experiments were carried out on both healthy and multiple sclerosis subjects, with no difference in the accuracy of our algorithm found between the groups. PMID:23847738

Three-dimensional murine airway segmentation in micro-CT images

NASA Astrophysics Data System (ADS)

Shi, Lijun; Thiesse, Jacqueline; McLennan, Geoffrey; Hoffman, Eric A.; Reinhardt, Joseph M.

2007-03-01

Thoracic imaging for small animals has emerged as an important tool for monitoring pulmonary disease progression and therapy response in genetically engineered animals. Micro-CT is becoming the standard thoracic imaging modality in small animal imaging because it can produce high-resolution images of the lung parenchyma, vasculature, and airways. Segmentation, measurement, and visualization of the airway tree is an important step in pulmonary image analysis. However, manual analysis of the airway tree in micro-CT images can be extremely time-consuming since a typical dataset is usually on the order of several gigabytes in size. Automated and semi-automated tools for micro-CT airway analysis are desirable. In this paper, we propose an automatic airway segmentation method for in vivo micro-CT images of the murine lung and validate our method by comparing the automatic results to manual tracing. Our method is based primarily on grayscale morphology. The results show good visual matches between manually segmented and automatically segmented trees. The average true positive volume fraction compared to manual analysis is 91.61%. The overall runtime for the automatic method is on the order of 30 minutes per volume compared to several hours to a few days for manual analysis.

3D knee segmentation based on three MRI sequences from different planes.

PubMed

Zhou, L; Chav, R; Cresson, T; Chartrand, G; de Guise, J

2016-08-01

In clinical practice, knee MRI sequences with 3.5~5 mm slice distance in sagittal, coronal, and axial planes are often requested for the knee examination since its acquisition is faster than high-resolution MRI sequence in a single plane, thereby reducing the probability of motion artifact. In order to take advantage of the three sequences from different planes, a 3D segmentation method based on the combination of three knee models obtained from the three sequences is proposed in this paper. In the method, the sub-segmentation is respectively performed with sagittal, coronal, and axial MRI sequence in the image coordinate system. With each sequence, an initial knee model is hierarchically deformed, and then the three deformed models are mapped to reference coordinate system defined by the DICOM standard and combined to obtain a patient-specific model. The experimental results verified that the three sub-segmentation results can complement each other, and their integration can compensate for the insufficiency of boundary information caused by 3.5~5 mm gap between consecutive slices. Therefore, the obtained patient-specific model is substantially more accurate than each sub-segmentation results.

Development of TlBr detectors for PET imaging.

PubMed

Ariño-Estrada, Gerard; Du, Junwei; Kim, Hadong; Cirignano, Leonard J; Shah, Kanai S; Cherry, Simon R; Mitchell, Gregory S

2018-05-04

Thallium bromide (TlBr) is a promising semiconductor detector material for positron emission tomography (PET) because it can offer very good energy resolution and 3-D segmentation capabilities, and it also provides detection efficiency surpassing that of commonly used scintillators. Energy, timing, and spatial resolution were measured for thin (<1 mm) TlBr detectors. The energy and timing resolution were measured simultaneously for the same planar 0.87 mm-thick TlBr device. An energy resolution of (6.41.3)% at 511 keV was achieved at -400 V bias voltage and at room temperature. A timing resolution of (27.84.1) ns FWHM was achieved for the same operating conditions when appropriate energy gating was applied. The intrinsic spatial resolution was measured to be 0.9 mm FWHM for a TlBr detector with metallic strip contacts of 0.5 mm pitch. As material properties improve, higher bias voltage should improve timing performance. A stack of thin detectors with finely segmented readout can create a modular detector with excellent energy and spatial resolution for PET applications. . © 2018 Institute of Physics and Engineering in Medicine.

Cross-Talk Limits of Highly Segmented Semiconductor Detectors

NASA Astrophysics Data System (ADS)

Pullia, Alberto; Weisshaar, Dirk; Zocca, Francesca; Bazzacco, Dino

2011-06-01

Cross-talk limits of monolithic highly-segmented semiconductor detectors for high-resolution X-gamma spectrometry are investigated. Cross-talk causes false signal components yielding amplitude losses and fold-dependent shifts of the spectral lines, which partially spoil the spectroscopic performance of the detector. Two complementary electrical models are developed, which describe quantitatively the inter-channel cross-talk of monolithic segmented detectors whose electrodes are read out by charge-sensitive preamplifiers. The first is here designated as Cross-Capacitance (CC) model, the second as Split-Charge (SC) model. The CC model builds around the parasitic capacitances Cij linking the preamplifier outputs and the neighbor channel inputs. The SC model builds around the finite-value of the decoupling capacitance CC used to read out the high-voltage detector electrode. The key parameters of the models are individuated and ideas are shown to minimize their impact. Using a quasi-coaxial germanium segmented detector it is found that the SC cross-talk becomes negligible for decoupling capacitances larger than 1 nF, where instead the CC cross-talk tends to dominate. The residual cross-talk may be reduced by minimization of stray capacitances Cij, through a careful design of the layout of the Printed Circuit Board (PCB) where the input transistors are mounted. Cij can be made as low as 5 fF, but it is shown that even in such case the impact of the CC cross-talk on the detector performance is not negligible. Finally, an algorithm for cross-talk correction is presented and elaborated.

Dynamic rupture simulations of the 2016 Mw7.8 Kaikōura earthquake: a cascading multi-fault event

NASA Astrophysics Data System (ADS)

Ulrich, T.; Gabriel, A. A.; Ampuero, J. P.; Xu, W.; Feng, G.

2017-12-01

The Mw7.8 Kaikōura earthquake struck the Northern part of New Zealand's South Island roughly one year ago. It ruptured multiple segments of the contractional North Canterbury fault zone and of the Marlborough fault system. Field observations combined with satellite data suggest a rupture path involving partly unmapped faults separated by large stepover distances larger than 5 km, the maximum distance usually considered by the latest seismic hazard assessment methods. This might imply distant rupture transfer mechanisms generally not considered in seismic hazard assessment. We present high-resolution 3D dynamic rupture simulations of the Kaikōura earthquake under physically self-consistent initial stress and strength conditions. Our simulations are based on recent finite-fault slip inversions that constrain fault system geometry and final slip distribution from remote sensing, surface rupture and geodetic data (Xu et al., 2017). We assume a uniform background stress field, without lateral fault stress or strength heterogeneity. We use the open-source software SeisSol (www.seissol.org) which is based on an arbitrary high-order accurate DERivative Discontinuous Galerkin method (ADER-DG). Our method can account for complex fault geometries, high resolution topography and bathymetry, 3D subsurface structure, off-fault plasticity and modern friction laws. It enables the simulation of seismic wave propagation with high-order accuracy in space and time in complex media. We show that a cascading rupture driven by dynamic triggering can break all fault segments that were involved in this earthquake without mechanically requiring an underlying thrust fault. Our prefered fault geometry connects most fault segments: it does not features stepover larger than 2 km. The best scenario matches the main macroscopic characteristics of the earthquake, including its apparently slow rupture propagation caused by zigzag cascading, the moment magnitude and the overall inferred slip distribution. We observe a high sensitivity of cascading dynamics on fault-step over distance and off-fault energy dissipation.

Automated diagnosis of interstitial lung diseases and emphysema in MDCT imaging

NASA Astrophysics Data System (ADS)

Fetita, Catalin; Chang Chien, Kuang-Che; Brillet, Pierre-Yves; Prêteux, Françoise

2007-09-01

Diffuse lung diseases (DLD) include a heterogeneous group of non-neoplasic disease resulting from damage to the lung parenchyma by varying patterns of inflammation. Characterization and quantification of DLD severity using MDCT, mainly in interstitial lung diseases and emphysema, is an important issue in clinical research for the evaluation of new therapies. This paper develops a 3D automated approach for detection and diagnosis of diffuse lung diseases such as fibrosis/honeycombing, ground glass and emphysema. The proposed methodology combines multi-resolution 3D morphological filtering (exploiting the sup-constrained connection cost operator) and graph-based classification for a full characterization of the parenchymal tissue. The morphological filtering performs a multi-level segmentation of the low- and medium-attenuated lung regions as well as their classification with respect to a granularity criterion (multi-resolution analysis). The original intensity range of the CT data volume is thus reduced in the segmented data to a number of levels equal to the resolution depth used (generally ten levels). The specificity of such morphological filtering is to extract tissue patterns locally contrasting with their neighborhood and of size inferior to the resolution depth, while preserving their original shape. A multi-valued hierarchical graph describing the segmentation result is built-up according to the resolution level and the adjacency of the different segmented components. The graph nodes are then enriched with the textural information carried out by their associated components. A graph analysis-reorganization based on the nodes attributes delivers the final classification of the lung parenchyma in normal and ILD/emphysematous regions. It also makes possible to discriminate between different types, or development stages, among the same class of diseases.

Concealed object segmentation and three-dimensional localization with passive millimeter-wave imaging

NASA Astrophysics Data System (ADS)

Yeom, Seokwon

2013-05-01

Millimeter waves imaging draws increasing attention in security applications for weapon detection under clothing. In this paper, concealed object segmentation and three-dimensional localization schemes are reviewed. A concealed object is segmented by the k-means algorithm. A feature-based stereo-matching method estimates the longitudinal distance of the concealed object. The distance is estimated by the discrepancy between the corresponding centers of the segmented objects. Experimental results are provided with the analysis of the depth resolution.

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.

Modeling Stokes flow in real pore geometries derived by high resolution micro CT imaging

NASA Astrophysics Data System (ADS)

Halisch, M.; Müller, C.

2012-04-01

Meanwhile, numerical modeling of rock properties forms an important part of modern petrophysics. Substantially, equivalent rock models are used to describe and assess specific properties and phenomena, like fluid transport or complex electrical properties. In recent years, non-destructive computed X-ray tomography got more and more important - not only to take a quick and three dimensional look into rock samples but also to get access to in-situ sample information for highly accurate modeling purposes. Due to - by now - very high resolution of the 3D CT data sets (micron- to submicron range) also very small structures and sample features - e.g. micro porosity - can be visualized and used for numerical models of very high accuracy. Special demands even arise before numerical modeling can take place. Inappropriate filter applications (e.g. improper type of filter, wrong kernel, etc.) may lead to a significant corruption of spatial sample structure and / or even sample or void space volume. Because of these difficulties, especially small scale mineral- and pore space textures are very often lost and valuable in-situ information is erased. Segmentation of important sample features - porosity as well as rock matrix - based upon grayscale values strongly depends upon the scan quality and upon the experience of the application engineer, respectively. If the threshold for matrix-porosity separation is set too low, porosity can be quickly (and even more, due to restrictions of scanning resolution) underestimated. Contrary to this, a too high threshold over-determines porosity and small void space features as well as interfaces are changed and falsified. Image based phase separation in close combination with "conventional" analytics, as scanning electron microscopy or thin sectioning, greatly increase the reliability of this preliminary work. For segmentation and quantification purposes, a special CT imaging and processing software (Avizo Fire) has been used. By using this tool, 3D rock data can be assessed and interpreted by petrophysical means. Furthermore, pore structures can be directly segmented and hence could be used for so called image based modeling approach. The special XLabHydro module grants a finite volume solver for the direct assessment of Stokes flow (incompressible fluid, constant dynamic viscosity, stationary conditions and laminar flow) in real pore geometries. Nevertheless, also pore network extraction and numerical modeling with standard FE or lattice Boltzmann solvers is possible. By using the achieved voxel resolution as smallest node distance, fluid flow properties can be analyzed even in very small sample structures and hence with very high accuracy, especially with interaction to bigger parts of the pore network. The so derived results in combination with a direct 3D visualization within the structures offer great new insights and understanding in range of meso- and microscopic pore space phenomena.

Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography.

PubMed

Ahlers, C; Simader, C; Geitzenauer, W; Stock, G; Stetson, P; Dastmalchi, S; Schmidt-Erfurth, U

2008-02-01

A limited number of scans compromise conventional optical coherence tomography (OCT) to track chorioretinal disease in its full extension. Failures in edge-detection algorithms falsify the results of retinal mapping even further. High-definition-OCT (HD-OCT) is based on raster scanning and was used to visualise the localisation and volume of intra- and sub-pigment-epithelial (RPE) changes in fibrovascular pigment epithelial detachments (fPED). Two different scanning patterns were evaluated. 22 eyes with fPED were imaged using a frequency-domain, high-speed prototype of the Cirrus HD-OCT. The axial resolution was 6 mum, and the scanning speed was 25 kA scans/s. Two different scanning patterns covering an area of 6 x 6 mm in the macular retina were compared. Three-dimensional topographic reconstructions and volume calculations were performed using MATLAB-based automatic segmentation software. Detailed information about layer-specific distribution of fluid accumulation and volumetric measurements can be obtained for retinal- and sub-RPE volumes. Both raster scans show a high correlation (p<0.01; R2>0.89) of measured values, that is PED volume/area, retinal volume and mean retinal thickness. Quality control of the automatic segmentation revealed reasonable results in over 90% of the examinations. Automatic segmentation allows for detailed quantitative and topographic analysis of the RPE and the overlying retina. In fPED, the 128 x 512 scanning-pattern shows mild advantages when compared with the 256 x 256 scan. Together with the ability for automatic segmentation, HD-OCT clearly improves the clinical monitoring of chorioretinal disease by adding relevant new parameters. HD-OCT is likely capable of enhancing the understanding of pathophysiology and benefits of treatment for current anti-CNV strategies in future.

Improving left ventricular segmentation in four-dimensional flow MRI using intramodality image registration for cardiac blood flow analysis.

PubMed

Gupta, Vikas; Bustamante, Mariana; Fredriksson, Alexandru; Carlhäll, Carl-Johan; Ebbers, Tino

2018-01-01

Assessment of blood flow in the left ventricle using four-dimensional flow MRI requires accurate left ventricle segmentation that is often hampered by the low contrast between blood and the myocardium. The purpose of this work is to improve left-ventricular segmentation in four-dimensional flow MRI for reliable blood flow analysis. The left ventricle segmentations are first obtained using morphological cine-MRI with better in-plane resolution and contrast, and then aligned to four-dimensional flow MRI data. This alignment is, however, not trivial due to inter-slice misalignment errors caused by patient motion and respiratory drift during breath-hold based cine-MRI acquisition. A robust image registration based framework is proposed to mitigate such errors automatically. Data from 20 subjects, including healthy volunteers and patients, was used to evaluate its geometric accuracy and impact on blood flow analysis. High spatial correspondence was observed between manually and automatically aligned segmentations, and the improvements in alignment compared to uncorrected segmentations were significant (P < 0.01). Blood flow analysis from manual and automatically corrected segmentations did not differ significantly (P > 0.05). Our results demonstrate the efficacy of the proposed approach in improving left-ventricular segmentation in four-dimensional flow MRI, and its potential for reliable blood flow analysis. Magn Reson Med 79:554-560, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Integration of Sparse Multi-modality Representation and Anatomical Constraint for Isointense Infant Brain MR Image Segmentation

PubMed Central

Wang, Li; Shi, Feng; Gao, Yaozong; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to poor spatial resolution, severe partial volume effect, and the ongoing maturation and myelination process. During the first year of life, the brain image contrast between white and gray matters undergoes dramatic changes. In particular, the image contrast inverses around 6–8 months of age, where the white and gray matter tissues are isointense in T1 and T2 weighted images and hence exhibit the extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a general framework that adopts sparse representation to fuse the multi-modality image information and further incorporate the anatomical constraints for brain tissue segmentation. Specifically, we first derive an initial segmentation from a library of aligned images with ground-truth segmentations by using sparse representation in a patch-based fashion for the multi-modality T1, T2 and FA images. The segmentation result is further iteratively refined by integration of the anatomical constraint. The proposed method was evaluated on 22 infant brain MR images acquired at around 6 months of age by using a leave-one-out cross-validation, as well as other 10 unseen testing subjects. Our method achieved a high accuracy for the Dice ratios that measure the volume overlap between automated and manual segmentations, i.e., 0.889±0.008 for white matter and 0.870±0.006 for gray matter. PMID:24291615

TerraSAR-X mission

NASA Astrophysics Data System (ADS)

Werninghaus, Rolf

2004-01-01

The TerraSAR-X is a German national SAR- satellite system for scientific and commercial applications. It is the continuation of the scientifically and technologically successful radar missions X-SAR (1994) and SRTM (2000) and will bring the national technology developments DESA and TOPAS into operational use. The space segment of TerraSAR-X is an advanced high-resolution X-Band radar satellite. The system design is based on a sound market analysis performed by Infoterra. The TerraSAR-X features an advanced high-resolution X-Band Synthetic Aperture Radar based on the active phased array technology which allows the operation in Spotlight-, Stripmap- and ScanSAR Mode with various polarizations. It combines the ability to acquire high resolution images for detailed analysis as well as wide swath images for overview applications. In addition, experimental modes like the Dual Receive Antenna Mode allow for full-polarimetric imaging as well as along track interferometry, i.e. moving target identification. The Ground Segment is optimized for flexible response to (scientific and commercial) User requests and fast image product turn-around times. The TerraSAR-X mission will serve two main goals. The first goal is to provide the strongly supportive scientific community with multi-mode X-Band SAR data. The broad spectrum of scientific application areas include Hydrology, Geology, Climatology, Oceanography, Environmental Monitoring and Disaster Monitoring as well as Cartography (DEM Generation) and Interferometry. The second goal is the establishment of a commercial EO-market in Europe which is driven by Infoterra. The commercial goal is the development of a sustainable EO-business so that the e.g. follow-on systems can be completely financed by industry from the profit. Due to its commercial potential, the TerraSAR-X project will be implemented based on a public-private partnership with the Astrium GmbH. This paper will describe first the mission objectives as well as the project organisation and major milestones. Then an overview on the satellite as well as the SAR instrument is given followed by a description of the system design. Finally the principle layout of the TerraSAR-X Ground Segment and some remarks on the European context are presented.

Changepoint detection in base-resolution methylome data reveals a robust signature of methylated domain landscape.

PubMed

Yokoyama, Takao; Miura, Fumihito; Araki, Hiromitsu; Okamura, Kohji; Ito, Takashi

2015-08-12

Base-resolution methylome data generated by whole-genome bisulfite sequencing (WGBS) is often used to segment the genome into domains with distinct methylation levels. However, most segmentation methods include many parameters to be carefully tuned and/or fail to exploit the unsurpassed resolution of the data. Furthermore, there is no simple method that displays the composition of the domains to grasp global trends in each methylome. We propose to use changepoint detection for domain demarcation based on base-resolution methylome data. While the proposed method segments the methylome in a largely comparable manner to conventional approaches, it has only a single parameter to be tuned. Furthermore, it fully exploits the base-resolution of the data to enable simultaneous detection of methylation changes in even contrasting size ranges, such as focal hypermethylation and global hypomethylation in cancer methylomes. We also propose a simple plot termed methylated domain landscape (MDL) that globally displays the size, the methylation level and the number of the domains thus defined, thereby enabling one to intuitively grasp trends in each methylome. Since the pattern of MDL often reflects cell lineages and is largely unaffected by data size, it can serve as a novel signature of methylome. Changepoint detection in base-resolution methylome data followed by MDL plotting provides a novel method for methylome characterization and will facilitate global comparison among various WGBS data differing in size and even species origin.

Automatic 3D segmentation of spinal cord MRI using propagated deformable models

NASA Astrophysics Data System (ADS)

De Leener, B.; Cohen-Adad, J.; Kadoury, S.

