Binding and segmentation via a neural mass model trained with Hebbian and anti-Hebbian mechanisms.

PubMed

Cona, Filippo; Zavaglia, Melissa; Ursino, Mauro

2012-04-01

Synchronization of neural activity in the gamma band, modulated by a slower theta rhythm, is assumed to play a significant role in binding and segmentation of multiple objects. In the present work, a recent neural mass model of a single cortical column is used to analyze the synaptic mechanisms which can warrant synchronization and desynchronization of cortical columns, during an autoassociation memory task. The model considers two distinct layers communicating via feedforward connections. The first layer receives the external input and works as an autoassociative network in the theta band, to recover a previously memorized object from incomplete information. The second realizes segmentation of different objects in the gamma band. To this end, units within both layers are connected with synapses trained on the basis of previous experience to store objects. The main model assumptions are: (i) recovery of incomplete objects is realized by excitatory synapses from pyramidal to pyramidal neurons in the same object; (ii) binding in the gamma range is realized by excitatory synapses from pyramidal neurons to fast inhibitory interneurons in the same object. These synapses (both at points i and ii) have a few ms dynamics and are trained with a Hebbian mechanism. (iii) Segmentation is realized with faster AMPA synapses, with rise times smaller than 1 ms, trained with an anti-Hebbian mechanism. Results show that the model, with the previous assumptions, can correctly reconstruct and segment three simultaneous objects, starting from incomplete knowledge. Segmentation of more objects is possible but requires an increased ratio between the theta and gamma periods.

Novel use of gamma correction for precise (99m)Tc-HDP pinhole bone scan diagnosis and classification of knee occult fractures.

PubMed

Bahk, Yong-Whee; Jeon, Ho-Seung; Kim, Jang Min; Park, Jung Mee; Chung, Yong-An; Kim, E Edmund; Kim, Sung-Hoon; Chung, Soo-Kyo

2010-08-01

The aim of this study was to introduce gamma correction pinhole bone scan (GCPBS) to depict specific signs of knee occult fractures (OF) on (99m)Tc-hydroxydiphosphonate (HDP) scan. Thirty-six cases of six different types of knee OF in 27 consecutive patients (male = 20, female = 7, and age = 18-86 years) were enrolled. The diagnosis was made on the basis of a history of acute or subacute knee trauma, local pain, tenderness, cutaneous injury, negative conventional radiography, and positive magnetic resonance imaging (MRI). Because of the impracticability of histological verification of individual OF, MRI was utilized as a gold standard of diagnosis and classification. All patients had (99m)Tc-HDP bone scanning and supplementary GCPBS. GCPBS signs were correlated and compared with those of MRI. The efficacy of gamma correction of ordinary parallel collimator and pinhole collimator scans were collated. Gamma correction pinhole bone scan depicted the signs characteristic of six different types of OF. They were well defined stuffed globular tracer uptake in geographic I fractures (n = 9), block-like uptake in geographic II fractures (n = 7), simple or branching linear uptake in linear cancellous fractures (n = 4), compression in impacted fractures (n = 2), stippled-serpentine uptake in reticular fractures (n = 11), and irregular subcortical uptake in osteochondral fractures (n = 3). All fractures were equally well or more distinctly depicted on GCPBS than on MRI except geographic II fracture, the details of which were not appreciated on GCPBS. Parallel collimator scan also yielded to gamma correction, but the results were inferior to those of the pinhole scan. Gamma correction pinhole bone scan can depict the specific diagnostic signs in six different types of knee occult fractures. The specific diagnostic capability along with the lower cost and wider global availability of bone scanning would make GCPBS an effective alternative.

Gallbladder radionuclide scan (image)

MedlinePlus

... gallbladder radionuclide scan is performed by injecting a tracer (radioactive chemical) into the bloodstream. A gamma camera ... detect the gamma rays being emitted from the tracer, and the image of where the tracer is ...

A low-cost three-dimensional laser surface scanning approach for defining body segment parameters.

PubMed

Pandis, Petros; Bull, Anthony Mj

2017-11-01

Body segment parameters are used in many different applications in ergonomics as well as in dynamic modelling of the musculoskeletal system. Body segment parameters can be defined using different methods, including techniques that involve time-consuming manual measurements of the human body, used in conjunction with models or equations. In this study, a scanning technique for measuring subject-specific body segment parameters in an easy, fast, accurate and low-cost way was developed and validated. The scanner can obtain the body segment parameters in a single scanning operation, which takes between 8 and 10 s. The results obtained with the system show a standard deviation of 2.5% in volumetric measurements of the upper limb of a mannequin and 3.1% difference between scanning volume and actual volume. Finally, the maximum mean error for the moment of inertia by scanning a standard-sized homogeneous object was 2.2%. This study shows that a low-cost system can provide quick and accurate subject-specific body segment parameter estimates.

Scan-rescan reproducibility of segmental aortic wall shear stress as assessed by phase-specific segmentation with 4D flow MRI in healthy volunteers.

PubMed

van der Palen, Roel L F; Roest, Arno A W; van den Boogaard, Pieter J; de Roos, Albert; Blom, Nico A; Westenberg, Jos J M

2018-05-26

The aim was to investigate scan-rescan reproducibility and observer variability of segmental aortic 3D systolic wall shear stress (WSS) by phase-specific segmentation with 4D flow MRI in healthy volunteers. Ten healthy volunteers (age 26.5 ± 2.6 years) underwent aortic 4D flow MRI twice. Maximum 3D systolic WSS (WSSmax) and mean 3D systolic WSS (WSSmean) for five thoracic aortic segments over five systolic cardiac phases by phase-specific segmentations were calculated. Scan-rescan analysis and observer reproducibility analysis were performed. Scan-rescan data showed overall good reproducibility for WSSmean (coefficient of variation, COV 10-15%) with moderate-to-strong intraclass correlation coefficient (ICC 0.63-0.89). The variability in WSSmax was high (COV 16-31%) with moderate-to-good ICC (0.55-0.79) for different aortic segments. Intra- and interobserver reproducibility was good-to-excellent for regional aortic WSSmax (ICC ≥ 0.78; COV ≤ 17%) and strong-to-excellent for WSSmean (ICC ≥ 0.86; COV ≤ 11%). In general, ascending aortic segments showed more WSSmax/WSSmean variability compared to aortic arch or descending aortic segments for scan-rescan, intraobserver and interobserver comparison. Scan-rescan reproducibility was good for WSSmean and moderate for WSSmax for all thoracic aortic segments over multiple systolic phases in healthy volunteers. Intra/interobserver reproducibility for segmental WSS assessment was good-to-excellent. Variability of WSSmax is higher and should be taken into account in case of individual follow-up or in comparative rest-stress studies to avoid misinterpretation.

Validation of automated white matter hyperintensity segmentation.

PubMed

Smart, Sean D; Firbank, Michael J; O'Brien, John T

2011-01-01

Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scans were also segmented in a fully automated fashion by three different programmes. The voxel overlap between manual and automated segmentation was compared. Results. Between observer overlap ratio was 63%. Using our previously described in-house software, we had overlap of 62.2%. We investigated the use of a modified version of SPM segmentation; however, this was not successful, with only 14% overlap. Discussion. Using our previously reported software, we demonstrated good segmentation of WMHs in a fully automated fashion.

Gamma Knife treatment of low-grade gliomas in children.

PubMed

Ekşi, Murat Şakir; Yılmaz, Baran; Akakın, Akın; Toktaş, Zafer Orkun; Kaur, Ahmet Cemil; Demir, Mustafa Kemal; Kılıç, Türker

2015-11-01

Low-grade gliomas have good overall survival rates in pediatric patients compared to adults. There are some case series that reported the effectiveness and safety of Gamma Knife radiosurgery, yet they are limited in number of patients. We aimed to review the relevant literature for pediatric low-grade glial tumors treated with stereotactic radiosurgery, specifically Gamma Knife radiosurgery, and to present an exemplary case. A 6-year-old boy was admitted to clinic due to head trauma. He was alert, cooperative, and had no obvious motor or sensorial deficit. A head CT scan depicted a hypodense zone at the right caudate nucleus. The brain magnetic resonance imaging (MRI) depicted a mass lesion at the same location. A stereotactic biopsy was performed. Histopathological diagnosis was low-grade astrocytoma (grade II, World Health Organization (WHO) classification, 2007). Gamma Knife radiosurgery was applied to the tumor bed. Tumor volume was 21.85 cm(3). Fourteen gray was given to 50% isodose segment of the lesion (maximal dose of 28 Gy). The tumor has disappeared totally in 4 months, and the patient was tumor-free 21 months after the initial treatment. The presented literature review represents mostly single-center experiences with different patient and treatment characteristics. Accordingly, a mean/median margin dose of 11.3-15 Gy with Gamma Knife radiosurgery (GKRS) is successful in treatment of pediatric and adult low-grade glial tumor patients. However, prospective studies with a large cohort of pediatric patients should be conducted to make a more comprehensive conclusion for effectiveness and safety of GKRS in pediatric low-grade glial tumors.

A new graphical user interface for fast construction of computation phantoms and MCNP calculations: application to calibration of in vivo measurement systems.

PubMed

Borisov, N; Franck, D; de Carlan, L; Laval, L

2002-08-01

The paper reports on a new utility for development of computational phantoms for Monte Carlo calculations and data analysis for in vivo measurements of radionuclides deposited in tissues. The individual properties of each worker can be acquired for a rather precise geometric representation of his (her) anatomy, which is particularly important for low energy gamma ray emitting sources such as thorium, uranium, plutonium and other actinides. The software discussed here enables automatic creation of an MCNP input data file based on scanning data. The utility includes segmentation of images obtained with either computed tomography or magnetic resonance imaging by distinguishing tissues according to their signal (brightness) and specification of the source and detector. In addition, a coupling of individual voxels within the tissue is used to reduce the memory demand and to increase the calculational speed. The utility was tested for low energy emitters in plastic and biological tissues as well as for computed tomography and magnetic resonance imaging scanning information.

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

PubMed

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

2011-10-01

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

NDA BATCH 2002-02

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

Lawrence Livermore National Laboratory

2009-12-09

QC sample results (daily background checks, 20-gram and 100-gram SGS drum checks) were within acceptable criteria established by WIPP's Quality Assurance Objectives for TRU Waste Characterization. Replicate runs were performed on 5 drums with IDs LL85101099TRU, LL85801147TRU, LL85801109TRU, LL85300999TRU and LL85500979TRU. All replicate measurement results are identical at the 95% confidence level as established by WIPP criteria. Note that the batch covered 5 weeks of SGS measurements from 23-Jan-2002 through 22-Feb-2002. Data packet for SGS Batch 2002-02 generated using gamma spectroscopy with the Pu Facility SGS unit is technically reasonable. All QC samples are in compliance with established control limits.more » The batch data packet has been reviewed for correctness, completeness, consistency and compliance with WIPP's Quality Assurance Objectives and determined to be acceptable. An Expert Review was performed on the data packet between 28-Feb-02 and 09-Jul-02 to check for potential U-235, Np-237 and Am-241 interferences and address drum cases where specific scan segments showed Se gamma ray transmissions for the 136-keV gamma to be below 0.1 %. Two drums in the batch showed Pu-238 at a relative mass ratio more than 2% of all the Pu isotopes.« less

TIGRESS: TRIUMF-ISAC gamma-ray escape-suppressed spectrometer

NASA Astrophysics Data System (ADS)

Svensson, C. E.; Amaudruz, P.; Andreoiu, C.; Andreyev, A.; Austin, R. A. E.; Ball, G. C.; Bandyopadhyay, D.; Boston, A. J.; Chakrawarthy, R. S.; Chen, A. A.; Churchman, R.; Drake, T. E.; Finlay, P.; Garrett, P. E.; Grinyer, G. F.; Hackman, G.; Hyland, B.; Jones, B.; Kanungo, R.; Maharaj, R.; Martin, J. P.; Morris, D.; Morton, A. C.; Pearson, C. J.; Phillips, A. A.; Ressler, J. J.; Roy, R.; Sarazin, F.; Schumaker, M. A.; Scraggs, H. C.; Smith, M. B.; Starinsky, N.; Valiente-Dobón, J. J.; Waddington, J. C.; Watters, L. M.

2005-10-01

The TRIUMF-ISAC gamma-ray escape-suppressed spectrometer (TIGRESS) is a new γ-ray detector array being developed for use at TRIUMF's Isotope Separator and Accelerator (ISAC) radioactive ion beam facility. TIGRESS will comprise 12 32-fold segmented clover-type HPGe detectors coupled with 20-fold segmented modular Compton suppression shields and custom digital signal processing electronics. This paper provides an overview of the TIGRESS project and progress in its development to date.

Automated volumetric segmentation of retinal fluid on optical coherence tomography

PubMed Central

Wang, Jie; Zhang, Miao; Pechauer, Alex D.; Liu, Liang; Hwang, Thomas S.; Wilson, David J.; Li, Dengwang; Jia, Yali

2016-01-01

We propose a novel automated volumetric segmentation method to detect and quantify retinal fluid on optical coherence tomography (OCT). The fuzzy level set method was introduced for identifying the boundaries of fluid filled regions on B-scans (x and y-axes) and C-scans (z-axis). The boundaries identified from three types of scans were combined to generate a comprehensive volumetric segmentation of retinal fluid. Then, artefactual fluid regions were removed using morphological characteristics and by identifying vascular shadowing with OCT angiography obtained from the same scan. The accuracy of retinal fluid detection and quantification was evaluated on 10 eyes with diabetic macular edema. Automated segmentation had good agreement with manual segmentation qualitatively and quantitatively. The fluid map can be integrated with OCT angiogram for intuitive clinical evaluation. PMID:27446676

Validation of Automated White Matter Hyperintensity Segmentation

PubMed Central

Smart, Sean D.; Firbank, Michael J.; O'Brien, John T.

2011-01-01

Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scans were also segmented in a fully automated fashion by three different programmes. The voxel overlap between manual and automated segmentation was compared. Results. Between observer overlap ratio was 63%. Using our previously described in-house software, we had overlap of 62.2%. We investigated the use of a modified version of SPM segmentation; however, this was not successful, with only 14% overlap. Discussion. Using our previously reported software, we demonstrated good segmentation of WMHs in a fully automated fashion. PMID:21904678

Metabolic cardiac imaging in severe coronary disease: assessment of viability with iodine-123-iodophenylpentadecanoic acid and multicrystal gamma camera, and correlation with biopsy.

PubMed

Murray, G; Schad, N; Ladd, W; Allie, D; vander Zwagg, R; Avet, P; Rockett, J

1992-07-01

Fifteen patients with coronary disease and resting left ventricular ejection fractions of less than or equal to 0.35 underwent resting metabolic cardiac imaging utilizing 1 mCi [123I]iodophenylpentadecanoic acid (IPPA) intravenously and a multicrystal gamma camera. Parametric images of regional rates of IPPA clearance and accumulation were generated. Forty-two vascular territories (22 infarcted) were evaluated by metabolic imaging as well as transmural myocardial biopsy. Despite resting akinesis or dyskinesis in 20/22 (91%) infarcted territories, 16/22 (73%) of these territories were metabolically viable. Transmural myocardial biopsies in all patients (43 sites, 42 vascular territories) during coronary bypass surgery confirmed IPPA results in 39/43 patients (91%). When compared to biopsy, scan sensitivity for viability was 33/36 (92%) with a specificity of 6/7 (86%). Eighty percent of bypassed, infarcted but IPPA viable segments demonstrated improved regional systolic wall motion postoperatively as assessed by exercise radionuclide angiography. We conclude resting IPPA imaging identifies viable myocardium, thereby providing a safe, cost-effective technique for myocardial viability assessment.

Dynamic 3D scanning as a markerless method to calculate multi-segment foot kinematics during stance phase: methodology and first application.

PubMed

Van den Herrewegen, Inge; Cuppens, Kris; Broeckx, Mario; Barisch-Fritz, Bettina; Vander Sloten, Jos; Leardini, Alberto; Peeraer, Louis

2014-08-22

Multi-segmental foot kinematics have been analyzed by means of optical marker-sets or by means of inertial sensors, but never by markerless dynamic 3D scanning (D3DScanning). The use of D3DScans implies a radically different approach for the construction of the multi-segment foot model: the foot anatomy is identified via the surface shape instead of distinct landmark points. We propose a 4-segment foot model consisting of the shank (Sha), calcaneus (Cal), metatarsus (Met) and hallux (Hal). These segments are manually selected on a static scan. To track the segments in the dynamic scan, the segments of the static scan are matched on each frame of the dynamic scan using the iterative closest point (ICP) fitting algorithm. Joint rotations are calculated between Sha-Cal, Cal-Met, and Met-Hal. Due to the lower quality scans at heel strike and toe off, the first and last 10% of the stance phase is excluded. The application of the method to 5 healthy subjects, 6 trials each, shows a good repeatability (intra-subject standard deviations between 1° and 2.5°) for Sha-Cal and Cal-Met joints, and inferior results for the Met-Hal joint (>3°). The repeatability seems to be subject-dependent. For the validation, a qualitative comparison with joint kinematics from a corresponding established marker-based multi-segment foot model is made. This shows very consistent patterns of rotation. The ease of subject preparation and also the effective and easy to interpret visual output, make the present technique very attractive for functional analysis of the foot, enhancing usability in clinical practice. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Comparison of myocardial perfusion imaging between the new high-speed gamma camera and the standard anger camera.

PubMed

Tanaka, Hirokazu; Chikamori, Taishiro; Hida, Satoshi; Uchida, Kenji; Igarashi, Yuko; Yokoyama, Tsuyoshi; Takahashi, Masaki; Shiba, Chie; Yoshimura, Mana; Tokuuye, Koichi; Yamashina, Akira

2013-01-01

Cadmium-zinc-telluride (CZT) solid-state detectors have been recently introduced into the field of myocardial perfusion imaging. The aim of this study was to prospectively compare the diagnostic performance of the CZT high-speed gamma camera (Discovery NM 530c) with that of the standard 3-head gamma camera in the same group of patients. The study group consisted of 150 consecutive patients who underwent a 1-day stress-rest (99m)Tc-sestamibi or tetrofosmin imaging protocol. Image acquisition was performed first on a standard gamma camera with a 15-min scan time each for stress and for rest. All scans were immediately repeated on a CZT camera with a 5-min scan time for stress and a 3-min scan time for rest, using list mode. The correlations between the CZT camera and the standard camera for perfusion and function analyses were strong within narrow Bland-Altman limits of agreement. Using list mode analysis, image quality for stress was rated as good or excellent in 97% of the 3-min scans, and in 100% of the ≥4-min scans. For CZT scans at rest, similarly, image quality was rated as good or excellent in 94% of the 1-min scans, and in 100% of the ≥2-min scans. The novel CZT camera provides excellent image quality, which is equivalent to standard myocardial single-photon emission computed tomography, despite a short scan time of less than half of the standard time.

Automatic, accurate, and reproducible segmentation of the brain and cerebro-spinal fluid in T1-weighted volume MRI scans and its application to serial cerebral and intracranial volumetry

NASA Astrophysics Data System (ADS)

Lemieux, Louis

2001-07-01

A new fully automatic algorithm for the segmentation of the brain and cerebro-spinal fluid (CSF) from T1-weighted volume MRI scans of the head was specifically developed in the context of serial intra-cranial volumetry. The method is an extension of a previously published brain extraction algorithm. The brain mask is used as a basis for CSF segmentation based on morphological operations, automatic histogram analysis and thresholding. Brain segmentation is then obtained by iterative tracking of the brain-CSF interface. Grey matter (GM), white matter (WM) and CSF volumes are calculated based on a model of intensity probability distribution that includes partial volume effects. Accuracy was assessed using a digital phantom scan. Reproducibility was assessed by segmenting pairs of scans from 20 normal subjects scanned 8 months apart and 11 patients with epilepsy scanned 3.5 years apart. Segmentation accuracy as measured by overlap was 98% for the brain and 96% for the intra-cranial tissues. The volume errors were: total brain (TBV): -1.0%, intra-cranial (ICV):0.1%, CSF: +4.8%. For repeated scans, matching resulted in improved reproducibility. In the controls, the coefficient of reliability (CR) was 1.5% for the TVB and 1.0% for the ICV. In the patients, the Cr for the ICV was 1.2%.

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.

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.

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

Structure and strength at the bonding interface of a titanium-segmented polyurethane composite through 3-(trimethoxysilyl) propyl methacrylate for artificial organs.

PubMed

Sakamoto, Harumi; Doi, Hisashi; Kobayashi, Equo; Yoneyama, Takayuki; Suzuki, Yoshiaki; Hanawa, Takao

2007-07-01

The objective of this study was to investigate the structure and strength at the bonding interface of a titanium (Ti)-segmented polyurethane (SPU) composite through (3-trimethoxysilyl) propyl methacrylate (gamma-MPS) for artificial organs. The effects of the thickness of the gamma-MPS layer on the shear bonding strength between Ti and SPU were investigated. Ti disks were immersed in various concentrations of gamma-MPS solutions for several immersion times. The depth profiles of elements and the thickness of the gamma-MPS layer were determined by glow discharge optical emission spectroscopy and ellipsometry, respectively. The bonding stress at the Ti/gamma-MPS/SPU interface was evaluated with a shear bonding test. Furthermore, the fractured surface of a Ti-SPU composite was observed by optical microscopy and characterized using X-ray photoelectron spectroscopy. Consequently, the thickness of the gamma-MPS layer was controlled by the concentration of the gamma-MPS solution and immersion time. The shear bonding stress at the interface increased with the increase of the thickness of the gamma-MPS layer. Therefore, the control of the thickness of the gamma-MPS layer is significant to increase the shear bonding stress at the Ti/gamma-MPS/SPU interface. These results are significant to create composites for artificial organs consisting of other metals and polymers. Copyright 2007 Wiley Periodicals, Inc.

The mechanism of chromosome 7 inversion in human lymphocytes expressing chimeric gamma beta TCR.

PubMed

Retière, C; Halary, F; Peyrat, M A; Le Deist, F; Bonneville, M; Hallet, M M

1999-01-15

Functional chimeric TCR chains, encoded by V gamma J gamma C beta or V gamma J beta C beta hybrid gene TCR, are expressed at the surface of a small fraction of alpha beta T lymphocytes in healthy individuals. Their frequency is dramatically increased in patients with ataxia-telangiectasia, a syndrome associated with inherited genomic instability. As the TCR gamma and beta loci are in an inverted orientation on chromosome 7, the generation of such hybrid genes requires at least an inversion event. Until now, neither the sequences involved in this genetic mechanism nor the number of recombinations leading to the formation of functional transcriptional units have been characterized. In this manuscript, we demonstrate that at least two rearrangements, involving classical recombination signal sequence and the V(D)J recombinase complex, lead to the formation of productive hybrid genes. A primary inversion 7 event between D beta and J gamma genic segments generates C gamma V beta and C beta V gamma hybrid loci. Within the C gamma V beta locus, secondary rearrangements between V gamma and J gamma or V gamma and J beta elements generate functional genes. Besides, our results suggest that secondary rearrangements were blocked in the C beta V gamma locus of normal but not ataxia-telangiectasia T lymphocytes. We also provide formal evidence that the same D beta-3' recombination signal sequence can be used in successive rearrangements with J gamma and J beta genic segments, thus showing that a signal joint has been involved in a secondary recombination event.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

The Impact of Dose Rate on the Accuracy of Step-and-Shoot Intensity-modulated Radiation Therapy Quality Assurance Using Varian 2300CD.

PubMed

Njeh, Christopher F; Salmon, Howard W; Schiller, Claire

2017-01-01

Intensity-modulated radiation therapy (IMRT) delivery using "step-and-shoot" technique on Varian C-Series linear accelerator (linac) is influenced by the communication frequency between the multileaf collimator and linac controllers. Hence, the dose delivery accuracy is affected by the dose rate. Our aim was to quantify the impact of using two dose rates on plan quality assurance (QA). Twenty IMRT patients were selected for this study. The plan QA was measured at two different dose rates. A gamma analysis was performed, and the degree of plan modulation on the QA pass rate was also evaluated in terms of average monitor unit per segment (MU/segment) and the total number of segments. The mean percentage gamma pass rate of 94.9% and 93.5% for 300 MU/min and 600 MU/min dose rate, respectively, was observed. There was a significant ( P = 0.001) decrease in percentage gamma pass rate when the dose rate was increased from 300 MU/min to 600 MU/min. There was a weak, but significant association between the percentage pass rate at both dose rate and total number of segments. The total number of MU was significantly correlated to the total number of segments ( r = 0.59). We found a positive correlation between the percentage pass rate and mean MU/segment, r = 0.52 and r = 0.57 for 300 MU/min and 600 MU/min, respectively. IMRT delivery using step-and-shoot technique on Varian 2300CD is impacted by the dose rate and the total amount of segments.

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.

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.

Optical Coherence Tomography (OCT) Device Independent Intraretinal Layer Segmentation

PubMed Central

Ehnes, Alexander; Wenner, Yaroslava; Friedburg, Christoph; Preising, Markus N.; Bowl, Wadim; Sekundo, Walter; zu Bexten, Erdmuthe Meyer; Stieger, Knut; Lorenz, Birgit

2014-01-01

Purpose To develop and test an algorithm to segment intraretinal layers irrespectively of the actual Optical Coherence Tomography (OCT) device used. Methods The developed algorithm is based on the graph theory optimization. The algorithm's performance was evaluated against that of three expert graders for unsigned boundary position difference and thickness measurement of a retinal layer group in 50 and 41 B-scans, respectively. Reproducibility of the algorithm was tested in 30 C-scans of 10 healthy subjects each with the Spectralis and the Stratus OCT. Comparability between different devices was evaluated in 84 C-scans (volume or radial scans) obtained from 21 healthy subjects, two scans per subject with the Spectralis OCT, and one scan per subject each with the Stratus OCT and the RTVue-100 OCT. Each C-scan was segmented and the mean thickness for each retinal layer in sections of the early treatment of diabetic retinopathy study (ETDRS) grid was measured. Results The algorithm was able to segment up to 11 intraretinal layers. Measurements with the algorithm were within the 95% confidence interval of a single grader and the difference was smaller than the interindividual difference between the expert graders themselves. The cross-device examination of ETDRS-grid related layer thicknesses highly agreed between the three OCT devices. The algorithm correctly segmented a C-scan of a patient with X-linked retinitis pigmentosa. Conclusions The segmentation software provides device-independent, reliable, and reproducible analysis of intraretinal layers, similar to what is obtained from expert graders. Translational Relevance Potential application of the software includes routine clinical practice and multicenter clinical trials. PMID:24820053

The role of DNA repair in herpesvirus pathogenesis.

PubMed

Brown, Jay C

2014-10-01

In cells latently infected with a herpesvirus, the viral DNA is present in the cell nucleus, but it is not extensively replicated or transcribed. In this suppressed state the virus DNA is vulnerable to mutagenic events that affect the host cell and have the potential to destroy the virus' genetic integrity. Despite the potential for genetic damage, however, herpesvirus sequences are well conserved after reactivation from latency. To account for this apparent paradox, I have tested the idea that host cell-encoded mechanisms of DNA repair are able to control genetic damage to latent herpesviruses. Studies were focused on homologous recombination-dependent DNA repair (HR). Methods of DNA sequence analysis were employed to scan herpesvirus genomes for DNA features able to activate HR. Analyses were carried out with a total of 39 herpesvirus DNA sequences, a group that included viruses from the alpha-, beta- and gamma-subfamilies. The results showed that all 39 genome sequences were enriched in two or more of the eight recombination-initiating features examined. The results were interpreted to indicate that HR can stabilize latent herpesvirus genomes. The results also showed, unexpectedly, that repair-initiating DNA features differed in alpha- compared to gamma-herpesviruses. Whereas inverted and tandem repeats predominated in alpha-herpesviruses, gamma-herpesviruses were enriched in short, GC-rich initiation sequences such as CCCAG and depleted in repeats. In alpha-herpesviruses, repair-initiating repeat sequences were found to be concentrated in a specific region (the S segment) of the genome while repair-initiating short sequences were distributed more uniformly in gamma-herpesviruses. The results suggest that repair pathways are activated differently in alpha- compared to gamma-herpesviruses. Copyright © 2014. Published by Elsevier Inc.

An enhanced fast scanning algorithm for image segmentation

NASA Astrophysics Data System (ADS)

Ismael, Ahmed Naser; Yusof, Yuhanis binti

2015-12-01

Segmentation is an essential and important process that separates an image into regions that have similar characteristics or features. This will transform the image for a better image analysis and evaluation. An important benefit of segmentation is the identification of region of interest in a particular image. Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical images. It scans all pixels in the image and cluster each pixel according to the upper and left neighbor pixels. The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold. Such an approach will lead to a weak reliability and shape matching of the produced segments. This paper proposes an adaptive threshold function to be used in the clustering process of the Fast Scanning algorithm. This function used the gray'value in the image's pixels and variance Also, the level of the image that is more the threshold are converted into intensity values between 0 and 1, and other values are converted into intensity values zero. The proposed enhanced Fast Scanning algorithm is realized on images of the public and private transportation in Iraq. Evaluation is later made by comparing the produced images of proposed algorithm and the standard Fast Scanning algorithm. The results showed that proposed algorithm is faster in terms the time from standard fast scanning.

Magnetic Resonance–Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region

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

Zheng, Weili; Kim, Joshua P.; Kadbi, Mo

2015-11-01

Purpose: To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Methods and Materials: Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessedmore » by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. Results: On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone–air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. Conclusions: A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated into our synCT pipeline for brain, and results agreed well with clinical CTs, thereby supporting MR-only radiation therapy treatment planning in the brain.« less

Magnetic Resonance-Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region.