2014-03-01

Spinal cord diseases or injuries can cause dysfunction of the sensory and locomotor systems. Segmentation of the spinal cord provides measures of atrophy and allows group analysis of multi-parametric MRI via inter-subject registration to a template. All these measures were shown to improve diagnostic and surgical intervention. We developed a framework to automatically segment the spinal cord on T2-weighted MR images, based on the propagation of a deformable model. The algorithm is divided into three parts: first, an initialization step detects the spinal cord position and orientation by using the elliptical Hough transform on multiple adjacent axial slices to produce an initial tubular mesh. Second, a low-resolution deformable model is iteratively propagated along the spinal cord. To deal with highly variable contrast levels between the spinal cord and the cerebrospinal fluid, the deformation is coupled with a contrast adaptation at each iteration. Third, a refinement process and a global deformation are applied on the low-resolution mesh to provide an accurate segmentation of the spinal cord. Our method was evaluated against a semi-automatic edge-based snake method implemented in ITK-SNAP (with heavy manual adjustment) by computing the 3D Dice coefficient, mean and maximum distance errors. Accuracy and robustness were assessed from 8 healthy subjects. Each subject had two volumes: one at the cervical and one at the thoracolumbar region. Results show a precision of 0.30 +/- 0.05 mm (mean absolute distance error) in the cervical region and 0.27 +/- 0.06 mm in the thoracolumbar region. The 3D Dice coefficient was of 0.93 for both regions.

[An object-oriented remote sensing image segmentation approach based on edge detection].

PubMed

Tan, Yu-Min; Huai, Jian-Zhu; Tang, Zhong-Shi

2010-06-01

Satellite sensor technology endorsed better discrimination of various landscape objects. Image segmentation approaches to extracting conceptual objects and patterns hence have been explored and a wide variety of such algorithms abound. To this end, in order to effectively utilize edge and topological information in high resolution remote sensing imagery, an object-oriented algorithm combining edge detection and region merging is proposed. Susan edge filter is firstly applied to the panchromatic band of Quickbird imagery with spatial resolution of 0.61 m to obtain the edge map. Thanks to the resulting edge map, a two-phrase region-based segmentation method operates on the fusion image from panchromatic and multispectral Quickbird images to get the final partition result. In the first phase, a quad tree grid consisting of squares with sides parallel to the image left and top borders agglomerates the square subsets recursively where the uniform measure is satisfied to derive image object primitives. Before the merger of the second phrase, the contextual and spatial information, (e. g., neighbor relationship, boundary coding) of the resulting squares are retrieved efficiently by means of the quad tree structure. Then a region merging operation is performed with those primitives, during which the criterion for region merging integrates edge map and region-based features. This approach has been tested on the QuickBird images of some site in Sanxia area and the result is compared with those of ENVI Zoom Definiens. In addition, quantitative evaluation of the quality of segmentation results is also presented. Experiment results demonstrate stable convergence and efficiency.

Inner Segment Remodeling and Mitochondrial Translocation in Cone Photoreceptors in Age-Related Macular Degeneration With Outer Retinal Tubulation.

PubMed

Litts, Katie M; Messinger, Jeffrey D; Freund, K Bailey; Zhang, Yuhua; Curcio, Christine A

2015-04-01

To quantify impressions of mitochondrial translocation in degenerating cones and to determine the nature of accumulated material in the subretinal space with apparent inner segment (IS)-like features by examining cone IS ultrastructure. Human donor eyes with advanced age-related macular degeneration (AMD) were screened for outer retinal tubulation (ORT) in macula-wide, high-resolution digital sections. Degenerating cones inside ORT (ORT cones) and outside ORT (non-ORT cones) from AMD eyes and unaffected cones in age-matched control eyes were imaged using transmission electron microscopy. The distances of mitochondria to the external limiting membrane (ELM), cone IS length, and cone IS width at the ELM were measured. Outer retinal tubulation and non-ORT cones lose outer segments (OS), followed by shortening of IS and mitochondria. In non-ORT cones, IS broaden. Outer retinal tubulation and non-ORT cone IS myoids become undetectable due to mitochondria redistribution toward the nucleus. Some ORT cones were found lacking IS and containing mitochondria in the outer fiber (between soma and ELM). Unlike long, thin IS mitochondria in control cones, ORT and non-ORT IS mitochondria are ovoid or reniform. Shed IS, some containing mitochondria, were found in the subretinal space. In AMD, macula cones exhibit loss of detectable myoid due to IS shortening in addition to OS loss, as described. Mitochondria shrink and translocate toward the nucleus. As reflectivity sources, translocating mitochondria may be detectable using in vivo imaging to monitor photoreceptor degeneration in retinal disorders. These results improve the knowledge basis for interpreting high-resolution clinical retinal imaging.

DR HAGIS-a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients.

PubMed

Holm, Sven; Russell, Greg; Nourrit, Vincent; McLoughlin, Niall

2017-01-01

A database of retinal fundus images, the DR HAGIS database, is presented. This database consists of 39 high-resolution color fundus images obtained from a diabetic retinopathy screening program in the UK. The NHS screening program uses service providers that employ different fundus and digital cameras. This results in a range of different image sizes and resolutions. Furthermore, patients enrolled in such programs often display other comorbidities in addition to diabetes. Therefore, in an effort to replicate the normal range of images examined by grading experts during screening, the DR HAGIS database consists of images of varying image sizes and resolutions and four comorbidity subgroups: collectively defined as the diabetic retinopathy, hypertension, age-related macular degeneration, and Glaucoma image set (DR HAGIS). For each image, the vasculature has been manually segmented to provide a realistic set of images on which to test automatic vessel extraction algorithms. Modified versions of two previously published vessel extraction algorithms were applied to this database to provide some baseline measurements. A method based purely on the intensity of images pixels resulted in a mean segmentation accuracy of 95.83% ([Formula: see text]), whereas an algorithm based on Gabor filters generated an accuracy of 95.71% ([Formula: see text]).

Recent Progress in Adjustable X-ray Optics for Astronomy

NASA Technical Reports Server (NTRS)

Reid, Paul B.; Allured, Ryan; Cotroneo, Vincenzo; McMuldroch, Stuart; Marquez, Vanessa; Schwartz, Daniel A.; Vikhlinin, Alexey; ODell, Stephen L.; Ramsey, Brian; Trolier-McKinstry, Susan;

Calibration of large area Micromegas detectors using cosmic rays

NASA Astrophysics Data System (ADS)

Biebel, O.; Flierl, B.; Herrmann, M.; Hertenberger, R.; Klitzner, F.; Lösel, P.; Müller, R.; Valderanis, C.; Zibell, A.

2017-06-01

Currently m2-sized micropattern detectors with spatial resolution better than 100 μm and online trigger capability are of big interest for many experiments. Large size in combination with superb spatial resolution and trigger capability implicates that the construction of these detectors is highly sophisticated and imposes strict mechanical tolerances. We developed a method to survey assembled and working detectors on potential deviations of the micro pattern readout structures from design value as well as deformations of the whole detector, using cosmic muons in a tracking facility. The LMU Cosmic Ray Facility consists of two 8 m2 ATLAS Monitored Drift Tube chambers (MDT) for precision muon reference tracking and two segmented trigger hodoscopes with sub-ns time-resolution and additional 10 cm position information along the wires of the MDTs. It provides information on homogeneity in efficiency and pulse height of one or several micropattern detectors installed in between the MDTs. With an angular acceptance of -30° to +30° the comparison of the reference muon tracking with centroidal position determination or time projection chamber like track reconstruction in the micropattern detector allows for calibration in three dimensions. We present results of a m2-sized one-dimensional resistive strip Micromegas detector consisting of two readout boards with in total 2048 strips, read out by 16 APV25 front-end boards. This 16-fold segmentation along the precision direction in combination with a 10-fold segmentation in orthogonal direction by the resolution of the trigger hodoscope, allows for very detailed analysis of the 1 m2 detector under study by subdivision into 160 partitions, each being analyzed separately. We are able to disentangle deviations from the readout strip straightness and global deformation due to the small overpressure caused by the Ar:CO2 (93:7) gas mixture flux. We introduce the alignment and calibration procedure, report on homogeneity in efficiency and pulse height and present results on deformation and performance of the m2-sized Micromegas.

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

PubMed

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

2015-08-01

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

Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy

NASA Astrophysics Data System (ADS)

Plassard, Andrew J.; McHugo, Maureen; Heckers, Stephan; Landman, Bennett A.

2017-02-01

Known for its distinct role in memory, the hippocampus is one of the most studied regions of the brain. Recent advances in magnetic resonance imaging have allowed for high-contrast, reproducible imaging of the hippocampus. Typically, a trained rater takes 45 minutes to manually trace the hippocampus and delineate the anterior from the posterior segment at millimeter resolution. As a result, there has been a significant desire for automated and robust segmentation of the hippocampus. In this work we use a population of 195 atlases based on T1-weighted MR images with the left and right hippocampus delineated into the head and body. We initialize the multi-atlas segmentation to a region directly around each lateralized hippocampus to both speed up and improve the accuracy of registration. This initialization allows for incorporation of nearly 200 atlases, an accomplishment which would typically involve hundreds of hours of computation per target image. The proposed segmentation results in a Dice similiarity coefficient over 0.9 for the full hippocampus. This result outperforms a multi-atlas segmentation using the BrainCOLOR atlases (Dice 0.85) and FreeSurfer (Dice 0.75). Furthermore, the head and body delineation resulted in a Dice coefficient over 0.87 for both structures. The head and body volume measurements also show high reproducibility on the Kirby 21 reproducibility population (R2 greater than 0.95, p < 0.05 for all structures). This work signifies the first result in an ongoing work to develop a robust tool for measurement of the hippocampus and other temporal lobe structures.

Image Segmentation, Registration, Compression, and Matching

NASA Technical Reports Server (NTRS)

Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

2011-01-01

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Quantification of photoreceptor layer thickness in different macular pathologies using ultrahigh-resolution optical coherence tomography

NASA Astrophysics Data System (ADS)

Drexler, Wolfgang; Hermann, Boris; Unterhuber, Angelika; Sattmann, Harald; Wirtitsch, Matthias; Stur, Michael; Scholda, Christoph; Ergun, Erdem; Anger, Elisabeth; Ko, Tony H.; Schubert, Christian; Ahnelt, Peter K.; Fujimoto, James G.; Fercher, Adolf F.

2004-07-01

In vivo ultrahigh resolution ophthalmic OCT has been performed in more than 300 eyes of 200 patients with several retinal pathologies, demonstrating unprecedented visualization of all major intraretinal layers, in particular the photoreceptor layer. Visualization as well as quantification of the inner and outer segment of the photoreceptor layer especially in the foveal region has been acvhieved. In normal subjects the photoreceptor layer thickness in the center of the fovea is about of 90 μm, approximately equally distributed to the inner and the outer photoreceptor segment. In the parafoveal region this thickness is reduced to ~50 μm (~30 μm for the inner and ~20 μm for the outer segment). This is in good agreement with well known increase of cone outer segments in the central foveal region. Photoreceptor layer impairment in different macular pathologies like macular hole, central serous chorioretinopathy, age related macular degeneration, foveomacular dystrophies, Stargardt dystrophy as well as retinitis pigmentosa has been investigated. Photoreceptor layer loss significantly correlated with visual acuity (R2 = 0.6, p < 0.001) and microperimetry findings for the first time in 22 eyes with Stargardt dystrophy. Visualization and quantification of photoreceptor inner and outer segment using ultrahigh resolution OCT has the potential to improve early ophthalmic diagnosis, contributes to a better understanding of pathogenesis of retinal diseases as well as might have impact in the development and monitoring of novel therapy approaches.

Sub-diffraction Limit Localization of Proteins in Volumetric Space Using Bayesian Restoration of Fluorescence Images from Ultrathin Specimens

PubMed Central

Wang, Gordon; Smith, Stephen J.

2012-01-01

Photon diffraction limits the resolution of conventional light microscopy at the lateral focal plane to 0.61λ/NA (λ = wavelength of light, NA = numerical aperture of the objective) and at the axial plane to 1.4nλ/NA2 (n = refractive index of the imaging medium, 1.51 for oil immersion), which with visible wavelengths and a 1.4NA oil immersion objective is ∼220 nm and ∼600 nm in the lateral plane and axial plane respectively. This volumetric resolution is too large for the proper localization of protein clustering in subcellular structures. Here we combine the newly developed proteomic imaging technique, Array Tomography (AT), with its native 50–100 nm axial resolution achieved by physical sectioning of resin embedded tissue, and a 2D maximum likelihood deconvolution method, based on Bayes' rule, which significantly improves the resolution of protein puncta in the lateral plane to allow accurate and fast computational segmentation and analysis of labeled proteins. The physical sectioning of AT allows tissue specimens to be imaged at the physical optimum of modern high NA plan-apochormatic objectives. This translates to images that have little out of focus light, minimal aberrations and wave-front distortions. Thus, AT is able to provide images with truly invariant point spread functions (PSF), a property critical for accurate deconvolution. We show that AT with deconvolution increases the volumetric analytical fidelity of protein localization by significantly improving the modulation of high spatial frequencies up to and potentially beyond the spatial frequency cut-off of the objective. Moreover, we are able to achieve this improvement with no noticeable introduction of noise or artifacts and arrive at object segmentation and localization accuracies on par with image volumes captured using commercial implementations of super-resolution microscopes. PMID:22956902

Sub-diffraction limit localization of proteins in volumetric space using Bayesian restoration of fluorescence images from ultrathin specimens.

PubMed

Wang, Gordon; Smith, Stephen J

2012-01-01

Photon diffraction limits the resolution of conventional light microscopy at the lateral focal plane to 0.61λ/NA (λ = wavelength of light, NA = numerical aperture of the objective) and at the axial plane to 1.4nλ/NA(2) (n = refractive index of the imaging medium, 1.51 for oil immersion), which with visible wavelengths and a 1.4NA oil immersion objective is -220 nm and -600 nm in the lateral plane and axial plane respectively. This volumetric resolution is too large for the proper localization of protein clustering in subcellular structures. Here we combine the newly developed proteomic imaging technique, Array Tomography (AT), with its native 50-100 nm axial resolution achieved by physical sectioning of resin embedded tissue, and a 2D maximum likelihood deconvolution method, based on Bayes' rule, which significantly improves the resolution of protein puncta in the lateral plane to allow accurate and fast computational segmentation and analysis of labeled proteins. The physical sectioning of AT allows tissue specimens to be imaged at the physical optimum of modern high NA plan-apochormatic objectives. This translates to images that have little out of focus light, minimal aberrations and wave-front distortions. Thus, AT is able to provide images with truly invariant point spread functions (PSF), a property critical for accurate deconvolution. We show that AT with deconvolution increases the volumetric analytical fidelity of protein localization by significantly improving the modulation of high spatial frequencies up to and potentially beyond the spatial frequency cut-off of the objective. Moreover, we are able to achieve this improvement with no noticeable introduction of noise or artifacts and arrive at object segmentation and localization accuracies on par with image volumes captured using commercial implementations of super-resolution microscopes.

Asymmetric histone modifications between the original and derived loci of human segmental duplications

PubMed Central

Zheng, Deyou

2008-01-01

Background Sequencing and annotation of several mammalian genomes have revealed that segmental duplications are a common architectural feature of primate genomes; in fact, about 5% of the human genome is composed of large blocks of interspersed segmental duplications. These segmental duplications have been implicated in genomic copy-number variation, gene novelty, and various genomic disorders. However, the molecular processes involved in the evolution and regulation of duplicated sequences remain largely unexplored. Results In this study, the profile of about 20 histone modifications within human segmental duplications was characterized using high-resolution, genome-wide data derived from a ChIP-Seq study. The analysis demonstrates that derivative loci of segmental duplications often differ significantly from the original with respect to many histone methylations. Further investigation showed that genes are present three times more frequently in the original than in the derivative, whereas pseudogenes exhibit the opposite trend. These asymmetries tend to increase with the age of segmental duplications. The uneven distribution of genes and pseudogenes does not, however, fully account for the asymmetry in the profile of histone modifications. Conclusion The first systematic analysis of histone modifications between segmental duplications demonstrates that two seemingly 'identical' genomic copies are distinct in their epigenomic properties. Results here suggest that local chromatin environments may be implicated in the discrimination of derived copies of segmental duplications from their originals, leading to a biased pseudogenization of the new duplicates. The data also indicate that further exploration of the interactions between histone modification and sequence degeneration is necessary in order to understand the divergence of duplicated sequences. PMID:18598352

Coating Thin Mirror Segments for Lightweight X-ray Optics

NASA Technical Reports Server (NTRS)

Chan, Kai-Wing; Sharpe, Marton V.; Zhang, William; Kolosc, Linette; Hong, Melinda; McClelland, Ryan; Hohl, Bruce R.; Saha, Timo; Mazzarellam, James

2013-01-01

Next generations lightweight, high resolution, high throughput optics for x-ray astronomy requires integration of very thin mirror segments into a lightweight telescope housing without distortion. Thin glass substrates with linear dimension of 200 mm and thickness as small as 0.4 mm can now be fabricated to a precision of a few arc-seconds for grazing incidence optics. Subsequent implementation requires a distortion-free deposition of metals such as iridium or platinum. These depositions, however, generally have high coating stresses that cause mirror distortion. In this paper, we discuss the coating stress on these thin glass mirrors and the effort to eliminate their induced distortion. It is shown that balancing the coating distortion either by coating films with tensile and compressive stresses, or on both sides of the mirrors is not sufficient. Heating the mirror in a moderately high temperature turns out to relax the coated films reasonably well to a precision of about a second of arc and therefore provide a practical solution to the coating problem.

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

USGS Publications Warehouse

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

2016-01-01

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

Optical coherence tomography in anterior segment imaging

PubMed Central

Kalev-Landoy, Maya; Day, Alexander C.; Cordeiro, M. Francesca; Migdal, Clive

2008-01-01

Purpose To evaluate the ability of optical coherence tomography (OCT), designed primarily to image the posterior segment, to visualize the anterior chamber angle (ACA) in patients with different angle configurations. Methods In a prospective observational study, the anterior segments of 26 eyes of 26 patients were imaged using the Zeiss Stratus OCT, model 3000. Imaging of the anterior segment was achieved by adjusting the focusing control on the Stratus OCT. A total of 16 patients had abnormal angle configurations including narrow or closed angles and plateau irides, and 10 had normal angle configurations as determined by prior full ophthalmic examination, including slit-lamp biomicroscopy and gonioscopy. Results In all cases, OCT provided high-resolution information regarding iris configuration. The ACA itself was clearly visualized in patients with narrow or closed angles, but not in patients with open angles. Conclusions Stratus OCT offers a non-contact, convenient and rapid method of assessing the configuration of the anterior chamber. Despite its limitations, it may be of help during the routine clinical assessment and treatment of patients with glaucoma, particularly when gonioscopy is not possible or difficult to interpret. PMID:17355288

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Nucleus segmentation in histology images with hierarchical multilevel thresholding

NASA Astrophysics Data System (ADS)

Ahmady Phoulady, Hady; Goldgof, Dmitry B.; Hall, Lawrence O.; Mouton, Peter R.

2016-03-01

Automatic segmentation of histological images is an important step for increasing throughput while maintaining high accuracy, avoiding variation from subjective bias, and reducing the costs for diagnosing human illnesses such as cancer and Alzheimer's disease. In this paper, we present a novel method for unsupervised segmentation of cell nuclei in stained histology tissue. Following an initial preprocessing step involving color deconvolution and image reconstruction, the segmentation step consists of multilevel thresholding and a series of morphological operations. The only parameter required for the method is the minimum region size, which is set according to the resolution of the image. Hence, the proposed method requires no training sets or parameter learning. Because the algorithm requires no assumptions or a priori information with regard to cell morphology, the automatic approach is generalizable across a wide range of tissues. Evaluation across a dataset consisting of diverse tissues, including breast, liver, gastric mucosa and bone marrow, shows superior performance over four other recent methods on the same dataset in terms of F-measure with precision and recall of 0.929 and 0.886, respectively.

Segment fusion of ToF-SIMS images.

PubMed

Milillo, Tammy M; Miller, Mary E; Fischione, Remo; Montes, Angelina; Gardella, Joseph A

2016-06-08

The imaging capabilities of time-of-flight secondary ion mass spectrometry (ToF-SIMS) have not been used to their full potential in the analysis of polymer and biological samples. Imaging has been limited by the size of the dataset and the chemical complexity of the sample being imaged. Pixel and segment based image fusion algorithms commonly used in remote sensing, ecology, geography, and geology provide a way to improve spatial resolution and classification of biological images. In this study, a sample of Arabidopsis thaliana was treated with silver nanoparticles and imaged with ToF-SIMS. These images provide insight into the uptake mechanism for the silver nanoparticles into the plant tissue, giving new understanding to the mechanism of uptake of heavy metals in the environment. The Munechika algorithm was programmed in-house and applied to achieve pixel based fusion, which improved the spatial resolution of the image obtained. Multispectral and quadtree segment or region based fusion algorithms were performed using ecognition software, a commercially available remote sensing software suite, and used to classify the images. The Munechika fusion improved the spatial resolution for the images containing silver nanoparticles, while the segment fusion allowed classification and fusion based on the tissue types in the sample, suggesting potential pathways for the uptake of the silver nanoparticles.

Subcortical brain segmentation of two dimensional T1-weighted data sets with FMRIB's Integrated Registration and Segmentation Tool (FIRST).

PubMed

Amann, Michael; Andělová, Michaela; Pfister, Armanda; Mueller-Lenke, Nicole; Traud, Stefan; Reinhardt, Julia; Magon, Stefano; Bendfeldt, Kerstin; Kappos, Ludwig; Radue, Ernst-Wilhelm; Stippich, Christoph; Sprenger, Till

2015-01-01

Brain atrophy has been identified as an important contributing factor to the development of disability in multiple sclerosis (MS). In this respect, more and more interest is focussing on the role of deep grey matter (DGM) areas. Novel data analysis pipelines are available for the automatic segmentation of DGM using three-dimensional (3D) MRI data. However, in clinical trials, often no such high-resolution data are acquired and hence no conclusions regarding the impact of new treatments on DGM atrophy were possible so far. In this work, we used FMRIB's Integrated Registration and Segmentation Tool (FIRST) to evaluate the possibility of segmenting DGM structures using standard two-dimensional (2D) T1-weighted MRI. In a cohort of 70 MS patients, both 2D and 3D T1-weighted data were acquired. The thalamus, putamen, pallidum, nucleus accumbens, and caudate nucleus were bilaterally segmented using FIRST. Volumes were calculated for each structure and for the sum of basal ganglia (BG) as well as for the total DGM. The accuracy and reliability of the 2D data segmentation were compared with the respective results of 3D segmentations using volume difference, volume overlap and intra-class correlation coefficients (ICCs). The mean differences for the individual substructures were between 1.3% (putamen) and -25.2% (nucleus accumbens). The respective values for the BG were -2.7% and for DGM 1.3%. Mean volume overlap was between 89.1% (thalamus) and 61.5% (nucleus accumbens); BG: 84.1%; DGM: 86.3%. Regarding ICC, all structures showed good agreement with the exception of the nucleus accumbens. The results of the segmentation were additionally validated through expert manual delineation of the caudate nucleus and putamen in a subset of the 3D data. In conclusion, we demonstrate that subcortical segmentation of 2D data are feasible using FIRST. The larger subcortical GM structures can be segmented with high consistency. This forms the basis for the application of FIRST in large 2D MRI data sets of clinical trials in order to determine the impact of therapeutic interventions on DGM atrophy in MS.

Automatic reconstruction of fault networks from seismicity catalogs: Three-dimensional optimal anisotropic dynamic clustering

NASA Astrophysics Data System (ADS)

Ouillon, G.; Ducorbier, C.; Sornette, D.

2008-01-01

We propose a new pattern recognition method that is able to reconstruct the three-dimensional structure of the active part of a fault network using the spatial location of earthquakes. The method is a generalization of the so-called dynamic clustering (or k means) method, that partitions a set of data points into clusters, using a global minimization criterion of the variance of the hypocenters locations about their center of mass. The new method improves on the original k means method by taking into account the full spatial covariance tensor of each cluster in order to partition the data set into fault-like, anisotropic clusters. Given a catalog of seismic events, the output is the optimal set of plane segments that fits the spatial structure of the data. Each plane segment is fully characterized by its location, size, and orientation. The main tunable parameter is the accuracy of the earthquake locations, which fixes the resolution, i.e., the residual variance of the fit. The resolution determines the number of fault segments needed to describe the earthquake catalog: the better the resolution, the finer the structure of the reconstructed fault segments. The algorithm successfully reconstructs the fault segments of synthetic earthquake catalogs. Applied to the real catalog constituted of a subset of the aftershock sequence of the 28 June 1992 Landers earthquake in southern California, the reconstructed plane segments fully agree with faults already known on geological maps or with blind faults that appear quite obvious in longer-term catalogs. Future improvements of the method are discussed, as well as its potential use in the multiscale study of the inner structure of fault zones.

CMEIAS color segmentation: an improved computing technology to process color images for quantitative microbial ecology studies at single-cell resolution.

PubMed

Gross, Colin A; Reddy, Chandan K; Dazzo, Frank B

2010-02-01

Quantitative microscopy and digital image analysis are underutilized in microbial ecology largely because of the laborious task to segment foreground object pixels from background, especially in complex color micrographs of environmental samples. In this paper, we describe an improved computing technology developed to alleviate this limitation. The system's uniqueness is its ability to edit digital images accurately when presented with the difficult yet commonplace challenge of removing background pixels whose three-dimensional color space overlaps the range that defines foreground objects. Image segmentation is accomplished by utilizing algorithms that address color and spatial relationships of user-selected foreground object pixels. Performance of the color segmentation algorithm evaluated on 26 complex micrographs at single pixel resolution had an overall pixel classification accuracy of 99+%. Several applications illustrate how this improved computing technology can successfully resolve numerous challenges of complex color segmentation in order to produce images from which quantitative information can be accurately extracted, thereby gain new perspectives on the in situ ecology of microorganisms. Examples include improvements in the quantitative analysis of (1) microbial abundance and phylotype diversity of single cells classified by their discriminating color within heterogeneous communities, (2) cell viability, (3) spatial relationships and intensity of bacterial gene expression involved in cellular communication between individual cells within rhizoplane biofilms, and (4) biofilm ecophysiology based on ribotype-differentiated radioactive substrate utilization. The stand-alone executable file plus user manual and tutorial images for this color segmentation computing application are freely available at http://cme.msu.edu/cmeias/ . This improved computing technology opens new opportunities of imaging applications where discriminating colors really matter most, thereby strengthening quantitative microscopy-based approaches to advance microbial ecology in situ at individual single-cell resolution.

Temporal and spatial resolution required for imaging myocardial function

NASA Astrophysics Data System (ADS)

Eusemann, Christian D.; Robb, Richard A.

2004-05-01

4-D functional analysis of myocardial mechanics is an area of significant interest and research in cardiology and vascular/interventional radiology. Current multidimensional analysis is limited by insufficient temporal resolution of x-ray and magnetic resonance based techniques, but recent improvements in system design holds hope for faster and higher resolution scans to improve images of moving structures allowing more accurate functional studies, such as in the heart. This paper provides a basis for the requisite temporal and spatial resolution for useful imaging during individual segments of the cardiac cycle. Multiple sample rates during systole and diastole are compared to determine an adequate sample frequency to reduce regional myocardial tracking errors. Concurrently, out-of-plane resolution has to be sufficiently high to minimize partial volume effect. Temporal resolution and out-of-plane spatial resolution are related factors that must be considered together. The data used for this study is a DSR dynamic volume image dataset with high temporal and spatial resolution using implanted fiducial markers to track myocardial motion. The results of this study suggest a reduced exposure and scan time for x-ray and magnetic resonance imaging methods, since a lower sample rate during systole is sufficient, whereas the period of rapid filling during diastole requires higher sampling. This could potentially reduce the cost of these procedures and allow higher patient throughput.

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

PubMed Central

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

2015-01-01

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

Purification of Training Samples Based on Spectral Feature and Superpixel Segmentation

NASA Astrophysics Data System (ADS)

Guan, X.; Qi, W.; He, J.; Wen, Q.; Chen, T.; Wang, Z.

2018-04-01

Remote sensing image classification is an effective way to extract information from large volumes of high-spatial resolution remote sensing images. Generally, supervised image classification relies on abundant and high-precision training data, which is often manually interpreted by human experts to provide ground truth for training and evaluating the performance of the classifier. Remote sensing enterprises accumulated lots of manually interpreted products from early lower-spatial resolution remote sensing images by executing their routine research and business programs. However, these manually interpreted products may not match the very high resolution (VHR) image properly because of different dates or spatial resolution of both data, thus, hindering suitability of manually interpreted products in training classification models, or small coverage area of these manually interpreted products. We also face similar problems in our laboratory in 21st Century Aerospace Technology Co. Ltd (short for 21AT). In this work, we propose a method to purify the interpreted product to match newly available VHRI data and provide the best training data for supervised image classifiers in VHR image classification. And results indicate that our proposed method can efficiently purify the input data for future machine learning use.

Anterior-segment imaging for assessment of glaucoma

PubMed Central

Ursea, Roxana; Silverman, Ronald H

2010-01-01

This article summarizes the physics, technology and clinical application of ultrasound biomicroscopy (UBM) and optical coherence tomography (OCT) for assessment of the anterior segment in glaucoma. UBM systems use frequencies ranging from approximately 35 to 80 MHz, as compared with typical 10-MHz systems used for general-purpose ophthalmic imaging. OCT systems use low-coherence, near-infrared light to provide detailed images of anterior segment structures at resolutions exceeding that of UBM. Both technologies allow visualization of the iridocorneal angle and, thus, can contribute to the diagnosis and management of glaucoma. OCT systems are advantageous, being noncontact proceedures and providing finer resolution than UBM, but UBM systems are superior for the visualization of retroiridal structures, including the ciliary body, posterior chamber and zonules, which can provide crucial diagnostic information for the assessment of glaucoma. PMID:20305726

JWST testbed telescope: a functionally accurate scaled version of the flight optical telescope element used to develop the flight wavefront sensing and control algorithm

NASA Astrophysics Data System (ADS)

Kingsbury, Lana K.; Atcheson, Paul D.

2004-10-01

The Northrop-Grumman/Ball/Kodak team is building the JWST observatory that will be launched in 2011. To develop the flight wavefront sensing and control (WFS&C) algorithms and software, Ball is designing and building a 1 meter diameter, functionally accurate version of the JWST optical telescope element (OTE). This testbed telescope (TBT) will incorporate the same optical element control capability as the flight OTE. The secondary mirror will be controlled by a 6 degree of freedom (dof) hexapod and each of the 18 segmented primary mirror assemblies will have 6 dof hexapod control as well as radius of curvature adjustment capability. In addition to the highly adjustable primary and secondary mirrors, the TBT will include a rigid tertiary mirror, 2 fold mirrors (to direct light into the TBT) and a very stable supporting structure. The total telescope system configured residual wavefront error will be better than 175 nm RMS double pass. The primary and secondary mirror hexapod assemblies enable 5 nm piston resolution, 0.0014 arcsec tilt resolution, 100 nm translation resolution, and 0.04497 arcsec clocking resolution. The supporting structure (specifically the secondary mirror support structure) is designed to ensure that the primary mirror segments will not change their despace position relative to the secondary mirror (spaced > 1 meter apart) by greater than 500 nm within a one hour period of ambient clean room operation.

Segmental and Suprasegmental Perception in Children Using Hearing Aids.

PubMed

Wenrich, Kaitlyn A; Davidson, Lisa S; Uchanski, Rosalie M

Suprasegmental perception (perception of stress, intonation, "how something is said" and "who says it") and segmental speech perception (perception of individual phonemes or perception of "what is said") are perceptual abilities that provide the foundation for the development of spoken language and effective communication. While there are numerous studies examining segmental perception in children with hearing aids (HAs), there are far fewer studies examining suprasegmental perception, especially for children with greater degrees of residual hearing. Examining the relation between acoustic hearing thresholds, and both segmental and suprasegmental perception for children with HAs, may ultimately enable better device recommendations (bilateral HAs, bimodal devices [one CI and one HA in opposite ears], bilateral CIs) for a particular degree of residual hearing. Examining both types of speech perception is important because segmental and suprasegmental cues are affected differentially by the type of hearing device(s) used (i.e., cochlear implant [CI] and/or HA). Additionally, suprathreshold measures, such as frequency resolution ability, may partially predict benefit from amplification and may assist audiologists in making hearing device recommendations. The purpose of this study is to explore the relationship between audibility (via hearing thresholds and speech intelligibility indices), and segmental and suprasegmental speech perception for children with HAs. A secondary goal is to explore the relationships among frequency resolution ability (via spectral modulation detection [SMD] measures), segmental and suprasegmental speech perception, and receptive language in these same children. A prospective cross-sectional design. Twenty-three children, ages 4 yr 11 mo to 11 yr 11 mo, participated in the study. Participants were recruited from pediatric clinic populations, oral schools for the deaf, and mainstream schools. Audiological history and hearing device information were collected from participants and their families. Segmental and suprasegmental speech perception, SMD, and receptive vocabulary skills were assessed. Correlations were calculated to examine the significance (p < 0.05) of relations between audibility and outcome measures. Measures of audibility and segmental speech perception are not significantly correlated, while low-frequency pure-tone average (unaided) is significantly correlated with suprasegmental speech perception. SMD is significantly correlated with all measures (measures of audibility, segmental and suprasegmental perception and vocabulary). Lastly, although age is not significantly correlated with measures of audibility, it is significantly correlated with all other outcome measures. The absence of a significant correlation between audibility and segmental speech perception might be attributed to overall audibility being maximized through well-fit HAs. The significant correlation between low-frequency unaided audibility and suprasegmental measures is likely due to the strong, predominantly low-frequency nature of suprasegmental acoustic properties. Frequency resolution ability, via SMD performance, is significantly correlated with all outcomes and requires further investigation; its significant correlation with vocabulary suggests that linguistic ability may be partially related to frequency resolution ability. Last, all of the outcome measures are significantly correlated with age, suggestive of developmental effects. American Academy of Audiology

Are needles of Pinus pinaster more vulnerable to xylem embolism than branches? New insights from X-ray computed tomography.

PubMed

Bouche, Pauline S; Delzon, Sylvain; Choat, Brendan; Badel, Eric; Brodribb, Timothy J; Burlett, Regis; Cochard, Hervé; Charra-Vaskou, Katline; Lavigne, Bruno; Li, Shan; Mayr, Stefan; Morris, Hugh; Torres-Ruiz, José M; Zufferey, Vivian; Jansen, Steven

2016-04-01

Plants can be highly segmented organisms with an independently redundant design of organs. In the context of plant hydraulics, leaves may be less embolism resistant than stems, allowing hydraulic failure to be restricted to distal organs that can be readily replaced. We quantified drought-induced embolism in needles and stems of Pinus pinaster using high-resolution computed tomography (HRCT). HRCT observations of needles were compared with the rehydration kinetics method to estimate the contribution of extra-xylary pathways to declining hydraulic conductance. High-resolution computed tomography images indicated that the pressure inducing 50% of embolized tracheids was similar between needle and stem xylem (P50 needle xylem  = -3.62 MPa, P50 stem xylem  = -3.88 MPa). Tracheids in both organs showed no difference in torus overlap of bordered pits. However, estimations of the pressure inducing 50% loss of hydraulic conductance at the whole needle level by the rehydration kinetics method were significantly higher (P50 needle  = -1.71 MPa) than P50 needle xylem derived from HRCT. The vulnerability segmentation hypothesis appears to be valid only when considering hydraulic failure at the entire needle level, including extra-xylary pathways. Our findings suggest that native embolism in needles is limited and highlight the importance of imaging techniques for vulnerability curves. © 2015 John Wiley & Sons Ltd.

Formation Flying: The Future of Remote Sensing from Space

NASA Technical Reports Server (NTRS)

Leitner, Jesse

2004-01-01

Over the next two decades a revolution is likely to occur in how remote sensing of Earth, other planets or bodies, and a range of phenomena in the universe is performed from space. In particular, current launch vehicle fairing volume and mass constraints will continue to restrict the size of monolithic telescope apertures which can be launched to little or no greater size than that of the Hubble Space Telescope, the largest aperture currently flying in space. Systems under formulation today, such as the James Webb Space Telescope will be able to increase aperture size and, hence, imaging resolution, by deploying segmented optics. However, this approach is limited as well, by our ability to control such segments to optical tolerances over long distances with highly uncertain structural dynamics connecting them. Consequently, for orders of magnitude improved resolution as required for imaging black holes, imaging planets, or performing asteroseismology, the only viable approach will be to fly a collection of spacecraft in formation to synthesize a virtual segmented telescope or interferometer with very large baselines. This paper provides some basic definitions in the area of formation flying, describes some of the strategic science missions planned in the National Aeronautics and Space Administration, and identifies some of the critical technologies needed to enable some of the most challenging space missions ever conceived which have realistic hopes of flying.

Object-Oriented Analysis of Satellite Images Using Artificial Neural Networks for Post-Earthquake Buildings Change Detection

NASA Astrophysics Data System (ADS)

Khodaverdi zahraee, N.; Rastiveis, H.

2017-09-01

Earthquake is one of the most divesting natural events that threaten human life during history. After the earthquake, having information about the damaged area, the amount and type of damage can be a great help in the relief and reconstruction for disaster managers. It is very important that these measures should be taken immediately after the earthquake because any negligence could be more criminal losses. The purpose of this paper is to propose and implement an automatic approach for mapping destructed buildings after an earthquake using pre- and post-event high resolution satellite images. In the proposed method after preprocessing, segmentation of both images is performed using multi-resolution segmentation technique. Then, the segmentation results are intersected with ArcGIS to obtain equal image objects on both images. After that, appropriate textural features, which make a better difference between changed or unchanged areas, are calculated for all the image objects. Finally, subtracting the extracted textural features from pre- and post-event images, obtained values are applied as an input feature vector in an artificial neural network for classifying the area into two classes of changed and unchanged areas. The proposed method was evaluated using WorldView2 satellite images, acquired before and after the 2010 Haiti earthquake. The reported overall accuracy of 93% proved the ability of the proposed method for post-earthquake buildings change detection.

White matter segmentation by estimating tissue optical attenuation from volumetric OCT massive histology of whole rodent brains

NASA Astrophysics Data System (ADS)

Lefebvre, Joël.; Castonguay, Alexandre; Lesage, Frédéric

2017-02-01

A whole rodent brain was imaged using an automated massive histology setup and an Optical Coherence Tomography (OCT) microscope. Thousands of OCT volumetric tiles were acquired, each covering a size of about 2.5x2.5x0.8 mm3 with a sampling resolution of 4.9x4.9x6.5 microns. This paper shows the techniques for reconstruction, attenuation compensation and segmentation of the sliced brains. The tile positions within the mosaic were evaluated using a displacement model of the motorized stage and pairwise coregistration. Volume blending was then performed by solving the 3D Laplace equation, and consecutive slices were assembled using the cross-correlation of their 2D image gradient. This reconstruction algorithm resulted in a 3D map of optical reflectivity for the whole brain at micrometric resolution. OCT tissue slices were then used to estimate the local attenuation coefficient based on a single scattering photon model. The attenuation map obtained exhibits a high contrast for all white matter fibres, regardless of their orientation. The tissue optical attenuation from the intrinsic OCT reflectivity contributes to better white matter tissue segmentation. The combined 3D maps of reflectivity and attenuation is a step toward the study of white matter at a microscopic scale for the whole brain in small animals.

Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters.

PubMed

Schneider, Matthias; Hirsch, Sven; Weber, Bruno; Székely, Gábor; Menze, Bjoern H

2015-01-01

We propose a novel framework for joint 3-D vessel segmentation and centerline extraction. The approach is based on multivariate Hough voting and oblique random forests (RFs) that we learn from noisy annotations. It relies on steerable filters for the efficient computation of local image features at different scales and orientations. We validate both the segmentation performance and the centerline accuracy of our approach both on synthetic vascular data and four 3-D imaging datasets of the rat visual cortex at 700 nm resolution. First, we evaluate the most important structural components of our approach: (1) Orthogonal subspace filtering in comparison to steerable filters that show, qualitatively, similarities to the eigenspace filters learned from local image patches. (2) Standard RF against oblique RF. Second, we compare the overall approach to different state-of-the-art methods for (1) vessel segmentation based on optimally oriented flux (OOF) and the eigenstructure of the Hessian, and (2) centerline extraction based on homotopic skeletonization and geodesic path tracing. Our experiments reveal the benefit of steerable over eigenspace filters as well as the advantage of oblique split directions over univariate orthogonal splits. We further show that the learning-based approach outperforms different state-of-the-art methods and proves highly accurate and robust with regard to both vessel segmentation and centerline extraction in spite of the high level of label noise in the training data. Copyright © 2014 Elsevier B.V. All rights reserved.

Feasibility of high-resolution quantitative perfusion analysis in patients with heart failure.

PubMed

Sammut, Eva; Zarinabad, Niloufar; Wesolowski, Roman; Morton, Geraint; Chen, Zhong; Sohal, Manav; Carr-White, Gerry; Razavi, Reza; Chiribiri, Amedeo

2015-02-12

Cardiac magnetic resonance (CMR) is playing an expanding role in the assessment of patients with heart failure (HF). The assessment of myocardial perfusion status in HF can be challenging due to left ventricular (LV) remodelling and wall thinning, coexistent scar and respiratory artefacts. The aim of this study was to assess the feasibility of quantitative CMR myocardial perfusion analysis in patients with HF. A group of 58 patients with heart failure (HF; left ventricular ejection fraction, LVEF ≤ 50%) and 33 patients with normal LVEF (LVEF >50%), referred for suspected coronary artery disease, were studied. All subjects underwent quantitative first-pass stress perfusion imaging using adenosine according to standard acquisition protocols. The feasibility of quantitative perfusion analysis was then assessed using high-resolution, 3 T kt perfusion and voxel-wise Fermi deconvolution. 30/58 (52%) subjects in the HF group had underlying ischaemic aetiology. Perfusion abnormalities were seen amongst patients with ischaemic HF and patients with normal LV function. No regional perfusion defect was observed in the non-ischaemic HF group. Good agreement was found between visual and quantitative analysis across all groups. Absolute stress perfusion rate, myocardial perfusion reserve (MPR) and endocardial-epicardial MPR ratio identified areas with abnormal perfusion in the ischaemic HF group (p = 0.02; p = 0.04; p = 0.02, respectively). In the Normal LV group, MPR and endocardial-epicardial MPR ratio were able to distinguish between normal and abnormal segments (p = 0.04; p = 0.02 respectively). No significant differences of absolute stress perfusion rate or MPR were observed comparing visually normal segments amongst groups. Our results demonstrate the feasibility of high-resolution voxel-wise perfusion assessment in patients with HF.

Dominance of layer-specific microvessel dilation in contrast-enhanced high-resolution fMRI: Comparison between hemodynamic spread and vascular architecture with CLARITY.

PubMed

Poplawsky, Alexander John; Fukuda, Mitsuhiro; Kang, Bok-Man; Kim, Jae Hwan; Suh, Minah; Kim, Seong-Gi

2017-08-16

Contrast-enhanced cerebral blood volume-weighted (CBVw) fMRI response peaks are specific to the layer of evoked synaptic activity (Poplawsky et al., 2015), but the spatial resolution limit of CBVw fMRI is unknown. In this study, we measured the laminar spread of the CBVw fMRI evoked response in the external plexiform layer (EPL, 265 ± 65 μm anatomical thickness, mean ± SD, n = 30 locations from 5 rats) of the rat olfactory bulb during electrical stimulation of the lateral olfactory tract and examined its potential vascular source. First, we obtained the evoked CBVw fMRI responses with a 55 × 55 μm 2 in-plane resolution and a 500-μm thickness at 9.4 T, and found that the fMRI signal peaked predominantly in the inner half of EPL (136 ± 54 μm anatomical thickness). The mean full-width at half-maximum of these fMRI peaks was 347 ± 102 μm and the functional spread was approximately 100 or 200 μm when the effects of the laminar thicknesses of EPL or inner EPL were removed, respectively. Second, we visualized the vascular architecture of EPL from a different rat using a Clear Lipid-exchanged Anatomically Rigid Imaging/immunostaining-compatible Tissue hYdrogel (CLARITY)-based tissue preparation method and confocal microscopy. Microvascular segments with an outer diameter of <11 μm accounted for 64.3% of the total vascular volume within EPL and had a mean segment length of 55 ± 40 μm (n = 472). Additionally, vessels that crossed the EPL border had a mean segment length outside of EPL equal to 73 ± 61 μm (n = 28), which is comparable to half of the functional spread (50-100 μm). Therefore, we conclude that dilation of these microvessels, including capillaries, likely dominate the CBVw fMRI response and that the biological limit of the fMRI spatial resolution is approximately the average length of 1-2 microvessel segments, which may be sufficient for examining sublaminar circuits. Copyright © 2017 Elsevier Inc. All rights reserved.

Image-based models of cardiac structure in health and disease

PubMed Central

Vadakkumpadan, Fijoy; Arevalo, Hermenegild; Prassl, Anton J.; Chen, Junjie; Kickinger, Ferdinand; Kohl, Peter; Plank, Gernot; Trayanova, Natalia

2010-01-01

Computational approaches to investigating the electromechanics of healthy and diseased hearts are becoming essential for the comprehensive understanding of cardiac function. In this article, we first present a brief review of existing image-based computational models of cardiac structure. We then provide a detailed explanation of a processing pipeline which we have recently developed for constructing realistic computational models of the heart from high resolution structural and diffusion tensor (DT) magnetic resonance (MR) images acquired ex vivo. The presentation of the pipeline incorporates a review of the methodologies that can be used to reconstruct models of cardiac structure. In this pipeline, the structural image is segmented to reconstruct the ventricles, normal myocardium, and infarct. A finite element mesh is generated from the segmented structural image, and fiber orientations are assigned to the elements based on DTMR data. The methods were applied to construct seven different models of healthy and diseased hearts. These models contain millions of elements, with spatial resolutions in the order of hundreds of microns, providing unprecedented detail in the representation of cardiac structure for simulation studies. PMID:20582162

Immobilized Pepsin Microreactor for Rapid Peptide Mapping with Nanoelectrospray Ionization Mass Spectrometry

NASA Astrophysics Data System (ADS)

Long, Ying; Wood, Troy D.

2015-01-01

Most enzymatic microreactors for protein digestion are based on trypsin, but proteins with hydrophobic segments may be difficult to digest because of the paucity of Arg and Lys residues. Microreactors based on pepsin, which is less specific than trypsin, can overcome this challenge. Here, an integrated immobilized pepsin microreactor (IPMR)/nanoelectrospray emitter is examined for its potential for peptide mapping. For myoglobin, equivalent sequence coverage is obtained in a thousandth the time of solution digestion with better sequence coverage. While sequence coverage of cytochrome c is lesser than solution in this short duration, more highly-charged peptic peptides are produced and a number of peaks are unidentified at low-resolution, suggesting that high-resolution mass spectrometry is needed to take full advantage of integrated IPMR/nanoelectrospray devices.

Shallow high-resolution geophysical investigation along the western segment of the Victoria Lines Fault (island of Malta)

NASA Astrophysics Data System (ADS)

Villani, Fabio; D'Amico, Sebastiano; Panzera, Francesco; Vassallo, Maurizio; Bozionelos, George; Farrugia, Daniela; Galea, Pauline

2018-01-01

The Victoria Lines Fault (island of Malta) is a >15 km-long and N260°-striking segmented normal fault-system, which is probably inactive since the late Pliocene. In the westernmost part, the Fomm Ir-Rih segment displays comparable geologic throw and escarpment height ( 150-170 m), moreover its hangingwall hosts thin patches of Middle Pleistocene clastic continental deposits (red beds), which are poorly preserved elsewhere. We acquired two seismic transects, by collecting ambient vibration recordings, processed by using horizontal-to-vertical spectral ratios, complemented by one high-resolution 2-D refraction tomography survey crossing this fault where it is locally covered by red beds and recent colluvial deposits. We found a resonance peak at 1.0 Hz in the hangingwall block, whereas clear peaks in the range 5.0-10.0 Hz appear when approaching the subsurface fault, and we relate them to the fractured bedrock within the fault zone. The best-fit tomographic model shows a relatively high-Vp shallow body (Vp 2200-2400 m/s) that we relate to the weathered top of the Miocene Upper Coralline Limestone Fm., bounded on both sides by low-Vp regions (<1400 m/s). The latter are the smeared images of steep fault zones. Tomography further reveals a thick ( 15-20 m) low-Vp (<1000 m/s) zone, which could be a syn-tectonic wedge of colluvial deposits developed in the downthrown block. Surface waves analysis indicates lateral changes of the average shallow shear wave velocity, with Vs 130 m/s within the inferred fault zone, and Vs >230 m/s above the weathered top-bedrock. Our results depict a clear seismic signature of the Victoria Lines Fault, characterized by low seismic velocity and high amplification of ground motion. We hypothesize that, during the Middle Pleistocene, faulting may have affected the basal part of the red beds, so that this part of the investigated complex fault-system may be considered inactive since 0.6 Myr ago.

Quantitative analysis of vascular parameters for micro-CT imaging of vascular networks with multi-resolution.

PubMed

Zhao, Fengjun; Liang, Jimin; Chen, Xueli; Liu, Junting; Chen, Dongmei; Yang, Xiang; Tian, Jie

2016-03-01

Previous studies showed that all the vascular parameters from both the morphological and topological parameters were affected with the altering of imaging resolutions. However, neither the sensitivity analysis of the vascular parameters at multiple resolutions nor the distinguishability estimation of vascular parameters from different data groups has been discussed. In this paper, we proposed a quantitative analysis method of vascular parameters for vascular networks of multi-resolution, by analyzing the sensitivity of vascular parameters at multiple resolutions and estimating the distinguishability of vascular parameters from different data groups. Combining the sensitivity and distinguishability, we designed a hybrid formulation to estimate the integrated performance of vascular parameters in a multi-resolution framework. Among the vascular parameters, degree of anisotropy and junction degree were two insensitive parameters that were nearly irrelevant with resolution degradation; vascular area, connectivity density, vascular length, vascular junction and segment number were five parameters that could better distinguish the vascular networks from different groups and abide by the ground truth. Vascular area, connectivity density, vascular length and segment number not only were insensitive to multi-resolution but could also better distinguish vascular networks from different groups, which provided guidance for the quantification of the vascular networks in multi-resolution frameworks.

High-Resolution Topography and its Implications for the Formation of Europa's Ridged Plains

NASA Astrophysics Data System (ADS)

Leonard, E. J.; Pappalardo, R. T.; Yin, A.; Patthoff, D. A.; Schenk, P.

2015-12-01

The Galileo Solid State Imager (SSI) recorded nine very high-resolution frames—eight at 12 m/pixel and one at 6 m/pixel—during the E12 flyby of Europa in Dec. 1997. To understand the implications for the small-scale structure and evolution of Europa, we mosaicked these frames (observations 12ESMOTTLE01 and 02, incidence ≈18°, emission ≈77°) into their regional context (part of observation 11ESREGMAP01, 220 m/pixel, incidence ≈74°, emission ≈23°). The topography data, which was created from the image mosaic overlaps, is sparse and segmented over the high-resolution images but connected by the underlying regional resolution topography. The high-resolution topography (24 m/pixel) is among the best for the current Europan dataset. From this dataset we ascertain the root mean square, or RMS, slope for some of the most common Europan surface features in a new region. We also employ a Fourier Transform method previously used on Ganymede and on other areas of Europa (Patel et al., 1999 JGR), to derive common wavelengths for the subunits of the ubiquitous ridged plains terrain. These results have important implications for differentiating between possible formation mechanisms—extensional tilt blocks (Pappalardo et al., 1995 JGR) or folds (Leonard et al., 2015 LPSC Abstract)—and for potential future missions. We continue this method for another high-resolution region taken in the E12 orbit, WEDGES01 and 02, with the specific goal of investigating how the variations in ridged plains morphologies relate across the surface of Europa.

High-resolution melting analysis for prenatal diagnosis of beta-thalassemia in northern Thailand.

PubMed

Charoenkwan, Pimlak; Sirichotiyakul, Supatra; Phusua, Arunee; Suanta, Sudjai; Fanhchaksai, Kanda; Sae-Tung, Rattika; Sanguansermsri, Torpong

2017-12-01

High-resolution melting (HRM) analysis is a rapid mutation analysis which assesses the pattern of reduction of fluorescence signal after subjecting the amplified PCR product with saturated fluorescence dye to an increasing temperature. We used HRM analysis for prenatal diagnosis of beta-thalassemia disease in northern Thailand. Five PCR-HRM protocols were used to detect point mutations in five different segments of the beta-globin gene, and one protocol to detect the 3.4 kb beta-globin deletion. We sought to characterize the mutations in carriers and to enable prenatal diagnosis in 126 couples at risk of having a fetus with beta-thalassemia disease. The protocols identified 18 common mutations causing beta-thalassemia, including the rare codon 132 (A-T) mutation. Each mutation showed a specific HRM pattern and all results were in concordance with those from direct DNA sequencing or gap-PCR methods. In cases of beta-thalassemia disease resulting from homozygosity for a mutation or compound heterozygosity for two mutations on the same amplified segment, the HRM patterns were different to those of a single mutation and were specific for each combination. HRM analysis is a simple and useful method for mutation identification in beta-thalassemia carriers and prenatal diagnosis of beta-thalassemia in northern Thailand.

Time-efficient high-resolution whole-brain three-dimensional macromolecular proton fraction mapping

PubMed Central

Yarnykh, Vasily L.

2015-01-01

Purpose Macromolecular proton fraction (MPF) mapping is a quantitative MRI method that reconstructs parametric maps of a relative amount of macromolecular protons causing the magnetization transfer (MT) effect and provides a biomarker of myelination in neural tissues. This study aimed to develop a high-resolution whole-brain MPF mapping technique utilizing a minimal possible number of source images for scan time reduction. Methods The described technique is based on replacement of an actually acquired reference image without MT saturation by a synthetic one reconstructed from R1 and proton density maps, thus requiring only three source images. This approach enabled whole-brain three-dimensional MPF mapping with isotropic 1.25×1.25×1.25 mm3 voxel size and scan time of 20 minutes. The synthetic reference method was validated against standard MPF mapping with acquired reference images based on data from 8 healthy subjects. Results Mean MPF values in segmented white and gray matter appeared in close agreement with no significant bias and small within-subject coefficients of variation (<2%). High-resolution MPF maps demonstrated sharp white-gray matter contrast and clear visualization of anatomical details including gray matter structures with high iron content. Conclusions Synthetic reference method improves resolution of MPF mapping and combines accurate MPF measurements with unique neuroanatomical contrast features. PMID:26102097

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.

High-speed microstrip multi-anode multichannel plate detector system

NASA Astrophysics Data System (ADS)

Riedo, Andreas; Tulej, Marek; Rohner, Urs; Wurz, Peter

2017-04-01

High-speed detector systems with high dynamic range and pulse width characteristics in the sub-nanosecond regime are mandatory for high resolution and highly sensitive time-of-flight mass spectrometers. Typically, for a reasonable detector area, an impedance-matched anode design is necessary to transmit the registered signal fast and distortion-free from the anode to the signal acquisition system. In this report, a high-speed microstrip multi-anode multichannel plate detector is presented and discussed. The anode consists of four separate active concentric anode segments allowing a simultaneous readout of signal with a dynamic range of about eight orders of magnitude. The impedance matched anode segments show pulse width of about 250 ps, measured at full width at half maximum, and rise time of ˜170 ps, measured with an oscilloscope with a sampling rate of 20 GS/s and 4 GHz analogue bandwidth. The usage of multichannel plates as signal amplifier allowed the design of a lightweight, low power consuming, and compact detector system, suitable, e.g., for the integration into space instrumentation or portable systems where size, weight, and power consumption are limited parameters.

Techniques for efficient, real-time, 3D visualization of multi-modality cardiac data using consumer graphics hardware.

PubMed

Levin, David; Aladl, Usaf; Germano, Guido; Slomka, Piotr

2005-09-01

We exploit consumer graphics hardware to perform real-time processing and visualization of high-resolution, 4D cardiac data. We have implemented real-time, realistic volume rendering, interactive 4D motion segmentation of cardiac data, visualization of multi-modality cardiac data and 3D display of multiple series cardiac MRI. We show that an ATI Radeon 9700 Pro can render a 512x512x128 cardiac Computed Tomography (CT) study at 0.9 to 60 frames per second (fps) depending on rendering parameters and that 4D motion based segmentation can be performed in real-time. We conclude that real-time rendering and processing of cardiac data can be implemented on consumer graphics cards.

Dynamic radionuclide determination of regional left ventricular wall motion using a new digital imaging device

NASA Technical Reports Server (NTRS)

Steele, P.; Kirch, D.

1975-01-01

In 47 men with arteriographically defined coronary artery disease comparative studies of left ventricular ejection fraction and segmental wall motion were made with radionuclide data obtained from the image intensifier camera computer system and with contrast cineventriculography. The radionuclide data was digitized and the images corresponding to left ventricular end-diastole and end-systole were identified from the left ventricular time-activity curve. The left ventricular end-diastolic and end-systolic images were subtracted to form a silhouette difference image which described wall motion of the anterior and inferior left ventricular segments. The image intensifier camera allows manipulation of dynamically acquired radionuclide data because of the high count rate and consequently improved resolution of the left ventricular image.

Core segment 15008 - Regolith stratigraphy at Apennine Front Station 2 using multispectral imaging

NASA Technical Reports Server (NTRS)

Pieters, C. M.; Meloy, A.; Hawke, B. R.; Nagle, J. S.

1982-01-01

High precision multispectral images for Apennine Front core segment 15008 are presented. These data have a spatial resolution less than approximately 0.5 mm and are analyzed for their compositional information using image analysis techniques. The stratigraphy of the regolith sampled by 15008 is documented here as three distinct zones, the most prominent of which is a feldspathic fragment-rich zone with a chaotic fabric that occurs between 10 and 18 cm depth. It is suggested that this material is the primary rim crest deposit of the local 10 m crater. Above this zone the stratigraphy is more horizontal in nature. Below this zone the soil is observed to be relatively homogeneous with no distinctive structure to 23 cm depth.

Pars plana Ahmed valve and vitrectomy in patients with glaucoma associated with posterior segment disease.