PubMed

Zheng, Weili; Kim, Joshua P; Kadbi, Mo; Movsas, Benjamin; Chetty, Indrin J; Glide-Hurst, Carri K

2015-11-01

To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessed by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone-air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated into our synCT pipeline for brain, and results agreed well with clinical CTs, thereby supporting MR-only radiation therapy treatment planning in the brain. Copyright © 2015 Elsevier Inc. 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.

Segmented Gamma Scanner for Small Containers of Uranium Processing Waste- 12295

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

Morris, K.E.; Smith, S.K.; Gailey, S.

2012-07-01

The Segmented Gamma Scanner (SGS) is commonly utilized in the assay of 55-gallon drums containing radioactive waste. Successfully deployed calibration methods include measurement of vertical line source standards in representative matrices and mathematical efficiency calibrations. The SGS technique can also be utilized to assay smaller containers, such as those used for criticality safety in uranium processing facilities. For such an application, a Can SGS System is aptly suited for the identification and quantification of radionuclides present in fuel processing wastes. Additionally, since the significant presence of uranium lumping can confound even a simple 'pass/fail' measurement regimen, the high-resolution gamma spectroscopymore » allows for the use of lump-detection techniques. In this application a lump correction is not required, but the application of a differential peak approach is used to simply identify the presence of U-235 lumps. The Can SGS is similar to current drum SGSs, but differs in the methodology for vertical segmentation. In the current drum SGS, the drum is placed on a rotator at a fixed vertical position while the detector, collimator, and transmission source are moved vertically to effect vertical segmentation. For the Can SGS, segmentation is more efficiently done by raising and lowering the rotator platform upon which the small container is positioned. This also reduces the complexity of the system mechanism. The application of the Can SGS introduces new challenges to traditional calibration and verification approaches. In this paper, we revisit SGS calibration methodology in the context of smaller waste containers, and as applied to fuel processing wastes. Specifically, we discuss solutions to the challenges introduced by requiring source standards to fit within the confines of the small containers and the unavailability of high-enriched uranium source standards. We also discuss the implementation of a previously used technique for identifying the presence of uranium lumping. The SGS technique is a well-accepted NDA technique applicable to containers of almost any size. It assumes a homogenous matrix and activity distribution throughout the entire container; an assumption that is at odds with the detection of lumps within the assay item typical of uranium-processing waste. This fact, in addition to the difficultly in constructing small reference standards of uranium-bearing materials, required the methodology used for performing an efficiency curve calibration to be altered. The solution discussed in this paper is demonstrated to provide good results for both the segment activity and full container activity when measuring heterogeneous source distributions. The application of this approach will need to be based on process knowledge of the assay items, as biases can be introduced if used with homogenous, or nearly homogenous, activity distributions. The bias will need to be quantified for each combination of container geometry and SGS scanning settings. One recommended approach for using the heterogeneous calibration discussed here is to assay each item using a homogenous calibration initially. Review of the segment activities compared to the full container activity will signal the presence of a non-uniform activity distribution as the segment activity will be grossly disproportionate to the full container activity. Upon seeing this result, the assay should either be reanalyzed or repeated using the heterogeneous calibration. (authors)« less

Segmentation of organs at risk in CT volumes of head, thorax, abdomen, and pelvis

NASA Astrophysics Data System (ADS)

Han, Miaofei; Ma, Jinfeng; Li, Yan; Li, Meiling; Song, Yanli; Li, Qiang

2015-03-01

Accurate segmentation of organs at risk (OARs) is a key step in treatment planning system (TPS) of image guided radiation therapy. We are developing three classes of methods to segment 17 organs at risk throughout the whole body, including brain, brain stem, eyes, mandible, temporomandibular joints, parotid glands, spinal cord, lungs, trachea, heart, livers, kidneys, spleen, prostate, rectum, femoral heads, and skin. The three classes of segmentation methods include (1) threshold-based methods for organs of large contrast with adjacent structures such as lungs, trachea, and skin; (2) context-driven Generalized Hough Transform-based methods combined with graph cut algorithm for robust localization and segmentation of liver, kidneys and spleen; and (3) atlas and registration-based methods for segmentation of heart and all organs in CT volumes of head and pelvis. The segmentation accuracy for the seventeen organs was subjectively evaluated by two medical experts in three levels of score: 0, poor (unusable in clinical practice); 1, acceptable (minor revision needed); and 2, good (nearly no revision needed). A database was collected from Ruijin Hospital, Huashan Hospital, and Xuhui Central Hospital in Shanghai, China, including 127 head scans, 203 thoracic scans, 154 abdominal scans, and 73 pelvic scans. The percentages of "good" segmentation results were 97.6%, 92.9%, 81.1%, 87.4%, 85.0%, 78.7%, 94.1%, 91.1%, 81.3%, 86.7%, 82.5%, 86.4%, 79.9%, 72.6%, 68.5%, 93.2%, 96.9% for brain, brain stem, eyes, mandible, temporomandibular joints, parotid glands, spinal cord, lungs, trachea, heart, livers, kidneys, spleen, prostate, rectum, femoral heads, and skin, respectively. Various organs at risk can be reliably segmented from CT scans by use of the three classes of segmentation methods.

Automated Segmentation Errors When Using Optical Coherence Tomography to Measure Retinal Nerve Fiber Layer Thickness in Glaucoma.

PubMed

Mansberger, Steven L; Menda, Shivali A; Fortune, Brad A; Gardiner, Stuart K; Demirel, Shaban

2017-02-01

To characterize the error of optical coherence tomography (OCT) measurements of retinal nerve fiber layer (RNFL) thickness when using automated retinal layer segmentation algorithms without manual refinement. Cross-sectional study. This study was set in a glaucoma clinical practice, and the dataset included 3490 scans from 412 eyes of 213 individuals with a diagnosis of glaucoma or glaucoma suspect. We used spectral domain OCT (Spectralis) to measure RNFL thickness in a 6-degree peripapillary circle, and exported the native "automated segmentation only" results. In addition, we exported the results after "manual refinement" to correct errors in the automated segmentation of the anterior (internal limiting membrane) and the posterior boundary of the RNFL. Our outcome measures included differences in RNFL thickness and glaucoma classification (i.e., normal, borderline, or outside normal limits) between scans with automated segmentation only and scans using manual refinement. Automated segmentation only resulted in a thinner global RNFL thickness (1.6 μm thinner, P < .001) when compared to manual refinement. When adjusted by operator, a multivariate model showed increased differences with decreasing RNFL thickness (P < .001), decreasing scan quality (P < .001), and increasing age (P < .03). Manual refinement changed 298 of 3486 (8.5%) of scans to a different global glaucoma classification, wherein 146 of 617 (23.7%) of borderline classifications became normal. Superior and inferior temporal clock hours had the largest differences. Automated segmentation without manual refinement resulted in reduced global RNFL thickness and overestimated the classification of glaucoma. Differences increased in eyes with a thinner RNFL thickness, older age, and decreased scan quality. Operators should inspect and manually refine OCT retinal layer segmentation when assessing RNFL thickness in the management of patients with glaucoma. Copyright © 2016 Elsevier Inc. All rights reserved.

Expanding the peptide beta-turn in alphagamma hybrid sequences: 12 atom hydrogen bonded helical and hairpin turns.

PubMed

Chatterjee, Sunanda; Vasudev, Prema G; Raghothama, Srinivasarao; Ramakrishnan, Chandrasekharan; Shamala, Narayanaswamy; Balaram, Padmanabhan

2009-04-29

Hybrid peptide segments containing contiguous alpha and gamma amino acid residues can form C(12) hydrogen bonded turns which may be considered as backbone expanded analogues of C(10) (beta-turns) found in alphaalpha segments. Exploration of the regular hydrogen bonded conformations accessible for hybrid alphagamma sequences is facilitated by the use of a stereochemically constrained gamma amino acid residue gabapentin (1-aminomethylcyclohexaneacetic acid, Gpn), in which the two torsion angles about C(gamma)-C(beta) (theta(1)) and C(beta)-C(alpha) (theta(2)) are predominantly restricted to gauche conformations. The crystal structures of the octapeptides Boc-Gpn-Aib-Gpn-Aib-Gpn-Aib-Gpn-Aib-OMe (1) and Boc-Leu-Phe-Val-Aib-Gpn-Leu-Phe-Val-OMe (2) reveal two distinct conformations for the Aib-Gpn segment. Peptide 1 forms a continuous helix over the Aib(2)-Aib(6) segment, while the peptide 2 forms a beta-hairpin structure stabilized by four cross-strand hydrogen bonds with the Aib-Gpn segment forming a nonhelical C(12) turn. The robustness of the helix in peptide 1 in solution is demonstrated by NMR methods. Peptide 2 is conformationally fragile in solution with evidence of beta-hairpin conformations being obtained in methanol. Theoretical calculations permit delineation of the various C(12) hydrogen bonded structures which are energetically feasible in alphagamma and gammaalpha sequences.

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

GLISTR: Glioma Image Segmentation and Registration

PubMed Central

Pohl, Kilian M.; Bilello, Michel; Cirillo, Luigi; Biros, George; Melhem, Elias R.; Davatzikos, Christos

2015-01-01

We present a generative approach for simultaneously registering a probabilistic atlas of a healthy population to brain magnetic resonance (MR) scans showing glioma and segmenting the scans into tumor as well as healthy tissue labels. The proposed method is based on the expectation maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the original atlas into one with tumor and edema adapted to best match a given set of patient’s images. The modified atlas is registered into the patient space and utilized for estimating the posterior probabilities of various tissue labels. EM iteratively refines the estimates of the posterior probabilities of tissue labels, the deformation field and the tumor growth model parameters. Hence, in addition to segmentation, the proposed method results in atlas registration and a low-dimensional description of the patient scans through estimation of tumor model parameters. We validate the method by automatically segmenting 10 MR scans and comparing the results to those produced by clinical experts and two state-of-the-art methods. The resulting segmentations of tumor and edema outperform the results of the reference methods, and achieve a similar accuracy from a second human rater. We additionally apply the method to 122 patients scans and report the estimated tumor model parameters and their relations with segmentation and registration results. Based on the results from this patient population, we construct a statistical atlas of the glioma by inverting the estimated deformation fields to warp the tumor segmentations of patients scans into a common space. PMID:22907965

Combined use of high-definition and volumetric optical coherence tomography for the segmentation of neural canal opening in cases of optic nerve edema

NASA Astrophysics Data System (ADS)

Wang, Jui-Kai; Kardon, Randy H.; Garvin, Mona K.

2015-03-01

In cases of optic-nerve-head edema, the presence of the swelling reduces the visibility of the underlying neural canal opening (NCO) within spectral-domain optical coherence tomography (SD-OCT) volumes. Consequently, traditional SD-OCT-based NCO segmentation methods often overestimate the size of the NCO. The visibility of the NCO can be improved using high-definition 2D raster scans, but such scans do not provide 3D contextual image information. In this work, we present a semi-automated approach for the segmentation of the NCO in cases of optic disc edema by combining image information from volumetric and high-definition raster SD-OCT image sequences. In particular, for each subject, five high-definition OCT B-scans and the OCT volume are first separately segmented, and then the five high-definition B-scans are automatically registered to the OCT volume. Next, six NCO points are placed (manually, in this work) in the central three high-definition OCT B-scans (two points for each central B-scans) and are automatically transferred into the OCT volume. Utilizing a combination of these mapped points and the 3D image information from the volumetric scans, a graph-based approach is used to identify the complete NCO on the OCT en-face image. The segmented NCO points using the new approach were significantly closer to expert-marked points than the segmented NCO points using a traditional approach (root mean square differences in pixels: 5.34 vs. 21.71, p < 0.001).

The possibility of gamma-ray astronomy measurements on the Russian segment of the International Space Station.

NASA Astrophysics Data System (ADS)

Fradkin, M. I.; Gorchakov, E. V.; Kaplin, V. A.; Kaplin, D. V.; Kurnosova, L. V.; Labenskij, A. G.; Runtso, M. F.; Topchiev, N. P.

The conditions required for gamma-ray astronomy measurements at energies of 10 - 1000 GeV by a gamma-ray telescope on the International Space Station are discussed. It is shown that the properties of the detected gamma rays can be determined accurately at 30 - 1000 GeV, even if the space station solar arrays fall in the aperture of the gamma-ray telescope. Measurements of the secondary gamma-ray spectrum using a ground-based model of the gamma-ray telescope have been carried out, and the resulting spectrum at energies of 1 - 100 GeV is presented.

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.

Segmentation of pulmonary nodules in three-dimensional CT images by use of a spiral-scanning technique

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

Wang Jiahui; Engelmann, Roger; Li Qiang

2007-12-15

Accurate segmentation of pulmonary nodules in computed tomography (CT) is an important and difficult task for computer-aided diagnosis of lung cancer. Therefore, the authors developed a novel automated method for accurate segmentation of nodules in three-dimensional (3D) CT. First, a volume of interest (VOI) was determined at the location of a nodule. To simplify nodule segmentation, the 3D VOI was transformed into a two-dimensional (2D) image by use of a key 'spiral-scanning' technique, in which a number of radial lines originating from the center of the VOI spirally scanned the VOI from the 'north pole' to the 'south pole'. Themore » voxels scanned by the radial lines provided a transformed 2D image. Because the surface of a nodule in the 3D image became a curve in the transformed 2D image, the spiral-scanning technique considerably simplified the segmentation method and enabled reliable segmentation results to be obtained. A dynamic programming technique was employed to delineate the 'optimal' outline of a nodule in the 2D image, which corresponded to the surface of the nodule in the 3D image. The optimal outline was then transformed back into 3D image space to provide the surface of the nodule. An overlap between nodule regions provided by computer and by the radiologists was employed as a performance metric for evaluating the segmentation method. The database included two Lung Imaging Database Consortium (LIDC) data sets that contained 23 and 86 CT scans, respectively, with 23 and 73 nodules that were 3 mm or larger in diameter. For the two data sets, six and four radiologists manually delineated the outlines of the nodules as reference standards in a performance evaluation for nodule segmentation. The segmentation method was trained on the first and was tested on the second LIDC data sets. The mean overlap values were 66% and 64% for the nodules in the first and second LIDC data sets, respectively, which represented a higher performance level than those of two existing segmentation methods that were also evaluated by use of the LIDC data sets. The segmentation method provided relatively reliable results for pulmonary nodule segmentation and would be useful for lung cancer quantification, detection, and diagnosis.« less

Segmentation and intensity estimation of microarray images using a gamma-t mixture model.

PubMed

Baek, Jangsun; Son, Young Sook; McLachlan, Geoffrey J

2007-02-15

We present a new approach to the analysis of images for complementary DNA microarray experiments. The image segmentation and intensity estimation are performed simultaneously by adopting a two-component mixture model. One component of this mixture corresponds to the distribution of the background intensity, while the other corresponds to the distribution of the foreground intensity. The intensity measurement is a bivariate vector consisting of red and green intensities. The background intensity component is modeled by the bivariate gamma distribution, whose marginal densities for the red and green intensities are independent three-parameter gamma distributions with different parameters. The foreground intensity component is taken to be the bivariate t distribution, with the constraint that the mean of the foreground is greater than that of the background for each of the two colors. The degrees of freedom of this t distribution are inferred from the data but they could be specified in advance to reduce the computation time. Also, the covariance matrix is not restricted to being diagonal and so it allows for nonzero correlation between R and G foreground intensities. This gamma-t mixture model is fitted by maximum likelihood via the EM algorithm. A final step is executed whereby nonparametric (kernel) smoothing is undertaken of the posterior probabilities of component membership. The main advantages of this approach are: (1) it enjoys the well-known strengths of a mixture model, namely flexibility and adaptability to the data; (2) it considers the segmentation and intensity simultaneously and not separately as in commonly used existing software, and it also works with the red and green intensities in a bivariate framework as opposed to their separate estimation via univariate methods; (3) the use of the three-parameter gamma distribution for the background red and green intensities provides a much better fit than the normal (log normal) or t distributions; (4) the use of the bivariate t distribution for the foreground intensity provides a model that is less sensitive to extreme observations; (5) as a consequence of the aforementioned properties, it allows segmentation to be undertaken for a wide range of spot shapes, including doughnut, sickle shape and artifacts. We apply our method for gridding, segmentation and estimation to cDNA microarray real images and artificial data. Our method provides better segmentation results in spot shapes as well as intensity estimation than Spot and spotSegmentation R language softwares. It detected blank spots as well as bright artifact for the real data, and estimated spot intensities with high-accuracy for the synthetic data. The algorithms were implemented in Matlab. The Matlab codes implementing both the gridding and segmentation/estimation are available upon request. Supplementary material is available at Bioinformatics online.

An atlas of Copernicus ultraviolet spectra of Wolf-Rayet stars

NASA Technical Reports Server (NTRS)

Johnson, H. M.

1978-01-01

An atlas of Copernicus UV scans is presented, and line identifications are tabulated, for the Wolf-Rayet stars Gamma-2 Vel (WC 8 + O7), HD 50896 (= EZ CMa; WN 5), and HD 92740 (WN 7). The atlas covers the wavelength ranges from 946.8 to 3182 A for Gamma-2 Vel, from 1012 to 1294 A for HD 50896, and from 1051 to 1243 A for HD 92740. The wavelengths include corrections for components of satellite velocity, earth velocity, and stellar heliocentric velocity; each spectral feature is classified as interstellar, photospheric, emission, UV-displaced P Cygni line absorption, or P Cygni line emission. UV-edge velocities of the P Cygni profiles are estimated, P Cygni profile types are discussed, and the results are compared with Copernicus scans of OB stars exhibiting UV P Cygni profiles. It is noted that: (1) the line-strength ratio of molecular hydrogen to atomic species appears to be substantially greater in the scans of the WN stars than in the Gamma-2 Vel scans; (2) some of the P Cygni profiles in Gamma-2 Vel differ significantly from the corresponding profiles in OB stars; and (3) there may be a slight inverse correlation between ejection velocities and excitation potentials in Gamma-2 Vel.

MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans.

PubMed

Mendrik, Adriënne M; Vincken, Koen L; Kuijf, Hugo J; Breeuwer, Marcel; Bouvy, Willem H; de Bresser, Jeroen; Alansary, Amir; de Bruijne, Marleen; Carass, Aaron; El-Baz, Ayman; Jog, Amod; Katyal, Ranveer; Khan, Ali R; van der Lijn, Fedde; Mahmood, Qaiser; Mukherjee, Ryan; van Opbroek, Annegreet; Paneri, Sahil; Pereira, Sérgio; Persson, Mikael; Rajchl, Martin; Sarikaya, Duygu; Smedby, Örjan; Silva, Carlos A; Vrooman, Henri A; Vyas, Saurabh; Wang, Chunliang; Zhao, Liang; Biessels, Geert Jan; Viergever, Max A

2015-01-01

Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65-80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand.

MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

PubMed Central

Mendrik, Adriënne M.; Vincken, Koen L.; Kuijf, Hugo J.; Breeuwer, Marcel; Bouvy, Willem H.; de Bresser, Jeroen; Alansary, Amir; de Bruijne, Marleen; Carass, Aaron; El-Baz, Ayman; Jog, Amod; Katyal, Ranveer; Khan, Ali R.; van der Lijn, Fedde; Mahmood, Qaiser; Mukherjee, Ryan; van Opbroek, Annegreet; Paneri, Sahil; Pereira, Sérgio; Rajchl, Martin; Sarikaya, Duygu; Smedby, Örjan; Silva, Carlos A.; Vrooman, Henri A.; Vyas, Saurabh; Wang, Chunliang; Zhao, Liang; Biessels, Geert Jan; Viergever, Max A.

2015-01-01

Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65–80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand. PMID:26759553

3D printer generated thorax phantom with mobile tumor for radiation dosimetry

NASA Astrophysics Data System (ADS)

Mayer, Rulon; Liacouras, Peter; Thomas, Andrew; Kang, Minglei; Lin, Liyong; Simone, Charles B.

2015-07-01

This article describes the design, construction, and properties of an anthropomorphic thorax phantom with a moving surrogate tumor. This novel phantom permits detection of dose both inside and outside a moving tumor and within the substitute lung tissue material. A 3D printer generated the thorax shell composed of a chest wall, spinal column, and posterior regions of the phantom. Images of a computed tomography scan of the thorax from a patient with lung cancer provided the template for the 3D printing. The plastic phantom is segmented into two materials representing the muscle and bones, and its geometry closely matches a patient. A surrogate spherical plastic tumor controlled by a 3D linear stage simulates a lung tumor's trajectory during normal breathing. Sawdust emulates the lung tissue in terms of average and distribution in Hounsfield numbers. The sawdust also provides a forgiving medium that permits tumor motion and sandwiching of radiochromic film inside the mobile surrogate plastic tumor for dosimetry. A custom cork casing shields the film and tumor and eliminates film bending during extended scans. The phantom, lung tissue surrogate, and radiochromic film are exposed to a seven field plan based on an ECLIPSE plan for 6 MV photons from a Trilogy machine delivering 230 cGy to the isocenter. The dose collected in a sagittal plane is compared to the calculated plan. Gamma analysis finds 8.8% and 5.5% gamma failure rates for measurements of large amplitude trajectory and static measurements relative to the large amplitude plan, respectively. These particular gamma analysis results were achieved using parameters of 3% dose and 3 mm, for regions receiving doses >150 cGy. The plan assumes a stationary detection grid unlike the moving radiochromic film and tissues. This difference was experimentally observed and motivated calculated dose distributions that incorporated the phase of the tumor periodic motion. These calculations modestly improve agreement between the measured and intended doses.

3D printer generated thorax phantom with mobile tumor for radiation dosimetry.

PubMed

Mayer, Rulon; Liacouras, Peter; Thomas, Andrew; Kang, Minglei; Lin, Liyong; Simone, Charles B

2015-07-01

This article describes the design, construction, and properties of an anthropomorphic thorax phantom with a moving surrogate tumor. This novel phantom permits detection of dose both inside and outside a moving tumor and within the substitute lung tissue material. A 3D printer generated the thorax shell composed of a chest wall, spinal column, and posterior regions of the phantom. Images of a computed tomography scan of the thorax from a patient with lung cancer provided the template for the 3D printing. The plastic phantom is segmented into two materials representing the muscle and bones, and its geometry closely matches a patient. A surrogate spherical plastic tumor controlled by a 3D linear stage simulates a lung tumor's trajectory during normal breathing. Sawdust emulates the lung tissue in terms of average and distribution in Hounsfield numbers. The sawdust also provides a forgiving medium that permits tumor motion and sandwiching of radiochromic film inside the mobile surrogate plastic tumor for dosimetry. A custom cork casing shields the film and tumor and eliminates film bending during extended scans. The phantom, lung tissue surrogate, and radiochromic film are exposed to a seven field plan based on an ECLIPSE plan for 6 MV photons from a Trilogy machine delivering 230 cGy to the isocenter. The dose collected in a sagittal plane is compared to the calculated plan. Gamma analysis finds 8.8% and 5.5% gamma failure rates for measurements of large amplitude trajectory and static measurements relative to the large amplitude plan, respectively. These particular gamma analysis results were achieved using parameters of 3% dose and 3 mm, for regions receiving doses >150 cGy. The plan assumes a stationary detection grid unlike the moving radiochromic film and tissues. This difference was experimentally observed and motivated calculated dose distributions that incorporated the phase of the tumor periodic motion. These calculations modestly improve agreement between the measured and intended doses.

3D printer generated thorax phantom with mobile tumor for radiation dosimetry

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

Mayer, Rulon; Liacouras, Peter; Thomas, Andrew

2015-07-15

This article describes the design, construction, and properties of an anthropomorphic thorax phantom with a moving surrogate tumor. This novel phantom permits detection of dose both inside and outside a moving tumor and within the substitute lung tissue material. A 3D printer generated the thorax shell composed of a chest wall, spinal column, and posterior regions of the phantom. Images of a computed tomography scan of the thorax from a patient with lung cancer provided the template for the 3D printing. The plastic phantom is segmented into two materials representing the muscle and bones, and its geometry closely matches amore » patient. A surrogate spherical plastic tumor controlled by a 3D linear stage simulates a lung tumor’s trajectory during normal breathing. Sawdust emulates the lung tissue in terms of average and distribution in Hounsfield numbers. The sawdust also provides a forgiving medium that permits tumor motion and sandwiching of radiochromic film inside the mobile surrogate plastic tumor for dosimetry. A custom cork casing shields the film and tumor and eliminates film bending during extended scans. The phantom, lung tissue surrogate, and radiochromic film are exposed to a seven field plan based on an ECLIPSE plan for 6 MV photons from a Trilogy machine delivering 230 cGy to the isocenter. The dose collected in a sagittal plane is compared to the calculated plan. Gamma analysis finds 8.8% and 5.5% gamma failure rates for measurements of large amplitude trajectory and static measurements relative to the large amplitude plan, respectively. These particular gamma analysis results were achieved using parameters of 3% dose and 3 mm, for regions receiving doses >150 cGy. The plan assumes a stationary detection grid unlike the moving radiochromic film and tissues. This difference was experimentally observed and motivated calculated dose distributions that incorporated the phase of the tumor periodic motion. These calculations modestly improve agreement between the measured and intended doses.« less

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Observational techniques for solar flare gamma-rays, hard X-rays, and neutrons

NASA Technical Reports Server (NTRS)

Lin, Robert P.

1989-01-01

The development of new instrumentation and techniques for solar hard X-ray, gamma ray and neutron observations from spacecraft and/or balloon-borne platforms is examined. The principal accomplishments are: (1) the development of a two segment germanium detector which is near ideal for solar hard X-ray and gamma ray spectroscopy; (2) the development of long duration balloon flight techniques and associated instrumentation; and (3) the development of innovative new position sensitive detectors for hard X-ray and gamma rays.

Analysis of Agreement of Retinal-Layer Thickness Measures Derived from the Segmentation of Horizontal and Vertical Spectralis OCT Macular Scans.

PubMed

Gonzalez Caldito, Natalia; Antony, Bhavna; He, Yufan; Lang, Andrew; Nguyen, James; Rothman, Alissa; Ogbuokiri, Esther; Avornu, Ama; Balcer, Laura; Frohman, Elliot; Frohman, Teresa C; Bhargava, Pavan; Prince, Jerry; Calabresi, Peter A; Saidha, Shiv

2018-03-01

Optical coherence tomography (OCT) is a reliable method used to quantify discrete layers of the retina. Spectralis OCT is a device used for this purpose. Spectralis OCT macular scan imaging acquisition can be obtained on either the horizontal or vertical plane. The vertical protocol has been proposed as favorable, due to postulated reduction in confound of Henle's fibers on segmentation-derived metrics. Yet, agreement of the segmentation measures of horizontal and vertical macular scans remains unexplored. Our aim was to determine this agreement. Horizontal and vertical macular scans on Spectralis OCT were acquired in 20 healthy controls (HCs) and 20 multiple sclerosis (MS) patients. All scans were segmented using Heidelberg software and a Johns Hopkins University (JHU)-developed method. Agreement was analyzed using Bland-Altman analyses and intra-class correlation coefficients (ICCs). Using both segmentation techniques, mean differences (agreement at the cohort level) in the thicknesses of all macular layers derived from both acquisition protocols in MS patients and HCs were narrow (<1 µm), while the limits of agreement (LOA) (agreement at the individual level) were wider. Using JHU segmentation mean differences (and LOA) for the macular retinal nerve fiber layer (RNFL) and ganglion cell layer + inner plexiform layer (GCIP) in MS were 0.21 µm (-1.57-1.99 µm) and -0.36 µm (-1.44-1.37 µm), respectively. OCT segmentation measures of discrete retinal-layer thicknesses derived from both vertical and horizontal protocols on Spectralis OCT agree excellently at the cohort level (narrow mean differences), but only moderately at the individual level (wide LOA). This suggests patients scanned using either protocol should continue to be scanned with the same protocol. However, due to excellent agreement at the cohort level, measures derived from both acquisitions can be pooled for outcome purposes in clinical trials.

Segmental Musculoskeletal Examinations using Dual-Energy X-Ray Absorptiometry (DXA): Positioning and Analysis Considerations

PubMed Central

Hart, Nicolas H.; Nimphius, Sophia; Spiteri, Tania; Cochrane, Jodie L.; Newton, Robert U.

2015-01-01

Musculoskeletal examinations provide informative and valuable quantitative insight into muscle and bone health. DXA is one mainstream tool used to accurately and reliably determine body composition components and bone mass characteristics in-vivo. Presently, whole body scan models separate the body into axial and appendicular regions, however there is a need for localised appendicular segmentation models to further examine regions of interest within the upper and lower extremities. Similarly, inconsistencies pertaining to patient positioning exist in the literature which influence measurement precision and analysis outcomes highlighting a need for standardised procedure. This paper provides standardised and reproducible: 1) positioning and analysis procedures using DXA and 2) reliable segmental examinations through descriptive appendicular boundaries. Whole-body scans were performed on forty-six (n = 46) football athletes (age: 22.9 ± 4.3 yrs; height: 1.85 ± 0.07 cm; weight: 87.4 ± 10.3 kg; body fat: 11.4 ± 4.5 %) using DXA. All segments across all scans were analysed three times by the main investigator on three separate days, and by three independent investigators a week following the original analysis. To examine intra-rater and inter-rater, between day and researcher reliability, coefficients of variation (CV) and intraclass correlation coefficients (ICC) were determined. Positioning and segmental analysis procedures presented in this study produced very high, nearly perfect intra-tester (CV ≤ 2.0%; ICC ≥ 0.988) and inter-tester (CV ≤ 2.4%; ICC ≥ 0.980) reliability, demonstrating excellent reproducibility within and between practitioners. Standardised examinations of axial and appendicular segments are necessary. Future studies aiming to quantify and report segmental analyses of the upper- and lower-body musculoskeletal properties using whole-body DXA scans are encouraged to use the patient positioning and image analysis procedures outlined in this paper. Key points Musculoskeletal examinations using DXA technology require highly standardised and reproducible patient positioning and image analysis procedures to accurately measure and monitor axial, appendicular and segmental regions of interest. Internal rotation and fixation of the lower-limbs is strongly recommended during whole-body DXA scans to prevent undesired movement, improve frontal mass accessibility and enhance ankle joint visibility during scan performance and analysis. Appendicular segmental analyses using whole-body DXA scans are highly reliable for all regional upper-body and lower-body segmentations, with hard-tissue (CV ≤ 1.5%; R ≥ 0.990) achieving greater reliability and lower error than soft-tissue (CV ≤ 2.4%; R ≥ 0.980) masses when using our appendicular segmental boundaries. PMID:26336349

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.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Reading Center Characterization of Central Retinal Vein Occlusion Using Optical Coherence Tomography During the COPERNICUS Trial.