PubMed

Wallsh, Josh O; Gallemore, Ron P; Taban, Mehran; Hu, Charles; Sharareh, Behnam

2013-01-01

To assess the safety and efficacy of a modified technique for pars plana placement of the Ahmed valve in combination with pars plana vitrectomy in the treatment of glaucoma associated with posterior segment disease. Thirty-nine eyes with glaucoma associated with posterior segment disease underwent pars plana vitrectomy combined with Ahmed valve placement. All valves were placed in the pars plana using a modified technique, without the pars plana clip, and using a scleral patch graft. The 24 eyes diagnosed with neovascular glaucoma had an improvement in intraocular pressure from 37.6 mmHg to 13.8 mmHg and best-corrected visual acuity from 2.13 logarithm of minimum angle of resolution to 1.40 logarithm of minimum angle of resolution. Fifteen eyes diagnosed with steroid-induced glaucoma had an improvement in intraocular pressure from 27.9 mmHg to 14.1 mmHg and best-corrected visual acuity from 1.38 logarithm of minimum angle of resolution to 1.13 logarithm of minimum angle of resolution. Complications included four cases of cystic bleb formation and one case of choroidal detachment and explantation for hypotony. Ahmed valve placement through the pars plana during vitrectomy is an effective option for managing complex cases of glaucoma without the use of the pars plana clip.

Phylogenetic implications of the 38 putative ancestral chromosome segments for four canid species.

PubMed

Graphodatsky, A S; Yang, F; O'Brien, P C; Perelman, P; Milne, B S; Serdukova, N; Kawada, S I; Ferguson-Smith, M A

2001-01-01

Chromosome homologies between the Japanese raccoon dog (Nectereutes procyonoides viverrinus, 2n = 39 + 2-4 B chromosomes) and domestic dog (Canis familiaris, 2n = 78) have been established by hybridizing a complete set of canine paint probes onto high-resolution G-banded chromosomes of the raccoon dog. Dog chromosomes 1, 13, and 19 each correspond to two raccoon dog chromosome segments, while the remaining 35 dog autosomes each correspond to a single segment. In total, 38 dog autosome paints revealed 41 conserved segments in the raccoon dog. The use of dog painting probes has enabled integration of the raccoon dog chromosomes into the previously established comparative map for the domestic dog, Arctic fox (Alopex lagopus), and red fox (Vulpes vulpes). Extensive chromosome arm homologies were found among chromosomes of the red fox, Arctic fox, and raccoon dog. Contradicting previous findings, our results show that the raccoon dog does not share a single biarmed autosome in common with the Arctic fox, red fox, or domestic cat. Comparative analysis of the distribution patterns of conserved chromosome segments revealed by dog paints in the genomes of the canids, cats, and human reveals 38 ancestral autosome segments. These segments could represent the ancestral chromosome arms in the karyotype of the most recent ancestor of the Canidae family, which we suggest could have had a low diploid number, based on comparisons with outgroup species. Copyright 2001 S. Karger AG, Basel.

Automatic Organ Segmentation for CT Scans Based on Super-Pixel and Convolutional Neural Networks.

PubMed

Liu, Xiaoming; Guo, Shuxu; Yang, Bingtao; Ma, Shuzhi; Zhang, Huimao; Li, Jing; Sun, Changjian; Jin, Lanyi; Li, Xueyan; Yang, Qi; Fu, Yu

2018-04-20

Accurate segmentation of specific organ from computed tomography (CT) scans is a basic and crucial task for accurate diagnosis and treatment. To avoid time-consuming manual optimization and to help physicians distinguish diseases, an automatic organ segmentation framework is presented. The framework utilized convolution neural networks (CNN) to classify pixels. To reduce the redundant inputs, the simple linear iterative clustering (SLIC) of super-pixels and the support vector machine (SVM) classifier are introduced. To establish the perfect boundary of organs in one-pixel-level, the pixels need to be classified step-by-step. First, the SLIC is used to cut an image into grids and extract respective digital signatures. Next, the signature is classified by the SVM, and the rough edges are acquired. Finally, a precise boundary is obtained by the CNN, which is based on patches around each pixel-point. The framework is applied to abdominal CT scans of livers and high-resolution computed tomography (HRCT) scans of lungs. The experimental CT scans are derived from two public datasets (Sliver 07 and a Chinese local dataset). Experimental results show that the proposed method can precisely and efficiently detect the organs. This method consumes 38 s/slice for liver segmentation. The Dice coefficient of the liver segmentation results reaches to 97.43%. For lung segmentation, the Dice coefficient is 97.93%. This finding demonstrates that the proposed framework is a favorable method for lung segmentation of HRCT scans.

Early detection of lung cancer from CT images: nodule segmentation and classification using deep learning

NASA Astrophysics Data System (ADS)

Sharma, Manu; Bhatt, Jignesh S.; Joshi, Manjunath V.

2018-04-01

Lung cancer is one of the most abundant causes of the cancerous deaths worldwide. It has low survival rate mainly due to the late diagnosis. With the hardware advancements in computed tomography (CT) technology, it is now possible to capture the high resolution images of lung region. However, it needs to be augmented by efficient algorithms to detect the lung cancer in the earlier stages using the acquired CT images. To this end, we propose a two-step algorithm for early detection of lung cancer. Given the CT image, we first extract the patch from the center location of the nodule and segment the lung nodule region. We propose to use Otsu method followed by morphological operations for the segmentation. This step enables accurate segmentation due to the use of data-driven threshold. Unlike other methods, we perform the segmentation without using the complete contour information of the nodule. In the second step, a deep convolutional neural network (CNN) is used for the better classification (malignant or benign) of the nodule present in the segmented patch. Accurate segmentation of even a tiny nodule followed by better classification using deep CNN enables the early detection of lung cancer. Experiments have been conducted using 6306 CT images of LIDC-IDRI database. We achieved the test accuracy of 84.13%, with the sensitivity and specificity of 91.69% and 73.16%, respectively, clearly outperforming the state-of-the-art algorithms.

A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images

PubMed Central

Tang, Yunwei; Jing, Linhai; Ding, Haifeng

2017-01-01

The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA). Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods. PMID:29064416

Recent patents on electrophoretic displays and materials.

PubMed

Christophersen, Marc; Phlips, Bernard F

2010-11-01

Electrophoretic displays (EPDs) have made their way into consumer products. EPDs enable displays that offer the look and form of a printed page, often called "electronic paper". We will review recent apparatus and method patents for EPD devices and their fabrication. A brief introduction into the basic display operation and history of EPDs is given, while pointing out the technological challenges and difficulties for inventors. Recently, the majority of scientific publications and patenting activity has been directed to micro-segmented EPDs. These devices exhibit high optical reflectance and contrast, wide viewing angle, and high image resolution. Micro-segmented EPDs can also be integrated with flexible transistors technologies into flexible displays. Typical particles size ranges from 200 nm to 2 micrometer. Currently one very active area of patenting is the development of full-color EPDs. We summarize the recent patenting activity for EPDs and provide comments on perceiving factors driving intellectual property protection for EPD technologies.

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

PubMed Central

Moran, Emilio Federico.

2010-01-01

High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

A Genetically Engineered Mouse Model of Sporadic Colorectal Cancer.

PubMed

Betzler, Alexander M; Kochall, Susan; Blickensdörfer, Linda; Garcia, Sebastian A; Thepkaysone, May-Linn; Nanduri, Lahiri K; Muders, Michael H; Weitz, Jürgen; Reissfelder, Christoph; Schölch, Sebastian

2017-07-06

Despite the advantages of easy applicability and cost-effectiveness, colorectal cancer mouse models based on tumor cell injection have severe limitations and do not accurately simulate tumor biology and tumor cell dissemination. Genetically engineered mouse models have been introduced to overcome these limitations; however, such models are technically demanding, especially in large organs such as the colon in which only a single tumor is desired. As a result, an immunocompetent, genetically engineered mouse model of colorectal cancer was developed which develops highly uniform tumors and can be used for tumor biology studies as well as therapeutic trials. Tumor development is initiated by surgical, segmental infection of the distal colon with adeno-cre virus in compound conditionally mutant mice. The tumors can be easily detected and monitored via colonoscopy. We here describe the surgical technique of segmental adeno-cre infection of the colon, the surveillance of the tumor via high-resolution colonoscopy and present the resulting colorectal tumors.

Blood vessel segmentation algorithms - Review of methods, datasets and evaluation metrics.

PubMed

Moccia, Sara; De Momi, Elena; El Hadji, Sara; Mattos, Leonardo S

2018-05-01

Blood vessel segmentation is a topic of high interest in medical image analysis since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and evaluation of clinical outcomes in different fields, including laryngology, neurosurgery and ophthalmology. Automatic or semi-automatic vessel segmentation can support clinicians in performing these tasks. Different medical imaging techniques are currently used in clinical practice and an appropriate choice of the segmentation algorithm is mandatory to deal with the adopted imaging technique characteristics (e.g. resolution, noise and vessel contrast). This paper aims at reviewing the most recent and innovative blood vessel segmentation algorithms. Among the algorithms and approaches considered, we deeply investigated the most novel blood vessel segmentation including machine learning, deformable model, and tracking-based approaches. This paper analyzes more than 100 articles focused on blood vessel segmentation methods. For each analyzed approach, summary tables are presented reporting imaging technique used, anatomical region and performance measures employed. Benefits and disadvantages of each method are highlighted. Despite the constant progress and efforts addressed in the field, several issues still need to be overcome. A relevant limitation consists in the segmentation of pathological vessels. Unfortunately, not consistent research effort has been addressed to this issue yet. Research is needed since some of the main assumptions made for healthy vessels (such as linearity and circular cross-section) do not hold in pathological tissues, which on the other hand require new vessel model formulations. Moreover, image intensity drops, noise and low contrast still represent an important obstacle for the achievement of a high-quality enhancement. This is particularly true for optical imaging, where the image quality is usually lower in terms of noise and contrast with respect to magnetic resonance and computer tomography angiography. No single segmentation approach is suitable for all the different anatomical region or imaging modalities, thus the primary goal of this review was to provide an up to date source of information about the state of the art of the vessel segmentation algorithms so that the most suitable methods can be chosen according to the specific task. Copyright © 2018 Elsevier B.V. All rights reserved.

A tree canopy height delineation method based on Morphological Reconstruction—Open Crown Decomposition

NASA Astrophysics Data System (ADS)

Liu, Q.; Jing, L.; Li, Y.; Tang, Y.; Li, H.; Lin, Q.

2016-04-01

For the purpose of forest management, high resolution LIDAR and optical remote sensing imageries are used for treetop detection, tree crown delineation, and classification. The purpose of this study is to develop a self-adjusted dominant scales calculation method and a new crown horizontal cutting method of tree canopy height model (CHM) to detect and delineate tree crowns from LIDAR, under the hypothesis that a treetop is radiometric or altitudinal maximum and tree crowns consist of multi-scale branches. The major concept of the method is to develop an automatic selecting strategy of feature scale on CHM, and a multi-scale morphological reconstruction-open crown decomposition (MRCD) to get morphological multi-scale features of CHM by: cutting CHM from treetop to the ground; analysing and refining the dominant multiple scales with differential horizontal profiles to get treetops; segmenting LiDAR CHM using watershed a segmentation approach marked with MRCD treetops. This method has solved the problems of false detection of CHM side-surface extracted by the traditional morphological opening canopy segment (MOCS) method. The novel MRCD delineates more accurate and quantitative multi-scale features of CHM, and enables more accurate detection and segmentation of treetops and crown. Besides, the MRCD method can also be extended to high optical remote sensing tree crown extraction. In an experiment on aerial LiDAR CHM of a forest of multi-scale tree crowns, the proposed method yielded high-quality tree crown maps.

The robustness of T2 value as a trabecular structural index at multiple spatial resolutions of 7 Tesla MRI.

PubMed

Lee, D K; Song, Y K; Park, B W; Cho, H P; Yeom, J S; Cho, G; Cho, H

2018-04-15

To evaluate the robustness of MR transverse relaxation times of trabecular bone from spin-echo and gradient-echo acquisitions at multiple spatial resolutions of 7 T. The effects of MRI resolutions to T 2 and T2* of trabecular bone were numerically evaluated by Monte Carlo simulations. T 2 , T2*, and trabecular structural indices from multislice multi-echo and UTE acquisitions were measured in defatted human distal femoral condyles on a 7 T scanner. Reference structural indices were extracted from high-resolution microcomputed tomography images. For bovine knee trabecular samples with intact bone marrow, T 2 and T2* were measured by degrading spatial resolutions on a 7 T system. In the defatted trabecular experiment, both T 2 and T2* values showed strong ( |r| > 0.80) correlations with trabecular spacing and number, at a high spatial resolution of 125 µm 3 . The correlations for MR image-segmentation-derived structural indices were significantly degraded ( |r| < 0.50) at spatial resolutions of 250 and 500 µm 3 . The correlations for T2* rapidly dropped ( |r| < 0.50) at a spatial resolution of 500 µm 3 , whereas those for T 2 remained consistently high ( |r| > 0.85). In the bovine trabecular experiments with intact marrow, low-resolution (approximately 1 mm 3 , 2 minutes) T 2 values did not shorten ( |r| > 0.95 with respect to approximately 0.4 mm 3 , 11 minutes) and maintained consistent correlations ( |r| > 0.70) with respect to trabecular spacing (turbo spin echo, 22.5 minutes). T 2 measurements of trabeculae at 7 T are robust with degrading spatial resolution and may be preferable in assessing trabecular spacing index with reduced scan time, when high-resolution 3D micro-MRI is difficult to obtain. © 2018 International Society for Magnetic Resonance in Medicine.

[An improved low spectral distortion PCA fusion method].

PubMed

Peng, Shi; Zhang, Ai-Wu; Li, Han-Lun; Hu, Shao-Xing; Meng, Xian-Gang; Sun, Wei-Dong

2013-10-01

Aiming at the spectral distortion produced in PCA fusion process, the present paper proposes an improved low spectral distortion PCA fusion method. This method uses NCUT (normalized cut) image segmentation algorithm to make a complex hyperspectral remote sensing image into multiple sub-images for increasing the separability of samples, which can weaken the spectral distortions of traditional PCA fusion; Pixels similarity weighting matrix and masks were produced by using graph theory and clustering theory. These masks are used to cut the hyperspectral image and high-resolution image into some sub-region objects. All corresponding sub-region objects between the hyperspectral image and high-resolution image are fused by using PCA method, and all sub-regional integration results are spliced together to produce a new image. In the experiment, Hyperion hyperspectral data and Rapid Eye data were used. And the experiment result shows that the proposed method has the same ability to enhance spatial resolution and greater ability to improve spectral fidelity performance.

Non-contact high resolution Bessel beam probe for diagnostic imaging of cornea and trabecular meshwork region in eye

NASA Astrophysics Data System (ADS)

Murukeshan, V. M.; Jesmond, Hong Xun J.; Shinoj, V. K.; Baskaran, M.; Tin, Aung

2015-07-01

Primary angle closure glaucoma is a major form of disease that causes blindness in Asia and worldwide. In glaucoma, irregularities in the ocular aqueous outflow system cause an elevation in intraocular pressure (IOP) with subsequent death of retinal ganglion cells, resulting in loss of vision. High resolution visualization of the iridocorneal angle region has great diagnostic value in understanding the disease condition which enables monitoring of surgical interventions that decrease IOP. None of the current diagnostic techniques such as goniophotography, ultrasound biomicroscopy (UBM), anterior segment optical coherence tomography (AS-OCT) and RetCam™ can image with molecular specificity and required spatial resolution that can delineate the trabecular meshwork structures. This paper in this context proposes new concepts and methodology using Bessel beams based illumination and imaging for such diagnostic ocular imaging applications. The salient features using Bessel beams instead of the conventional Gaussian beam, and the optimization challenges in configuring the probe system will be illustrated with porcine eye samples.

Spatial Resolution Effect on Forest Road Gradient Calculation and Erosion Modelling

NASA Astrophysics Data System (ADS)

Cao, L.; Elliot, W.

2017-12-01

Road erosion is one of the main sediment sources in a forest watershed and should be properly evaluated. With the help of GIS technology, road topography can be determined and soil loss can be predicted at a watershed scale. As a vector geographical feature, the road gradient should be calculated following road direction rather than hillslope direction. This calculation might be difficult with a coarse (30-m) DEM which only provides the underlying topography information. This study was designed to explore the effect of road segmentation and DEM resolution on the road gradient calculation and erosion prediction at a watershed scale. The Water Erosion Prediction Project (WEPP) model was run on road segments of 9 lengths ranging from 40m to 200m. Road gradient was calculated from three DEM data sets: 1m LiDAR, and 10m and 30m USGS DEMs. The 1m LiDAR DEM calculated gradients were very close to the field observed road gradients, so we assumed the 1m LiDAR DEM predicted the true road gradient. The results revealed that longer road segments skipped detail topographical undulations and resulted in lower road gradients. Coarser DEMs computed steeper road gradients as larger grid cells covered more adjacent areas outside road resulting in larger elevation differences. Field surveyed results also revealed that coarser DEM might result in more gradient deviation in a curved road segment when it passes through a convex or concave slope. As road segment length increased, the gradient difference between three DEMs was reduced. There were no significant differences between road gradients of different segment lengths and DEM resolution when segments were longer than 100m. For long segments, the 10m DEM calculated road gradient was similar to the 1m LiDAR gradient. When evaluating the effects of road segment length, the predicted erosion rate decreased with increasing length when road gradient was less than 3%. In cases where the road gradients exceed 3% and rill erosion dominates, predicted erosion rates exponentially increased with segment length. At the watershed scale, most of the predicted soil loss occurred on segments with gradients ranging from 3% to 9%. Based on the road gradient calculated with the 10-m and 30-m DEMs, soil loss was overestimated when compared to the 1m LiDAR DEM. Both the 10m and 30m DEM result in similar total road soil loss.

Nondestructive analysis of automotive paints with spectral domain optical coherence tomography.

PubMed

Dong, Yue; Lawman, Samuel; Zheng, Yalin; Williams, Dominic; Zhang, Jinke; Shen, Yao-Chun

2016-05-01

We have demonstrated for the first time, to our knowledge, the use of optical coherence tomography (OCT) as an analytical tool for nondestructively characterizing the individual paint layer thickness of multiple layered automotive paints. A graph-based segmentation method was used for automatic analysis of the thickness distribution for the top layers of solid color paints. The thicknesses measured with OCT were in good agreement with the optical microscope and ultrasonic techniques that are the current standard in the automobile industry. Because of its high axial resolution (5.5 μm), the OCT technique was shown to be able to resolve the thickness of individual paint layers down to 11 μm. With its high lateral resolution (12.4 μm), the OCT system was also able to measure the cross-sectional area of the aluminum flakes in a metallic automotive paint. The range of values measured was 300-1850  μm². In summary, the proposed OCT is a noncontact, high-resolution technique that has the potential for inclusion as part of the quality assurance process in automobile coating.

SU-F-J-93: Automated Segmentation of High-Resolution 3D WholeBrain Spectroscopic MRI for Glioblastoma Treatment Planning

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

Schreibmann, E; Shu, H; Cordova, J

Purpose: We report on an automated segmentation algorithm for defining radiation therapy target volumes using spectroscopic MR images (sMRI) acquired at nominal voxel resolution of 100 microliters. Methods: Wholebrain sMRI combining 3D echo-planar spectroscopic imaging, generalized auto-calibrating partially-parallel acquisitions, and elliptical k-space encoding were conducted on 3T MRI scanner with 32-channel head coil array creating images. Metabolite maps generated include choline (Cho), creatine (Cr), and N-acetylaspartate (NAA), as well as Cho/NAA, Cho/Cr, and NAA/Cr ratio maps. Automated segmentation was achieved by concomitantly considering sMRI metabolite maps with standard contrast enhancing (CE) imaging in a pipeline that first uses the watermore » signal for skull stripping. Subsequently, an initial blob of tumor region is identified by searching for regions of FLAIR abnormalities that also display reduced NAA activity using a mean ratio correlation and morphological filters. These regions are used as starting point for a geodesic level-set refinement that adapts the initial blob to the fine details specific to each metabolite. Results: Accuracy of the segmentation model was tested on a cohort of 12 patients that had sMRI datasets acquired pre, mid and post-treatment, providing a broad range of enhancement patterns. Compared to classical imaging, where heterogeneity in the tumor appearance and shape across posed a greater challenge to the algorithm, sMRI’s regions of abnormal activity were easily detected in the sMRI metabolite maps when combining the detail available in the standard imaging with the local enhancement produced by the metabolites. Results can be imported in the treatment planning, leading in general increase in the target volumes (GTV60) when using sMRI+CE MRI compared to the standard CE MRI alone. Conclusion: Integration of automated segmentation of sMRI metabolite maps into planning is feasible and will likely streamline acceptance of this new acquisition modality in clinical practice.« less

Pupil-segmentation-based adaptive optics for microscopy

NASA Astrophysics Data System (ADS)

Ji, Na; Milkie, Daniel E.; Betzig, Eric

2011-03-01

Inhomogeneous optical properties of biological samples make it difficult to obtain diffraction-limited resolution in depth. Correcting the sample-induced optical aberrations needs adaptive optics (AO). However, the direct wavefront-sensing approach commonly used in astronomy is not suitable for most biological samples due to their strong scattering of light. We developed an image-based AO approach that is insensitive to sample scattering. By comparing images of the sample taken with different segments of the pupil illuminated, local tilt in the wavefront is measured from image shift. The aberrated wavefront is then obtained either by measuring the local phase directly using interference or with phase reconstruction algorithms similar to those used in astronomical AO. We implemented this pupil-segmentation-based approach in a two-photon fluorescence microscope and demonstrated that diffraction-limited resolution can be recovered from nonbiological and biological samples.

Finite element analysis of human joints

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

Bossart, P.L.; Hollerbach, K.

1996-09-01

Our work focuses on the development of finite element models (FEMs) that describe the biomechanics of human joints. Finite element modeling is becoming a standard tool in industrial applications. In highly complex problems such as those found in biomechanics research, however, the full potential of FEMs is just beginning to be explored, due to the absence of precise, high resolution medical data and the difficulties encountered in converting these enormous datasets into a form that is usable in FEMs. With increasing computing speed and memory available, it is now feasible to address these challenges. We address the first by acquiringmore » data with a high resolution C-ray CT scanner and the latter by developing semi-automated method for generating the volumetric meshes used in the FEM. Issues related to tomographic reconstruction, volume segmentation, the use of extracted surfaces to generate volumetric hexahedral meshes, and applications of the FEM are described.« less

Alignment and Distortion-Free Integration of Lightweight Mirrors into Meta-Shells for High-Resolution Astronomical X-Ray Optics

NASA Technical Reports Server (NTRS)

Chan, Kai-Wing; Zhang, William W.; Schofield, Mark J.; Numata, Ai; Mazzarella, James R.; Saha, Timo T.; Biskach, Michael P.; McCelland, Ryan S.; Niemeyer, Jason; Sharpe, Marton V.;

Thin Shell, Segmented X-Ray Mirrors

NASA Technical Reports Server (NTRS)

Petre, Robert

2010-01-01

Thin foil mirrors were introduced as a means of achieving high throughput in an X-ray astronomical imaging system in applications for which high angular resolution were not necessary. Since their introduction, their high filling factor, modest mass, relative ease of construction, and modest cost have led to their use in numerous X-ray observatories, including the Broad Band X-ray Telescope, ASCA, and Suzaku. The introduction of key innovations, including epoxy replicated surfaces, multilayer coatings, and glass mirror substrates, has led to performance improvements, and in their becoming widely used for X-ray astronomical imaging at energies above 10 keV. The use of glass substrates has also led to substantial improvement in angular resolution, and thus their incorporation into the NASA concept for the International X-ray Observatory with a planned 3 in diameter aperture. This paper traces the development of foil mirrors from their inception in the 1970's through their current and anticipated future applications.

Bone suppression in CT angiography data by region-based multiresolution segmentation

NASA Astrophysics Data System (ADS)

Blaffert, Thomas; Wiemker, Rafael; Lin, Zhong Min

2003-05-01

Multi slice CT (MSCT) scanners have the advantage of high and isotropic image resolution, which broadens the range of examinations for CT angiography (CTA). A very important method to present the large amount of high-resolution 3D data is the visualization by maximum intensity projections (MIP). A problem with MIP projections in angiography is that bones often hide the vessels of interest, especially the scull and vertebral column. Software tools for a manual selection of bone regions and their suppression in the MIP are available, but processing is time-consuming and tedious. A highly computer-assisted of even fully automated suppression of bones would considerably speed up the examination and probably increase the number of examined cases. In this paper we investigate the suppression (or removal) of bone regions in 3D CT data sets for vascular examinations of the head with a visualization of the carotids and the circle of Willis.

Late summer sea ice segmentation with multi-polarisation SAR features in C- and X-band

NASA Astrophysics Data System (ADS)

Fors, A. S.; Brekke, C.; Doulgeris, A. P.; Eltoft, T.; Renner, A. H. H.; Gerland, S.

2015-09-01

In this study we investigate the potential of sea ice segmentation by C- and X-band multi-polarisation synthetic aperture radar (SAR) features during late summer. Five high-resolution satellite SAR scenes were recorded in the Fram Strait covering iceberg-fast first-year and old sea ice during a week with air temperatures varying around zero degrees Celsius. In situ data consisting of sea ice thickness, surface roughness and aerial photographs were collected during a helicopter flight at the site. Six polarimetric SAR features were extracted for each of the scenes. The ability of the individual SAR features to discriminate between sea ice types and their temporally consistency were examined. All SAR features were found to add value to sea ice type discrimination. Relative kurtosis, geometric brightness, cross-polarisation ratio and co-polarisation correlation angle were found to be temporally consistent in the investigated period, while co-polarisation ratio and co-polarisation correlation magnitude were found to be temporally inconsistent. An automatic feature-based segmentation algorithm was tested both for a full SAR feature set, and for a reduced SAR feature set limited to temporally consistent features. In general, the algorithm produces a good late summer sea ice segmentation. Excluding temporally inconsistent SAR features improved the segmentation at air temperatures above zero degrees Celcius.

A diabetic retinopathy detection method using an improved pillar K-means algorithm.

PubMed

Gogula, Susmitha Valli; Divakar, Ch; Satyanarayana, Ch; Rao, Allam Appa

2014-01-01

The paper presents a new approach for medical image segmentation. Exudates are a visible sign of diabetic retinopathy that is the major reason of vision loss in patients with diabetes. If the exudates extend into the macular area, blindness may occur. Automated detection of exudates will assist ophthalmologists in early diagnosis. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after getting optimized by Pillar algorithm; pillars are constructed in such a way that they can withstand the pressure. Improved pillar algorithm can optimize the K-means clustering for image segmentation in aspects of precision and computation time. This evaluates the proposed approach for image segmentation by comparing with Kmeans and Fuzzy C-means in a medical image. Using this method, identification of dark spot in the retina becomes easier and the proposed algorithm is applied on diabetic retinal images of all stages to identify hard and soft exudates, where the existing pillar K-means is more appropriate for brain MRI images. This proposed system help the doctors to identify the problem in the early stage and can suggest a better drug for preventing further retinal damage.

Spectral-spatial classification of hyperspectral data with mutual information based segmented stacked autoencoder approach

NASA Astrophysics Data System (ADS)

Paul, Subir; Nagesh Kumar, D.

2018-04-01

Hyperspectral (HS) data comprises of continuous spectral responses of hundreds of narrow spectral bands with very fine spectral resolution or bandwidth, which offer feature identification and classification with high accuracy. In the present study, Mutual Information (MI) based Segmented Stacked Autoencoder (S-SAE) approach for spectral-spatial classification of the HS data is proposed to reduce the complexity and computational time compared to Stacked Autoencoder (SAE) based feature extraction. A non-parametric dependency measure (MI) based spectral segmentation is proposed instead of linear and parametric dependency measure to take care of both linear and nonlinear inter-band dependency for spectral segmentation of the HS bands. Then morphological profiles are created corresponding to segmented spectral features to assimilate the spatial information in the spectral-spatial classification approach. Two non-parametric classifiers, Support Vector Machine (SVM) with Gaussian kernel and Random Forest (RF) are used for classification of the three most popularly used HS datasets. Results of the numerical experiments carried out in this study have shown that SVM with a Gaussian kernel is providing better results for the Pavia University and Botswana datasets whereas RF is performing better for Indian Pines dataset. The experiments performed with the proposed methodology provide encouraging results compared to numerous existing approaches.

The effects of transient attention on spatial resolution and the size of the attentional cue.

PubMed

Yeshurun, Yaffa; Carrasco, Marisa

2008-01-01

It has been shown that transient attention enhances spatial resolution, but is the effect of transient attention on spatial resolution modulated by the size of the attentional cue? Would a gradual increase in the size of the cue lead to a gradual decrement in spatial resolution? To test these hypotheses, we used a texture segmentation task in which performance depends on spatial resolution, and systematically manipulated the size of the attentional cue: A bar of different lengths (Experiment 1) or a frame of different sizes (Experiments 2-3) indicated the target region in a texture segmentation display. Observers indicated whether a target patch region (oriented line elements in a background of an orthogonal orientation), appearing at a range of eccentricities, was present in the first or the second interval. We replicated the attentional enhancement of spatial resolution found with small cues; attention improved performance at peripheral locations but impaired performance at central locations. However, there was no evidence of gradual resolution decrement with large cues. Transient attention enhanced spatial resolution at the attended location when it was attracted to that location by a small cue but did not affect resolution when it was attracted by a large cue. These results indicate that transient attention cannot adapt its operation on spatial resolution on the basis of the size of the attentional cue.

Enhancement pattern of the normal facial nerve at 3.0 T temporal MRI.

PubMed

Hong, H S; Yi, B-H; Cha, J-G; Park, S-J; Kim, D H; Lee, H K; Lee, J-D

2010-02-01

The purpose of this study was to evaluate the enhancement pattern of the normal facial nerve at 3.0 T temporal MRI. We reviewed the medical records of 20 patients and evaluated 40 clinically normal facial nerves demonstrated by 3.0 T temporal MRI. The grade of enhancement of the facial nerve was visually scaled from 0 to 3. The patients comprised 11 men and 9 women, and the mean age was 39.7 years. The reasons for the MRI were sudden hearing loss (11 patients), Méniàre's disease (6) and tinnitus (7). Temporal MR scans were obtained by fluid-attenuated inversion-recovery (FLAIR) and diffusion-weighted imaging of the brain; three-dimensional (3D) fast imaging employing steady-state acquisition (FIESTA) images of the temporal bone with a 0.77 mm thickness, and pre-contrast and contrast-enhanced 3D spoiled gradient record acquisition in the steady state (SPGR) of the temporal bone with a 1 mm thickness, were obtained with 3.0 T MR scanning. 40 nerves (100%) were visibly enhanced along at least one segment of the facial nerve. The enhanced segments included the geniculate ganglion (77.5%), tympanic segment (37.5%) and mastoid segment (100%). Even the facial nerve in the internal auditory canal (15%) and labyrinthine segments (5%) showed mild enhancement. The use of high-resolution, high signal-to-noise ratio (with 3 T MRI), thin-section contrast-enhanced 3D SPGR sequences showed enhancement of the normal facial nerve along the whole course of the nerve; however, only mild enhancement was observed in areas associated with acute neuritis, namely the canalicular and labyrinthine segment.

Variation in center of mass estimates for extant sauropsids and its importance for reconstructing inertial properties of extinct archosaurs.

PubMed

Allen, Vivian; Paxton, Heather; Hutchinson, John R

2009-09-01

Inertial properties of animal bodies and segments are critical input parameters for biomechanical analysis of standing and moving, and thus are important for paleobiological inquiries into the broader behaviors, ecology and evolution of extinct taxa such as dinosaurs. But how accurately can these be estimated? Computational modeling was used to estimate the inertial properties including mass, density, and center of mass (COM) for extant crocodiles (adult and juvenile Crocodylus johnstoni) and birds (Gallus gallus; junglefowl and broiler chickens), to identify the chief sources of variation and methodological errors, and their significance. High-resolution computed tomography scans were segmented into 3D objects and imported into inertial property estimation software that allowed for the examination of variable body segment densities (e.g., air spaces such as lungs, and deformable body outlines). Considerable biological variation of inertial properties was found within groups due to ontogenetic changes as well as evolutionary changes between chicken groups. COM positions shift in variable directions during ontogeny in different groups. Our method was repeatable and the resolution was sufficient for accurate estimations of mass and density in particular. However, we also found considerable potential methodological errors for COM related to (1) assumed body segment orientation, (2) what frames of reference are used to normalize COM for size-independent comparisons among animals, and (3) assumptions about tail shape. Methods and assumptions are suggested to minimize these errors in the future and thereby improve estimation of inertial properties for extant and extinct animals. In the best cases, 10%-15% errors in these estimates are unavoidable, but particularly for extinct taxa errors closer to 50% should be expected, and therefore, cautiously investigated. Nonetheless in the best cases these methods allow rigorous estimation of inertial properties. (c) 2009 Wiley-Liss, Inc.

Charge Collection Efficiency in a segmented semiconductor detector interstrip region

NASA Astrophysics Data System (ADS)

Alarcon-Diez, V.; Vickridge, I.; Jakšić, M.; Grilj, V.; Schmidt, B.; Lange, H.

2017-09-01

Charged particle semiconductor detectors have been used in Ion Beam Analysis (IBA) for over four decades without great changes in either design or fabrication. However one area where improvement is desirable would be to increase the detector solid angle so as to improve spectrum statistics for a given incident beam fluence. This would allow the use of very low fluences opening the way, for example, to increase the time resolution in real-time RBS or for analysis of materials that are highly sensitive to beam damage. In order to achieve this goal without incurring the costs of degraded resolution due to kinematic broadening or large detector capacitance, a single-chip segmented detector (SEGDET) was designed and built within the SPIRIT EU infrastructure project. In this work we present the Charge Collection Efficiency (CCE) in the vicinity between two adjacent segments focusing on the interstrip zone. Microbeam Ion Beam Induced Charge (IBIC) measurements with different ion masses and energies were used to perform X-Y mapping of (CCE), as a function of detector operating conditions (bias voltage changes, detector housing possibilities and guard ring configuration). We show the (CCE) in the edge region of the active area and have also mapped the charge from the interstrip region, shared between adjacent segments. The results indicate that the electrical extent of the interstrip region is very close to the physical extent of the interstrip and guard ring structure with interstrip impacts contributing very little to the complete spectrum. The interstrip contributions to the spectra that do occur, can be substantially reduced by an offline anti-coincidence criterion applied to list mode data, which should also be easy to implement directly in the data acquisition software.

Digital Mapping and Environmental Characterization of National Wild and Scenic River Systems

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

McManamay, Ryan A; Bosnall, Peter; Hetrick, Shelaine L

2013-09-01

Spatially accurate geospatial information is required to support decision-making regarding sustainable future hydropower development. Under a memorandum of understanding among several federal agencies, a pilot study was conducted to map a subset of National Wild and Scenic Rivers (WSRs) at a higher resolution and provide a consistent methodology for mapping WSRs across the United States and across agency jurisdictions. A subset of rivers (segments falling under the jurisdiction of the National Park Service) were mapped at a high resolution using the National Hydrography Dataset (NHD). The spatial extent and representation of river segments mapped at NHD scale were compared withmore » the prevailing geospatial coverage mapped at a coarser scale. Accurately digitized river segments were linked to environmental attribution datasets housed within the Oak Ridge National Laboratory s National Hydropower Asset Assessment Program database to characterize the environmental context of WSR segments. The results suggest that both the spatial scale of hydrography datasets and the adherence to written policy descriptions are critical to accurately mapping WSRs. The environmental characterization provided information to deduce generalized trends in either the uniqueness or the commonness of environmental variables associated with WSRs. Although WSRs occur in a wide range of human-modified landscapes, environmental data layers suggest that they provide habitats important to terrestrial and aquatic organisms and recreation important to humans. Ultimately, the research findings herein suggest that there is a need for accurate, consistent, mapping of the National WSRs across the agencies responsible for administering each river. Geospatial applications examining potential landscape and energy development require accurate sources of information, such as data layers that portray realistic spatial representations.« less

Segmentation and tracking of anticyclonic eddies during a submarine volcanic eruption using ocean colour imagery.

PubMed

Marcello, Javier; Eugenio, Francisco; Estrada-Allis, Sheila; Sangrà, Pablo

2015-04-14

The eruptive phase of a submarine volcano located 2 km away from the southern coast of El Hierro Island started on October 2011. This extraordinary event provoked a dramatic perturbation of the water column. In order to understand and quantify the environmental impacts caused, a regular multidisciplinary monitoring was carried out using remote sensing sensors. In this context, we performed the systematic processing of every MODIS and MERIS and selected high resolution Worldview-2 imagery to provide information on the concentration of a number of biological, physical and chemical parameters. On the other hand, the eruption provided an exceptional source of tracer that allowed the study a variety of oceanographic structures. Specifically, the Canary Islands belong to a very active zone of long-lived eddies. Such structures are usually monitored using sea level anomaly fields. However these products have coarse spatial resolution and they are not suitable to perform submesoscale studies. Thanks to the volcanic tracer, detailed studies were undertaken with ocean colour imagery allowing, using the diffuse attenuation coefficient, to monitor the process of filamentation and axisymmetrization predicted by theoretical studies and numerical modelling. In our work, a novel 2-step segmentation methodology has been developed. The approach incorporates different segmentation algorithms and region growing techniques. In particular, the first step obtains an initial eddy segmentation using thresholding or clustering methods and, next, the fine detail is achieved by the iterative identification of the points to grow and the subsequent application of watershed or thresholding strategies. The methodology has demonstrated an excellent performance and robustness and it has proven to properly capture the eddy and its filaments.

Segmentation of arterial vessel wall motion to sub-pixel resolution using M-mode ultrasound.

PubMed

Fancourt, Craig; Azer, Karim; Ramcharan, Sharmilee L; Bunzel, Michelle; Cambell, Barry R; Sachs, Jeffrey R; Walker, Matthew

2008-01-01

We describe a method for segmenting arterial vessel wall motion to sub-pixel resolution, using the returns from M-mode ultrasound. The technique involves measuring the spatial offset between all pairs of scans from their cross-correlation, converting the spatial offsets to relative wall motion through a global optimization, and finally translating from relative to absolute wall motion by interpolation over the M-mode image. The resulting detailed wall distension waveform has the potential to enhance existing vascular biomarkers, such as strain and compliance, as well as enable new ones.

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

PubMed

Wang, Jun Yi; Ngo, Michael M; Hessl, David; Hagerman, Randi J; Rivera, Susan M

2016-01-01

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well.

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem

PubMed Central

Wang, Jun Yi; Ngo, Michael M.; Hessl, David; Hagerman, Randi J.; Rivera, Susan M.

2016-01-01

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer’s segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well. PMID:27213683

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

PubMed

Rajab, Maher I

2011-11-01

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

Consistent interactive segmentation of pulmonary ground glass nodules identified in CT studies

NASA Astrophysics Data System (ADS)

Zhang, Li; Fang, Ming; Naidich, David P.; Novak, Carol L.