PubMed

Decroos, Francis Char; Stinnett, Sandra S; Heydary, Cynthia S; Burns, Russell E; Jaffe, Glenn J

2013-11-01

To determine the impact of segmentation error correction and precision of standardized grading of time domain optical coherence tomography (OCT) scans obtained during an interventional study for macular edema secondary to central retinal vein occlusion (CRVO). A reading center team of two readers and a senior reader evaluated 1199 OCT scans. Manual segmentation error correction (SEC) was performed. The frequency of SEC, resulting change in central retinal thickness after SEC, and reproducibility of SEC were quantified. Optical coherence tomography characteristics associated with the need for SECs were determined. Reading center teams graded all scans, and the reproducibility of this evaluation for scan quality at the fovea and cystoid macular edema was determined on 97 scans. Segmentation errors were observed in 360 (30.0%) scans, of which 312 were interpretable. On these 312 scans, the mean machine-generated central subfield thickness (CST) was 507.4 ± 208.5 μm compared to 583.0 ± 266.2 μm after SEC. Segmentation error correction resulted in a mean absolute CST correction of 81.3 ± 162.0 μm from baseline uncorrected CST. Segmentation error correction was highly reproducible (intraclass correlation coefficient [ICC] = 0.99-1.00). Epiretinal membrane (odds ratio [OR] = 2.3, P < 0.0001), subretinal fluid (OR = 2.1, P = 0.0005), and increasing CST (OR = 1.6 per 100-μm increase, P < 0.001) were associated with need for SEC. Reading center teams reproducibly graded scan quality at the fovea (87% agreement, kappa = 0.64, 95% confidence interval [CI] 0.45-0.82) and cystoid macular edema (92% agreement, kappa = 0.84, 95% CI 0.74-0.94). Optical coherence tomography images obtained during an interventional CRVO treatment trial can be reproducibly graded. Segmentation errors can cause clinically meaningful deviation in central retinal thickness measurements; however, these errors can be corrected reproducibly in a reading center setting. Segmentation errors are common on these images, can cause clinically meaningful errors in central retinal thickness measurement, and can be corrected reproducibly in a reading center setting.

A novel system to diagnose cutaneous adverse drug reactions employing the cellscan--comparison with histamine releasing test and Inf-gamma Releasing Test.

PubMed

Goldberg, Ilan; Gilburd, Boris; Kravitz, Martine Szyper; Kivity, Shmuel; Chaim, Berta Ben; Klein, Tirza; Schiffenbauer, Yael; Trubniykovr, Ela; Brenner, Sarah; Shoenfeld, Yehuda

2005-03-01

There are several mechanisms to describe allergic drug reactions yet the methods to diagnose them are limited. To compare several conventional clinical and laboratory methods to diagnose skin reactions to drugs to a new method of diagnosing drug reactions by the CellScan system. The study entailed 21 patients who were diagnosed as suffering from drug eruptions, and 105 healthy controls with no history of drug allergy. The drugs were classified into two groups according to suspicion of causing drug allergy: high and low. Most of the patients were on more than one drug, leading to 41 patient-drug interactions (assays). Histamine releasing test (HRT), interferon (INF)-gamma releasing test and CellScan examination were performed on lymphocytes of the patients and controls. The HRTwas interpreted as positive in 9 out of 18 (50%) patients and in 13 out of 35 (37%) assays. Based on the INF-gamma releasing test, positive results were observed in 16 out of 21 (76%) patients and in 24 out of 41 (59%) assays. In the CellScan test (CST), positive results were observed in 17 out of 21 (81%) patients and in 29 out of 41 (71%) assays. The rate of identifying the drug for eruption in the high suspicion level drugs was 9 out of 22 (41%) assays in the HRT, 20 out of 24 (83%) assays in the INF-gamma releasing test, and 21 out of 24 (87%) studies with the CellScan method. The rate of determining of the drug that caused the eruption in the low suspicion level drugs was 4 out of 13 (31 %) in the HRT, 4 out of 17 (24%) assays in the INF-gamma releasing test, and 8 out of 17 (47%) analyses in the CST. When examined in the CellScan, 99 out of 105 (94%) controls were interpreted as negative. This preliminary study indicates that the CellScan seems to be an easy and promising method for the detection of drugs responsible for adverse skin reactions. In contrast to the HRT and to the Interferon-gamma secretion test, the CellScan method is characterized by its ability to track and monitor the reaction of individual cells. By measuring the kinetic parameters of selected cells before and after adding the suspected drug, we were able to identify the culprit drug. The CellScan method had the highest sensitivity, and the interferon-gamma secretion test had the highest specificity for detection of the culprit drug. In contrast, the analysis of 105 normal control sera disclosed a high specificity of 94% for the CellScan method.

Efficient terrestrial laser scan segmentation exploiting data structure

NASA Astrophysics Data System (ADS)

Mahmoudabadi, Hamid; Olsen, Michael J.; Todorovic, Sinisa

2016-09-01

New technologies such as lidar enable the rapid collection of massive datasets to model a 3D scene as a point cloud. However, while hardware technology continues to advance, processing 3D point clouds into informative models remains complex and time consuming. A common approach to increase processing efficiently is to segment the point cloud into smaller sections. This paper proposes a novel approach for point cloud segmentation using computer vision algorithms to analyze panoramic representations of individual laser scans. These panoramas can be quickly created using an inherent neighborhood structure that is established during the scanning process, which scans at fixed angular increments in a cylindrical or spherical coordinate system. In the proposed approach, a selected image segmentation algorithm is applied on several input layers exploiting this angular structure including laser intensity, range, normal vectors, and color information. These segments are then mapped back to the 3D point cloud so that modeling can be completed more efficiently. This approach does not depend on pre-defined mathematical models and consequently setting parameters for them. Unlike common geometrical point cloud segmentation methods, the proposed method employs the colorimetric and intensity data as another source of information. The proposed algorithm is demonstrated on several datasets encompassing variety of scenes and objects. Results show a very high perceptual (visual) level of segmentation and thereby the feasibility of the proposed algorithm. The proposed method is also more efficient compared to Random Sample Consensus (RANSAC), which is a common approach for point cloud segmentation.

Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies.

PubMed

Vivanti, Refael; Joskowicz, Leo; Lev-Cohain, Naama; Ephrat, Ariel; Sosna, Jacob

2018-03-10

Radiological longitudinal follow-up of tumors in CT scans is essential for disease assessment and liver tumor therapy. Currently, most tumor size measurements follow the RECIST guidelines, which can be off by as much as 50%. True volumetric measurements are more accurate but require manual delineation, which is time-consuming and user-dependent. We present a convolutional neural networks (CNN) based method for robust automatic liver tumor delineation in longitudinal CT studies that uses both global and patient specific CNNs trained on a small database of delineated images. The inputs are the baseline scan and the tumor delineation, a follow-up scan, and a liver tumor global CNN voxel classifier built from radiologist-validated liver tumor delineations. The outputs are the tumor delineations in the follow-up CT scan. The baseline scan tumor delineation serves as a high-quality prior for the tumor characterization in the follow-up scans. It is used to evaluate the global CNN performance on the new case and to reliably predict failures of the global CNN on the follow-up scan. High-scoring cases are segmented with a global CNN; low-scoring cases, which are predicted to be failures of the global CNN, are segmented with a patient-specific CNN built from the baseline scan. Our experimental results on 222 tumors from 31 patients yield an average overlap error of 17% (std = 11.2) and surface distance of 2.1 mm (std = 1.8), far better than stand-alone segmentation. Importantly, the robustness of our method improved from 67% for stand-alone global CNN segmentation to 100%. Unlike other medical imaging deep learning approaches, which require large annotated training datasets, our method exploits the follow-up framework to yield accurate tumor tracking and failure detection and correction with a small training dataset. Graphical abstract Flow diagram of the proposed method. In the offline mode (orange), a global CNN is trained as a voxel classifier to segment liver tumor as in [31]. The online mode (blue) is used for each new case. The input is baseline scan with delineation and the follow-up CT scan to be segmented. The main novelty is the ability to predict failures by trying the system on the baseline scan and the ability to correct them using the patient-specific CNN.

Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

NASA Astrophysics Data System (ADS)

Li, X. L.; Zhao, Q. H.; Li, Y.

2017-09-01

Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

Segmentation of left atrial intracardiac ultrasound images for image guided cardiac ablation therapy

NASA Astrophysics Data System (ADS)

Rettmann, M. E.; Stephens, T.; Holmes, D. R.; Linte, C.; Packer, D. L.; Robb, R. A.

2013-03-01

Intracardiac echocardiography (ICE), a technique in which structures of the heart are imaged using a catheter navigated inside the cardiac chambers, is an important imaging technique for guidance in cardiac ablation therapy. Automatic segmentation of these images is valuable for guidance and targeting of treatment sites. In this paper, we describe an approach to segment ICE images by generating an empirical model of blood pool and tissue intensities. Normal, Weibull, Gamma, and Generalized Extreme Value (GEV) distributions are fit to histograms of tissue and blood pool pixels from a series of ICE scans. A total of 40 images from 4 separate studies were evaluated. The model was trained and tested using two approaches. In the first approach, the model was trained on all images from 3 studies and subsequently tested on the 40 images from the 4th study. This procedure was repeated 4 times using a leave-one-out strategy. This is termed the between-subjects approach. In the second approach, the model was trained on 10 randomly selected images from a single study and tested on the remaining 30 images in that study. This is termed the within-subjects approach. For both approaches, the model was used to automatically segment ICE images into blood and tissue regions. Each pixel is classified using the Generalized Liklihood Ratio Test across neighborhood sizes ranging from 1 to 49. Automatic segmentation results were compared against manual segmentations for all images. In the between-subjects approach, the GEV distribution using a neighborhood size of 17 was found to be the most accurate with a misclassification rate of approximately 17%. In the within-subjects approach, the GEV distribution using a neighborhood size of 19 was found to be the most accurate with a misclassification rate of approximately 15%. As expected, the majority of misclassified pixels were located near the boundaries between tissue and blood pool regions for both methods.

3-D segmentation of retinal blood vessels in spectral-domain OCT volumes of the optic nerve head

NASA Astrophysics Data System (ADS)

Lee, Kyungmoo; Abràmoff, Michael D.; Niemeijer, Meindert; Garvin, Mona K.; Sonka, Milan

2010-03-01

Segmentation of retinal blood vessels can provide important information for detecting and tracking retinal vascular diseases including diabetic retinopathy, arterial hypertension, arteriosclerosis and retinopathy of prematurity (ROP). Many studies on 2-D segmentation of retinal blood vessels from a variety of medical images have been performed. However, 3-D segmentation of retinal blood vessels from spectral-domain optical coherence tomography (OCT) volumes, which is capable of providing geometrically accurate vessel models, to the best of our knowledge, has not been previously studied. The purpose of this study is to develop and evaluate a method that can automatically detect 3-D retinal blood vessels from spectral-domain OCT scans centered on the optic nerve head (ONH). The proposed method utilized a fast multiscale 3-D graph search to segment retinal surfaces as well as a triangular mesh-based 3-D graph search to detect retinal blood vessels. An experiment on 30 ONH-centered OCT scans (15 right eye scans and 15 left eye scans) from 15 subjects was performed, and the mean unsigned error in 3-D of the computer segmentations compared with the independent standard obtained from a retinal specialist was 3.4 +/- 2.5 voxels (0.10 +/- 0.07 mm).

Role of B-scan ultrasonography in pre-operative cataract patients.

PubMed

Qureshi, Manzoor A; Laghari, Khalida

2010-01-01

To visualize the posterior portion of eye globe in dense cataract patients with B scan ultrasound, and to find out any posterior segment lesion in such pre-operative cases. We performed diagnostic B-scan ultrasound on 750 cataract patients before surgery. This was a prospective diagnostic study which was conducted in the Department of Opthalmology, Liaquat University Eye Hospital, Hyderabad Sind, Pakistan from January 2007 to July 2007. Detailed history and some basic eye examination techniques, like slit lamp and tonometry were done in two groups of patients, traumatic (71) and non traumatic(679). Patients in the age range of 1 to 79 years of both sexes were included. Patients having already posterior segment lesions and those who had previous history of ocular surgery were excluded from the study. An ultrasound machine Nidek Echo Scan Model US-3300 with a probe of direct contact was used. Out of 750 patients, 90 patients had posterior segment lesions. Among traumatic group of 71 patients, 39 (55%) had positive posterior segment lesions, while in the non traumatic group of 679 patients, only 51 (7%) cases had positive posterior segment lesions. Out of the 90 positive cases, 25 (3%) had retinal detachment, 14 (2%) had posterior vitreous detachment, 24 (3%) had vitreous hemorrhage, 12 (2%) were asteroid hyolosis, while posterior staphyloma and intra-ocular foreign body were found with the frequency of 9 (1.2%) and 6 (1%), respectively. We concluded that two dimensional B-scan ultrasound can be one of the diagnostic tool for the detection of hidden posterior segment lesions and can be performed routinely in pre-operative cataract patients, as this would help in surgical planning. In cases, where a two dimensional B-scan is not sufficient or helpful. a three dimensional ultrasound would be justified.

A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning.

PubMed

Rundo, Leonardo; Stefano, Alessandro; Militello, Carmelo; Russo, Giorgio; Sabini, Maria Gabriella; D'Arrigo, Corrado; Marletta, Francesco; Ippolito, Massimo; Mauri, Giancarlo; Vitabile, Salvatore; Gilardi, Maria Carla

2017-06-01

Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [ 11 C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation. A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife ® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTV MRI . A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment, the feasibility and the clinical value of BTV integration in Gamma Knife treatment planning were considered. Therefore, a qualitative evaluation was carried out by three experienced clinicians. The achieved experimental results showed that GTV and BTV segmentations are statistically correlated (Spearman's rank correlation coefficient: 0.898) but they have low similarity degree (average Dice Similarity Coefficient: 61.87 ± 14.64). Therefore, volume measurements as well as evaluation metrics values demonstrated that MRI and PET convey different but complementary imaging information. GTV and BTV could be combined to enhance treatment planning. In more than 50% of cases the CTV was strongly or moderately conditioned by metabolic imaging. Especially, BTV MRI enhanced the CTV more accurately than BTV in 25% of cases. The proposed fully automatic multimodal PET/MRI segmentation method is a valid operator-independent methodology helping the clinicians to define a CTV that includes both metabolic and morphologic information. BTV MRI and GTV should be considered for a comprehensive treatment planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic segmentation of vessels in in-vivo ultrasound scans

NASA Astrophysics Data System (ADS)

Tamimi-Sarnikowski, Philip; Brink-Kjær, Andreas; Moshavegh, Ramin; Arendt Jensen, Jørgen

2017-03-01

Ultrasound has become highly popular to monitor atherosclerosis, by scanning the carotid artery. The screening involves measuring the thickness of the vessel wall and diameter of the lumen. An automatic segmentation of the vessel lumen, can enable the determination of lumen diameter. This paper presents a fully automatic segmentation algorithm, for robustly segmenting the vessel lumen in longitudinal B-mode ultrasound images. The automatic segmentation is performed using a combination of B-mode and power Doppler images. The proposed algorithm includes a series of preprocessing steps, and performs a vessel segmentation by use of the marker-controlled watershed transform. The ultrasound images used in the study were acquired using the bk3000 ultrasound scanner (BK Ultrasound, Herlev, Denmark) with two transducers "8L2 Linear" and "10L2w Wide Linear" (BK Ultrasound, Herlev, Denmark). The algorithm was evaluated empirically and applied to a dataset of in-vivo 1770 images recorded from 8 healthy subjects. The segmentation results were compared to manual delineation performed by two experienced users. The results showed a sensitivity and specificity of 90.41+/-11.2 % and 97.93+/-5.7% (mean+/-standard deviation), respectively. The amount of overlap of segmentation and manual segmentation, was measured by the Dice similarity coefficient, which was 91.25+/-11.6%. The empirical results demonstrated the feasibility of segmenting the vessel lumen in ultrasound scans using a fully automatic algorithm.

Three-Dimensions Segmentation of Pulmonary Vascular Trees for Low Dose CT Scans

NASA Astrophysics Data System (ADS)

Lai, Jun; Huang, Ying; Wang, Ying; Wang, Jun

2016-12-01

Due to the low contrast and the partial volume effects, providing an accurate and in vivo analysis for pulmonary vascular trees from low dose CT scans is a challenging task. This paper proposes an automatic integration segmentation approach for the vascular trees in low dose CT scans. It consists of the following steps: firstly, lung volumes are acquired by the knowledge based method from the CT scans, and then the data are smoothed by the 3D Gaussian filter; secondly, two or three seeds are gotten by the adaptive 2D segmentation and the maximum area selecting from different position scans; thirdly, each seed as the start voxel is inputted for a quick multi-seeds 3D region growing to get vascular trees; finally, the trees are refined by the smooth filter. Through skeleton analyzing for the vascular trees, the results show that the proposed method can provide much better and lower level vascular branches.

Computer-based radiological longitudinal evaluation of meningiomas following stereotactic radiosurgery.

PubMed

Shimol, Eli Ben; Joskowicz, Leo; Eliahou, Ruth; Shoshan, Yigal

2018-02-01

Stereotactic radiosurgery (SRS) is a common treatment for intracranial meningiomas. SRS is planned on a pre-therapy gadolinium-enhanced T1-weighted MRI scan (Gd-T1w MRI) in which the meningioma contours have been delineated. Post-SRS therapy serial Gd-T1w MRI scans are then acquired for longitudinal treatment evaluation. Accurate tumor volume change quantification is required for treatment efficacy evaluation and for treatment continuation. We present a new algorithm for the automatic segmentation and volumetric assessment of meningioma in post-therapy Gd-T1w MRI scans. The inputs are the pre- and post-therapy Gd-T1w MRI scans and the meningioma delineation in the pre-therapy scan. The output is the meningioma delineations and volumes in the post-therapy scan. The algorithm uses the pre-therapy scan and its meningioma delineation to initialize an extended Chan-Vese active contour method and as a strong patient-specific intensity and shape prior for the post-therapy scan meningioma segmentation. The algorithm is automatic, obviates the need for independent tumor localization and segmentation initialization, and incorporates the same tumor delineation criteria in both the pre- and post-therapy scans. Our experimental results on retrospective pre- and post-therapy scans with a total of 32 meningiomas with volume ranges 0.4-26.5 cm[Formula: see text] yield a Dice coefficient of [Formula: see text]% with respect to ground-truth delineations in post-therapy scans created by two clinicians. These results indicate a high correspondence to the ground-truth delineations. Our algorithm yields more reliable and accurate tumor volume change measurements than other stand-alone segmentation methods. It may be a useful tool for quantitative meningioma prognosis evaluation after SRS.

Measurements of Soil Carbon by Neutron-Gamma Analysis in Static and Scanning Modes.

PubMed

Yakubova, Galina; Kavetskiy, Aleksandr; Prior, Stephen A; Torbert, H Allen

2017-08-24

The herein described application of the inelastic neutron scattering (INS) method for soil carbon analysis is based on the registration and analysis of gamma rays created when neutrons interact with soil elements. The main parts of the INS system are a pulsed neutron generator, NaI(Tl) gamma detectors, split electronics to separate gamma spectra due to INS and thermo-neutron capture (TNC) processes, and software for gamma spectra acquisition and data processing. This method has several advantages over other methods in that it is a non-destructive in situ method that measures the average carbon content in large soil volumes, is negligibly impacted by local sharp changes in soil carbon, and can be used in stationary or scanning modes. The result of the INS method is the carbon content from a site with a footprint of ~2.5 - 3 m 2 in the stationary regime, or the average carbon content of the traversed area in the scanning regime. The measurement range of the current INS system is >1.5 carbon weight % (standard deviation ± 0.3 w%) in the upper 10 cm soil layer for a 1 hmeasurement.

Manual versus Automated Carotid Artery Plaque Component Segmentation in High and Lower Quality 3.0 Tesla MRI Scans

PubMed Central

Smits, Loek P.; van Wijk, Diederik F.; Duivenvoorden, Raphael; Xu, Dongxiang; Yuan, Chun; Stroes, Erik S.; Nederveen, Aart J.

2016-01-01

Purpose To study the interscan reproducibility of manual versus automated segmentation of carotid artery plaque components, and the agreement between both methods, in high and lower quality MRI scans. Methods 24 patients with 30–70% carotid artery stenosis were planned for 3T carotid MRI, followed by a rescan within 1 month. A multicontrast protocol (T1w,T2w, PDw and TOF sequences) was used. After co-registration and delineation of the lumen and outer wall, segmentation of plaque components (lipid-rich necrotic cores (LRNC) and calcifications) was performed both manually and automated. Scan quality was assessed using a visual quality scale. Results Agreement for the detection of LRNC (Cohen’s kappa (k) is 0.04) and calcification (k = 0.41) between both manual and automated segmentation methods was poor. In the high-quality scans (visual quality score ≥ 3), the agreement between manual and automated segmentation increased to k = 0.55 and k = 0.58 for, respectively, the detection of LRNC and calcification larger than 1 mm2. Both manual and automated analysis showed good interscan reproducibility for the quantification of LRNC (intraclass correlation coefficient (ICC) of 0.94 and 0.80 respectively) and calcified plaque area (ICC of 0.95 and 0.77, respectively). Conclusion Agreement between manual and automated segmentation of LRNC and calcifications was poor, despite a good interscan reproducibility of both methods. The agreement between both methods increased to moderate in high quality scans. These findings indicate that image quality is a critical determinant of the performance of both manual and automated segmentation of carotid artery plaque components. PMID:27930665

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

PubMed Central

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

2014-01-01

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

Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences.

PubMed

Ghose, Soumya; Greer, Peter B; Sun, Jidi; Pichler, Peter; Rivest-Henault, David; Mitra, Jhimli; Richardson, Haylea; Wratten, Chris; Martin, Jarad; Arm, Jameen; Best, Leah; Dowling, Jason A

2017-10-27

In MR only radiation therapy planning, generation of the tissue specific HU map directly from the MRI would eliminate the need of CT image acquisition and may improve radiation therapy planning. The aim of this work is to generate and validate substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans in prostate radiation therapy dose planning. A Siemens Skyra 3T MRI scanner with laser bridge, flat couch and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole pelvis MRI (1.6 mm 3D isotropic T2w SPACE sequence) was acquired. Patients received a routine planning CT scan. Co-registered whole pelvis CT and T2w MRI pairs were used as training images. Advanced tissue specific non-linear regression models to predict HU for the fat, muscle, bladder and air were created from co-registered CT-MRI image pairs. On a test case T2w MRI, the bones and bladder were automatically segmented using a novel statistical shape and appearance model, while other soft tissues were separated using an Expectation-Maximization based clustering model. The CT bone in the training database that was most 'similar' to the segmented bone was then transformed with deformable registration to create the sCT component of the test case T2w MRI bone tissue. Predictions for the bone, air and soft tissue from the separate regression models were successively combined to generate a whole pelvis sCT. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same IMRT dose plan was found to be [Formula: see text] (mean  ±  standard deviation) for 39 patients. The 3D Gamma pass rate was [Formula: see text] (2 mm/2%). The novel hybrid model is computationally efficient, generating an sCT in 20 min from standard T2w images for prostate cancer radiation therapy dose planning and DRR generation.

Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences

NASA Astrophysics Data System (ADS)

Ghose, Soumya; Greer, Peter B.; Sun, Jidi; Pichler, Peter; Rivest-Henault, David; Mitra, Jhimli; Richardson, Haylea; Wratten, Chris; Martin, Jarad; Arm, Jameen; Best, Leah; Dowling, Jason A.

2017-11-01

In MR only radiation therapy planning, generation of the tissue specific HU map directly from the MRI would eliminate the need of CT image acquisition and may improve radiation therapy planning. The aim of this work is to generate and validate substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans in prostate radiation therapy dose planning. A Siemens Skyra 3T MRI scanner with laser bridge, flat couch and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole pelvis MRI (1.6 mm 3D isotropic T2w SPACE sequence) was acquired. Patients received a routine planning CT scan. Co-registered whole pelvis CT and T2w MRI pairs were used as training images. Advanced tissue specific non-linear regression models to predict HU for the fat, muscle, bladder and air were created from co-registered CT-MRI image pairs. On a test case T2w MRI, the bones and bladder were automatically segmented using a novel statistical shape and appearance model, while other soft tissues were separated using an Expectation-Maximization based clustering model. The CT bone in the training database that was most ‘similar’ to the segmented bone was then transformed with deformable registration to create the sCT component of the test case T2w MRI bone tissue. Predictions for the bone, air and soft tissue from the separate regression models were successively combined to generate a whole pelvis sCT. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same IMRT dose plan was found to be 0.3%+/-0.9% (mean  ±  standard deviation) for 39 patients. The 3D Gamma pass rate was 99.8+/-0.00 (2 mm/2%). The novel hybrid model is computationally efficient, generating an sCT in 20 min from standard T2w images for prostate cancer radiation therapy dose planning and DRR generation.

Multivendor Spectral-Domain Optical Coherence Tomography Dataset, Observer Annotation Performance Evaluation, and Standardized Evaluation Framework for Intraretinal Cystoid Fluid Segmentation.

PubMed

Wu, Jing; Philip, Ana-Maria; Podkowinski, Dominika; Gerendas, Bianca S; Langs, Georg; Simader, Christian; Waldstein, Sebastian M; Schmidt-Erfurth, Ursula M

2016-01-01

Development of image analysis and machine learning methods for segmentation of clinically significant pathology in retinal spectral-domain optical coherence tomography (SD-OCT), used in disease detection and prediction, is limited due to the availability of expertly annotated reference data. Retinal segmentation methods use datasets that either are not publicly available, come from only one device, or use different evaluation methodologies making them difficult to compare. Thus we present and evaluate a multiple expert annotated reference dataset for the problem of intraretinal cystoid fluid (IRF) segmentation, a key indicator in exudative macular disease. In addition, a standardized framework for segmentation accuracy evaluation, applicable to other pathological structures, is presented. Integral to this work is the dataset used which must be fit for purpose for IRF segmentation algorithm training and testing. We describe here a multivendor dataset comprised of 30 scans. Each OCT scan for system training has been annotated by multiple graders using a proprietary system. Evaluation of the intergrader annotations shows a good correlation, thus making the reproducibly annotated scans suitable for the training and validation of image processing and machine learning based segmentation methods. The dataset will be made publicly available in the form of a segmentation Grand Challenge.

Multivendor Spectral-Domain Optical Coherence Tomography Dataset, Observer Annotation Performance Evaluation, and Standardized Evaluation Framework for Intraretinal Cystoid Fluid Segmentation

PubMed Central

Wu, Jing; Philip, Ana-Maria; Podkowinski, Dominika; Gerendas, Bianca S.; Langs, Georg; Simader, Christian

2016-01-01

Development of image analysis and machine learning methods for segmentation of clinically significant pathology in retinal spectral-domain optical coherence tomography (SD-OCT), used in disease detection and prediction, is limited due to the availability of expertly annotated reference data. Retinal segmentation methods use datasets that either are not publicly available, come from only one device, or use different evaluation methodologies making them difficult to compare. Thus we present and evaluate a multiple expert annotated reference dataset for the problem of intraretinal cystoid fluid (IRF) segmentation, a key indicator in exudative macular disease. In addition, a standardized framework for segmentation accuracy evaluation, applicable to other pathological structures, is presented. Integral to this work is the dataset used which must be fit for purpose for IRF segmentation algorithm training and testing. We describe here a multivendor dataset comprised of 30 scans. Each OCT scan for system training has been annotated by multiple graders using a proprietary system. Evaluation of the intergrader annotations shows a good correlation, thus making the reproducibly annotated scans suitable for the training and validation of image processing and machine learning based segmentation methods. The dataset will be made publicly available in the form of a segmentation Grand Challenge. PMID:27579177

Automated vessel shadow segmentation of fovea-centered spectral-domain images from multiple OCT devices

NASA Astrophysics Data System (ADS)

Wu, Jing; Gerendas, Bianca S.; Waldstein, Sebastian M.; Simader, Christian; Schmidt-Erfurth, Ursula

2014-03-01

Spectral-domain Optical Coherence Tomography (SD-OCT) is a non-invasive modality for acquiring high reso- lution, three-dimensional (3D) cross sectional volumetric images of the retina and the subretinal layers. SD-OCT also allows the detailed imaging of retinal pathology, aiding clinicians in the diagnosis of sight degrading diseases such as age-related macular degeneration (AMD) and glaucoma.1 Disease diagnosis, assessment, and treatment requires a patient to undergo multiple OCT scans, possibly using different scanning devices, to accurately and precisely gauge disease activity, progression and treatment success. However, the use of OCT imaging devices from different vendors, combined with patient movement may result in poor scan spatial correlation, potentially leading to incorrect patient diagnosis or treatment analysis. Image registration can be used to precisely compare disease states by registering differing 3D scans to one another. In order to align 3D scans from different time- points and vendors using registration, landmarks are required, the most obvious being the retinal vasculature. Presented here is a fully automated cross-vendor method to acquire retina vessel locations for OCT registration from fovea centred 3D SD-OCT scans based on vessel shadows. Noise filtered OCT scans are flattened based on vendor retinal layer segmentation, to extract the retinal pigment epithelium (RPE) layer of the retina. Voxel based layer profile analysis and k-means clustering is used to extract candidate vessel shadow regions from the RPE layer. In conjunction, the extracted RPE layers are combined to generate a projection image featuring all candidate vessel shadows. Image processing methods for vessel segmentation of the OCT constructed projection image are then applied to optimize the accuracy of OCT vessel shadow segmentation through the removal of false positive shadow regions such as those caused by exudates and cysts. Validation of segmented vessel shadows uses ground truth vessel shadow regions identified by expert graders at the Vienna Reading Center (VRC). The results presented here are intended to show the feasibility of this method for the accurate and precise extraction of suitable retinal vessel shadows from multiple vendor 3D SD-OCT scans for use in intra-vendor and cross-vendor 3D OCT registration, 2D fundus registration and actual retinal vessel segmentation. The resulting percentage of true vessel shadow segments to false positive segments identified by the proposed system compared to mean grader ground truth is 95%.

Morphobiochemical diagnosis of acute trabecular microfractures using gamma correction Tc-99m HDP pinhole bone scan with histopathological verification.

PubMed

Bahk, Yong-Whee; Hwang, Seok-Ha; Lee, U-Young; Chung, Yong-An; Jung, Joo-Young; Jeong, Hyeonseok S

2017-11-01

We prospectively performed gamma correction pinhole bone scan (GCPBS) and histopathologic verification study to make simultaneous morphobiochemical diagnosis of trabecular microfractures (TMF) occurred in the femoral head as a part of femoral neck fracture.Materials consisted of surgical specimens of the femoral head in 6 consecutive patients. The specimens were imaged using Tc-99m hydroxymethylene diphosphonate (HDP) pinhole scan and processed by the gamma correction. After cleansing with 10% formalin solution, injured specimen surface was observed using a surgical microscope to record TMF. Morphological findings shown in the photograph, naive pinhole bone scan, GCPBS, and hematoxylin-eosin (H&E) stain of the specimen were reciprocally correlated for histological verification and the usefulness of suppression and enhancement of Tc-99m HDP uptake was biochemically investigated in TMF and edema and hemorrhage using gamma correction.On the one hand, GCPBS was able to depict the calcifying calluses in TMF with enhanced Tc-99m HDP uptake. They were pinpointed, speckled, round, ovoid, rod-like, geographic, and crushed in shape. The smallest callus measured was 0.23 mm in this series. On the other hand, GCPBS biochemically was able to discern the calluses with enhanced high Tc-99m HDP uptake from the normal and edema dipped and hemorrhage irritated trabeculae with washed out uptake.Morphobiochemically, GCPBS can clearly depict microfractures in the femoral head produced by femoral neck fracture. It discerns the microcalluses with enhanced Tc-99m HDP uptake from the intact and edema dipped and hemorrhage irritated trabeculae with suppressed washed out Tc-99m HDP uptake. Both conventional pinhole bone scan and gamma correction are useful imaging means to specifically diagnose the microcalluses naturally formed in TMF.

Results of the survey activities and mobile gamma scanning in Monticello, Utah

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

Little, C.A.; Berven, B.A.

The town of Monticello, Utah, was once the site of an active mill which processed vanadium ore (1942 to 1948), and uranium ore (1948 to 1960). Properties in the vicinity of that mill have become contaminated with radioactive material from ore processing. The Radiological Survey Activities (RASA) group at Oak Ridge National Laboratory (ORNL) was requested by the Division of Remedial Action Projects (DRAP) in the Department of Energy (DOE) to: (1) identify potentially contaminated properties; (2) assess natural background radiation levels; and (3) rapidly assess the magnitude, extent, and type (i.e. ore, tailings, etc.) of contamination present on thesemore » properties (if any). This survey was conducted by RASA during April 1983. In addition to the 114 properties previously identified from historical information, the ORNL mobile gamma scanning van located 36 new properties exhibiting anomalous gamma radiation levels. Onsite surveys were conducted on 145 of the 150 total properties identified either historically or with the gamma scanning van. Of these 145 properties, 122 of them appeared to have some type of contaminated material present on them; however, only 48 appeared to be contaminated to the extent where they were in excess of Environmental Protection Agency (EPA) criteria (40 CFR 192). Twenty-one other properties were recommended for additional investigation (indoor gamma scanning and radon daughter measurements); of these, only ten required further analysis. This report provides the detailed data and analyses related to the radiological survey efforts performed by ORNL in Monticello, Utah.« less

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

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

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

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

On the use of video projectors for three-dimensional scanning

NASA Astrophysics Data System (ADS)

Juarez-Salazar, Rigoberto; Diaz-Ramirez, Victor H.; Robledo-Sanchez, Carlos; Diaz-Gonzalez, Gerardo

2017-08-01

Structured light projection is one of the most useful methods for accurate three-dimensional scanning. Video projectors are typically used as the illumination source. However, because video projectors are not designed for structured light systems, some considerations such as gamma calibration must be taken into account. In this work, we present a simple method for gamma calibration of video projectors. First, the experimental fringe patterns are normalized. Then, the samples of the fringe patterns are sorted in ascending order. The sample sorting leads to a simple three-parameter sine curve that is fitted using the Gauss-Newton algorithm. The novelty of this method is that the sorting process removes the effect of the unknown phase. Thus, the resulting gamma calibration algorithm is significantly simplified. The feasibility of the proposed method is illustrated in a three-dimensional scanning experiment.

Multiparameter linear least-squares fitting to Poisson data one count at a time

NASA Technical Reports Server (NTRS)

Wheaton, Wm. A.; Dunklee, Alfred L.; Jacobsen, Allan S.; Ling, James C.; Mahoney, William A.; Radocinski, Robert G.

1995-01-01

A standard problem in gamma-ray astronomy data analysis is the decomposition of a set of observed counts, described by Poisson statistics, according to a given multicomponent linear model, with underlying physical count rates or fluxes which are to be estimated from the data. Despite its conceptual simplicity, the linear least-squares (LLSQ) method for solving this problem has generally been limited to situations in which the number n(sub i) of counts in each bin i is not too small, conventionally more than 5-30. It seems to be widely believed that the failure of the LLSQ method for small counts is due to the failure of the Poisson distribution to be even approximately normal for small numbers. The cause is more accurately the strong anticorrelation between the data and the wieghts w(sub i) in the weighted LLSQ method when square root of n(sub i) instead of square root of bar-n(sub i) is used to approximate the uncertainties, sigma(sub i), in the data, where bar-n(sub i) = E(n(sub i)), the expected value of N(sub i). We show in an appendix that, avoiding this approximation, the correct equations for the Poisson LLSQ (PLLSQ) problems are actually identical to those for the maximum likelihood estimate using the exact Poisson distribution. We apply the method to solve a problem in high-resolution gamma-ray spectroscopy for the JPL High-Resolution Gamma-Ray Spectrometer flown on HEAO 3. Systematic error in subtracting the strong, highly variable background encountered in the low-energy gamma-ray region can be significantly reduced by closely pairing source and background data in short segments. Significant results can be built up by weighted averaging of the net fluxes obtained from the subtraction of many individual source/background pairs. Extension of the approach to complex situations, with multiple cosmic sources and realistic background parameterizations, requires a means of efficiently fitting to data from single scans in the narrow (approximately = 1.2 keV, HEAO 3) energy channels of a Ge spectrometer, where the expected number of counts obtained per scan may be very low. Such an analysis system is discussed and compared to the method previously used.

A patient-specific segmentation framework for longitudinal MR images of traumatic brain injury

NASA Astrophysics Data System (ADS)

Wang, Bo; Prastawa, Marcel; Irimia, Andrei; Chambers, Micah C.; Vespa, Paul M.; Van Horn, John D.; Gerig, Guido

2012-02-01

Traumatic brain injury (TBI) is a major cause of death and disability worldwide. Robust, reproducible segmentations of MR images with TBI are crucial for quantitative analysis of recovery and treatment efficacy. However, this is a significant challenge due to severe anatomy changes caused by edema (swelling), bleeding, tissue deformation, skull fracture, and other effects related to head injury. In this paper, we introduce a multi-modal image segmentation framework for longitudinal TBI images. The framework is initialized through manual input of primary lesion sites at each time point, which are then refined by a joint approach composed of Bayesian segmentation and construction of a personalized atlas. The personalized atlas construction estimates the average of the posteriors of the Bayesian segmentation at each time point and warps the average back to each time point to provide the updated priors for Bayesian segmentation. The difference between our approach and segmenting longitudinal images independently is that we use the information from all time points to improve the segmentations. Given a manual initialization, our framework automatically segments healthy structures (white matter, grey matter, cerebrospinal fluid) as well as different lesions such as hemorrhagic lesions and edema. Our framework can handle different sets of modalities at each time point, which provides flexibility in analyzing clinical scans. We show results on three subjects with acute baseline scans and chronic follow-up scans. The results demonstrate that joint analysis of all the points yields improved segmentation compared to independent analysis of the two time points.

Contour-Driven Atlas-Based Segmentation

PubMed Central

Wachinger, Christian; Fritscher, Karl; Sharp, Greg; Golland, Polina

2016-01-01

We propose new methods for automatic segmentation of images based on an atlas of manually labeled scans and contours in the image. First, we introduce a Bayesian framework for creating initial label maps from manually annotated training images. Within this framework, we model various registration- and patch-based segmentation techniques by changing the deformation field prior. Second, we perform contour-driven regression on the created label maps to refine the segmentation. Image contours and image parcellations give rise to non-stationary kernel functions that model the relationship between image locations. Setting the kernel to the covariance function in a Gaussian process establishes a distribution over label maps supported by image structures. Maximum a posteriori estimation of the distribution over label maps conditioned on the outcome of the atlas-based segmentation yields the refined segmentation. We evaluate the segmentation in two clinical applications: the segmentation of parotid glands in head and neck CT scans and the segmentation of the left atrium in cardiac MR angiography images. PMID:26068202

Patency of the infarct-related coronary artery--a pertinent factor in late recovery of myocardial fatty acid metabolism among patients receiving thrombolytic therapy?

PubMed

Walamies, M; Virtanen, V; Koskinen, M; Uusitalo, A

1994-09-01

The decrease in mortality among patients receiving thrombolytic therapy for myocardial infarction is greater than would be expected from the improvement in left ventricular contractile function alone; thus some additional advantage of recanalization of the infarct-related coronary artery probably exists. Changes in the post-infarction myocardial metabolic state with respect to artery patency have not been studied with a gamma camera previously. A single-photon emission tomography scan using the fatty acid analogue para-123I-iodophenylpentadecanoic acid was performed at rest before hospital discharge on nine patients with first anterior myocardial infarction. All patients had received intravenous thrombolytic therapy at the beginning of the insult. The semiquantitative analysis of the left ventricle included a total of 44 segments in each patient. The test was repeated 3 months later, with the patients divided into two groups: six patients had an angiographically patent left anterior descending coronary artery (group A), and three an occluded artery (group B). In group A the number of myocardial segments with abnormal (< 70% of maximum) fatty acid uptake was initially 20.2 +/- 4.7 (mean +/- SD) and was reduced to 11.3 +/- 6.1 during the follow-up (95% confidence interval of the decrease 16.0-1.7 segments). In group B the number of these aberrant segments was fairly constant (21.7 +/- 13.1, initial test, and 21.3 +/- 13.3, retest). Our preliminary results suggest that even when thrombolytic therapy fails to prevent myocardial infarction, myocardial fatty acid metabolism has a better change of recovering if the relevant coronary artery has regained its patency.(ABSTRACT TRUNCATED AT 250 WORDS)

Patterns of pulmonary perfusion scans in normal subjects

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

Wallace, J.M.; Moser, K.M.; Hartman, M.T.

1981-01-01

A vital factor conditioning the usage of the pulmonary perfusion (Q) scan in the evaluation of patients suspected of pulmonary embolism is the prevalence of abnormal Q scans in subjects free of cardiopulmonary disease. Because this prevalence has not been well defined, we performed Q scans in 80 nonsmoking subjects 18 to 29 yr of age having no known active cardiopulmonary disease. Each subject underwent a history, physical examination, electrocardiogram, spirometry, and PA chest roentgenogram, followed by a 6-view Q scan. Two subjects in whom a Q defect was suspected underwent a /sup 133/Xe equilibrium-washout ventilation (V) scan. All Qmore » scans were interpreted blindly and independently by 2 experienced readers. Seventy-nine of the 80 Q scans were read as normal. No subject demonstrated a lobar or segmental defect. One of the 80 subjects, who had a mild pectus excavatum, had a left upper lobe subsegmental defect, which was not seen on the V scan. Based on the statistical analysis of these data, no more than 3.68% of normal nonsmoking persons in this age group may have a lobar or segmental Q scan defect and no more than 6.77% may have a subsegmental defect (with 95% confidence). Therefore, our study indicated that Q scan defects, particularly lobar or segmental, are rarely present among normal nonsmokers in this age group.« less

High energy gamma ray results from the second small astronomy satellite

NASA Technical Reports Server (NTRS)

Fichtel, C. E.; Hartman, R. C.; Kniffen, D. A.; Thompson, D. J.; Bignami, G. F.; Oegelman, H.; Oezel, M. F.; Tuemer, T.

1974-01-01

A high energy (35 MeV) gamma ray telescope employing a thirty-two level magnetic core spark chamber system was flown on SAS 2. The high energy galactic gamma radiation is observed to dominate over the general diffuse radiation along the entire galactic plane, and when examined in detail, the longitudinal and latitudinal distribution seem generally correlated with galactic structural features, particularly with arm segments. The general high energy gamma radiation from the galactic plane, explained on the basis of its angular distribution and magnitude, probably results primarily from cosmic ray interactions with interstellar matter.

Microscopy image segmentation tool: Robust image data analysis

NASA Astrophysics Data System (ADS)

Valmianski, Ilya; Monton, Carlos; Schuller, Ivan K.

2014-03-01

We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

Assessment of individual organ doses in a realistic human phantom from neutron and gamma stimulated spectroscopy of the breast and liver

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

Belley, Matthew D.; Segars, William Paul; Kapadia, Anuj J., E-mail: anuj.kapadia@duke.edu

2014-06-15

Purpose: Understanding the radiation dose to a patient is essential when considering the use of an ionizing diagnostic imaging test for clinical diagnosis and screening. Using Monte Carlo simulations, the authors estimated the three-dimensional organ-dose distribution from neutron and gamma irradiation of the male liver, female liver, and female breasts for neutron- and gamma-stimulated spectroscopic imaging. Methods: Monte Carlo simulations were developed using the Geant4 GATE application and a voxelized XCAT human phantom. A male and a female whole body XCAT phantom was voxelized into 256 × 256 × 600 voxels (3.125 × 3.125 × 3.125 mm{sup 3}). A monoenergeticmore » rectangular beam of 5.0 MeV neutrons or 7.0 MeV photons was made incident on a 2 cm thick slice of the phantom. The beam was rotated at eight different angles around the phantom ranging from 0° to 180°. Absorbed dose was calculated for each individual organ in the body and dose volume histograms were computed to analyze the absolute and relative doses in each organ. Results: The neutron irradiations of the liver showed the highest organ dose absorption in the liver, with appreciably lower doses in other proximal organs. The dose distribution within the irradiated slice exhibited substantial attenuation with increasing depth along the beam path, attenuating to ∼15% of the maximum value at the beam exit side. The gamma irradiation of the liver imparted the highest organ dose to the stomach wall. The dose distribution from the gammas showed a region of dose buildup at the beam entrance, followed by a relatively uniform dose distribution to all of the deep tissue structures, attenuating to ∼75% of the maximum value at the beam exit side. For the breast scans, both the neutron and gamma irradiation registered maximum organ doses in the breasts, with all other organs receiving less than 1% of the breast dose. Effective doses ranged from 0.22 to 0.37 mSv for the neutron scans and 41 to 66 mSv for the gamma scans. Conclusions: Neutron and gamma irradiation of a primary target organ was found to impart the majority of the total dose to the primary target organ (and other large organs) within the beam plane and considerably lower dose to proximal organs outside of the beam. These results also indicate that despite the use of a highly scattering particle such as a neutron, the dose from neutron stimulated emission computed tomography scans is on par with other clinical imaging techniques such as x-ray computed tomography (x-ray CT). Given the high nonuniformity in the dose across an organ during the neutron scan, care must be taken when computing average doses from neutron irradiations. The effective doses from neutron scanning were found to be comparable to x-ray CT. Further technique modifications are needed to reduce the effective dose levels from the gamma scans.« less

Automated coronary artery calcification detection on low-dose chest CT images

NASA Astrophysics Data System (ADS)

Xie, Yiting; Cham, Matthew D.; Henschke, Claudia; Yankelevitz, David; Reeves, Anthony P.

2014-03-01

Coronary artery calcification (CAC) measurement from low-dose CT images can be used to assess the risk of coronary artery disease. A fully automatic algorithm to detect and measure CAC from low-dose non-contrast, non-ECG-gated chest CT scans is presented. Based on the automatically detected CAC, the Agatston score (AS), mass score and volume score were computed. These were compared with scores obtained manually from standard-dose ECG-gated scans and low-dose un-gated scans of the same patient. The automatic algorithm segments the heart region based on other pre-segmented organs to provide a coronary region mask. The mitral valve and aortic valve calcification is identified and excluded. All remaining voxels greater than 180HU within the mask region are considered as CAC candidates. The heart segmentation algorithm was evaluated on 400 non-contrast cases with both low-dose and regular dose CT scans. By visual inspection, 371 (92.8%) of the segmentations were acceptable. The automated CAC detection algorithm was evaluated on 41 low-dose non-contrast CT scans. Manual markings were performed on both low-dose and standard-dose scans for these cases. Using linear regression, the correlation of the automatic AS with the standard-dose manual scores was 0.86; with the low-dose manual scores the correlation was 0.91. Standard risk categories were also computed. The automated method risk category agreed with manual markings of gated scans for 24 cases while 15 cases were 1 category off. For low-dose scans, the automatic method agreed with 33 cases while 7 cases were 1 category off.

Dielectron widths of the Gamma(1S,2S,3S) resonances.

PubMed

Rosner, J L; Adam, N E; Alexander, J P; Berkelman, K; Cassel, D G; Duboscq, J E; Ecklund, K M; Ehrlich, R; Fields, L; Galik, R S; Gibbons, L; Gray, R; Gray, S W; Hartill, D L; Heltsley, B K; Hertz, D; Jones, C D; Kandaswamy, J; Kreinick, D L; Kuznetsov, V E; Mahlke-Krüger, H; Meyer, T O; Onyisi, P U E; Patterson, J R; Peterson, D; Phillips, E A; Pivarski, J; Riley, D; Ryd, A; Sadoff, A J; Schwarthoff, H; Shi, X; Stroiney, S; Sun, W M; Wilksen, T; Weinberger, M; Athar, S B; Avery, P; Breva-Newell, L; Patel, R; Potlia, V; Stoeck, H; Yelton, J; Rubin, P; Cawlfield, C; Eisenstein, B I; Karliner, I; Kim, D; Lowrey, N; Naik, P; Sedlack, C; Selen, M; White, E J; Wiss, J; Shepherd, M R; Besson, D; Pedlar, T K; Cronin-Hennessy, D; Gao, K Y; Gong, D T; Hietala, J; Kubota, Y; Klein, T; Lang, B W; Poling, R; Scott, A W; Smith, A; Dobbs, S; Metreveli, Z; Seth, K K; Tomaradze, A; Zweber, P; Ernst, J; Arms, K; Severini, H; Dytman, S A; Love, W; Mehrabyan, S; Savinov, V; Aquines, O; Li, Z; Lopez, A; Mendez, H; Ramirez, J; Huang, G S; Miller, D H; Pavlunin, V; Sanghi, B; Shipsey, I P J; Xin, B; Adams, G S; Anderson, M; Cummings, J P; Danko, I; Napolitano, J; He, Q; Insler, J; Muramatsu, H; Park, C S; Thorndike, E H; Coan, T E; Gao, Y S; Liu, F; Stroynowski, R; Artuso, M; Blusk, S; Butt, J; Li, J; Menaa, N; Mountain, R; Nisar, S; Randrianarivony, K; Redjimi, R; Sia, R; Skwarnicki, T; Stone, S; Wang, J C; Zhang, K; Csorna, S E; Bonvicini, G; Cinabro, D; Dubrovin, M; Lincoln, A; Asner, D M; Edwards, K W; Briere, R A; Chen, J; Ferguson, T; Tatishvili, G; Vogel, H; Watkins, M E

2006-03-10

We determine the dielectron widths of the Gamma(1S), Gamma(2S), and Gamma(3S) resonances with better than 2% precision by integrating the cross section of e+e- -->Gamma over the e+e- center-of-mass energy. Using e+e- energy scans of the Gamma resonances at the Cornell Electron Storage Ring and measuring Gamma production with the CLEO detector, we find dielectron widths of 1.252+/-0.004(sigma(stat))+/-0.019(sigma(syst)) keV, 0.581+/-0.004+/-0.009 keV, and 0.413+/-0.004+/-0.006 keV for the Gamma(1S), Gamma(2S), and Gamma(3S), respectively.

INTERIM REPORT--INDEPENDENT VERIFICATION SURVEY OF SECTION 3, SURVEY UNITS 1, 4 AND 5 EXCAVATED SURFACES, WHITTAKER CORPORATION, REYNOLDS INDUSTRIAL PARK, TRANSFER, PENNSYLVANIA DCN: 5002-SR-04-0"

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

ADAMS, WADE C

At Pennsylvania Department of Environmental Protection's request, ORAU's IEAV program conducted verification surveys on the excavated surfaces of Section 3, SUs 1, 4, and 5 at the Whittaker site on March 13 and 14, 2013. The survey activities included visual inspections, gamma radiation surface scans, gamma activity measurements, and soil sampling activities. Verification activities also included the review and assessment of the licensee's project documentation and methodologies. Surface scans identified four areas of elevated direct gamma radiation distinguishable from background; one area within SUs 1 and 4 and two areas within SU5. One area within SU5 was remediated by removingmore » a golf ball size piece of slag while ORAU staff was onsite. With the exception of the golf ball size piece of slag within SU5, a review of the ESL Section 3 EXS data packages for SUs 1, 4, and 5 indicated that these locations of elevated gamma radiation were also identified by the ESL gamma scans and that ESL personnel performed additional investigations and soil sampling within these areas. The investigative results indicated that the areas met the release criteria.« less

Automatic identification of IASLC-defined mediastinal lymph node stations on CT scans using multi-atlas organ segmentation

NASA Astrophysics Data System (ADS)

Hoffman, Joanne; Liu, Jiamin; Turkbey, Evrim; Kim, Lauren; Summers, Ronald M.

2015-03-01

Station-labeling of mediastinal lymph nodes is typically performed to identify the location of enlarged nodes for cancer staging. Stations are usually assigned in clinical radiology practice manually by qualitative visual assessment on CT scans, which is time consuming and highly variable. In this paper, we developed a method that automatically recognizes the lymph node stations in thoracic CT scans based on the anatomical organs in the mediastinum. First, the trachea, lungs, and spines are automatically segmented to locate the mediastinum region. Then, eight more anatomical organs are simultaneously identified by multi-atlas segmentation. Finally, with the segmentation of those anatomical organs, we convert the text definitions of the International Association for the Study of Lung Cancer (IASLC) lymph node map into patient-specific color-coded CT image maps. Thus, a lymph node station is automatically assigned to each lymph node. We applied this system to CT scans of 86 patients with 336 mediastinal lymph nodes measuring equal or greater than 10 mm. 84.8% of mediastinal lymph nodes were correctly mapped to their stations.

Joint Segmentation and Deformable Registration of Brain Scans Guided by a Tumor Growth Model

PubMed Central

Gooya, Ali; Pohl, Kilian M.; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR ) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth. PMID:21995070

Joint segmentation and deformable registration of brain scans guided by a tumor growth model.

PubMed

Gooya, Ali; Pohl, Kilian M; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth.

Multicenter reliability of semiautomatic retinal layer segmentation using OCT

PubMed Central

Oberwahrenbrock, Timm; Traber, Ghislaine L.; Lukas, Sebastian; Gabilondo, Iñigo; Nolan, Rachel; Songster, Christopher; Balk, Lisanne; Petzold, Axel; Paul, Friedemann; Villoslada, Pablo; Brandt, Alexander U.; Green, Ari J.

2018-01-01

Objective To evaluate the inter-rater reliability of semiautomated segmentation of spectral domain optical coherence tomography (OCT) macular volume scans. Methods Macular OCT volume scans of left eyes from 17 subjects (8 patients with MS and 9 healthy controls) were automatically segmented by Heidelberg Eye Explorer (v1.9.3.0) beta-software (Spectralis Viewing Module v6.0.0.7), followed by manual correction by 5 experienced operators from 5 different academic centers. The mean thicknesses within a 6-mm area around the fovea were computed for the retinal nerve fiber layer, ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer, outer plexiform layer (OPL), and outer nuclear layer (ONL). Intraclass correlation coefficients (ICCs) were calculated for mean layer thickness values. Spatial distribution of ICC values for the segmented volume scans was investigated using heat maps. Results Agreement between raters was good (ICC > 0.84) for all retinal layers, particularly inner retinal layers showed excellent agreement across raters (ICC > 0.96). Spatial distribution of ICC showed highest values in the perimacular area, whereas the ICCs were poorer for the foveola and the more peripheral macular area. The automated segmentation of the OPL and ONL required the most correction and showed the least agreement, whereas differences were less prominent for the remaining layers. Conclusions Automated segmentation with manual correction of macular OCT scans is highly reliable when performed by experienced raters and can thus be applied in multicenter settings. Reliability can be improved by restricting analysis to the perimacular area and compound segmentation of GCL and IPL. PMID:29552598

Comparison and assessment of semi-automatic image segmentation in computed tomography scans for image-guided kidney surgery.

PubMed

Glisson, Courtenay L; Altamar, Hernan O; Herrell, S Duke; Clark, Peter; Galloway, Robert L

2011-11-01

Image segmentation is integral to implementing intraoperative guidance for kidney tumor resection. Results seen in computed tomography (CT) data are affected by target organ physiology as well as by the segmentation algorithm used. This work studies variables involved in using level set methods found in the Insight Toolkit to segment kidneys from CT scans and applies the results to an image guidance setting. A composite algorithm drawing on the strengths of multiple level set approaches was built using the Insight Toolkit. This algorithm requires image contrast state and seed points to be identified as input, and functions independently thereafter, selecting and altering method and variable choice as needed. Semi-automatic results were compared to expert hand segmentation results directly and by the use of the resultant surfaces for registration of intraoperative data. Direct comparison using the Dice metric showed average agreement of 0.93 between semi-automatic and hand segmentation results. Use of the segmented surfaces in closest point registration of intraoperative laser range scan data yielded average closest point distances of approximately 1 mm. Application of both inverse registration transforms from the previous step to all hand segmented image space points revealed that the distance variability introduced by registering to the semi-automatically segmented surface versus the hand segmented surface was typically less than 3 mm both near the tumor target and at distal points, including subsurface points. Use of the algorithm shortened user interaction time and provided results which were comparable to the gold standard of hand segmentation. Further, the use of the algorithm's resultant surfaces in image registration provided comparable transformations to surfaces produced by hand segmentation. These data support the applicability and utility of such an algorithm as part of an image guidance workflow.

Curvature-Based Environment Description for Robot Navigation Using Laser Range Sensors

PubMed Central

Vázquez-Martín, Ricardo; Núñez, Pedro; Bandera, Antonio; Sandoval, Francisco

2009-01-01

This work proposes a new feature detection and description approach for mobile robot navigation using 2D laser range sensors. The whole process consists of two main modules: a sensor data segmentation module and a feature detection and characterization module. The segmentation module is divided in two consecutive stages: First, the segmentation stage divides the laser scan into clusters of consecutive range readings using a distance-based criterion. Then, the second stage estimates the curvature function associated to each cluster and uses it to split it into a set of straight-line and curve segments. The curvature is calculated using a triangle-area representation where, contrary to previous approaches, the triangle side lengths at each range reading are adapted to the local variations of the laser scan, removing noise without missing relevant points. This representation remains unchanged in translation or rotation, and it is also robust against noise. Thus, it is able to provide the same segmentation results although the scene will be perceived from different viewpoints. Therefore, segmentation results are used to characterize the environment using line and curve segments, real and virtual corners and edges. Real scan data collected from different environments by using different platforms are used in the experiments in order to evaluate the proposed environment description algorithm. PMID:22461732

Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

PubMed Central

Rudyanto, Rina D.; Kerkstra, Sjoerd; van Rikxoort, Eva M.; Fetita, Catalin; Brillet, Pierre-Yves; Lefevre, Christophe; Xue, Wenzhe; Zhu, Xiangjun; Liang, Jianming; Öksüz, İlkay; Ünay, Devrim; Kadipaşaogandcaron;lu, Kamuran; Estépar, Raúl San José; Ross, James C.; Washko, George R.; Prieto, Juan-Carlos; Hoyos, Marcela Hernández; Orkisz, Maciej; Meine, Hans; Hüllebrand, Markus; Stöcker, Christina; Mir, Fernando Lopez; Naranjo, Valery; Villanueva, Eliseo; Staring, Marius; Xiao, Changyan; Stoel, Berend C.; Fabijanska, Anna; Smistad, Erik; Elster, Anne C.; Lindseth, Frank; Foruzan, Amir Hossein; Kiros, Ryan; Popuri, Karteek; Cobzas, Dana; Jimenez-Carretero, Daniel; Santos, Andres; Ledesma-Carbayo, Maria J.; Helmberger, Michael; Urschler, Martin; Pienn, Michael; Bosboom, Dennis G.H.; Campo, Arantza; Prokop, Mathias; de Jong, Pim A.; Ortiz-de-Solorzano, Carlos; Muñoz-Barrutia, Arrate; van Ginneken, Bram

2016-01-01

The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases. PMID:25113321

Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis

NASA Astrophysics Data System (ADS)

Che, E.; Olsen, M. J.