2004-05-01

Ground glass nodules (GGNs) have proved especially problematic in lung cancer diagnosis, as despite frequently being malignant they characteristically have extremely slow rates of growth. This problem is further magnified by the small size of many of these lesions now being routinely detected following the introduction of multislice CT scanners capable of acquiring contiguous high resolution 1 to 1.25 mm sections throughout the thorax in a single breathhold period. Although segmentation of solid nodules can be used clinically to determine volume doubling times quantitatively, reliable methods for segmentation of pure ground glass nodules have yet to be introduced. Our purpose is to evaluate a newly developed computer-based segmentation method for rapid and reproducible measurements of pure ground glass nodules. 23 pure or mixed ground glass nodules were identified in a total of 8 patients by a radiologist and subsequently segmented by our computer-based method using Markov random field and shape analysis. The computer-based segmentation was initialized by a click point. Methodological consistency was assessed using the overlap ratio between 3 segmentations initialized by 3 different click points for each nodule. The 95% confidence interval on the mean of the overlap ratios proved to be [0.984, 0.998]. The computer-based method failed on two nodules that were difficult to segment even manually either due to especially low contrast or markedly irregular margins. While achieving consistent manual segmentation of ground glass nodules has proven problematic most often due to indistinct boundaries and interobserver variability, our proposed method introduces a powerful new tool for obtaining reproducible quantitative measurements of these lesions. It is our intention to further document the value of this approach with a still larger set of ground glass nodules.

Bone architecture adaptations after spinal cord injury: impact of long-term vibration of a constrained lower limb.

PubMed

Dudley-Javoroski, S; Petrie, M A; McHenry, C L; Amelon, R E; Saha, P K; Shields, R K

2016-03-01

This study examined the effect of a controlled dose of vibration upon bone density and architecture in people with spinal cord injury (who eventually develop severe osteoporosis). Very sensitive computed tomography (CT) imaging revealed no effect of vibration after 12 months, but other doses of vibration may still be useful to test. The purposes of this report were to determine the effect of a controlled dose of vibratory mechanical input upon individual trabecular bone regions in people with chronic spinal cord injury (SCI) and to examine the longitudinal bone architecture changes in both the acute and chronic state of SCI. Participants with SCI received unilateral vibration of the constrained lower limb segment while sitting in a wheelchair (0.6g, 30 Hz, 20 min, three times weekly). The opposite limb served as a control. Bone mineral density (BMD) and trabecular micro-architecture were measured with high-resolution multi-detector CT. For comparison, one participant was studied from the acute (0.14 year) to the chronic state (2.7 years). Twelve months of vibration training did not yield adaptations of BMD or trabecular micro-architecture for the distal tibia or the distal femur. BMD and trabecular network length continued to decline at several distal femur sub-regions, contrary to previous reports suggesting a "steady state" of bone in chronic SCI. In the participant followed from acute to chronic SCI, BMD and architecture decline varied systematically across different anatomical segments of the tibia and femur. This study supports that vibration training, using this study's dose parameters, is not an effective anti-osteoporosis intervention for people with chronic SCI. Using a high-spatial-resolution CT methodology and segmental analysis, we illustrate novel longitudinal changes in bone that occur after spinal cord injury.

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

PubMed Central

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

2012-01-01

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

Development of a high temporal-spatial resolution vehicle emission inventory based on NRT traffic data and its impact on air pollution in Beijing - Part 1: Development and evaluation of vehicle emission inventory

NASA Astrophysics Data System (ADS)

Jing, B. Y.; Wu, L.; Mao, H. J.; Gong, S. L.; He, J. J.; Zou, C.; Song, G. H.; Li, X. Y.; Wu, Z.

2015-10-01

As the ownership of vehicles and frequency of utilization increase, vehicle emissions have become an important source of air pollution in Chinese cities. An accurate emission inventory for on-road vehicles is necessary for numerical air quality simulation and the assessment of implementation strategies. This paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near real time (NRT) traffic data on road segments to develop a high temporal-spatial resolution vehicle emission inventory (HTSVE) for the urban Beijing area. To simulate real-world vehicle emissions accurately, the road has been divided into segments according to the driving cycle (traffic speed) on this road segment. The results show that the vehicle emissions of NOx, CO, HC and PM were 10.54 × 104, 42.51 × 104 and 2.13 × 104 and 0.41 × 104 Mg, respectively. The vehicle emissions and fuel consumption estimated by the model were compared with the China Vehicle Emission Control Annual Report and fuel sales thereafter. The grid-based emissions were also compared with the vehicular emission inventory developed by the macro-scale approach. This method indicates that the bottom-up approach better estimates the levels and spatial distribution of vehicle emissions than the macro-scale method, which relies on more information. Additionally, the on-road vehicle emission inventory model and control effect assessment system in Beijing, a vehicle emission inventory model, was established based on this study in a companion paper (He et al., 2015).

Continuous on-line monitoring of left ventricular function with a new nonimaging detector:validation and clinical use in the evaluation of patients post angioplasty.

PubMed

Breisblatt, W M; Schulman, D S; Follansbee, W P

1991-06-01

A new miniaturized nonimaging radionuclide detector (Cardioscint, Oxford, England) was evaluated for the continuous on-line assessment of left ventricular function. This cesium iodide probe can be placed on the patient's chest and can be interfaced to an IBM compatible personal computer conveniently placed at the patient's bedside. This system can provide a beat-to-beat or gated determination of left ventricular ejection fraction and ST segment analysis. In 28 patients this miniaturized probe was correlated against a high resolution gamma camera study. Over a wide range of ejection fraction (31% to 76%) in patients with and without regional wall motion abnormalities, the correlation between the Cardioscint detector and the gamma camera was excellent (r = 0.94, SEE +/- 2.1). This detector system has high temporal (10 msec) resolution, and comparison of peak filling rate (PFR) and time to peak filling (TPFR) also showed close agreement with the gamma camera (PFR, r = 0.94, SEE +/- 0.17; TPFR, r = 0.92, SEE +/- 6.8). In 18 patients on bed rest the long-term stability of this system for measuring ejection fraction and ST segments was verified. During the monitoring period (108 +/- 28 minutes) only minor changes in ejection fraction occurred (coefficient of variation 0.035 +/- 0.016) and ST segment analysis showed no significant change from baseline. To determine whether continuous on-line measurement of ejection fraction would be useful after coronary angioplasty, 12 patients who had undergone a successful procedure were evaluated for 280 +/- 35 minutes with the Cardioscint system.(ABSTRACT TRUNCATED AT 250 WORDS)

Image analysis driven single-cell analytics for systems microbiology.

PubMed

Balomenos, Athanasios D; Tsakanikas, Panagiotis; Aspridou, Zafiro; Tampakaki, Anastasia P; Koutsoumanis, Konstantinos P; Manolakos, Elias S

2017-04-04

Time-lapse microscopy is an essential tool for capturing and correlating bacterial morphology and gene expression dynamics at single-cell resolution. However state-of-the-art computational methods are limited in terms of the complexity of cell movies that they can analyze and lack of automation. The proposed Bacterial image analysis driven Single Cell Analytics (BaSCA) computational pipeline addresses these limitations thus enabling high throughput systems microbiology. BaSCA can segment and track multiple bacterial colonies and single-cells, as they grow and divide over time (cell segmentation and lineage tree construction) to give rise to dense communities with thousands of interacting cells in the field of view. It combines advanced image processing and machine learning methods to deliver very accurate bacterial cell segmentation and tracking (F-measure over 95%) even when processing images of imperfect quality with several overcrowded colonies in the field of view. In addition, BaSCA extracts on the fly a plethora of single-cell properties, which get organized into a database summarizing the analysis of the cell movie. We present alternative ways to analyze and visually explore the spatiotemporal evolution of single-cell properties in order to understand trends and epigenetic effects across cell generations. The robustness of BaSCA is demonstrated across different imaging modalities and microscopy types. BaSCA can be used to analyze accurately and efficiently cell movies both at a high resolution (single-cell level) and at a large scale (communities with many dense colonies) as needed to shed light on e.g. how bacterial community effects and epigenetic information transfer play a role on important phenomena for human health, such as biofilm formation, persisters' emergence etc. Moreover, it enables studying the role of single-cell stochasticity without losing sight of community effects that may drive it.

Reliability and repeatability of swept-source Fourier-domain optical coherence tomography and Scheimpflug imaging in keratoconus.

PubMed

Szalai, Eszter; Berta, András; Hassan, Ziad; Módis, László

2012-03-01

To evaluate the repeatability and reliability of a recently introduced swept-source Fourier-domain anterior segment optical coherence tomography (AS-OCT) system and a high-resolution Scheimpflug camera and to assess the agreement between the 2 instruments when measuring healthy eyes and eyes with keratoconus. Department of Ophthalmology, Medical and Health Science Center, University of Debrecen, Debrecen, Hungary. Evaluation of diagnostic test or technology. Three consecutive series of anterior segment images were taken with AS-OCT (Casia SS-1000) followed by rotating Scheimpflug imaging (Pentacam high resolution). Axial keratometry in the steep and flat meridians and astigmatism values were recorded. Pachymetry in the apex, center, and the thinnest position and anterior chamber depth (ACD) measurements were also taken. This study enrolled 57 healthy volunteers (57 eyes) and 56 patients (84 eyes) with keratoconus. Significant difference was found in all measured anterior segment parameters between normal eyes and keratoconic eyes (P<.05). In keratoconic eyes, the difference between repeated measurements was less with AS-OCT than with Scheimpflug imaging in every keratometry and astigmatism value, in apical thickness, and in ACD. For keratometry, the thinnest and central pachymetry measurement repeatability was better in healthy eyes than in keratoconic eyes with both instruments. In general, the mean difference between AS-OCT and Scheimpflug imaging was higher in cases of keratoconus. Significant differences in keratometry, pachymetry, and ACD results were found between AS-OCT and Scheimpflug imaging. However, the repeatability of the measurements was comparable. No author has a financial or proprietary interest in any material or method mentioned. Copyright © 2012 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

A new method of inshore ship detection in high-resolution optical remote sensing images

NASA Astrophysics Data System (ADS)

Hu, Qifeng; Du, Yaling; Jiang, Yunqiu; Ming, Delie

2015-10-01

Ship as an important military target and water transportation, of which the detection has great significance. In the military field, the automatic detection of ships can be used to monitor ship dynamic in the harbor and maritime of enemy, and then analyze the enemy naval power. In civilian field, the automatic detection of ships can be used in monitoring transportation of harbor and illegal behaviors such as illegal fishing, smuggling and pirates, etc. In recent years, research of ship detection is mainly concentrated in three categories: forward-looking infrared images, downward-looking SAR image, and optical remote sensing images with sea background. Little research has been done into ship detection of optical remote sensing images with harbor background, as the gray-scale and texture features of ships are similar to the coast in high-resolution optical remote sensing images. In this paper, we put forward an effective harbor ship target detection method. First of all, in order to overcome the shortage of the traditional difference method in obtaining histogram valley as the segmentation threshold, we propose an iterative histogram valley segmentation method which separates the harbor and ships from the water quite well. Secondly, as landing ships in optical remote sensing images usually lead to discontinuous harbor edges, we use Hough Transform method to extract harbor edges. First, lines are detected by Hough Transform. Then, lines that have similar slope are connected into a new line, thus we access continuous harbor edges. Secondary segmentation on the result of the land-and-sea separation, we eventually get the ships. At last, we calculate the aspect ratio of the ROIs, thereby remove those targets which are not ship. The experiment results show that our method has good robustness and can tolerate a certain degree of noise and occlusion.

Studying Spatial Resolution of CZT Detectors Using Sub-Pixel Positioning for SPECT

NASA Astrophysics Data System (ADS)

Montémont, Guillaume; Lux, Silvère; Monnet, Olivier; Stanchina, Sylvain; Verger, Loïck

2014-10-01

CZT detectors are the basic building block of a variety of new SPECT systems. Their modularity allows adapting system architecture to specific applications such as cardiac, breast, brain or small animal imaging. In semiconductors, a high number of electron-hole pairs is produced by a single interaction. This direct conversion process allows better energy and spatial resolutions than usual scintillation detectors based on NaI(Tl). However, it remains often unclear if SPECT imaging can really benefit of that performance gain. We investigate the system performance of a detection module, which is based on 5 mm thick CZT with a segmented anode having a 2.5 mm pitch by simulation and experimentation. This pitch allows an easy assembly of the crystal on the readout board and limits the space occupied by electronics without significantly degrading energy and spatial resolution.

The initiation of segmented buoyancy-driven melting during continental breakup

PubMed Central

Gallacher, Ryan J.; Keir, Derek; Harmon, Nicholas; Stuart, Graham; Leroy, Sylvie; Hammond, James O. S.; Kendall, J-Michael; Ayele, Atalay; Goitom, Berhe; Ogubazghi, Ghebrebrhan; Ahmed, Abdulhakim

2016-01-01

Melting of the mantle during continental breakup leads to magmatic intrusion and volcanism, yet our understanding of the location and dominant mechanisms of melt generation in rifting environments is impeded by a paucity of direct observations of mantle melting. It is unclear when during the rifting process the segmented nature of magma supply typical of seafloor spreading initiates. Here, we use Rayleigh-wave tomography to construct a high-resolution absolute three-dimensional shear-wave velocity model of the upper 250 km beneath the Afar triple junction, imaging the mantle response during progressive continental breakup. Our model suggests melt production is highest and melting depths deepest early during continental breakup. Elevated melt production during continental rifting is likely due to localized thinning and melt focusing when the rift is narrow. In addition, we interpret segmented zones of melt supply beneath the rift, suggesting that buoyancy-driven active upwelling of the mantle initiates early during continental rifting. PMID:27752044

Automated segmentation of retinal pigment epithelium cells in fluorescence adaptive optics images.

PubMed

Rangel-Fonseca, Piero; Gómez-Vieyra, Armando; Malacara-Hernández, Daniel; Wilson, Mario C; Williams, David R; Rossi, Ethan A

2013-12-01

Adaptive optics (AO) imaging methods allow the histological characteristics of retinal cell mosaics, such as photoreceptors and retinal pigment epithelium (RPE) cells, to be studied in vivo. The high-resolution images obtained with ophthalmic AO imaging devices are rich with information that is difficult and/or tedious to quantify using manual methods. Thus, robust, automated analysis tools that can provide reproducible quantitative information about the cellular mosaics under examination are required. Automated algorithms have been developed to detect the position of individual photoreceptor cells; however, most of these methods are not well suited for characterizing the RPE mosaic. We have developed an algorithm for RPE cell segmentation and show its performance here on simulated and real fluorescence AO images of the RPE mosaic. Algorithm performance was compared to manual cell identification and yielded better than 91% correspondence. This method can be used to segment RPE cells for morphometric analysis of the RPE mosaic and speed the analysis of both healthy and diseased RPE mosaics.

Diagnostic accuracy and image quality of cardiac dual-source computed tomography in patients with arrhythmia.

PubMed

Tsiflikas, Ilias; Drosch, Tanja; Brodoefel, Harald; Thomas, Christoph; Reimann, Anja; Till, Alexander; Nittka, Daniel; Kopp, Andreas F; Schroeder, Stephen; Heuschmid, Martin; Burgstahler, Christof

2010-08-06

Cardiac multi-detector computed tomography (MDCT) permits accurate visualization of high-grade coronary artery stenosis. However, in patients with heart rate irregularities, MDCT was found to have limitations. Thus, the aim of the present study was to evaluate the diagnostic accuracy of a new dual-source computed tomography (DSCT) scanner generation with 83 ms temporal resolution in patients without stable sinus rhythm. 44 patients (31 men, mean age 67.5+/-9.2 years) without stable sinus rhythm and scheduled for invasive coronary angiography (ICA) because of suspected (n=17) or known coronary artery disease (CAD, n=27) were included in this study. All patients were examined with DSCT (Somatom Definition, Siemens). Besides assessment of total calcium score, all coronary segments were analyzed with regard to the presence of significant coronary artery lesions (>50%). The findings were compared to ICA in a blinded fashion. During CT examination, heart rhythm was as follows: 25 patients (57%) atrial fibrillation, 7 patients (16%) ventricular extrasystoles (two of them with atrial fibrillation), 4 patients (9%) supraventricular extrasystoles, 10 patients (23%) sinus arrhythmia (heart rate variability>10 bpm). Mean heart rate was 69+/-14 bpm, median 65 bpm. Mean Agatston score equivalent (ASE) was 762, ranging from 0 to 4949.7 ASE. Prevalence of CAD was 68% (30/44). 155 segments (27%) showed "step-ladder" artifacts and 28 segments (5%) could not be visualized by DSCT. Only 70 segments (12%) were completely imaged without any artifacts. Based on a coronary segment model, sensitivity was 73%, specificity 91%, positive predictive value 63%, and negative predictive value 94% for the detection of significant lesions (>or=50% diameter stenosis). Overall accuracy was 88%. In patients with heart rate irregularities, including patients with atrial fibrillation and a high prevalence of coronary artery disease, the diagnostic yield of dual-source computed tomography is still hampered due to a high number of segments with "step-ladder" artifacts. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Liebel, L.; Körner, M.

2016-06-01

In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

Arc-Second Alignment of International X-Ray Observatory Mirror Segments in a Fixed Structure

NASA Technical Reports Server (NTRS)

Evans, Tyler, C.; Chan, Kai-Wing; Saha, Timo T.

2010-01-01

The optics for the International X-Ray Observatory (IXO) require alignment and integration of about fourteen thousand thin mirror segments to achieve the mission goal of 3.0 square meters of effective area at 1.25 keV with an angular resolution of five arc-seconds. These mirror segments are 0.4 mm thick, and 200 to 400 mm in size, which makes it hard to meet the strict angular resolution requirement of 5 arc-seconds for the telescope. This paper outlines the precise alignment, verification testing, and permanent bonding techniques developed at NASA's Goddard Space Flight Center (GSFC). These techniques are used to overcome the challenge of transferring thin mirror segments from a temporary mount to a fixed structure with arc-second alignment and minimal figure distortion. Recent advances in technology development in addition to the automation of several processes have produced significant results. Recent advances in the mirror fixture process known as the suspension mount has allowed for a mirror to be mounted to a fixture with minimal distortion. Once on the fixture, mirror segments have been aligned to around 5 arc-seconds which is halfway to the goal of 2.5 arc-seconds per mirror segment. This paper will highlight the recent advances in alignment, testing, and permanent bonding techniques as well as the results they have produced.

Integration of High-resolution Data for Temporal Bone Surgical Simulations

PubMed Central

Wiet, Gregory J.; Stredney, Don; Powell, Kimerly; Hittle, Brad; Kerwin, Thomas

2016-01-01

Purpose To report on the state of the art in obtaining high-resolution 3D data of the microanatomy of the temporal bone and to process that data for integration into a surgical simulator. Specifically, we report on our experience in this area and discuss the issues involved to further the field. Data Sources Current temporal bone image acquisition and image processing established in the literature as well as in house methodological development. Review Methods We reviewed the current English literature for the techniques used in computer-based temporal bone simulation systems to obtain and process anatomical data for use within the simulation. Search terms included “temporal bone simulation, surgical simulation, temporal bone.” Articles were chosen and reviewed that directly addressed data acquisition and processing/segmentation and enhancement with emphasis given to computer based systems. We present the results from this review in relationship to our approach. Conclusions High-resolution CT imaging (≤100μm voxel resolution), along with unique image processing and rendering algorithms, and structure specific enhancement are needed for high-level training and assessment using temporal bone surgical simulators. Higher resolution clinical scanning and automated processes that run in efficient time frames are needed before these systems can routinely support pre-surgical planning. Additionally, protocols such as that provided in this manuscript need to be disseminated to increase the number and variety of virtual temporal bones available for training and performance assessment. PMID:26762105

MicroCT angiography detects vascular formation and regression in skin wound healing

PubMed Central

Urao, Norifumi; Okonkwo, Uzoagu A.; Fang, Milie M.; Zhuang, Zhen W.; Koh, Timothy J.; DiPietro, Luisa A.