2017-09-01

Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.

The Registration and Segmentation of Heterogeneous Laser Scanning Data

NASA Astrophysics Data System (ADS)

Al-Durgham, Mohannad M.

Light Detection And Ranging (LiDAR) mapping has been emerging over the past few years as a mainstream tool for the dense acquisition of three dimensional point data. Besides the conventional mapping missions, LiDAR systems have proven to be very useful for a wide spectrum of applications such as forestry, structural deformation analysis, urban mapping, and reverse engineering. The wide application scope of LiDAR lead to the development of many laser scanning technologies that are mountable on multiple platforms (i.e., airborne, mobile terrestrial, and tripod mounted), this caused variations in the characteristics and quality of the generated point clouds. As a result of the increased popularity and diversity of laser scanners, one should address the heterogeneous LiDAR data post processing (i.e., registration and segmentation) problems adequately. Current LiDAR integration techniques do not take into account the varying nature of laser scans originating from various platforms. In this dissertation, the author proposes a methodology designed particularly for the registration and segmentation of heterogeneous LiDAR data. A data characterization and filtering step is proposed to populate the points' attributes and remove non-planar LiDAR points. Then, a modified version of the Iterative Closest Point (ICP), denoted by the Iterative Closest Projected Point (ICPP) is designed for the registration of heterogeneous scans to remove any misalignments between overlapping strips. Next, a region-growing-based heterogeneous segmentation algorithm is developed to ensure the proper extraction of planar segments from the point clouds. Validation experiments show that the proposed heterogeneous registration can successfully align airborne and terrestrial datasets despite the great differences in their point density and their noise level. In addition, similar testes have been conducted to examine the heterogeneous segmentation and it is shown that one is able to identify common planar features in airborne and terrestrial data without resampling or manipulating the data in any way. The work presented in this dissertation provides a framework for the registration and segmentation of airborne and terrestrial laser scans which has a positive impact on the completeness of the scanned feature. Therefore, the derived products from these point clouds have higher accuracy as seen in the full manuscript.

Resting State Dense Array Gamma Oscillatory Activity as a Response Marker for Cerebellar-Repetitive Transcranial Magnetic Stimulation (rTMS) in Schizophrenia.

PubMed

Tikka, Sai Krishna; Garg, Shobit; Sinha, Vinod Kumar; Nizamie, S Haque; Goyal, Nishant

2015-12-01

As cerebellum and its abnormalities have been implicated in the pathophysiology of schizophrenia, repetitive transcranial magnetic stimulation (rTMS) of this alternate site has been suggested as a novel target for treating patients with this disorder. As resting state gamma activity measures functional brain connectivity, it could be used as a specific treatment marker. To investigate the effect of cerebellar-rTMS on resting state gamma activity, while studying its efficacy in recent onset schizophrenia patients. This rater-blinded prospective study was completed by 11 schizophrenia patients. They received 10 sessions of high-frequency (theta patterned) rTMS to midline cerebellum over 2 weeks. Resting state EEG was recorded using high (192-channel) resolution EEG at baseline and post rTMS. Gamma spectral power was calculated using fast Fourier transformation, Hanning window averaged over 8 scalp segments corresponding 8 lobes. Clinical improvement rated on the Positive and Negative Syndrome Scale and depressive symptoms assessed using the Calgary Depression Scale for Schizophrenia were other outcome variables. Nonparametric statistics were used. Over the treatment course, significant reduction was seen on negative syndrome and depression scores. Gamma spectral power in left frontal and temporal segments reduced significantly. Spearman correlation analysis showed that percentage reduction in psychopathology scores had significant positive correlation with percentage reduction in gamma spectral power. Cerebellar-rTMS might be an effective adjunct to treat intricate and lingering negative and affective symptoms. Resting state gamma spectral power in frontal and temporal regions might be used as a biomarker for treatment response.

Measurements of soil carbon by neutron-gamma analysis in static and scanning modes

USDA-ARS?s Scientific Manuscript database

The herein described application of the inelastic neutron scattering (INS) method for soil carbon analysis is based on the registration and analysis of gamma rays created when neutrons interact with soil elements. The main parts of the INS system are a pulsed neutron generator, NaI(Tl) gamma detecto...

Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Yamada, Kazuma; Kojima, Takuya; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

2018-02-01

The purpose of this study is to evaluate and compare the performance of modern deep learning techniques for automatically recognizing and segmenting multiple organ regions on 3D CT images. CT image segmentation is one of the important task in medical image analysis and is still very challenging. Deep learning approaches have demonstrated the capability of scene recognition and semantic segmentation on nature images and have been used to address segmentation problems of medical images. Although several works showed promising results of CT image segmentation by using deep learning approaches, there is no comprehensive evaluation of segmentation performance of the deep learning on segmenting multiple organs on different portions of CT scans. In this paper, we evaluated and compared the segmentation performance of two different deep learning approaches that used 2D- and 3D deep convolutional neural networks (CNN) without- and with a pre-processing step. A conventional approach that presents the state-of-the-art performance of CT image segmentation without deep learning was also used for comparison. A dataset that includes 240 CT images scanned on different portions of human bodies was used for performance evaluation. The maximum number of 17 types of organ regions in each CT scan were segmented automatically and compared to the human annotations by using ratio of intersection over union (IU) as the criterion. The experimental results demonstrated the IUs of the segmentation results had a mean value of 79% and 67% by averaging 17 types of organs that segmented by a 3D- and 2D deep CNN, respectively. All the results of the deep learning approaches showed a better accuracy and robustness than the conventional segmentation method that used probabilistic atlas and graph-cut methods. The effectiveness and the usefulness of deep learning approaches were demonstrated for solving multiple organs segmentation problem on 3D CT images.

Automated measurement of uptake in cerebellum, liver, and aortic arch in full-body FDG PET/CT scans.

PubMed

Bauer, Christian; Sun, Shanhui; Sun, Wenqing; Otis, Justin; Wallace, Audrey; Smith, Brian J; Sunderland, John J; Graham, Michael M; Sonka, Milan; Buatti, John M; Beichel, Reinhard R

2012-06-01

The purpose of this work was to develop and validate fully automated methods for uptake measurement of cerebellum, liver, and aortic arch in full-body PET/CT scans. Such measurements are of interest in the context of uptake normalization for quantitative assessment of metabolic activity and/or automated image quality control. Cerebellum, liver, and aortic arch regions were segmented with different automated approaches. Cerebella were segmented in PET volumes by means of a robust active shape model (ASM) based method. For liver segmentation, a largest possible hyperellipsoid was fitted to the liver in PET scans. The aortic arch was first segmented in CT images of a PET/CT scan by a tubular structure analysis approach, and the segmented result was then mapped to the corresponding PET scan. For each of the segmented structures, the average standardized uptake value (SUV) was calculated. To generate an independent reference standard for method validation, expert image analysts were asked to segment several cross sections of each of the three structures in 134 F-18 fluorodeoxyglucose (FDG) PET/CT scans. For each case, the true average SUV was estimated by utilizing statistical models and served as the independent reference standard. For automated aorta and liver SUV measurements, no statistically significant scale or shift differences were observed between automated results and the independent standard. In the case of the cerebellum, the scale and shift were not significantly different, if measured in the same cross sections that were utilized for generating the reference. In contrast, automated results were scaled 5% lower on average although not shifted, if FDG uptake was calculated from the whole segmented cerebellum volume. The estimated reduction in total SUV measurement error ranged between 54.7% and 99.2%, and the reduction was found to be statistically significant for cerebellum and aortic arch. With the proposed methods, the authors have demonstrated that automated SUV uptake measurements in cerebellum, liver, and aortic arch agree with expert-defined independent standards. The proposed methods were found to be accurate and showed less intra- and interobserver variability, compared to manual analysis. The approach provides an alternative to manual uptake quantification, which is time-consuming. Such an approach will be important for application of quantitative PET imaging to large scale clinical trials. © 2012 American Association of Physicists in Medicine.

Prompt Gamma Imaging for In Vivo Range Verification of Pencil Beam Scanning Proton Therapy.

PubMed

Xie, Yunhe; Bentefour, El Hassane; Janssens, Guillaume; Smeets, Julien; Vander Stappen, François; Hotoiu, Lucian; Yin, Lingshu; Dolney, Derek; Avery, Stephen; O'Grady, Fionnbarr; Prieels, Damien; McDonough, James; Solberg, Timothy D; Lustig, Robert A; Lin, Alexander; Teo, Boon-Keng K

2017-09-01

To report the first clinical results and value assessment of prompt gamma imaging for in vivo proton range verification in pencil beam scanning mode. A stand-alone, trolley-mounted, prototype prompt gamma camera utilizing a knife-edge slit collimator design was used to record the prompt gamma signal emitted along the proton tracks during delivery of proton therapy for a brain cancer patient. The recorded prompt gamma depth detection profiles of individual pencil beam spots were compared with the expected profiles simulated from the treatment plan. In 6 treatment fractions recorded over 3 weeks, the mean (± standard deviation) range shifts aggregated over all spots in 9 energy layers were -0.8 ± 1.3 mm for the lateral field, 1.7 ± 0.7 mm for the right-superior-oblique field, and -0.4 ± 0.9 mm for the vertex field. This study demonstrates the feasibility and illustrates the distinctive benefits of prompt gamma imaging in pencil beam scanning treatment mode. Accuracy in range verification was found in this first clinical case to be better than the range uncertainty margin applied in the treatment plan. These first results lay the foundation for additional work toward tighter integration of the system for in vivo proton range verification and quantification of range uncertainties. Copyright © 2017 Elsevier Inc. All rights reserved.

Axial segmentation of lungs CT scan images using canny method and morphological operation

NASA Astrophysics Data System (ADS)

Noviana, Rina; Febriani, Rasal, Isram; Lubis, Eva Utari Cintamurni

2017-08-01

Segmentation is a very important topic in digital image process. It is found simply in varied fields of image analysis, particularly within the medical imaging field. Axial segmentation of lungs CT scan is beneficial in designation of abnormalities and surgery planning. It will do to ascertain every section within the lungs. The results of the segmentation are accustomed discover the presence of nodules. The method which utilized in this analysis are image cropping, image binarization, Canny edge detection and morphological operation. Image cropping is done so as to separate the lungs areas, that is the region of interest. Binarization method generates a binary image that has 2 values with grey level, that is black and white (ROI), from another space of lungs CT scan image. Canny method used for the edge detection. Morphological operation is applied to smoothing the lungs edge. The segmentation methodology shows an honest result. It obtains an awfully smooth edge. Moreover, the image background can also be removed in order to get the main focus, the lungs.

Automatic liver volume segmentation and fibrosis classification

NASA Astrophysics Data System (ADS)

Bal, Evgeny; Klang, Eyal; Amitai, Michal; Greenspan, Hayit

2018-02-01

In this work, we present an automatic method for liver segmentation and fibrosis classification in liver computed-tomography (CT) portal phase scans. The input is a full abdomen CT scan with an unknown number of slices, and the output is a liver volume segmentation mask and a fibrosis grade. A multi-stage analysis scheme is applied to each scan, including: volume segmentation, texture features extraction and SVM based classification. Data contains portal phase CT examinations from 80 patients, taken with different scanners. Each examination has a matching Fibroscan grade. The dataset was subdivided into two groups: first group contains healthy cases and mild fibrosis, second group contains moderate fibrosis, severe fibrosis and cirrhosis. Using our automated algorithm, we achieved an average dice index of 0.93 ± 0.05 for segmentation and a sensitivity of 0.92 and specificity of 0.81for classification. To the best of our knowledge, this is a first end to end automatic framework for liver fibrosis classification; an approach that, once validated, can have a great potential value in the clinic.

Extraction of Overt Verbal Response from the Acoustic Noise in a Functional Magnetic Resonance Imaging Scan by Use of Segmented Active Noise Cancellation

PubMed Central

Jung, Kwan-Jin; Prasad, Parikshit; Qin, Yulin; Anderson, John R.

2013-01-01

A method to extract the subject's overt verbal response from the obscuring acoustic noise in an fMRI scan is developed by applying active noise cancellation with a conventional MRI microphone. Since the EPI scanning and its accompanying acoustic noise in fMRI are repetitive, the acoustic noise in one time segment was used as a reference noise in suppressing the acoustic noise in subsequent segments. However, the acoustic noise from the scanner was affected by the subject's movements, so the reference noise was adaptively adjusted as the scanner's acoustic properties varied in time. This method was successfully applied to a cognitive fMRI experiment with overt verbal responses. PMID:15723385

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

PubMed

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

2012-03-01

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

Assessment of a spectral domain OCT segmentation software in a retrospective cohort study of exudative AMD patients.

PubMed

Tilleul, Julien; Querques, Giuseppe; Canoui-Poitrine, Florence; Leveziel, Nicolas; Souied, Eric H

2013-01-01

To assess the ability of the Spectralis optical coherence tomography (OCT) segmentation software to identify the inner limiting membrane and Bruch's membrane in exudative age-related macular degeneration (AMD) patients. Thirty-eight eyes of 38 naive exudative AMD patients were retrospectively included. They all had a complete ophthalmologic examination including Spectralis OCT at baseline, at month 1 and 2. Reliability of the segmentation software was assessed by 2 ophthalmologists. Reliability of the segmentation software was defined as good if both inner limiting membrane and Bruch's membrane were correctly drawn. A total of 38 patients charts were reviewed (114 scans). The inner limiting membrane was correctly drawn by the segmentation software in 114/114 spectral domain OCT scans (100%). Conversely, Bruch's membrane was correctly drawn in 59/114 scans (51.8%). The software was less reliable in locating Bruch's membrane in case of pigment epithelium detachment (PED) than without PED (42.5 vs. 73.5%, respectively; p = 0.049), but its reliability was not associated with SRF or CME (p = 0.55 and p = 0.10, respectively). Segmentation of the inner limiting membrane was constantly trustworthy but Bruch's membrane segmentation was poorly reliable using the automatic Spectralis segmentation software. Based on this software, evaluation of retinal thickness may be incorrect, particularly in case of PED. PED is effectively an important parameter which is not included when measuring retinal thickness. Copyright © 2012 S. Karger AG, Basel.

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

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

Measuring nanometre-scale electric fields in scanning transmission electron microscopy using segmented detectors.

PubMed

Brown, H G; Shibata, N; Sasaki, H; Petersen, T C; Paganin, D M; Morgan, M J; Findlay, S D

2017-11-01

Electric field mapping using segmented detectors in the scanning transmission electron microscope has recently been achieved at the nanometre scale. However, converting these results to quantitative field measurements involves assumptions whose validity is unclear for thick specimens. We consider three approaches to quantitative reconstruction of the projected electric potential using segmented detectors: a segmented detector approximation to differential phase contrast and two variants on ptychographical reconstruction. Limitations to these approaches are also studied, particularly errors arising from detector segment size, inelastic scattering, and non-periodic boundary conditions. A simple calibration experiment is described which corrects the differential phase contrast reconstruction to give reliable quantitative results despite the finite detector segment size and the effects of plasmon scattering in thick specimens. A plasmon scattering correction to the segmented detector ptychography approaches is also given. Avoiding the imposition of periodic boundary conditions on the reconstructed projected electric potential leads to more realistic reconstructions. Copyright © 2017 Elsevier B.V. All rights reserved.

Studying Phobos subsurface structure elementary composition by neutron and gamma-rays spectrometers "NS HEND" from "Phobos-Grunt" mission.

NASA Astrophysics Data System (ADS)

Kozyrev, S. Alexander; Litvak, Maxim; Malakhov, Alexey; Mokrousov, Maxim; Mitrofanov, Igor; Sanin, Anton; Schulz, Rita; Shvetsov, Valery; Rogozhin, Alexander; Timoshenko, Genagy; Tretyakov, Vladislav; Vostrukhin, Andrey

The Neutron Spectrometer HEND (NS HEND) has been proposed for studying elemental com-position of Phobos (the Mars's moon) regolith by "Phobos-Grunt" mission. NS HEND have been selected by the Federal Space Agency of Russia for the Lander of the "Phobos-Grunt" mission scheduled for launch in 2011. The shallow subsurface of Phobos might be studied by observations of induced nuclear gamma-ray lines and neutron emission. Secondary gamma-rays and neutrons are produced by energetic Galactic Cosmic Rays within 1-2 meter layer of subsur-face. The knowledge of the spectral density of neutrons in addition to measurements of nuclear gamma lines allows to deconvolve concentrations of soil-constituting elements. That is why nuclear instruments include both the segment for detection of gamma ray lines and segment of neutron spectrometer for the measurement of the neutron leakage spectra. Moreover, mea-surements of neutrons at 2.2 MeV line will also allow to study the content of hydrogen within subsurface layer about 1 meter deep. This instrument, will be able to provide observational data for composition of Phobos regolith and content of natural radioactive elements K, U and Th, and also for content of hydrogen or water ice in the Phobos subsurface. At present, the flight units of NS HEND instrument is manufactured, tested and current go through physical calibration.

Speech Rhythms and Multiplexed Oscillatory Sensory Coding in the Human Brain

PubMed Central

Gross, Joachim; Hoogenboom, Nienke; Thut, Gregor; Schyns, Philippe; Panzeri, Stefano; Belin, Pascal; Garrod, Simon

2013-01-01

Cortical oscillations are likely candidates for segmentation and coding of continuous speech. Here, we monitored continuous speech processing with magnetoencephalography (MEG) to unravel the principles of speech segmentation and coding. We demonstrate that speech entrains the phase of low-frequency (delta, theta) and the amplitude of high-frequency (gamma) oscillations in the auditory cortex. Phase entrainment is stronger in the right and amplitude entrainment is stronger in the left auditory cortex. Furthermore, edges in the speech envelope phase reset auditory cortex oscillations thereby enhancing their entrainment to speech. This mechanism adapts to the changing physical features of the speech envelope and enables efficient, stimulus-specific speech sampling. Finally, we show that within the auditory cortex, coupling between delta, theta, and gamma oscillations increases following speech edges. Importantly, all couplings (i.e., brain-speech and also within the cortex) attenuate for backward-presented speech, suggesting top-down control. We conclude that segmentation and coding of speech relies on a nested hierarchy of entrained cortical oscillations. PMID:24391472

Skeletal Scintigraphy (Bone Scan)

MedlinePlus

... The special camera and imaging techniques used in nuclear medicine include the gamma camera and single-photon emission-computed tomography (SPECT). The gamma camera, also called a scintillation camera, detects radioactive energy that is emitted from the patient's body and ...

Aorta and pulmonary artery segmentation using optimal surface graph cuts in non-contrast CT

NASA Astrophysics Data System (ADS)

Sedghi Gamechi, Zahra; Arias-Lorza, Andres M.; Pedersen, Jesper Holst; de Bruijne, Marleen

2018-03-01

Accurate measurements of the size and shape of the aorta and pulmonary arteries are important as risk factors for cardiovascular diseases, and for Chronicle Obstacle Pulmonary Disease (COPD).1 The aim of this paper is to propose an automated method for segmenting the aorta and pulmonary arteries in low-dose non-ECGgated non-contrast CT scans. Low contrast and the high noise level make the automatic segmentation in such images a challenging task. In the proposed method, first, a minimum cost path tracking algorithm traces the centerline between user-defined seed points. The cost function is based on a multi-directional medialness filter and a lumen intensity similarity metric. The vessel radius is also estimated from the medialness filter. The extracted centerlines are then smoothed and dilated non-uniformly according to the extracted local vessel radius and subsequently used as initialization for a graph-cut segmentation. The algorithm is evaluated on 225 low-dose non-ECG-gated non-contrast CT scans from a lung cancer screening trial. Quantitatively analyzing 25 scans with full manual annotations, we obtain a dice overlap of 0.94+/-0.01 for the aorta and 0.92+/-0.01 for pulmonary arteries. Qualitative validation by visual inspection on 200 scans shows successful segmentation in 93% of all cases for the aorta and 94% for pulmonary arteries.

A functional-based segmentation of human body scans in arbitrary postures.

PubMed

Werghi, Naoufel; Xiao, Yijun; Siebert, Jan Paul

2006-02-01

This paper presents a general framework that aims to address the task of segmenting three-dimensional (3-D) scan data representing the human form into subsets which correspond to functional human body parts. Such a task is challenging due to the articulated and deformable nature of the human body. A salient feature of this framework is that it is able to cope with various body postures and is in addition robust to noise, holes, irregular sampling and rigid transformations. Although whole human body scanners are now capable of routinely capturing the shape of the whole body in machine readable format, they have not yet realized their potential to provide automatic extraction of key body measurements. Automated production of anthropometric databases is a prerequisite to satisfying the needs of certain industrial sectors (e.g., the clothing industry). This implies that in order to extract specific measurements of interest, whole body 3-D scan data must be segmented by machine into subsets corresponding to functional human body parts. However, previously reported attempts at automating the segmentation process suffer from various limitations, such as being restricted to a standard specific posture and being vulnerable to scan data artifacts. Our human body segmentation algorithm advances the state of the art to overcome the above limitations and we present experimental results obtained using both real and synthetic data that confirm the validity, effectiveness, and robustness of our approach.

Cartilage segmentation of 3D MRI scans of the osteoarthritic knee combining user knowledge and active contours

NASA Astrophysics Data System (ADS)

Lynch, John A.; Zaim, Souhil; Zhao, Jenny; Stork, Alexander; Peterfy, Charles G.; Genant, Harry K.

2000-06-01

A technique for segmentation of articular cartilage from 3D MRI scans of the knee has been developed. It overcomes the limitations of the conventionally used region growing techniques, which are prone to inter- and intra-observer variability, and which can require much manual intervention. We describe a hybrid segmentation method combining expert knowledge with directionally oriented Canny filters, cost functions and cubic splines. After manual initialization, the technique utilized 3 cost functions which aided automated detection of cartilage and its boundaries. Using the sign of the edge strength, and the local direction of the boundary, this technique is more reliable than conventional 'snakes,' and the user had little control over smoothness of boundaries. This means that the automatically detected boundary can conform to the true shape of the real boundary, also allowing reliable detection of subtle local lesions on the normally smooth cartilage surface. Manual corrections, with possible re-optimization were sometimes needed. When compared to the conventionally used region growing techniques, this newly described technique measured local cartilage volume with 3 times better reproducibility, and involved two thirds less human interaction. Combined with the use of 3D image registration, the new technique should also permit unbiased segmentation of followup scans by automated initialization from a baseline segmentation of an earlier scan of the same patient.

TH-CD-202-05: DECT Based Tissue Segmentation as Input to Monte Carlo Simulations for Proton Treatment Verification Using PET Imaging

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

Berndt, B; Wuerl, M; Dedes, G

Purpose: To improve agreement of predicted and measured positron emitter yields in patients, after proton irradiation for PET-based treatment verification, using a novel dual energy CT (DECT) tissue segmentation approach, overcoming known deficiencies from single energy CT (SECT). Methods: DECT head scans of 5 trauma patients were segmented and compared to existing decomposition methods with a first focus on the brain. For validation purposes, three brain equivalent solutions [water, white matter (WM) and grey matter (GM) – equivalent with respect to their reference carbon and oxygen contents and CT numbers at 90kVp and 150kVp] were prepared from water, ethanol, sucrosemore » and salt. The activities of all brain solutions, measured during a PET scan after uniform proton irradiation, were compared to Monte Carlo simulations. Simulation inputs were various solution compositions obtained from different segmentation approaches from DECT, SECT scans, and known reference composition. Virtual GM solution salt concentration corrections were applied based on DECT measurements of solutions with varying salt concentration. Results: The novel tissue segmentation showed qualitative improvements in %C for patient brain scans (ground truth unavailable). The activity simulations based on reference solution compositions agree with the measurement within 3–5% (4–8Bq/ml). These reference simulations showed an absolute activity difference between WM (20%C) and GM (10%C) to H2O (0%C) of 43 Bq/ml and 22 Bq/ml, respectively. Activity differences between reference simulations and segmented ones varied from −6 to 1 Bq/ml for DECT and −79 to 8 Bq/ml for SECT. Conclusion: Compared to the conventionally used SECT segmentation, the DECT based segmentation indicates a qualitative and quantitative improvement. In controlled solutions, a MC input based on DECT segmentation leads to better agreement with the reference. Future work will address the anticipated improvement of quantification accuracy in patients, comparing different tissue decomposition methods with an MR brain segmentation. Acknowledgement: DFG-MAP and HIT-Heidelberg Deutsche Forschungsgemeinschaft (MAP); Bundesministerium fur Bildung und Forschung (01IB13001)« less

Automated Slide Scanning and Segmentation in Fluorescently-labeled Tissues Using a Widefield High-content Analysis System.

PubMed

Poon, Candice C; Ebacher, Vincent; Liu, Katherine; Yong, Voon Wee; Kelly, John James Patrick

2018-05-03

Automated slide scanning and segmentation of fluorescently-labeled tissues is the most efficient way to analyze whole slides or large tissue sections. Unfortunately, many researchers spend large amounts of time and resources developing and optimizing workflows that are only relevant to their own experiments. In this article, we describe a protocol that can be used by those with access to a widefield high-content analysis system (WHCAS) to image any slide-mounted tissue, with options for customization within pre-built modules found in the associated software. Not originally intended for slide scanning, the steps detailed in this article make it possible to acquire slide scanning images in the WHCAS which can be imported into the associated software. In this example, the automated segmentation of brain tumor slides is demonstrated, but the automated segmentation of any fluorescently-labeled nuclear or cytoplasmic marker is possible. Furthermore, there are a variety of other quantitative software modules including assays for protein localization/translocation, cellular proliferation/viability/apoptosis, and angiogenesis that can be run. This technique will save researchers time and effort and create an automated protocol for slide analysis.

Segmented Ge detector rejection of internal beta activity produced by neutron irradiation

NASA Technical Reports Server (NTRS)

Varnell, L. S.; Callas, J. L.; Mahoney, W. A.; Pehl, R. H.; Landis, D. A.

1991-01-01

Future Ge spectrometers flown in space to observe cosmic gamma-ray sources will incorporate segmented detectors to reduce the background from radioactivity produced by energetic particle reactions. To demonstrate the effectiveness of a segmented Ge detector in rejecting background events due to the beta decay of internal radioactivity, a laboratory experiment has been carried out in which radioactivity was produced in the detector by neutron irradiation. A Cf-252 source of neutrons was used to produce, by neutron capture on Ge-74 (36.5 percent of natural Ge) in the detector itself, Ge-75 (t sub 1/2 = 82.78 min), which decays by beta emission with a maximum electron kinetic energy of 1188 keV. By requiring that an ionizing event deposit energy in two or more of the five segments of the detector, each about 1-cm thick, the beta particles, which have a range of about 1-mm, are rejected, while most external gamma rays incident on the detector are counted. Analysis of this experiment indicates that over 85 percent of the beta events from the decay of Ge-75 are rejected, which is in good agreement with Monte Carlo calculations.

Endoscopic ultrasound description of liver segmentation and anatomy.

PubMed

Bhatia, Vikram; Hijioka, Susumu; Hara, Kazuo; Mizuno, Nobumasa; Imaoka, Hiroshi; Yamao, Kenji

2014-05-01

Endoscopic ultrasound (EUS) can demonstrate the detailed anatomy of the liver from the transgastric and transduodenal routes. Most of the liver segments can be imaged with EUS, except the right posterior segments. The intrahepatic vascular landmarks include the major hepatic veins, portal vein radicals, hepatic arterial branches, and the inferior vena cava, and the venosum and teres ligaments are other important intrahepatic landmarks. The liver hilum and gallbladder serve as useful surface landmarks. Deciphering liver segmentation and anatomy by EUS requires orienting the scan planes with these landmarkstructures, and is different from the static cross-sectional radiological images. Orientation during EUS requires appreciation of the numerous scan planes possible in real-time, and the direction of scanning from the stomach and duodenal bulb. We describe EUS imaging of the liver with a curved linear probe in a step-by-step approach, with the relevant anatomical details, potential applications, and pitfalls of this novel EUS application. © 2013 The Authors. Digestive Endoscopy © 2013 Japan Gastroenterological Endoscopy Society.

Choroidal vasculature characteristics based choroid segmentation for enhanced depth imaging optical coherence tomography images

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

Chen, Qiang; Niu, Sijie; Yuan, Songtao

Purpose: In clinical research, it is important to measure choroidal thickness when eyes are affected by various diseases. The main purpose is to automatically segment choroid for enhanced depth imaging optical coherence tomography (EDI-OCT) images with five B-scans averaging. Methods: The authors present an automated choroid segmentation method based on choroidal vasculature characteristics for EDI-OCT images with five B-scans averaging. By considering the large vascular of the Haller’s layer neighbor with the choroid-sclera junction (CSJ), the authors measured the intensity ascending distance and a maximum intensity image in the axial direction from a smoothed and normalized EDI-OCT image. Then, basedmore » on generated choroidal vessel image, the authors constructed the CSJ cost and constrain the CSJ search neighborhood. Finally, graph search with smooth constraints was utilized to obtain the CSJ boundary. Results: Experimental results with 49 images from 10 eyes in 8 normal persons and 270 images from 57 eyes in 44 patients with several stages of diabetic retinopathy and age-related macular degeneration demonstrate that the proposed method can accurately segment the choroid of EDI-OCT images with five B-scans averaging. The mean choroid thickness difference and overlap ratio between the authors’ proposed method and manual segmentation drawn by experts were −11.43 μm and 86.29%, respectively. Conclusions: Good performance was achieved for normal and pathologic eyes, which proves that the authors’ method is effective for the automated choroid segmentation of the EDI-OCT images with five B-scans averaging.« less

ADP-ribosylation of transducin by pertussis toxin

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

Watkins, P.A.; Burns, D.L.; Kanaho, Y.

1985-11-05

Transducin, the guanyl nucleotide-binding regulatory protein of retinal rod outer segments that couples the photon receptor, rhodopsin, with the light-activated cGMP phosphodiesterase, can be resolved into two functional components, T alpha and T beta gamma. T alpha (39 kDa), which is (TSP)ADP-ribosylated by pertussis toxin and (TSP)NAD in rod outer segments and in purified transducin, was also labeled by the toxin after separation from T beta gamma (36 kDa and approximately 10 kDa); neither component of T beta gamma was a pertussis toxin substrate. Labeling of T alpha was enhanced by T beta gamma and was maximal at approximately 1:1more » molar ratio of T alpha : T beta gamma. Limited proteolysis by trypsin of T alpha in the presence of guanyl-5'-yl imidodiphosphate (Gpp(NH)p) resulted in the sequential appearance of proteins of 38 and TS kDa. The amino terminus of both 38- and TS-kDa proteins was leucine, whereas that of T alpha could not be identified and was assumed to be blocked. The TS-kDa peptide was not a pertussis toxin substrate. Labeling of the 38-kDa protein was poor and was not enhanced by T beta gamma. Trypsin treatment of (TSP)ADP-ribosyl-T alpha produced a labeled 37-38-kDa doublet followed by appearance of radioactivity at the dye front. It appears, therefore, that, although the 38-kDa protein was poor toxin substrate, it contained the ADP-ribosylation site. Without rhodopsin, labeling of T alpha (in the presence of T beta gamma) was unaffected by Gpp(NH)p, guanosine 5'-O-(thiotriphosphate) (GTP gamma S), GTP, GDP, and guanosine 5'-O-(thiodiphosphate) (GDP beta S) but was increased by ATP. When photolyzed rhodopsin and T beta gamma were present, Gpp(NH)p and GTP gamma S decreased (TSP)ADP-ribosylation by pertussis toxin. Thus, pertussis toxin-catalyzed (TSP)ADP-ribosylation of T alpha was affected by nucleotides, rhodopsin and light in addition to T beta gamma.« less

Application of single- and dual-energy CT brain tissue segmentation to PET monitoring of proton therapy

NASA Astrophysics Data System (ADS)

Berndt, Bianca; Landry, Guillaume; Schwarz, Florian; Tessonnier, Thomas; Kamp, Florian; Dedes, George; Thieke, Christian; Würl, Matthias; Kurz, Christopher; Ganswindt, Ute; Verhaegen, Frank; Debus, Jürgen; Belka, Claus; Sommer, Wieland; Reiser, Maximilian; Bauer, Julia; Parodi, Katia

2017-03-01

The purpose of this work was to evaluate the ability of single and dual energy computed tomography (SECT, DECT) to estimate tissue composition and density for usage in Monte Carlo (MC) simulations of irradiation induced β + activity distributions. This was done to assess the impact on positron emission tomography (PET) range verification in proton therapy. A DECT-based brain tissue segmentation method was developed for white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). The elemental composition of reference tissues was assigned to closest CT numbers in DECT space (DECTdist). The method was also applied to SECT data (SECTdist). In a validation experiment, the proton irradiation induced PET activity of three brain equivalent solutions (BES) was compared to simulations based on different tissue segmentations. Five patients scanned with a dual source DECT scanner were analyzed to compare the different segmentation methods. A single magnetic resonance (MR) scan was used for comparison with an established segmentation toolkit. Additionally, one patient with SECT and post-treatment PET scans was investigated. For BES, DECTdist and SECTdist reduced differences to the reference simulation by up to 62% when compared to the conventional stoichiometric segmentation (SECTSchneider). In comparison to MR brain segmentation, Dice similarity coefficients for WM, GM and CSF were 0.61, 0.67 and 0.66 for DECTdist and 0.54, 0.41 and 0.66 for SECTdist. MC simulations of PET treatment verification in patients showed important differences between DECTdist/SECTdist and SECTSchneider for patients with large CSF areas within the treatment field but not in WM and GM. Differences could be misinterpreted as PET derived range shifts of up to 4 mm. DECTdist and SECTdist yielded comparable activity distributions, and comparison of SECTdist to a measured patient PET scan showed improved agreement when compared to SECTSchneider. The agreement between predicted and measured PET activity distributions was improved by employing a brain specific segmentation applicable to both DECT and SECT data.

Copper crystal lens for medical imaging: first results

NASA Astrophysics Data System (ADS)

Roa, Dante E.; Smither, Robert K.

2001-06-01

A copper crystal lens designed to focus gamma ray energies of 100 to 200 keV has been assembled at Argonne National Laboratory. In particular, the lens has been optimized to focus the 140.6 keV gamma rays from technetium-99 m typically used in radioactive tracers. This new approach to medical imaging relies on crystal diffraction to focus incoming gamma rays in a manner similar to a simple convex lens focusing visible light. The lens is envisioned to be part of an array of lenses that can be used as a complementary technique to gamma cameras for localized scans of suspected tumor regions in the body. In addition, a 2- lens array can be used to scan a woman's breast in search of tumors with no discomfort to the patient. The incoming gamma rays are diffracted by a set of 828 copper crystal cubes arranged in 13 concentric rings, which focus the gamma rays into a very small area on a well-shielded NaI detector. Experiments performance with technetium-99 m and cobalt 57 radioactive sources indicate that a 6-lens array should be capable of detecting sources with (mu) Ci strength.

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach.

PubMed

Beichel, Reinhard R; Van Tol, Markus; Ulrich, Ethan J; Bauer, Christian; Chang, Tangel; Plichta, Kristin A; Smith, Brian J; Sunderland, John J; Graham, Michael M; Sonka, Milan; Buatti, John M

2016-06-01

The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the "just-enough-interaction" principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction.

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach

PubMed Central

Beichel, Reinhard R.; Van Tol, Markus; Ulrich, Ethan J.; Bauer, Christian; Chang, Tangel; Plichta, Kristin A.; Smith, Brian J.; Sunderland, John J.; Graham, Michael M.; Sonka, Milan; Buatti, John M.

2016-01-01

Purpose: The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. Methods: A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Results: Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Conclusions: Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction. PMID:27277044

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach

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

Beichel, Reinhard R., E-mail: reinhard-beichel@uiowa.edu; Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242; Department of Internal Medicine, University of Iowa, Iowa City, Iowa 52242

Purpose: The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. Methods: A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behaviormore » of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Results: Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Conclusions: Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction.« less

Use of C-Arm Cone Beam CT During Hepatic Radioembolization: Protocol Optimization for Extrahepatic Shunting and Parenchymal Enhancement

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

Hoven, Andor F. van den, E-mail: a.f.vandenhoven@umcutrecht.nl; Prince, Jip F.; Keizer, Bart de

PurposeTo optimize a C-arm computed tomography (CT) protocol for radioembolization (RE), specifically for extrahepatic shunting and parenchymal enhancement.Materials and MethodsA prospective development study was performed per IDEAL recommendations. A literature-based protocol was applied in patients with unresectable and chemorefractory liver malignancies undergoing an angiography before radioembolization. Contrast and scan settings were adjusted stepwise and repeatedly reviewed in a consensus meeting. Afterwards, two independent raters analyzed all scans. A third rater evaluated the SPECT/CT scans as a reference standard for extrahepatic shunting and lack of target segment perfusion.ResultsFifty scans were obtained in 29 procedures. The first protocol, using a 6 s delaymore » and 10 s scan, showed insufficient parenchymal enhancement. In the second protocol, the delay was determined by timing parenchymal enhancement on DSA power injection (median 8 s, range 4–10 s): enhancement improved, but breathing artifacts increased (from 0 to 27 %). Since the third protocol with a 5 s scan decremented subjective image quality, the second protocol was deemed optimal. Median CNR (range) was 1.7 (0.6–3.2), 2.2 (−1.4–4.0), and 2.1 (−0.3–3.0) for protocol 1, 2, and 3 (p = 0.80). Delineation of perfused segments was possible in 57, 73, and 44 % of scans (p = 0.13). In all C-arm CTs combined, the negative predictive value was 95 % for extrahepatic shunting and 83 % for lack of target segment perfusion.ConclusionAn optimized C-arm CT protocol was developed that can be used to detect extrahepatic shunts and non-perfusion of target segments during RE.« less

Simulation Of A Photofission-Based Cargo Interrogation System

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

King, Michael; Gozani, Tsahi; Stevenson, John

A comprehensive model has been developed to characterize and optimize the detection of Bremsstrahlung x-ray induced fission signatures from nuclear materials hidden in cargo containers. An effective active interrogation system should not only induce a large number of fission events but also efficiently detect their signatures. The proposed scanning system utilizes a 9-MV commercially available linear accelerator and the detection of strong fission signals i.e. delayed gamma rays and prompt neutrons. Because the scanning system is complex and the cargo containers are large and often highly attenuating, the simulation method segments the model into several physical steps, representing each changemore » of radiation particle. Each approximation is carried-out separately, resulting in a major reduction in computational time and a significant improvement in tally statistics. The model investigates the effect on the fission rate and detection rate by various cargo types, densities and distributions. Hydrogenous and metallic cargos, homogeneous and heterogeneous, as well as various locations of the nuclear material inside the cargo container were studied. We will show that for the photofission-based interrogation system simulation, the final results are not only in good agreement with a full, single-step simulation but also with experimental results, further validating the full-system simulation.« less

Thermodynamic confinement and alpha-helix persistence length in poly(gamma-benzyl-L-glutamate)-b-poly(dimethyl siloxane)-b-poly(gamma-benzyl-L-glutamate) triblock copolymers.

PubMed

Papadopoulos, P; Floudas, G; Schnell, I; Lieberwirth, I; Nguyen, T Q; Klok, H-A

2006-02-01

The structure and the associated dynamics of a series of poly(gamma-benzyl-L-glutamate)-b-poly(dimethyl siloxane)-b-poly(gamma-benzyl-L-glutamate) (PBLG-b-PDMS-b-PBLG) triblock copolymers were investigated using small- and wide-angle X-ray scattering, NMR, transmission electron microscopy, and dielectric spectroscopy, respectively. The structural analysis revealed phase separation in the case of the longer blocks with defected alpha-helical segments embedded within the block copolymer nanodomains. The alpha-helical persistence length was found to depend on the degree of segregation; thermodynamic confinement and chain stretching results in the partial annihilation of helical defects.

Method for Reducing the Refresh Rate of Fiber Bragg Grating Sensors

NASA Technical Reports Server (NTRS)

Parker, Allen R., Jr. (Inventor)

2014-01-01

The invention provides a method of obtaining the FBG data in final form (transforming the raw data into frequency and location data) by taking the raw FBG sensor data and dividing the data into a plurality of segments over time. By transforming the raw data into a plurality of smaller segments, processing time is significantly decreased. Also, by defining the segments over time, only one processing step is required. By employing this method, the refresh rate of FBG sensor systems can be improved from about 1 scan per second to over 20 scans per second.

Poor symptom control is associated with reduced CT scan segmental airway lumen area in smokers with asthma.

PubMed

Thomson, Neil C; Chaudhuri, Rekha; Spears, Mark; Messow, Claudia-Martina; MacNee, William; Connell, Martin; Murchison, John T; Sproule, Michael; McSharry, Charles

2015-03-01

Cigarette smoking is associated with worse symptoms in asthma and abnormal segmental airways in healthy subjects. We tested the hypothesis that current symptom control in smokers with asthma is associated with altered segmental airway dimensions measured by CT scan. In 93 subjects with mild, moderate, and severe asthma (smokers and never smokers), we recorded Asthma Control Questionnaire-6 (ACQ-6) score, spirometry (FEV1; forced expiratory flow rate, midexpiratory phase [FEF(25%-75%)]), residual volume (RV), total lung capacity (TLC), and CT scan measures of the right bronchial (RB) and left bronchial (LB) segmental airway dimensions (wall thickness, mm; lumen area, mm²) in the RB3/LB3, RB6/LB6, and RB10/LB10 (smaller) airways. The CT scan segmental airway (RB10 and LB10) lumen area was reduced in smokers with asthma compared with never smokers with asthma; RB10, 16.6 mm² (interquartile range, 12.4-19.2 mm²) vs 19.6 mm² (14.7-24.2 mm²) (P = .01); LB10, 14.8 mm² (12.1-19.0 mm²) vs 19.9 mm² (14.5-25.0 mm²) (P = .003), particularly in severe disease, with no differences in wall thickness or in larger airway (RB3 and LB3) dimensions. In smokers with asthma, a reduced lumen area in fifth-generation airways (RB10 or LB10) was associated with poor symptom control (higher ACQ-6 score) (-0.463 [-0.666 to -0.196], P = .001, and -0.401 [-0.619 to -0.126], P = .007, respectively) and reduced postbronchodilator FEF(25%-75%) (0.521 [0.292-0.694], P < .001, and [0.471 [0.236-0.654], P = .001, respectively) and higher RV/TLC %. The CT scan segmental airway lumen area is reduced in smokers with asthma compared with never smokers with asthma, particularly in severe disease, and is associated with worse current symptom control and small airway dysfunction.

[Accuracy of attenuation coefficient obtained by 137Cs single-transmission scanning in PET: comparison with conventional germanium line source].

PubMed

Matsumoto, Keiichi; Kitamura, Keishi; Mizuta, Tetsuro; Shimizu, Keiji; Murase, Kenya; Senda, Michio

2006-02-20

Transmission scanning can be successfully performed with a Cs-137 single-photon-emitting point source for three-dimensional PET imaging. This method was effective for postinjection transmission scanning because of differences in physical energy. However, scatter contamination in the transmission data lowers measured attenuation coefficients. The purpose of this study was to investigate the accuracy of the influence of object scattering by measuring the attenuation coefficients on the transmission images. We also compared the results with the conventional germanium line source method. Two different types of PET scanner, the SET-3000 G/X (Shimadzu Corp.) and ECAT EXACT HR(+) (Siemens/CTI) , were used. For the transmission scanning, the SET-3000 G/X and ECAT HR(+) were the Cs-137 point source and Ge-68/Ga-68 line source, respectively. With the SET-3000 G/X, we performed transmission measurement at two energy gate settings, the standard 600-800 keV as well as 500-800 keV. The energy gate setting of the ECAT HR(+) was 350-650 keV. The effects of scattering in a uniform phantom with different cross-sectional areas ranging from 201 cm(2) to 314 cm(2) to 628 cm(2) (apposition of the two 20 cm diameter phantoms) and 943 cm(2) (stacking of the three 20 cm diameter phantoms) were acquired without emission activity. First, we evaluated the attenuation coefficients of the two different types of transmission scanning using region of interest (ROI) analysis. In addition, we evaluated the attenuation coefficients with and without segmentation for Cs-137 transmission images using the same analysis. The segmentation method was a histogram-based soft-tissue segmentation process that can also be applied to reconstructed transmission images. In the Cs-137 experiment, the maximum underestimation was 3% without segmentation, which was reduced to less than 1% with segmentation at the center of the largest phantom. In the Ge-68/Ga-68 experiment, the difference in mean attenuation coefficients was stable with all phantoms. We evaluated the accuracy of attenuation coefficients of Cs-137 single-transmission scans. The results for Cs-137 suggest that scattered photons depend on object size. Although Cs-137 single-transmission scans contained scattered photons, attenuation coefficient error could be reduced using by the segmentation method.

Multiatlas segmentation of thoracic and abdominal anatomy with level set-based local search.

PubMed

Schreibmann, Eduard; Marcus, David M; Fox, Tim

2014-07-08

Segmentation of organs at risk (OARs) remains one of the most time-consuming tasks in radiotherapy treatment planning. Atlas-based segmentation methods using single templates have emerged as a practical approach to automate the process for brain or head and neck anatomy, but pose significant challenges in regions where large interpatient variations are present. We show that significant changes are needed to autosegment thoracic and abdominal datasets by combining multi-atlas deformable registration with a level set-based local search. Segmentation is hierarchical, with a first stage detecting bulk organ location, and a second step adapting the segmentation to fine details present in the patient scan. The first stage is based on warping multiple presegmented templates to the new patient anatomy using a multimodality deformable registration algorithm able to cope with changes in scanning conditions and artifacts. These segmentations are compacted in a probabilistic map of organ shape using the STAPLE algorithm. Final segmentation is obtained by adjusting the probability map for each organ type, using customized combinations of delineation filters exploiting prior knowledge of organ characteristics. Validation is performed by comparing automated and manual segmentation using the Dice coefficient, measured at an average of 0.971 for the aorta, 0.869 for the trachea, 0.958 for the lungs, 0.788 for the heart, 0.912 for the liver, 0.884 for the kidneys, 0.888 for the vertebrae, 0.863 for the spleen, and 0.740 for the spinal cord. Accurate atlas segmentation for abdominal and thoracic regions can be achieved with the usage of a multi-atlas and perstructure refinement strategy. To improve clinical workflow and efficiency, the algorithm was embedded in a software service, applying the algorithm automatically on acquired scans without any user interaction.

ProxiScan™: A Novel Camera for Imaging Prostate Cancer

ScienceCinema

Ralph James

2017-12-09

ProxiScan is a compact gamma camera suited for high-resolution imaging of prostate cancer. Developed by Brookhaven National Laboratory and Hybridyne Imaging Technologies, Inc., ProxiScan won a 2009 R&D 100 Award, sponsored by R&D Magazine to recognize t

Dental measurements and Bolton index reliability and accuracy obtained from 2D digital, 3D segmented CBCT, and 3d intraoral laser scanner

PubMed Central

San José, Verónica; Bellot-Arcís, Carlos; Tarazona, Beatriz; Zamora, Natalia; O Lagravère, Manuel

2017-01-01

Background To compare the reliability and accuracy of direct and indirect dental measurements derived from two types of 3D virtual models: generated by intraoral laser scanning (ILS) and segmented cone beam computed tomography (CBCT), comparing these with a 2D digital model. Material and Methods One hundred patients were selected. All patients’ records included initial plaster models, an intraoral scan and a CBCT. Patients´ dental arches were scanned with the iTero® intraoral scanner while the CBCTs were segmented to create three-dimensional models. To obtain 2D digital models, plaster models were scanned using a conventional 2D scanner. When digital models had been obtained using these three methods, direct dental measurements were measured and indirect measurements were calculated. Differences between methods were assessed by means of paired t-tests and regression models. Intra and inter-observer error were analyzed using Dahlberg´s d and coefficients of variation. Results Intraobserver and interobserver error for the ILS model was less than 0.44 mm while for segmented CBCT models, the error was less than 0.97 mm. ILS models provided statistically and clinically acceptable accuracy for all dental measurements, while CBCT models showed a tendency to underestimate measurements in the lower arch, although within the limits of clinical acceptability. Conclusions ILS and CBCT segmented models are both reliable and accurate for dental measurements. Integration of ILS with CBCT scans would get dental and skeletal information altogether. Key words:CBCT, intraoral laser scanner, 2D digital models, 3D models, dental measurements, reliability. PMID:29410764

Active interrogation using low-energy nuclear reactions

NASA Astrophysics Data System (ADS)

Antolak, Arlyn; Doyle, Barney; Leung, Ka-Ngo; Morse, Daniel; Provencio, Paula

2005-09-01

High-energy photons and neutrons can be used to interrogate for heavily shielded fissile materials inside sealed cargo containers by detecting their prompt and/or delayed fission signatures. The FIND (Fissmat Inspection for Nuclear Detection) active interrogation system is based on a dual neutron+gamma source that uses low-energy (< 500 keV) proton- or deuteron-induced nuclear reactions to produce high intensities of mono-energetic gamma rays and/or neutrons. The source can be operated in either pulsed (e.g., to detect delayed photofission neutrons and gammas) or continuous (e.g., detecting prompt fission signatures) modes. For the gamma-rays, the source target can be segmented to incorporate different (p,γ) isotopes for producing gamma-rays at selective energies, thereby improving the probability of detection. The design parameters for the FIND system are discussed and preliminary accelerator-based measurements of gamma and neutron yields, background levels, and fission signals for several target materials under consideration are presented.

An Efficient Pipeline for Abdomen Segmentation in CT Images.

PubMed

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

2018-04-01

Computed tomography (CT) scans usually include some disadvantages due to the nature of the imaging procedure, and these handicaps prevent accurate abdomen segmentation. Discontinuous abdomen edges, bed section of CT, patient information, closeness between the edges of the abdomen and CT, poor contrast, and a narrow histogram can be regarded as the most important handicaps that occur in abdominal CT scans. Currently, one or more handicaps can arise and prevent technicians obtaining abdomen images through simple segmentation techniques. In other words, CT scans can include the bed section of CT, a patient's diagnostic information, low-quality abdomen edges, low-level contrast, and narrow histogram, all in one scan. These phenomena constitute a challenge, and an efficient pipeline that is unaffected by handicaps is required. In addition, analysis such as segmentation, feature selection, and classification has meaning for a real-time diagnosis system in cases where the abdomen section is directly used with a specific size. A statistical pipeline is designed in this study that is unaffected by the handicaps mentioned above. Intensity-based approaches, morphological processes, and histogram-based procedures are utilized to design an efficient structure. Performance evaluation is realized in experiments on 58 CT images (16 training, 16 test, and 26 validation) that include the abdomen and one or more disadvantage(s). The first part of the data (16 training images) is used to detect the pipeline's optimum parameters, while the second and third parts are utilized to evaluate and to confirm the segmentation performance. The segmentation results are presented as the means of six performance metrics. Thus, the proposed method achieves remarkable average rates for training/test/validation of 98.95/99.36/99.57% (jaccard), 99.47/99.67/99.79% (dice), 100/99.91/99.91% (sensitivity), 98.47/99.23/99.85% (specificity), 99.38/99.63/99.87% (classification accuracy), and 98.98/99.45/99.66% (precision). In summary, a statistical pipeline performing the task of abdomen segmentation is achieved that is not affected by the disadvantages, and the most detailed abdomen segmentation study is performed for the use before organ and tumor segmentation, feature extraction, and classification.

Study on the optimal moisture adding rate of brown rice during germination by using segmented moisture conditioning method.

PubMed

Cao, Yinping; Jia, Fuguo; Han, Yanlong; Liu, Yang; Zhang, Qiang

2015-10-01

The aim of this study was to find out the optimal moisture adding rate of brown rice during the process of germination. The process of water addition in brown rice could be divided into three stages according to different water absorption speeds in soaking process. Water was added with three different speeds in three stages to get the optimal water adding rate in the whole process of germination. Thus, the technology of segmented moisture conditioning which is a method of adding water gradually was put forward. Germinated brown rice was produced by using segmented moisture conditioning method to reduce the loss of water-soluble nutrients and was beneficial to the accumulation of gamma aminobutyric acid. The effects of once moisture adding amount in three stages on the gamma aminobutyric acid content in germinated brown rice and germination rate of brown rice were investigated by using response surface methodology. The optimum process parameters were obtained as follows: once moisture adding amount of stage I with 1.06 %/h, once moisture adding amount of stage II with 1.42 %/h and once moisture adding amount of stage III with 1.31 %/h. The germination rate under the optimum parameters was 91.33 %, which was 7.45 % higher than that of germinated brown rice produced by soaking method (84.97 %). The content of gamma aminobutyric acid in germinated brown rice under the optimum parameters was 29.03 mg/100 g, which was more than two times higher than that of germinated brown rice produced by soaking method (12.81 mg/100 g). The technology of segmented moisture conditioning has potential applications for studying many other cereals.

Automated segmentation of lesions including subretinal hyperreflective material in neovascular age-related macular degeneration.

PubMed

Lee, Hyungwoo; Kang, Kyung Eun; Chung, Hyewon; Kim, Hyung Chan

2018-04-12

To evaluate an automated segmentation algorithm with a convolutional neural network (CNN) to quantify and detect intraretinal fluid (IRF), subretinal fluid (SRF), pigment epithelial detachment (PED), and subretinal hyperreflective material (SHRM) through analyses of spectral domain optical coherence tomography (SD-OCT) images from patients with neovascular age-related macular degeneration (nAMD). Reliability and validity analysis of a diagnostic tool. We constructed a dataset including 930 B-scans from 93 eyes of 93 patients with nAMD. A CNN-based deep neural network was trained using 11550 augmented images derived from 550 B-scans. The performance of the trained network was evaluated using a validation set including 140 B-scans and a test set of 240 B-scans. The Dice coefficient, positive predictive value (PPV), sensitivity, relative area difference (RAD), and intraclass correlation coefficient (ICC) were used to evaluate segmentation and detection performance. Good agreement was observed for both segmentation and detection of lesions between the trained network and clinicians. The Dice coefficients for segmentation of IRF, SRF, SHRM, and PED were 0.78, 0.82, 0.75, and 0.80, respectively; the PPVs were 0.79, 0.80, 0.75, and 0.80, respectively; and the sensitivities were 0.77, 0.84, 0.73, and 0.81, respectively. The RADs were -4.32%, -10.29%, 4.13%, and 0.34%, respectively, and the ICCs were 0.98, 0.98, 0.97, and 0.98, respectively. All lesions were detected with high PPVs (range 0.94-0.99) and sensitivities (range 0.97-0.99). A CNN-based network provides clinicians with quantitative data regarding nAMD through automatic segmentation and detection of pathological lesions, including IRF, SRF, PED, and SHRM. Copyright © 2018 Elsevier Inc. All rights reserved.

Towards aging mechanisms of cross-linked polyethylene (XLPE) cable insulation materials in nuclear power plants

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

Liu, Shuaishuai; Fifield, Leonard S.; Bowler, Nicola

Cross-linked polyethylene (XLPE) cable insulation material undergoes simultaneous, accelerated thermal and gamma-radiation aging to simulate the long-term aging environment within nuclear power plants (NPPs). A variety of materials characterization tests, including scanning electron microscopy, thermo-gravimetric analysis, differential scanning calorimetry, oxidation induction time, gel-fraction and dielectric properties measurement, are conducted on pristine and differently aged XLPE samples. A preliminary model of one possible aging mechanism of XLPE cable insulation material under gamma radiation at elevated temperature of 115 °C is suggested.

A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images

USGS Publications Warehouse

Maxwell, S.K.; Schmidt, Gail L.; Storey, James C.

2007-01-01

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

Semi-automatic geographic atrophy segmentation for SD-OCT images.

PubMed

Chen, Qiang; de Sisternes, Luis; Leng, Theodore; Zheng, Luoluo; Kutzscher, Lauren; Rubin, Daniel L

2013-01-01

Geographic atrophy (GA) is a condition that is associated with retinal thinning and loss of the retinal pigment epithelium (RPE) layer. It appears in advanced stages of non-exudative age-related macular degeneration (AMD) and can lead to vision loss. We present a semi-automated GA segmentation algorithm for spectral-domain optical coherence tomography (SD-OCT) images. The method first identifies and segments a surface between the RPE and the choroid to generate retinal projection images in which the projection region is restricted to a sub-volume of the retina where the presence of GA can be identified. Subsequently, a geometric active contour model is employed to automatically detect and segment the extent of GA in the projection images. Two image data sets, consisting on 55 SD-OCT scans from twelve eyes in eight patients with GA and 56 SD-OCT scans from 56 eyes in 56 patients with GA, respectively, were utilized to qualitatively and quantitatively evaluate the proposed GA segmentation method. Experimental results suggest that the proposed algorithm can achieve high segmentation accuracy. The mean GA overlap ratios between our proposed method and outlines drawn in the SD-OCT scans, our method and outlines drawn in the fundus auto-fluorescence (FAF) images, and the commercial software (Carl Zeiss Meditec proprietary software, Cirrus version 6.0) and outlines drawn in FAF images were 72.60%, 65.88% and 59.83%, respectively.

Joint Segmentation of Anatomical and Functional Images: Applications in Quantification of Lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT Images

PubMed Central

Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967

Modeling envelope statistics of blood and myocardium for segmentation of echocardiographic images.

PubMed

Nillesen, Maartje M; Lopata, Richard G P; Gerrits, Inge H; Kapusta, Livia; Thijssen, Johan M; de Korte, Chris L

2008-04-01

The objective of this study was to investigate the use of speckle statistics as a preprocessing step for segmentation of the myocardium in echocardiographic images. Three-dimensional (3D) and biplane image sequences of the left ventricle of two healthy children and one dog (beagle) were acquired. Pixel-based speckle statistics of manually segmented blood and myocardial regions were investigated by fitting various probability density functions (pdf). The statistics of heart muscle and blood could both be optimally modeled by a K-pdf or Gamma-pdf (Kolmogorov-Smirnov goodness-of-fit test). Scale and shape parameters of both distributions could differentiate between blood and myocardium. Local estimation of these parameters was used to obtain parametric images, where window size was related to speckle size (5 x 2 speckles). Moment-based and maximum-likelihood estimators were used. Scale parameters were still able to differentiate blood from myocardium; however, smoothing of edges of anatomical structures occurred. Estimation of the shape parameter required a larger window size, leading to unacceptable blurring. Using these parameters as an input for segmentation resulted in unreliable segmentation. Adaptive mean squares filtering was then introduced using the moment-based scale parameter (sigma(2)/mu) of the Gamma-pdf to automatically steer the two-dimensional (2D) local filtering process. This method adequately preserved sharpness of the edges. In conclusion, a trade-off between preservation of sharpness of edges and goodness-of-fit when estimating local shape and scale parameters is evident for parametric images. For this reason, adaptive filtering outperforms parametric imaging for the segmentation of echocardiographic images.