2016-01-01

Properly regulated angiogenesis and arteriogenesis are essential for effective wound healing. Tissue injury induces robust new vessel formation and subsequent vessel maturation, which involves vessel regression and remodeling. Although formation of functional vasculature is essential for healing, alterations in vascular structure over the time course of skin wound healing are not well understood. Here, using high-resolution ex vivo X-ray micro-computed tomography (microCT), we describe the vascular network during healing of skin excisional wounds with highly detailed three-dimensional (3D) reconstructed images and associated quantitative analysis. We found that relative vessel volume, surface area and branching number are significantly decreased in wounds from day 7 to day 14 and 21. Segmentation and skeletonization analysis of selected branches from high-resolution images as small as 2.5 μm voxel size show that branching orders are decreased in the wound vessels during healing. In histological analysis, we found that the contrast agent fills mainly arterioles, but not small capillaries nor large veins. In summary, high-resolution microCT revealed dynamic alterations of vessel structures during wound healing. This technique may be useful as a key tool in the study of the formation and regression of wound vessels. PMID:27009591

High resolution CsI(Tl)/Si-PIN detector development for breast imaging

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

Patt, B.E.; Iwanczyk, J.S.; Tull, C.R.

High resolution multi-element (8x8) imaging arrays with collimators, size matched to discrete CsI(Tl) scintillator arrays and Si-PIN photodetector arrays (PDA`s) were developed as prototypes for larger arrays for breast imaging. Photodetector pixels were each 1.5 {times} 1.5 mm{sup 2} with 0.25 mm gaps. A 16-element quadrant of the detector was evaluated with a segmented CsI(Tl) scintillator array coupled to the silicon array. The scintillator thickness of 6 mm corresponds to >85% total gamma efficiency at 140 keV. Pixel energy resolution of <8% FWHM was obtained for Tc-99m. Electronic noise was 41 e{sup {minus}} RMS corresponding to a 3% FWHM contributionmore » to the 140 keV photopeak. Detection efficiency uniformity measured with a Tc-99m flood source was 4.3% for an {approximately}10% energy photopeak window. Spatial resolution was 1.53 mm FWHM and pitch was 1.75 mm as measured from the Co-57 (122 keV) line spread function. Signal to background was 34 and contrast was 0.94. The energy resolution and spatial characteristics of the new imaging detector exceed those of other scintillator based imaging detectors. A camera based on this technology will allow: (1) Improved Compton scatter rejection; (2) Detector positioning in close proximity to the breast to increase signal to noise; (3) Improved spatial resolution; and (4) Improved efficiency compared to high resolution collimated gamma cameras for the anticipated compressed breast geometries.« less

Study on Building Extraction from High-Resolution Images Using Mbi

NASA Astrophysics Data System (ADS)

Ding, Z.; Wang, X. Q.; Li, Y. L.; Zhang, S. S.

2018-04-01

Building extraction from high resolution remote sensing images is a hot research topic in the field of photogrammetry and remote sensing. However, the diversity and complexity of buildings make building extraction methods still face challenges in terms of accuracy, efficiency, and so on. In this study, a new building extraction framework based on MBI and combined with image segmentation techniques, spectral constraint, shadow constraint, and shape constraint is proposed. In order to verify the proposed method, worldview-2, GF-2, GF-1 remote sensing images covered Xiamen Software Park were used for building extraction experiments. Experimental results indicate that the proposed method improve the original MBI significantly, and the correct rate is over 86 %. Furthermore, the proposed framework reduces the false alarms by 42 % on average compared to the performance of the original MBI.

Retrospective case series of the imaging findings of facial nerve hemangioma.

PubMed

Yue, Yunlong; Jin, Yanfang; Yang, Bentao; Yuan, Hui; Li, Jiandong; Wang, Zhenchang

2015-09-01

The aim was to compare high-resolution computed tomography (HRCT) and thin-section magnetic resonance imaging (MRI) findings of facial nerve hemangioma. The HRCT and MRI characteristics of 17 facial nerve hemangiomas diagnosed between 2006 and 2013 were retrospectively analyzed. All patients included in the study suffered from a space-occupying lesion of soft tissues at the geniculate ganglion fossa. Affected nerve was compared for size and shape with the contralateral unaffected nerve. HRCT showed irregular expansion and broadening of the facial nerve canal, damage of the bone wall and destruction of adjacent bone, with "point"-like or "needle"-like calcifications in 14 cases. The average CT value was 320.9 ± 141.8 Hu. Fourteen patients had a widened labyrinthine segment; 6/17 had a tympanic segment widening; 2/17 had a greater superficial petrosal nerve canal involvement, and 2/17 had an affected internal auditory canal (IAC) segment. On MRI, all lesions were significantly enhanced due to high blood supply. Using 2D FSE T2WI, the lesion detection rate was 82.4 % (14/17). 3D fast imaging employing steady-state acquisition (3D FIESTA) revealed the lesions in all patients. HRCT showed that the average number of involved segments in the facial nerve canal was 2.41, while MRI revealed an average of 2.70 segments (P < 0.05). HRCT and MR findings of facial nerve hemangioma were typical, revealing irregular masses growing along the facial nerve canal, with calcifications and rich blood supply. Thin-section enhanced MRI was more accurate in lesion detection and assessment compared with HRCT.

A volumetric pulmonary CT segmentation method with applications in emphysema assessment

NASA Astrophysics Data System (ADS)

Silva, José Silvestre; Silva, Augusto; Santos, Beatriz S.

2006-03-01

A segmentation method is a mandatory pre-processing step in many automated or semi-automated analysis tasks such as region identification and densitometric analysis, or even for 3D visualization purposes. In this work we present a fully automated volumetric pulmonary segmentation algorithm based on intensity discrimination and morphologic procedures. Our method first identifies the trachea as well as primary bronchi and then the pulmonary region is identified by applying a threshold and morphologic operations. When both lungs are in contact, additional procedures are performed to obtain two separated lung volumes. To evaluate the performance of the method, we compared contours extracted from 3D lung surfaces with reference contours, using several figures of merit. Results show that the worst case generally occurs at the middle sections of high resolution CT exams, due the presence of aerial and vascular structures. Nevertheless, the average error is inferior to the average error associated with radiologist inter-observer variability, which suggests that our method produces lung contours similar to those drawn by radiologists. The information created by our segmentation algorithm is used by an identification and representation method in pulmonary emphysema that also classifies emphysema according to its severity degree. Two clinically proved thresholds are applied which identify regions with severe emphysema, and with highly severe emphysema. Based on this thresholding strategy, an application for volumetric emphysema assessment was developed offering new display paradigms concerning the visualization of classification results. This framework is easily extendable to accommodate other classifiers namely those related with texture based segmentation as it is often the case with interstitial diseases.

Parameter-space metric of semicoherent searches for continuous gravitational waves

NASA Astrophysics Data System (ADS)

Pletsch, Holger J.

2010-08-01

Continuous gravitational-wave (CW) signals such as emitted by spinning neutron stars are an important target class for current detectors. However, the enormous computational demand prohibits fully coherent broadband all-sky searches for prior unknown CW sources over wide ranges of parameter space and for yearlong observation times. More efficient hierarchical “semicoherent” search strategies divide the data into segments much shorter than one year, which are analyzed coherently; then detection statistics from different segments are combined incoherently. To optimally perform the incoherent combination, understanding of the underlying parameter-space structure is requisite. This problem is addressed here by using new coordinates on the parameter space, which yield the first analytical parameter-space metric for the incoherent combination step. This semicoherent metric applies to broadband all-sky surveys (also embedding directed searches at fixed sky position) for isolated CW sources. Furthermore, the additional metric resolution attained through the combination of segments is studied. From the search parameters (sky position, frequency, and frequency derivatives), solely the metric resolution in the frequency derivatives is found to significantly increase with the number of segments.

Computational high-resolution heart phantoms for medical imaging and dosimetry simulations

NASA Astrophysics Data System (ADS)

Gu, Songxiang; Gupta, Rajiv; Kyprianou, Iacovos

2011-09-01

Cardiovascular disease in general and coronary artery disease (CAD) in particular, are the leading cause of death worldwide. They are principally diagnosed using either invasive percutaneous transluminal coronary angiograms or non-invasive computed tomography angiograms (CTA). Minimally invasive therapies for CAD such as angioplasty and stenting are rendered under fluoroscopic guidance. Both invasive and non-invasive imaging modalities employ ionizing radiation and there is concern for deterministic and stochastic effects of radiation. Accurate simulation to optimize image quality with minimal radiation dose requires detailed, gender-specific anthropomorphic phantoms with anatomically correct heart and associated vasculature. Such phantoms are currently unavailable. This paper describes an open source heart phantom development platform based on a graphical user interface. Using this platform, we have developed seven high-resolution cardiac/coronary artery phantoms for imaging and dosimetry from seven high-quality CTA datasets. To extract a phantom from a coronary CTA, the relationship between the intensity distribution of the myocardium, the ventricles and the coronary arteries is identified via histogram analysis of the CTA images. By further refining the segmentation using anatomy-specific criteria such as vesselness, connectivity criteria required by the coronary tree and image operations such as active contours, we are able to capture excellent detail within our phantoms. For example, in one of the female heart phantoms, as many as 100 coronary artery branches could be identified. Triangular meshes are fitted to segmented high-resolution CTA data. We have also developed a visualization tool for adding stenotic lesions to the coronaries. The male and female heart phantoms generated so far have been cross-registered and entered in the mesh-based Virtual Family of phantoms with matched age/gender information. Any phantom in this family, along with user-defined stenoses, can be used to obtain clinically realistic projection images with the Monte Carlo code penMesh for optimizing imaging and dosimetry.

Light weight optics made by glass thermal forming for future x-ray telescopes

NASA Astrophysics Data System (ADS)

Winter, Anita; Vongehr, Monika; Friedrich, Peter

2010-07-01

Future X-ray observatory missions, such as IXO or Gen-X, require grazing incidence optics of large collecting area in combination with a very good angular resolution. Wolter type I X-ray telescopes made of slumped glass segments could be a possible alternative to silicon pore optics. To achieve these requirements we develop slumping methods for high accuracy segments by experimental means. In particular, we follow the approach of indirect slumping and aim to produce parabola and hyperbola in one piece. In order to avoid internal stress in the glass segments the thermal expansion coefficient of the glass should closely match the thermal expansion of the mould material. Currently we focus on a combination of the alloy KOVAR for the mould and D263 for the glass; additionally a platinum-coated silica as mould material is studied. We investigate the behaviour of both materials during slumping in order to obtain the ideal environment for the slumping process. Additionally we report on the design of different metrology methods to measure the figure and thickness variations of the glass segments in visual light, e.g. interference, and on bearings used for shape measurements and integration.

A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors

PubMed Central

Mishra, Abhishek; Ghosh, Rohan; Principe, Jose C.; Thakor, Nitish V.; Kukreja, Sunil L.

2017-01-01

Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available. To address these limitations, in this paper we develop a technique for generalized motion segmentation based on spatial statistics across time frames. First, we create micromotion on the platform to facilitate the separation of static and dynamic elements of a scene, inspired by human saccadic eye movements. Second, we introduce the concept of spike-groups as a methodology to partition spatio-temporal event groups, which facilitates computation of scene statistics and characterize objects in it. Experimental results show that our algorithm is able to classify dynamic objects with a moving camera with maximum accuracy of 92%. PMID:28316563

High-resolution myocardial stress perfusion at 3 T in patients with suspected coronary artery disease.

PubMed

Meyer, Carsten; Strach, Katharina; Thomas, Daniel; Litt, Harold; Nähle, Claas P; Tiemann, Klaus; Schwenger, Ulrich; Schild, Hans H; Sommer, Torsten

2008-02-01

To implement a high-resolution first-pass myocardial perfusion imaging protocol (HRPI) at 3 T, and to evaluate the feasibility, image quality and accuracy of this approach prospectively in patients with suspected CAD. We hypothesized that utilizing the gain in SNR at 3 T to increase spatial resolution would reduce partial volume effects and subendocardial dark rim artifacts in comparison to 1.5 T. HRPI studies were performed on 60 patients using a segmented k-space gradient echo sequence (in plane resolution 1.97 x 1.94 mm(2)). Semiquantitative assessment of dark rim artifacts was performed for the stress studies on a slice-by-slice basis. Qualitative visual analysis was compared to quantitative coronary angiography (QCA) results; hemodynamically significant CAD was defined as stenosis >or=70% at QCA. Dark rim artifacts appeared in 108 of 180 slices (average extent 1.3 +/- 1.2 mm representing 11.8 +/- 10.8% of the transmural myocardial thickness). Sensitivity, specifity, and test accuracy for the detection of significant CAD were 89%,79%, and 85%. HRPI studies at 3 T are feasible in a clinical setting, providing good image quality and high accuracy for detection of significant CAD. The presence of dark rim artifacts does not appear to represent a diagnostic problem when using a HRPI approach.

High resolution earth observation satellites and services in the next decade a European perspective

NASA Astrophysics Data System (ADS)

Schreier, Gunter; Dech, Stefan

2005-07-01

Projects to use very high resolution optical satellite sensor data started in the late 90s and are believed to be the major driver for the commercialisation of earth observation. The global political security situation and updated legislative frameworks created new opportunities for high resolution, dual use satellite systems. In addition to new optical sensors, very high resolution synthetic aperture radars will become in the next few years an important component in the imaging satellite fleet. The paper will review the development in this domain so far, and give perspectives on future emerging markets and opportunities. With dual-use satellite initiatives and new political frameworks agreed between the European Commission and the European Space Agency (ESA), the European market becomes very attractive for both service suppliers and customers. The political focus on "Global Monitoring for Environment and Security" (GMES) and the "European Defence and Security Policy" drive and amplify this demand which ranges from low resolution climate monitoring to very high resolution reconnaissance tasks. In order to create an operational and sustainable GMES in Europe by 2007, the European infrastructure need to be adapted and extended. This includes the ESA SENTINEL and OXYGEN programmes, aiming for a fleet of earth observation satellites and an open and operational earth observation ground segment. The harmonisation of national and regional geographic information is driven by the European Commission's INSPIRE programme. The necessary satellite capacity to complement existing systems in the delivery of space based data required for GMES is currently under definition. Embedded in a market with global competition and in the global political framework of a Global Earth Observation System of Systems, European companies, agencies and research institutions are now contributing to this joint undertaking. The paper addresses the chances, risks and options for the future.

Automated cortical bone segmentation for multirow-detector CT imaging with validation and application to human studies

PubMed Central

Li, Cheng; Jin, Dakai; Chen, Cheng; Letuchy, Elena M.; Janz, Kathleen F.; Burns, Trudy L.; Torner, James C; Levy, Steven M.; Saha, Punam K

2015-01-01

Purpose: Cortical bone supports and protects human skeletal functions and plays an important role in determining bone strength and fracture risk. Cortical bone segmentation at a peripheral site using multirow-detector CT (MD-CT) imaging is useful for in vivo assessment of bone strength and fracture risk. Major challenges for the task emerge from limited spatial resolution, low signal-to-noise ratio, presence of cortical pores, and structural complexity over the transition between trabecular and cortical bones. An automated algorithm for cortical bone segmentation at the distal tibia from in vivo MD-CT imaging is presented and its performance and application are examined. Methods: The algorithm is completed in two major steps—(1) bone filling, alignment, and region-of-interest computation and (2) segmentation of cortical bone. After the first step, the following sequence of tasks is performed to accomplish cortical bone segmentation—(1) detection of marrow space and possible pores, (2) computation of cortical bone thickness, detection of recession points, and confirmation and filling of true pores, and (3) detection of endosteal boundary and delineation of cortical bone. Effective generalizations of several digital topologic and geometric techniques are introduced and a fully automated algorithm is presented for cortical bone segmentation. Results: An accuracy of 95.1% in terms of volume of agreement with manual outlining of cortical bone was observed in human MD-CT scans, while an accuracy of 88.5% was achieved when compared with manual outlining on postregistered high resolution micro-CT imaging. An intraclass correlation coefficient of 0.98 was obtained in cadaveric repeat scans. A pilot study was conducted to describe gender differences in cortical bone properties. This study involved 51 female and 46 male participants (age: 19–20 yr) from the Iowa Bone Development Study. Results from this pilot study suggest that, on average after adjustment for height and weight differences, males have thicker cortex (mean difference 0.33 mm and effect size 0.92 at the anterior region) with lower bone mineral density (mean difference −28.73 mg/cm3 and effect size 1.35 at the posterior region) as compared to females. Conclusions: The algorithm presented is suitable for fully automated segmentation of cortical bone in MD-CT imaging of the distal tibia with high accuracy and reproducibility. Analysis of data from a pilot study demonstrated that the cortical bone indices allow quantification of gender differences in cortical bone from MD-CT imaging. Application to larger population groups, including those with compromised bone, is needed. PMID:26233184

Registration-based interpolation applied to cardiac MRI

NASA Astrophysics Data System (ADS)

Ólafsdóttir, Hildur; Pedersen, Henrik; Hansen, Michael S.; Lyksborg, Mark; Hansen, Mads Fogtmann; Darkner, Sune; Larsen, Rasmus

2010-03-01

Various approaches have been proposed for segmentation of cardiac MRI. An accurate segmentation of the myocardium and ventricles is essential to determine parameters of interest for the function of the heart, such as the ejection fraction. One problem with MRI is the poor resolution in one dimension. A 3D registration algorithm will typically use a trilinear interpolation of intensities to determine the intensity of a deformed template image. Due to the poor resolution across slices, such linear approximation is highly inaccurate since the assumption of smooth underlying intensities is violated. Registration-based interpolation is based on 2D registrations between adjacent slices and is independent of segmentations. Hence, rather than assuming smoothness in intensity, the assumption is that the anatomy is consistent across slices. The basis for the proposed approach is the set of 2D registrations between each pair of slices, both ways. The intensity of a new slice is then weighted by (i) the deformation functions and (ii) the intensities in the warped images. Unlike the approach by Penney et al. 2004, this approach takes into account deformation both ways, which gives more robustness where correspondence between slices is poor. We demonstrate the approach on a toy example and on a set of cardiac CINE MRI. Qualitative inspection reveals that the proposed approach provides a more convincing transition between slices than images obtained by linear interpolation. A quantitative validation reveals significantly lower reconstruction errors than both linear and registration-based interpolation based on one-way registrations.

ThermoYield actuators: nano-adjustable set-and-forget optics mounts

NASA Astrophysics Data System (ADS)

DeTienne, Michael D.; Bruccoleri, Alexander R.; Chalifoux, Brandon; Heilmann, Ralf K.; Tedesco, Ross E.; Schattenburg, Mark L.

2017-08-01

The X-ray optics community has been developing technology for high angular resolution, large collecting area X-ray telescopes such as the Lynx X-ray telescope concept. To meet the high collecting area requirements of such telescope concepts, research is being conducted on thin, segmented optics. The mounts that fixture and align segmented optics must be the correct length to sub-micron accuracy to satisfy the angular resolution goals of such a concept. Set-andforget adjustable length optical mounting posts have been developed to meet this need. The actuator consists of a cylinder made of metal. Halfway up the height of the metal cylinder, a reduced diameter cylindrical neck is cut. To change the length of this actuator, an axial compressive or tensile force is applied to the actuator. A high-current electrical pulse is sent through the actuator, and this electrical current resistively heats the neck of the actuator. This heating temporarily reduces the yield strength of the neck, so that the applied force plastically deforms the neck. Once the current stops and the neck cools, the neck will regain yield strength, and the plastic deformation will stop. All of the plastic deformation that occurred during heating is now permanent. Both compression and expansion of these actuators has been demonstrated in steps ranging from 6 nanometers to several microns. This paper will explain the concept of ThermoYield actuation, explore X-ray telescope applications, describe an experimental setup, show and discuss data, and propose future ideas.