Image processing based detection of lung cancer on CT scan images

NASA Astrophysics Data System (ADS)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

Low voltage electrophoresis chip with multi-segments synchronized scanning

NASA Astrophysics Data System (ADS)

Gu, Wenwen; Wen, Zhiyu; Xu, Yi

2017-03-01

For low voltage electrophoresis chip, there is always a problem that the samples are truncated and peaks are broadened, as well as longer time for separation. In this paper, a low voltage electrophoresis separation model was established, and the separation conditions were discussed. A new driving mode was proposed for applying low voltage, which was called multi-segments synchronized scanning. By using this driving mode, the reversed electric field that existed between the multi-segments can enrich samples and shorten the sample zone. The low voltage electrophoresis experiments using multi-segments synchronized scanning were carried out by home-made silicon-PDMS-based chip. The fluorescein isothiocyanate (FITC) labeled lysine and phenylalanine mixed samples with the concentration of 10-4 mol/L were successfully separated under the optimal conditions of 10 mmol/L borax buffer (pH = 10.0), 200 V/cm separation electric field and electrode switch time of 2.5 s. The separation was completed with a resolution of 2.0, and the peak time for lysine and phenylalanine was 4 min and 6 min, respectively.

Automated Identification and Characterization of Secondary & Tertiary gamma’ Precipitates in Nickel-Based Superalloys (PREPRINT)

DTIC Science & Technology

2010-01-01

and intensity information from the EFTEM images. The microstructural statistics obtained from the segmented γ’ precipitates agreed with those of the...is its ability to automate segmentation of precipitates in a reproducible manner for acquiring microstructural statistics that relate to both...were identified using a combination of visual inspection and intensity information from the EFTEM images. The microstructural statistics obtained

Minimum Detectable Activity for Tomographic Gamma Scanning System

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

Venkataraman, Ram; Smith, Susan; Kirkpatrick, J. M.

2015-01-01

For any radiation measurement system, it is useful to explore and establish the detection limits and a minimum detectable activity (MDA) for the radionuclides of interest, even if the system is to be used at far higher values. The MDA serves as an important figure of merit, and often a system is optimized and configured so that it can meet the MDA requirements of a measurement campaign. The non-destructive assay (NDA) systems based on gamma ray analysis are no exception and well established conventions, such the Currie method, exist for estimating the detection limits and the MDA. However, the Tomographicmore » Gamma Scanning (TGS) technique poses some challenges for the estimation of detection limits and MDAs. The TGS combines high resolution gamma ray spectrometry (HRGS) with low spatial resolution image reconstruction techniques. In non-imaging gamma ray based NDA techniques measured counts in a full energy peak can be used to estimate the activity of a radionuclide, independently of other counting trials. However, in the case of the TGS each “view” is a full spectral grab (each a counting trial), and each scan consists of 150 spectral grabs in the transmission and emission scans per vertical layer of the item. The set of views in a complete scan are then used to solve for the radionuclide activities on a voxel by voxel basis, over 16 layers of a 10x10 voxel grid. Thus, the raw count data are not independent trials any more, but rather constitute input to a matrix solution for the emission image values at the various locations inside the item volume used in the reconstruction. So, the validity of the methods used to estimate MDA for an imaging technique such as TGS warrant a close scrutiny, because the pair-counting concept of Currie is not directly applicable. One can also raise questions as to whether the TGS, along with other image reconstruction techniques which heavily intertwine data, is a suitable method if one expects to measure samples whose activities are at or just above MDA levels. The paper examines methods used to estimate MDAs for a TGS system, and explores possible solutions that can be rigorously defended.« less

Accuracy of patient-specific organ dose estimates obtained using an automated image segmentation algorithm.

PubMed

Schmidt, Taly Gilat; Wang, Adam S; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-10-01

The overall goal of this work is to develop a rapid, accurate, and automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using simulations to generate dose maps combined with automated segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. We hypothesized that the autosegmentation algorithm is sufficiently accurate to provide organ dose estimates, since small errors delineating organ boundaries will have minimal effect when computing mean organ dose. A leave-one-out validation study of the automated algorithm was performed with 20 head-neck CT scans expertly segmented into nine regions. Mean organ doses of the automatically and expertly segmented regions were computed from Monte Carlo-generated dose maps and compared. The automated segmentation algorithm estimated the mean organ dose to be within 10% of the expert segmentation for regions other than the spinal canal, with the median error for each organ region below 2%. In the spinal canal region, the median error was [Formula: see text], with a maximum absolute error of 28% for the single-atlas approach and 11% for the multiatlas approach. The results demonstrate that the automated segmentation algorithm can provide accurate organ dose estimates despite some segmentation errors.

Accuracy of patient-specific organ dose estimates obtained using an automated image segmentation algorithm

PubMed Central

Schmidt, Taly Gilat; Wang, Adam S.; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-01-01

Abstract. The overall goal of this work is to develop a rapid, accurate, and automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using simulations to generate dose maps combined with automated segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. We hypothesized that the autosegmentation algorithm is sufficiently accurate to provide organ dose estimates, since small errors delineating organ boundaries will have minimal effect when computing mean organ dose. A leave-one-out validation study of the automated algorithm was performed with 20 head-neck CT scans expertly segmented into nine regions. Mean organ doses of the automatically and expertly segmented regions were computed from Monte Carlo-generated dose maps and compared. The automated segmentation algorithm estimated the mean organ dose to be within 10% of the expert segmentation for regions other than the spinal canal, with the median error for each organ region below 2%. In the spinal canal region, the median error was −7%, with a maximum absolute error of 28% for the single-atlas approach and 11% for the multiatlas approach. The results demonstrate that the automated segmentation algorithm can provide accurate organ dose estimates despite some segmentation errors. PMID:27921070

Validity of Automated Choroidal Segmentation in SS-OCT and SD-OCT.

PubMed

Zhang, Li; Buitendijk, Gabriëlle H S; Lee, Kyungmoo; Sonka, Milan; Springelkamp, Henriët; Hofman, Albert; Vingerling, Johannes R; Mullins, Robert F; Klaver, Caroline C W; Abràmoff, Michael D

2015-05-01

To evaluate the validity of a novel fully automated three-dimensional (3D) method capable of segmenting the choroid from two different optical coherence tomography scanners: swept-source OCT (SS-OCT) and spectral-domain OCT (SD-OCT). One hundred eight subjects were imaged using SS-OCT and SD-OCT. A 3D method was used to segment the choroid and quantify the choroidal thickness along each A-scan. The segmented choroidal posterior boundary was evaluated by comparing to manual segmentation. Differences were assessed to test the agreement between segmentation results of the same subject. Choroidal thickness was defined as the Euclidian distance between Bruch's membrane and the choroidal posterior boundary, and reproducibility was analyzed using automatically and manually determined choroidal thicknesses. For SS-OCT, the average choroidal thickness of the entire 6- by 6-mm2 macular region was 219.5 μm (95% confidence interval [CI], 204.9-234.2 μm), and for SD-OCT it was 209.5 μm (95% CI, 197.9-221.0 μm). The agreement between automated and manual segmentations was high: Average relative difference was less than 5 μm, and average absolute difference was less than 15 μm. Reproducibility of choroidal thickness between repeated SS-OCT scans was high (coefficient of variation [CV] of 3.3%, intraclass correlation coefficient [ICC] of 0.98), and differences between SS-OCT and SD-OCT results were small (CV of 11.0%, ICC of 0.73). We have developed a fully automated 3D method for segmenting the choroid and quantifying choroidal thickness along each A-scan. The method yielded high validity. Our method can be used reliably to study local choroidal changes and may improve the diagnosis and management of patients with ocular diseases in which the choroid is affected.

The Whipple Strip Sky Survey

NASA Astrophysics Data System (ADS)

Kertzman, M. P.

As part of the normal operation of the Whipple 10m Gamma Ray telescope, ten minute drift scan “zenith” runs are made each night of observation for use as calibration. Most of the events recorded during a zenith run are due to the background of cosmic ray showers. However, it would be possible for a hitherto unknown source of gamma rays to drift through the field. This paper reports the results of a search for serendipitous high energy gamma ray sources in the Whipple 10m nightly calibration zenith data. From 2000-2004 nightly calibration runs were taken at an elevation of 89 º. A 2- D analysis of these drift scan runs produces a strip of width ~ 3.5º in declination and spanning the full range of right ascension. In the 2004-05 observing season the calibration runs were taken at elevations of 86° and 83°. Beginning in the 2005-06 season, the nightly calibration runs were taken at an elevation of 80º. Collectively, these drift scans cover a strip approximately 12.5º wide in declination, centered at declination 37.18º, and spanning the full range of RA. The analysis procedures developed for drift scan data, the sensitivity of the method, and the results will be presented.

Application of single- and dual-energy CT brain tissue segmentation to PET monitoring of proton therapy.

PubMed

Berndt, Bianca; Landry, Guillaume; Schwarz, Florian; Tessonnier, Thomas; Kamp, Florian; Dedes, George; Thieke, Christian; Würl, Matthias; Kurz, Christopher; Ganswindt, Ute; Verhaegen, Frank; Debus, Jürgen; Belka, Claus; Sommer, Wieland; Reiser, Maximilian; Bauer, Julia; Parodi, Katia

2017-03-21

The purpose of this work was to evaluate the ability of single and dual energy computed tomography (SECT, DECT) to estimate tissue composition and density for usage in Monte Carlo (MC) simulations of irradiation induced β + activity distributions. This was done to assess the impact on positron emission tomography (PET) range verification in proton therapy. A DECT-based brain tissue segmentation method was developed for white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). The elemental composition of reference tissues was assigned to closest CT numbers in DECT space (DECT dist ). The method was also applied to SECT data (SECT dist ). In a validation experiment, the proton irradiation induced PET activity of three brain equivalent solutions (BES) was compared to simulations based on different tissue segmentations. Five patients scanned with a dual source DECT scanner were analyzed to compare the different segmentation methods. A single magnetic resonance (MR) scan was used for comparison with an established segmentation toolkit. Additionally, one patient with SECT and post-treatment PET scans was investigated. For BES, DECT dist and SECT dist reduced differences to the reference simulation by up to 62% when compared to the conventional stoichiometric segmentation (SECT Schneider ). In comparison to MR brain segmentation, Dice similarity coefficients for WM, GM and CSF were 0.61, 0.67 and 0.66 for DECT dist and 0.54, 0.41 and 0.66 for SECT dist . MC simulations of PET treatment verification in patients showed important differences between DECT dist /SECT dist and SECT Schneider for patients with large CSF areas within the treatment field but not in WM and GM. Differences could be misinterpreted as PET derived range shifts of up to 4 mm. DECT dist and SECT dist yielded comparable activity distributions, and comparison of SECT dist to a measured patient PET scan showed improved agreement when compared to SECT Schneider . The agreement between predicted and measured PET activity distributions was improved by employing a brain specific segmentation applicable to both DECT and SECT data.

Gamma/x-ray linear pushbroom stereo for 3D cargo inspection

NASA Astrophysics Data System (ADS)

Zhu, Zhigang; Hu, Yu-Chi

2006-05-01

For evaluating the contents of trucks, containers, cargo, and passenger vehicles by a non-intrusive gamma-ray or X-ray imaging system to determine the possible presence of contraband, three-dimensional (3D) measurements could provide more information than 2D measurements. In this paper, a linear pushbroom scanning model is built for such a commonly used gamma-ray or x-ray cargo inspection system. Accurate 3D measurements of the objects inside a cargo can be obtained by using two such scanning systems with different scanning angles to construct a pushbroom stereo system. A simple but robust calibration method is proposed to find the important parameters of the linear pushbroom sensors. Then, a fast and automated stereo matching algorithm based on free-form deformable registration is developed to obtain 3D measurements of the objects under inspection. A user interface is designed for 3D visualization of the objects in interests. Experimental results of sensor calibration, stereo matching, 3D measurements and visualization of a 3D cargo container and the objects inside, are presented.

Chicken immunoglobulin gamma-heavy chains: limited VH gene repertoire, combinatorial diversification by D gene segments and evolution of the heavy chain locus.

PubMed

Parvari, R; Avivi, A; Lentner, F; Ziv, E; Tel-Or, S; Burstein, Y; Schechter, I

1988-03-01

cDNA clones encoding the variable and constant regions of chicken immunoglobulin (Ig) gamma-chains were obtained from spleen cDNA libraries. Southern blots of kidney DNA show that the variable region sequences of eight cDNA clones reveal the same set of bands corresponding to approximately 30 cross-hybridizing VH genes of one subgroup. Since the VH clones were randomly selected, it is likely that the bulk of chicken H-chains are encoded by a single VH subgroup. Nucleotide sequence determinations of two cDNA clones reveal VH, D, JH and the constant region. The VH segments are closely related to each other (83% homology) as expected for VH or the same subgroup. The JHs are 15 residues long and differ by one amino acid. The Ds differ markedly in sequence (20% homology) and size (10 and 20 residues). These findings strongly indicate multiple (at least two) D genes which by a combinatorial joining mechanism diversify the H-chains, a mechanism which is not operative in the chicken L-chain locus. The most notable among the chicken Igs is the so-called 7S IgG because its H-chain differs in many important aspects from any mammalian IgG. The sequence of the C gamma cDNA reported here resolves this issue. The chicken C gamma is 426 residues long with four CH domains (unlike mammalian C gamma which has three CH domains) and it shows 25% homology to the chicken C mu. The chicken C gamma is most related to the mammalian C epsilon in length, the presence of four CH domains and the distribution of cysteines in the CH1 and CH2 domains. We propose that the unique chicken C gamma is the ancestor of the mammalian C epsilon and C gamma subclasses, and discuss the evolution of the H-chain locus from that of chicken with presumably three genes (mu, gamma, alpha) to the mammalian loci with 8-10 H-chain genes.

Gamma ray energy tracking in GRETINA

NASA Astrophysics Data System (ADS)

Lee, I. Y.

2011-10-01

The next generation of stable and exotic beam accelerators will provide physics opportunities to study nuclei farther away from the line of stability. However, these experiments will be more demanding on instrumentation performance. These come from the lower production rate for more exotic beams, worse beam impurities, and large beam velocity from the fragmentation and inverse reactions. Gamma-ray spectroscopy will be one of the most effective tools to study exotic nuclei. However, to fully exploit the physics reach provided by these new facilities, better gamma-ray detector will be needed. In the last 10 years, a new concept, gamma-ray energy tracking array, was developed. Tracking arrays will increase the detection sensitivity by factors of several hundred compared to current arrays used in nuclear physics research. Particularly, the capability of reconstructing the position of the interaction with millimeters resolution is needed to correct the Doppler broadening of gamma rays emitted from high velocity nuclei. GRETINA is a gamma-ray tracking array which uses 28 Ge crystals, each with 36 segments, to cover ¼ of the 4 π of the 4 π solid angle. The gamma ray tracking technique requires detailed pulse shape information from each of the segments. These pulses are digitized using 14-bit 100 MHz flash ADCs, and digital signal analysis algorithms implemented in the on-board FPGAs provides energy, time and selection of pulse traces. A digital trigger system, provided flexible trigger functions including a fast trigger output, and also allows complicated trigger decisions to be made up to 20 microseconds. Further analyzed, carried out in a computer cluster, determine the energy, time, and three-dimensional positions of all gamma-ray interactions in the array. This information is then utilized, together with the characteristics of Compton scattering and pair-production processes, to track the scattering sequences of the gamma rays. GRETINA construction is completed in March 2011, and extensive engineering runs were carried out using radioactive sources, and beams from the 88-Inch Cyclotron at LBNL. The data obtained will be used to optimize its performance. Then the first scientific campaign will start in March 2012 at NSCL MSU.

Radiation absorbed dose to bladder walls from positron emitters in the bladder content.

PubMed

Powell, G F; Chen, C T

1987-01-01

A method to calculate absorbed doses at depths in the walls of a static spherical bladder from a positron emitter in the bladder content has been developed. The beta ray dose component is calculated for a spherical model by employing the solutions to the integration of Loevinger and Bochkarev point source functions over line segments and a line segment source array technique. The gamma ray dose is determined using the specific gamma ray constant. As an example, absorbed radiation doses to the bladder walls from F-18 in the bladder content are presented for static spherical bladder models having radii of 2.0 and 3.5 cm, respectively. Experiments with ultra-thin thermoluminescent dosimeters (TLD's) were performed to verify the results of the calculations. Good agreement between TLD measurements and calculations was obtained.

Evolutionarily conserved TCR binding sites, identification of T cells in primary lymphoid tissues, and surprising trans-rearrangements in nurse shark.

PubMed

Criscitiello, Michael F; Ohta, Yuko; Saltis, Mark; McKinney, E Churchill; Flajnik, Martin F

2010-06-15

Cartilaginous fish are the oldest animals that generate RAG-based Ag receptor diversity. We have analyzed the genes and expressed transcripts of the four TCR chains for the first time in a cartilaginous fish, the nurse shark (Ginglymostoma cirratum). Northern blotting found TCR mRNA expression predominantly in lymphoid and mucosal tissues. Southern blotting suggested translocon-type loci encoding all four chains. Based on diversity of V and J segments, the expressed combinatorial diversity for gamma is similar to that of human, alpha and beta may be slightly lower, and delta diversity is the highest of any organism studied to date. Nurse shark TCRdelta have long CDR3 loops compared with the other three chains, creating binding site topologies comparable to those of mammalian TCR in basic paratope structure; additionally, nurse shark TCRdelta CDR3 are more similar to IgH CDR3 in length and heterogeneity than to other TCR chains. Most interestingly, several cDNAs were isolated that contained IgM or IgW V segments rearranged to other gene segments of TCRdelta and alpha. Finally, in situ hybridization experiments demonstrate a conservation of both alpha/beta and gamma/delta T cell localization in the thymus across 450 million years of vertebrate evolution, with gamma/delta TCR expression especially high in the subcapsular region. Collectively, these data make the first cellular identification of TCR-expressing lymphocytes in a cartilaginous fish.

Automated estimation of leaf distribution for individual trees based on TLS point clouds

NASA Astrophysics Data System (ADS)

Koma, Zsófia; Rutzinger, Martin; Bremer, Magnus

2017-04-01

Light Detection and Ranging (LiDAR) especially the ground based LiDAR (Terrestrial Laser Scanning - TLS) is an operational used and widely available measurement tool supporting forest inventory updating and research in forest ecology. High resolution point clouds from TLS already represent single leaves which can be used for a more precise estimation of Leaf Area Index (LAI) and for higher accurate biomass estimation. However, currently the methodology for extracting single leafs from the unclassified point clouds for individual trees is still missing. The aim of this study is to present a novel segmentation approach in order to extract single leaves and derive features related to leaf morphology (such as area, slope, length and width) of each single leaf from TLS point cloud data. For the study two exemplary single trees were scanned in leaf-on condition on the university campus of Innsbruck during calm wind conditions. A northern red oak (Quercus rubra) was scanned by a discrete return recording Optech ILRIS-3D TLS scanner and a tulip tree (Liliodendron tulpifera) with Riegl VZ-6000 scanner. During the scanning campaign a reference dataset was measured parallel to scanning. In this case 230 leaves were randomly collected around the lower branches of the tree and photos were taken. The developed workflow steps were the following: in the first step normal vectors and eigenvalues were calculated based on the user specified neighborhood. Then using the direction of the largest eigenvalue outliers i.e. ghost points were removed. After that region growing segmentation based on the curvature and angles between normal vectors was applied on the filtered point cloud. On each segment a RANSAC plane fitting algorithm was applied in order to extract the segment based normal vectors. Using the related features of the calculated segments the stem and branches were labeled as non-leaf and other segments were classified as leaf. The validation of the different segmentation parameters was evaluated as the following: i) the sum area of the collected leaves and the point cloud, ii) the segmented leaf length-width ratio iii) the distribution of the leaf area for the segmented and the reference-ones were compared and the ideal parameter-set was found. The results show that the leaves can be captured with the developed workflow and the slope can be determined robustly for the segmented leaves. However, area, length and width values are systematically depending on the angle and the distance from the scanner. For correction of the systematic underestimation, more systematic measurement or LiDAR simulation is required for further detailed analysis. The results of leaf segmentation algorithm show high potential in generating more precise tree models with correctly located leaves in order to extract more precise input model for biological modeling of LAI or atmospheric corrections studies. The presented workflow also can be used in monitoring the change of angle of the leaves due to sun irradiation, water balance, and day-night rhythm.

Microstructural study of the nickel-base alloy WAZ-20 using qualitative and quantitative electron optical techniques

NASA Technical Reports Server (NTRS)

Young, S. G.

1973-01-01

The NASA nickel-base alloy WAZ-20 was analyzed by advanced metallographic techniques to qualitatively and quantitatively characterize its phases and stability. The as-cast alloy contained primary gamma-prime, a coarse gamma-gamma prime eutectic, a gamma-fine gamma prime matrix, and MC carbides. A specimen aged at 870 C for 1000 hours contained these same constituents and a few widely scattered high W particles. No detrimental phases (such as sigma or mu) were observed. Scanning electron microscope, light metallography, and replica electron microscope methods are compared. The value of quantitative electron microprobe techniques such as spot and area analysis is demonstrated.

Characterizing the Impact of Off-Axis Scan Acquisition on the Reproducibility of Total Retinal Thickness Measurements in SDOCT Volumes.

PubMed

Antony, Bhavna J; Stetson, Paul F; Abramoff, Michael D; Lee, Kyungmoo; Colijn, Johanna M; Buitendijk, Gabriëlle H S; Klaver, Caroline C W; Roorda, Austin; Lujan, Brandon J

2015-07-01

Off-axis acquisition of spectral domain optical coherence tomography (SDOCT) images has been shown to increase total retinal thickness (TRT) measurements. We analyzed the reproducibility of TRT measurements obtained using either the retinal pigment epithelium (RPE) or Bruch's membrane as reference surfaces in off-axis scans intentionally acquired through multiple pupil positions. Five volumetric SDOCT scans of the macula were obtained from one eye of 25 normal subjects. One scan was acquired through a central pupil position, while subsequent scans were acquired through four peripheral pupil positions. The internal limiting membrane, the RPE, and Bruch's membrane were segmented using automated approaches. These volumes were registered to each other and the TRT was evaluated in 9 Early Treatment of Diabetic Retinopathy Study (ETDRS) regions. The reproducibility of the TRT obtained using the RPE was computed using the mean difference, coefficient of variation (CV), and the intraclass correlation coefficient (ICC), and compared to those obtained using Bruch's membrane as the reference surface. A secondary set of 1545 SDOCT scans was also analyzed in order to gauge the incidence of off-axis scans in a typical acquisition environment. The photoreceptor tips were dimmer in off-axis images, which affected the RPE segmentation. The overall mean TRT difference and CV obtained using the RPE were 7.04 ± 4.31 μm and 1.46%, respectively, whereas Bruch's membrane was 1.16 ± 1.00 μm and 0.32%, respectively. The ICCs at the subfoveal TRT were 0.982 and 0.999, respectively. Forty-one percent of the scans in the secondary set showed large tilts (> 6%). RPE segmentation is confounded by its proximity to the interdigitation zone, a structure strongly affected by the optical Stiles-Crawford effect. Bruch's membrane, however, is unaffected leading to a more robust segmentation that is less dependent upon pupil position. The way in which OCT images are acquired can independently affect the accuracy of automated retinal thickness measurements. Assessment of scan angle in a clinical dataset demonstrates that off-axis scans are common, which emphasizes the need for caution when relying on automated thickness parameters when this component of scan acquisition is not controlled for.

The Fermi Gamma-Ray Space Telescope, Exploding Stars, Neutron Stars, and Black Holes

NASA Technical Reports Server (NTRS)

Thompson, David J.

2010-01-01

Since August, 2008, the Fermi Gamma-ray Space Telescope has been scanning the sky, producing a full-sky image every three hours. These cosmic gamma-rays come from extreme astrophysical phenomena, many related to exploding stars (supernovae) or what these explosions leave behind: supernova remnants, neutron stars, and black holes. This talk uses sample Fermi results, plus simple demonstrations, to illustrate the exotic properties of these endpoints of stellar evolution.

Segmentation of Planar Surfaces from Laser Scanning Data Using the Magnitude of Normal Position Vector for Adaptive Neighborhoods.

PubMed

Kim, Changjae; Habib, Ayman; Pyeon, Muwook; Kwon, Goo-rak; Jung, Jaehoon; Heo, Joon

2016-01-22

Diverse approaches to laser point segmentation have been proposed since the emergence of the laser scanning system. Most of these segmentation techniques, however, suffer from limitations such as sensitivity to the choice of seed points, lack of consideration of the spatial relationships among points, and inefficient performance. In an effort to overcome these drawbacks, this paper proposes a segmentation methodology that: (1) reduces the dimensions of the attribute space; (2) considers the attribute similarity and the proximity of the laser point simultaneously; and (3) works well with both airborne and terrestrial laser scanning data. A neighborhood definition based on the shape of the surface increases the homogeneity of the laser point attributes. The magnitude of the normal position vector is used as an attribute for reducing the dimension of the accumulator array. The experimental results demonstrate, through both qualitative and quantitative evaluations, the outcomes' high level of reliability. The proposed segmentation algorithm provided 96.89% overall correctness, 95.84% completeness, a 0.25 m overall mean value of centroid difference, and less than 1° of angle difference. The performance of the proposed approach was also verified with a large dataset and compared with other approaches. Additionally, the evaluation of the sensitivity of the thresholds was carried out. In summary, this paper proposes a robust and efficient segmentation methodology for abstraction of an enormous number of laser points into plane information.

Segmentation of Planar Surfaces from Laser Scanning Data Using the Magnitude of Normal Position Vector for Adaptive Neighborhoods

PubMed Central

Kim, Changjae; Habib, Ayman; Pyeon, Muwook; Kwon, Goo-rak; Jung, Jaehoon; Heo, Joon

2016-01-01

Diverse approaches to laser point segmentation have been proposed since the emergence of the laser scanning system. Most of these segmentation techniques, however, suffer from limitations such as sensitivity to the choice of seed points, lack of consideration of the spatial relationships among points, and inefficient performance. In an effort to overcome these drawbacks, this paper proposes a segmentation methodology that: (1) reduces the dimensions of the attribute space; (2) considers the attribute similarity and the proximity of the laser point simultaneously; and (3) works well with both airborne and terrestrial laser scanning data. A neighborhood definition based on the shape of the surface increases the homogeneity of the laser point attributes. The magnitude of the normal position vector is used as an attribute for reducing the dimension of the accumulator array. The experimental results demonstrate, through both qualitative and quantitative evaluations, the outcomes’ high level of reliability. The proposed segmentation algorithm provided 96.89% overall correctness, 95.84% completeness, a 0.25 m overall mean value of centroid difference, and less than 1° of angle difference. The performance of the proposed approach was also verified with a large dataset and compared with other approaches. Additionally, the evaluation of the sensitivity of the thresholds was carried out. In summary, this paper proposes a robust and efficient segmentation methodology for abstraction of an enormous number of laser points into plane information. PMID:26805849

A method for smoothing segmented lung boundary in chest CT images

NASA Astrophysics Data System (ADS)

Yim, Yeny; Hong, Helen

2007-03-01

To segment low density lung regions in chest CT images, most of methods use the difference in gray-level value of pixels. However, radiodense pulmonary vessels and pleural nodules that contact with the surrounding anatomy are often excluded from the segmentation result. To smooth lung boundary segmented by gray-level processing in chest CT images, we propose a new method using scan line search. Our method consists of three main steps. First, lung boundary is extracted by our automatic segmentation method. Second, segmented lung contour is smoothed in each axial CT slice. We propose a scan line search to track the points on lung contour and find rapidly changing curvature efficiently. Finally, to provide consistent appearance between lung contours in adjacent axial slices, 2D closing in coronal plane is applied within pre-defined subvolume. Our method has been applied for performance evaluation with the aspects of visual inspection, accuracy and processing time. The results of our method show that the smoothness of lung contour was considerably increased by compensating for pulmonary vessels and pleural nodules.

Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules

PubMed

K, Jalal Deen; R, Ganesan; A, Merline

2017-07-27

Objective: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. Methods: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. In the conventional methods using Markov–Gibbs Random Field (MGRF) model the required regions of interest (ROI) are identified. Result: The results of proposed FCM and CNN based process are compared with the results obtained from the conventional method using MGRF model. The results illustrate that the proposed method can able to segment the various kinds of complex multimodal medical images precisely. Conclusion: However, in this paper, to obtain an exact boundary of the regions, every empirical dispersion of the image is computed by Fuzzy C-Means Clustering segmentation. A classification process based on the Convolutional Neural Network (CNN) classifier is accomplished to distinguish the normal tissue and the abnormal tissue. The experimental evaluation is done using the Interstitial Lung Disease (ILD) database. Creative Commons Attribution License

Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules

PubMed Central

K, Jalal Deen; R, Ganesan; A, Merline

2017-01-01

Objective: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. Methods: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. In the conventional methods using Markov–Gibbs Random Field (MGRF) model the required regions of interest (ROI) are identified. Result: The results of proposed FCM and CNN based process are compared with the results obtained from the conventional method using MGRF model. The results illustrate that the proposed method can able to segment the various kinds of complex multimodal medical images precisely. Conclusion: However, in this paper, to obtain an exact boundary of the regions, every empirical dispersion of the image is computed by Fuzzy C-Means Clustering segmentation. A classification process based on the Convolutional Neural Network (CNN) classifier is accomplished to distinguish the normal tissue and the abnormal tissue. The experimental evaluation is done using the Interstitial Lung Disease (ILD) database. PMID:28749127

Spatial context learning approach to automatic segmentation of pleural effusion in chest computed tomography images

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Casas, Rafael; Linguraru, Marius G.

2016-03-01

Pleural effusion is an abnormal collection of fluid within the pleural cavity. Excessive accumulation of pleural fluid is an important bio-marker for various illnesses, including congestive heart failure, pneumonia, metastatic cancer, and pulmonary embolism. Quantification of pleural effusion can be indicative of the progression of disease as well as the effectiveness of any treatment being administered. Quantification, however, is challenging due to unpredictable amounts and density of fluid, complex topology of the pleural cavity, and the similarity in texture and intensity of pleural fluid to the surrounding tissues in computed tomography (CT) scans. Herein, we present an automated method for the segmentation of pleural effusion in CT scans based on spatial context information. The method consists of two stages: first, a probabilistic pleural effusion map is created using multi-atlas segmentation. The probabilistic map assigns a priori probabilities to the presence of pleural uid at every location in the CT scan. Second, a statistical pattern classification approach is designed to annotate pleural regions using local descriptors based on a priori probabilities, geometrical, and spatial features. Thirty seven CT scans from a diverse patient population containing confirmed cases of minimal to severe amounts of pleural effusion were used to validate the proposed segmentation method. An average Dice coefficient of 0.82685 and Hausdorff distance of 16.2155 mm was obtained.

Cloning and sequence analysis of complementary DNA encoding an aberrantly rearranged human T-cell gamma chain.

PubMed Central

Dialynas, D P; Murre, C; Quertermous, T; Boss, J M; Leiden, J M; Seidman, J G; Strominger, J L

1986-01-01

Complementary DNA (cDNA) encoding a human T-cell gamma chain has been cloned and sequenced. At the junction of the variable and joining regions, there is an apparent deletion of two nucleotides in the human cDNA sequence relative to the murine gamma-chain cDNA sequence, resulting simultaneously in the generation of an in-frame stop codon and in a translational frameshift. For this reason, the sequence presented here encodes an aberrantly rearranged human T-cell gamma chain. There are several surprising differences between the deduced human and murine gamma-chain amino acid sequences. These include poor homology in the variable region, poor homology in a discrete segment of the constant region precisely bounded by the expected junctions of exon CII, and the presence in the human sequence of five potential sites for N-linked glycosylation. Images PMID:3458221

Abdomen and spinal cord segmentation with augmented active shape models.

PubMed

Xu, Zhoubing; Conrad, Benjamin N; Baucom, Rebeccah B; Smith, Seth A; Poulose, Benjamin K; Landman, Bennett A

2016-07-01

Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework. Using AASM, landmark updates are optimized globally via a region-based LS evolution applied on the probability map generated from MALF. This augmentation effectively extends the searching range of correspondent landmarks while reducing sensitivity to the image contexts and improves the segmentation robustness. We propose the AASM framework as a two-dimensional segmentation technique targeting structures with one axis of regularity. We apply AASM approach to abdomen CT and spinal cord (SC) MR segmentation challenges. On 20 CT scans, the AASM segmentation of the whole abdominal wall enables the subcutaneous/visceral fat measurement, with high correlation to the measurement derived from manual segmentation. On 28 3T MR scans, AASM yields better performances than other state-of-the-art approaches in segmenting white/gray matter in SC.

Automated segmentation of intraretinal layers from macular optical coherence tomography images

NASA Astrophysics Data System (ADS)

Haeker, Mona; Sonka, Milan; Kardon, Randy; Shah, Vinay A.; Wu, Xiaodong; Abràmoff, Michael D.

2007-03-01

Commercially-available optical coherence tomography (OCT) systems (e.g., Stratus OCT-3) only segment and provide thickness measurements for the total retina on scans of the macula. Since each intraretinal layer may be affected differently by disease, it is desirable to quantify the properties of each layer separately. Thus, we have developed an automated segmentation approach for the separation of the retina on (anisotropic) 3-D macular OCT scans into five layers. Each macular series consisted of six linear radial scans centered at the fovea. Repeated series (up to six, when available) were acquired for each eye and were first registered and averaged together, resulting in a composite image for each angular location. The six surfaces defining the five layers were then found on each 3-D composite image series by transforming the segmentation task into that of finding a minimum-cost closed set in a geometric graph constructed from edge/regional information and a priori-determined surface smoothness and interaction constraints. The method was applied to the macular OCT scans of 12 patients with unilateral anterior ischemic optic neuropathy (corresponding to 24 3-D composite image series). The boundaries were independently defined by two human experts on one raw scan of each eye. Using the average of the experts' tracings as a reference standard resulted in an overall mean unsigned border positioning error of 6.7 +/- 4.0 μm, with five of the six surfaces showing significantly lower mean errors than those computed between the two observers (p < 0.05, pixel size of 50 × 2 μm).

The geometrical precision of virtual bone models derived from clinical computed tomography data for forensic anthropology.

PubMed

Colman, Kerri L; Dobbe, Johannes G G; Stull, Kyra E; Ruijter, Jan M; Oostra, Roelof-Jan; van Rijn, Rick R; van der Merwe, Alie E; de Boer, Hans H; Streekstra, Geert J

2017-07-01

Almost all European countries lack contemporary skeletal collections for the development and validation of forensic anthropological methods. Furthermore, legal, ethical and practical considerations hinder the development of skeletal collections. A virtual skeletal database derived from clinical computed tomography (CT) scans provides a potential solution. However, clinical CT scans are typically generated with varying settings. This study investigates the effects of image segmentation and varying imaging conditions on the precision of virtual modelled pelves. An adult human cadaver was scanned using varying imaging conditions, such as scanner type and standard patient scanning protocol, slice thickness and exposure level. The pelvis was segmented from the various CT images resulting in virtually modelled pelves. The precision of the virtual modelling was determined per polygon mesh point. The fraction of mesh points resulting in point-to-point distance variations of 2 mm or less (95% confidence interval (CI)) was reported. Colour mapping was used to visualise modelling variability. At almost all (>97%) locations across the pelvis, the point-to-point distance variation is less than 2 mm (CI = 95%). In >91% of the locations, the point-to-point distance variation was less than 1 mm (CI = 95%). This indicates that the geometric variability of the virtual pelvis as a result of segmentation and imaging conditions rarely exceeds the generally accepted linear error of 2 mm. Colour mapping shows that areas with large variability are predominantly joint surfaces. Therefore, results indicate that segmented bone elements from patient-derived CT scans are a sufficiently precise source for creating a virtual skeletal database.

The control and data acquisition structure for the GAMMA-400 space gamma-telescope

NASA Astrophysics Data System (ADS)

Arkhangelskiy, Andrey

2016-07-01

The GAMMA-400 space project is intended for precision investigation of the cosmic gamma-emission in the energy band from keV region up to several TeV, electrons and positrons fluxes from ˜~1~GeV up to ˜~10~TeV and high energy cosmic-ray nuclei fluxes. A description of the control and data acquisition structure for gamma-telescope involved in the GAMMA 400 space project is given. The technical capabilities of all specialized equipment providing the functioning of the scientific instrumentation and satellite support systems are unified in a single structure. Control of the scientific instruments is maintained using one-time pulse radio commands and program commands transmitted via onboard control system and scientific data acquisition system. Up to 100~GByte of data per day can be transferred to the ground segment of the project. The correctness of the proposed and implemented structure, engineering solutions and electronic elemental base selection has been verified experimentally with the scientific complex prototype in the laboratory conditions.

An Approach for Reducing the Error Rate in Automated Lung Segmentation

PubMed Central

Gill, Gurman; Beichel, Reinhard R.

2016-01-01

Robust lung segmentation is challenging, especially when tens of thousands of lung CT scans need to be processed, as required by large multi-center studies. The goal of this work was to develop and assess a method for the fusion of segmentation results from two different methods to generate lung segmentations that have a lower failure rate than individual input segmentations. As basis for the fusion approach, lung segmentations generated with a region growing and model-based approach were utilized. The fusion result was generated by comparing input segmentations and selectively combining them using a trained classification system. The method was evaluated on a diverse set of 204 CT scans of normal and diseased lungs. The fusion approach resulted in a Dice coefficient of 0.9855 ± 0.0106 and showed a statistically significant improvement compared to both input segmentation methods. In addition, the failure rate at different segmentation accuracy levels was assessed. For example, when requiring that lung segmentations must have a Dice coefficient of better than 0.97, the fusion approach had a failure rate of 6.13%. In contrast, the failure rate for region growing and model-based methods was 18.14% and 15.69%, respectively. Therefore, the proposed method improves the quality of the lung segmentations, which is important for subsequent quantitative analysis of lungs. Also, to enable a comparison with other methods, results on the LOLA11 challenge test set are reported. PMID:27447897

Superpixel guided active contour segmentation of retinal layers in OCT volumes

NASA Astrophysics Data System (ADS)

Bai, Fangliang; Gibson, Stuart J.; Marques, Manuel J.; Podoleanu, Adrian

2018-03-01

Retinal OCT image segmentation is a precursor to subsequent medical diagnosis by a clinician or machine learning algorithm. In the last decade, many algorithms have been proposed to detect retinal layer boundaries and simplify the image representation. Inspired by the recent success of superpixel methods for pre-processing natural images, we present a novel framework for segmentation of retinal layers in OCT volume data. In our framework, the region of interest (e.g. the fovea) is located using an adaptive-curve method. The cell layer boundaries are then robustly detected firstly using 1D superpixels, applied to A-scans, and then fitting active contours in B-scan images. Thereafter the 3D cell layer surfaces are efficiently segmented from the volume data. The framework was tested on healthy eye data and we show that it is capable of segmenting up to 12 layers. The experimental results imply the effectiveness of proposed method and indicate its robustness to low image resolution and intrinsic speckle noise.

METHOD AND MEANS FOR RECOGNIZING COMPLEX PATTERNS

DOEpatents

Hough, P.V.C.

1962-12-18

This patent relates to a method and means for recognizing a complex pattern in a picture. The picture is divided into framelets, each framelet being sized so that any segment of the complex pattern therewithin is essentially a straight line. Each framelet is scanned to produce an electrical pulse for each point scanned on the segment therewithin. Each of the electrical pulses of each segment is then transformed into a separate strnight line to form a plane transform in a pictorial display. Each line in the plane transform of a segment is positioned laterally so that a point on the line midway between the top and the bottom of the pictorial display occurs at a distance from the left edge of the pictorial display equal to the distance of the generating point in the segment from the left edge of the framelet. Each line in the plane transform of a segment is inclined in the pictorial display at an angle to the vertical whose tangent is proportional to the vertical displacement of the generating point in the segment from the center of the framelet. The coordinate position of the point of intersection of the lines in the pictorial display for each segment is determined and recorded. The sum total of said recorded coordinate positions being representative of the complex pattern. (AEC)

Dual Contrast CT Method Enables Diagnostics of Cartilage Injuries and Degeneration Using a Single CT Image.

PubMed

Saukko, Annina E A; Honkanen, Juuso T J; Xu, Wujun; Väänänen, Sami P; Jurvelin, Jukka S; Lehto, Vesa-Pekka; Töyräs, Juha

2017-12-01

Cartilage injuries may be detected using contrast-enhanced computed tomography (CECT) by observing variations in distribution of anionic contrast agent within cartilage. Currently, clinical CECT enables detection of injuries and related post-traumatic degeneration based on two subsequent CT scans. The first scan allows segmentation of articular surfaces and lesions while the latter scan allows evaluation of tissue properties. Segmentation of articular surfaces from the latter scan is difficult since the contrast agent diffusion diminishes the image contrast at surfaces. We hypothesize that this can be overcome by mixing anionic contrast agent (ioxaglate) with bismuth oxide nanoparticles (BINPs) too large to diffuse into cartilage, inducing a high contrast at the surfaces. Here, a dual contrast method employing this mixture is evaluated by determining the depth-wise X-ray attenuation profiles in intact, enzymatically degraded, and mechanically injured osteochondral samples (n = 3 × 10) using a microCT immediately and at 45 min after immersion in contrast agent. BiNPs were unable to diffuse into cartilage, producing high contrast at articular surfaces. Ioxaglate enabled the detection of enzymatic and mechanical degeneration. In conclusion, the dual contrast method allowed detection of injuries and degeneration simultaneously with accurate cartilage segmentation using a single scan conducted at 45 min after contrast agent administration.

A new pulsed laser deposition technique: scanning multi-component pulsed laser deposition method.

PubMed

Fischer, D; de la Fuente, G F; Jansen, M

2012-04-01

The scanning multi-component pulsed laser deposition (PLD) method realizes uniform depositions of desired coatings by a modified pulsed laser deposition process, preferably with a femto-second laser-system. Multi-component coatings (single or multilayered) are thus deposited onto substrates via laser induced ablation of segmented targets. This is achieved via horizontal line-scanning of a focused laser beam over a uniformly moving target's surface. This process allows to deposit the desired composition of the coating simultaneously, starting from the different segments of the target and adjusting the scan line as a function of target geometry. The sequence and thickness of multilayers can easily be adjusted by target architecture and motion, enabling inter/intra layer concentration gradients and thus functional gradient coatings. This new, simple PLD method enables the achievement of uniform, large-area coatings. Case studies were performed with segmented targets containing aluminum, titanium, and niobium. Under the laser irradiation conditions applied, all three metals were uniformly ablated. The elemental composition within the rough coatings obtained was fixed by the scanned area to Ti-Al-Nb = 1:1:1. Crystalline aluminum, titanium, and niobium were found to coexist side by side at room temperature within the substrate, without alloy formation up to 600 °C. © 2012 American Institute of Physics

SU-F-J-166: Volumetric Spatial Distortions Comparison for 1.5 Tesla Versus 3 Tesla MRI for Gamma Knife Radiosurgery Scans Using Frame Marker Fusion and Co-Registration Modes

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

Neyman, G

Purpose: To compare typical volumetric spatial distortions for 1.5 Tesla versus 3 Tesla MRI Gamma Knife radiosurgery scans in the frame marker fusion and co-registration frame-less modes. Methods: Quasar phantom by Modus Medical Devices Inc. with GRID image distortion software was used for measurements of volumetric distortions. 3D volumetric T1 weighted scans of the phantom were produced on 1.5 T Avanto and 3 T Skyra MRI Siemens scanners. The analysis was done two ways: for scans with localizer markers from the Leksell frame and relatively to the phantom only (simulated co-registration technique). The phantom grid contained a total of 2002more » vertices or control points that were used in the assessment of volumetric geometric distortion for all scans. Results: Volumetric mean absolute spatial deviations relatively to the frame localizer markers for 1.5 and 3 Tesla machine were: 1.39 ± 0.15 and 1.63 ± 0.28 mm with max errors of 1.86 and 2.65 mm correspondingly. Mean 2D errors from the Gamma Plan were 0.3 and 1.0 mm. For simulated co-registration technique the volumetric mean absolute spatial deviations relatively to the phantom for 1.5 and 3 Tesla machine were: 0.36 ± 0.08 and 0.62 ± 0.13 mm with max errors of 0.57 and 1.22 mm correspondingly. Conclusion: Volumetric spatial distortions are lower for 1.5 Tesla versus 3 Tesla MRI machines localized with markers on frames and significantly lower for co-registration techniques with no frame localization. The results show the advantage of using co-registration technique for minimizing MRI volumetric spatial distortions which can be especially important for steep dose gradient fields typically used in Gamma Knife radiosurgery. Consultant for Elekta AB.« less

The Photosensitivity of Rhodopsin Bleaching and Light-Induced Increases of Fundus Reflectance in Mice Measured In Vivo With Scanning Laser Ophthalmoscopy

PubMed Central

Zhang, Pengfei; Goswami, Mayank; Zawadzki, Robert J.; Pugh, Edward N.

2016-01-01

Purpose To quantify bleaching-induced changes in fundus reflectance in the mouse retina. Methods Light reflected from the fundus of albino (Balb/c) and pigmented (C57Bl/6J) mice was measured with a multichannel scanning laser ophthalmoscopy optical coherence tomography (SLO-OCT) optical system. Serial scanning of small retinal regions was used for bleaching rhodopsin and measuring reflectance changes. Results Serial scanning generated a saturating reflectance increase centered at 501 nm with a photosensitivity of 1.4 × 10−8 per molecule μm2 in both strains, 2-fold higher than expected were irradiance at the rod outer segment base equal to that at the retinal surface. The action spectrum of the reflectance increase corresponds to the absorption spectrum of mouse rhodopsin in situ. Spectra obtained before and after bleaching were fitted with a model of fundus reflectance, quantifying contributions from loss of rhodopsin absorption with bleaching, absorption by oxygenated hemoglobin (HbO2) in the choroid (Balb/c), and absorption by melanin (C57Bl/6J). Both mouse strains exhibited light-induced broadband reflectance changes explained as bleaching-induced reflectivity increases at photoreceptor inner segment/outer segment (IS/OS) junctions and OS tips. Conclusions The elevated photosensitivity of rhodopsin bleaching in vivo is explained by waveguide condensing of light in propagation from rod inner segment (RIS) to rod outer segment (ROS). The similar photosensitivity of rhodopsin in the two strains reveals that little light backscattered from the sclera can enter the ROS. The bleaching-induced increases in reflectance at the IS/OS junctions and OS tips resemble results previously reported in human cones, but are ascribed to rods due to their 30/1 predominance over cones in mice and to the relatively minor amount of cone M-opsin in the regions scanned. PMID:27403994

Spinal anaesthesia with gamma hydroxybutyrate. A study in a rat model.

PubMed

Chanimov, M; Bahar, M; Cohen, M L; Brenner, R; Koifman, I; Grinshpon, Y

1999-05-01

Gamma hydroxybutyric acid, a central inhibitory neurotransmitter and a cerebral metabolite of gamma-aminobutyric acid, is present in high concentrations in the mammalian hypothalamus and basal ganglia. Its sodium salt gamma hydroxybutyrate has been effectively used as an intravenous anaesthetic agent, and as an oral sedative, and in the management of the alcohol withdrawal syndrome. In an animal model, using 72 Wistar strain rats allocated to one of six groups of 12 animals each, with implanted lumbar intrathecal catheters, we examined whether gamma hydroxybutyrate, 20% 40 microL (32 mg kg-1) administered alone or combined with fentanyl, gamma hydroxybutyrate 20% 20 microL (16 mg kg-1), fentanyl 0.005% 20 microL (4 mg kg-1) as an intrathecal bolus, provides intraoperative anaesthesia, comparable with that produced by intrathecal lignocaine. We demonstrated that gamma hydroxybutyrate, given by an intrathecal bolus in the rat model, produced reversible segmental antinociception, together with muscular relaxation of the abdominal wall and rear limbs. This is accompanied by moderate sedation without haemodynamic or respiratory depression. This agent may thus be promising for use as a spinal anaesthetic drug.

Influence of therapeutic radiation on polycaprolactone and polyurethane biomaterials.

PubMed

Cooke, Shelley L; Whittington, Abby R

2016-03-01

Biomedical polymers are exposed in vivo to ionizing radiation as implants, coatings and bystander materials. High levels of ionizing radiation (e.g. X-ray and gamma) have been reported to cause degradation and/or cross-linking in many polymers. This pilot study sought to determine causes of failure, by investigating how therapeutic radiation affects two different porous polymeric scaffolds: polycaprolactone (PCL) and polyurethane (PU). PCL is a bioresorbable material used in biomedical devices (e.g., dentistry, internal fixation devices and targeted drug delivery capsules). PU is commonly used in medical applications (e.g., coatings for pacemakers, tissue expanders, catheter tubing and wound dressings). PU was specifically fabricated to be a non-degradable polymer in this study. Porous scaffolds, fabricated using solvent casting and/or salt leeching techniques, were placed in phosphate buffered saline (PBS, pH=7.4) and exposed to typical cancer radiotherapy. A total dose of 50 Gy was broken into 25 doses over an eleven-week period. Collected PBS was tested for polymer leachants and degradation products using Gas Chromatography Mass Spectroscopy (GC-MS), results revealed no analyzable leachants from either polymer. Scaffolds were characterized using Environmental Scanning Electron Microscopy, Size-exclusion chromatography (SEC), Differential Scanning Calorimetry (DSC) and Fourier Transform Infrared Spectroscopy (FTIR). No gross visual changes were observed in either polymer, however PU exhibited microstructure changes after irradiation. Increased number average molecular weight and weight average molecular weight in PCL and PU were observed after irradiation, indicating crosslinking. PU displayed an increase in intrinsic viscosity that further confirms increased crosslinking. PCL and PU showed decreases in crystallinity after irradiation, and PU crystallinity shifted from long-range-order hard segments to short-range-order hard segments after irradiation. Results from both PCL and PU suggest changes in polymer backbones. This preliminary study suggests that therapeutic radiation doses cause both degradation and crosslinking in PCL and PU. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Brezovich, I; Wu, X; Popple, R

Purpose: To test spatial and dosimetric accuracy of small cranial target irradiation based on 1.5 T MRI scans using static arcs with MLC-defined fields Methods: A plastic (PMMA) phantom simulating a small brain lesion was mounted on a GammaKnife headframe equipped with MRI localizer. The lesion was a 3 mm long, 3.175 mm diameter cylindrical cavity filled with MRI contrast. Radiochromic film passing through the cavity was marked with pin pricks at the cavity center. The cavity was contoured on an MRI image and fused with CT to simulate treatment of a lesion not visible on CT. The transfer ofmore » the target to CT involved registering the MRI contrast cannels of the localizer that were visible on both modalities. Treatments were planned to deliver 800 cGy to the cavity center using multiple static arcs with 5.0×2.4 mm MLC-defined fields. The phantom was aligned on a STx accelerator by registering the conebeam CT with the planning CT. Films from coronal and sagittal planes were scanned and evaluated using ImageJ software Results: Geographic errors in treatment based on 1.5 T scans agreed within 0.33, −0.27 and 1.21 mm in the vertical, lateral and longitudinal dimensions, respectively. The doses delivered to the cavity center were 7.2% higher than planned. The dose distributions were similar to those of a GammaKnife. Conclusion: Radiation can be delivered with an accelerator at mm accuracy to small cranial targets based on 1.5 MRI scans fused to CTs using a standard GammaKnife headframe and MRI localizer. MLC-defined static arcs produce isodose lines very similar to the GammaKnife.« less

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.

Accuracy of DXA scanning of the thoracic spine: cadaveric studies comparing BMC, areal BMD and geometric estimates of volumetric BMD against ash weight and CT measures of bone volume.

PubMed

Sran, Meena M; Khan, Karim M; Keiver, Kathy; Chew, Jason B; McKay, Heather A; Oxland, Thomas R

2005-12-01

Biomechanical studies of the thoracic spine often scan cadaveric segments by dual energy X-ray absorptiometry (DXA) to obtain measures of bone mass. Only one study has reported the accuracy of lateral scans of thoracic vertebral bodies. The accuracy of DXA scans of thoracic spine segments and of anterior-posterior (AP) thoracic scans has not been investigated. We have examined the accuracy of AP and lateral thoracic DXA scans by comparison with ash weight, the gold-standard for measuring bone mineral content (BMC). We have also compared three methods of estimating volumetric bone mineral density (vBMD) with a novel standard-ash weight (g)/bone volume (cm3) as measured by computed tomography (CT). Twelve T5-T8 spine segments were scanned with DXA (AP and lateral) and CT. The T6 vertebrae were excised, the posterior elements removed and then the vertebral bodies were ashed in a muffle furnace. We proposed a new method of estimating vBMD and compared it with two previously published methods. BMC values from lateral DXA scans displayed the strongest correlation with ash weight (r=0.99) and were on average 12.8% higher (p<0.001). As expected, BMC (AP or lateral) was more strongly correlated with ash weight than areal bone mineral density (aBMD; AP: r=0.54, or lateral: r=0.71) or estimated vBMD. Estimates of vBMD with either of the three methods were strongly and similarly correlated with volumetric BMD calculated by dividing ash weight by CT-derived volume. These data suggest that readily available DXA scanning is an appropriate surrogate measure for thoracic spine bone mineral and that the lateral scan might be the scan method of choice.

Pixelized Measurement of (99m)Tc-HDP Micro Particles Formed in Gamma Correction Phantom Pinhole Scan: a Reference Study.

PubMed

Jung, Joo-Young; Cheon, Gi Jeong; Lee, Yun-Sang; Ha, Seunggyun; Chae, Mi-Hye; Chung, Yong-An; Yoon, Do Kyun; Bahk, Yong-Whee

2016-09-01

Currently, traumatic bone diseases are diagnosed by assessing the micro (99m)Tc-hydroxymethylene diphosphonate (HDP) uptake in injured trabeculae with ongoing osteoneogenesis demonstrated by gamma correction pinhole scan (GCPS). However, the mathematic size quantification of micro-uptake is not yet available. We designed and performed this phantom-based study to set up an in-vitro model of the mathematical calculation of micro-uptake by the pixelized measurement. The micro (99m)Tc-HDP deposits used in this study were spontaneously formed both in a large standard flood and small house-made dish phantoms. The processing was as follows: first, phantoms were flooded with distilled water and (99m)Tc-HDP was therein injected to induce micro (99m)Tc-HDP deposition; second, the deposits were scanned using parallel-hole and pinhole collimator to generally survey (99m)Tc-HDP deposition pattern; and third, the scans underwent gamma correction (GC) to discern individual deposits for size measurement. In original naïve scans, tracer distribution was simply nebulous in appearance and, hence, could not be measured. Impressively, however, GCPS could discern individual micro deposits so that they were calculated by pixelized measurement. Phantoms naturally formed micro (99m)Tc-HDP deposits that are analogous to (99m)Tc-HDP uptake on in-vivo bone scan. The smallest one we measured was 0.414 mm. Flooded phantoms and therein injected (99m)Tc-HDP form nebulous micro (99m)Tc-HDP deposits that are rendered discernible by GCPB and precisely calculable using pixelized measurement. This method can be used for precise quantitative and qualitative diagnosis of bone and joint diseases at the trabecular level.

Graph cuts and neural networks for segmentation and porosity quantification in Synchrotron Radiation X-ray μCT of an igneous rock sample.

PubMed

Meneses, Anderson Alvarenga de Moura; Palheta, Dayara Bastos; Pinheiro, Christiano Jorge Gomes; Barroso, Regina Cely Rodrigues

2018-03-01

X-ray Synchrotron Radiation Micro-Computed Tomography (SR-µCT) allows a better visualization in three dimensions with a higher spatial resolution, contributing for the discovery of aspects that could not be observable through conventional radiography. The automatic segmentation of SR-µCT scans is highly valuable due to its innumerous applications in geological sciences, especially for morphology, typology, and characterization of rocks. For a great number of µCT scan slices, a manual process of segmentation would be impractical, either for the time expended and for the accuracy of results. Aiming the automatic segmentation of SR-µCT geological sample images, we applied and compared Energy Minimization via Graph Cuts (GC) algorithms and Artificial Neural Networks (ANNs), as well as the well-known K-means and Fuzzy C-Means algorithms. The Dice Similarity Coefficient (DSC), Sensitivity and Precision were the metrics used for comparison. Kruskal-Wallis and Dunn's tests were applied and the best methods were the GC algorithms and ANNs (with Levenberg-Marquardt and Bayesian Regularization). For those algorithms, an approximate Dice Similarity Coefficient of 95% was achieved. Our results confirm the possibility of usage of those algorithms for segmentation and posterior quantification of porosity of an igneous rock sample SR-µCT scan. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Effects of a Tantalum Addition on the Morphological and Compositional Evolutions of a Model Ni-AL-Cr Superalloy

NASA Technical Reports Server (NTRS)

Booth-Morrison, Christopher; Seidman, David N.; Noebe, Ronald D.

2008-01-01

The effects of a 2.0 at.% addition of Ta to a model Ni-Al-Cr superalloy aged at 1073 K are assessed using scanning electron microscopy and atom-probe tomography. The addition of Ta results in appreciable strengthening, and the morphology is found to evolve from a bimodal distribution of spheroidal precipitates, to cuboidal precipitates aligned along the elastically soft <001>-type directions. Tantalum is observed to partition preferentially to the gamma -precipitate phase and decreases the mobility of Ni in the gamma- matrix sufficiently to cause an accumulation of Ni on the gamma-matrix side of the gamma -precipitate/gamma-matrix heterophase interface.

The DAMPE experiment: 2 year in orbit

NASA Astrophysics Data System (ADS)

Gargano, Fabio; DAMPE Collaboration

2017-12-01

The DArk Matter Particle Explorer (DAMPE) is a space mission within the strategic framework of the Chinese Academy of Sciences, resulting from a collaboration of Chinese, Italian, and Swiss institutions, and is a new addition to the growing number of particle detectors in space. It was successfully launched in December 2015 and has commenced nominal science operations since shortly after launch. Lending technologies from its predecessors such as AMS and Fermi-LAT, it features a powerful segmented electromagnetic calorimeter which thanks to its 31 radiation lengths enables the study of charged cosmic rays in the energy domain of up to 100 TeV and gamma rays of up to 10 TeV. The calorimeter is complemented with a silicon-tungsten tracker converter which yields a comparable angular resolution as current space-borne pair-conversion gamma-ray detectors. In addition, the detector features a top anti-coincidence shield made of segmented silicon plastic scintillators and a boron-doped plastic scintillator on the bottom of the instrument to detect delayed neutrons arising from cosmic ray protons showering in the calorimeter. An overview of the mission and a summary of the latest results in the domain of charged cosmic rays, gamma rays and heavy ions will be presented.

Positive and negative regulation of V(D)J recombination by the E2A proteins.

PubMed

Bain, G; Romanow, W J; Albers, K; Havran, W L; Murre, C

1999-01-18

A key feature of B and T lymphocyte development is the generation of antigen receptors through the rearrangement and assembly of the germline variable (V), diversity (D), and joining (J) gene segments. However, the mechanisms responsible for regulating developmentally ordered gene rearrangements are largely unknown. Here we show that the E2A gene products are essential for the proper coordinated temporal regulation of V(D)J rearrangements within the T cell receptor (TCR) gamma and delta loci. Specifically, we show that E2A is required during adult thymocyte development to inhibit rearrangements to the gamma and delta V regions that normally recombine almost exclusively during fetal thymocyte development. The continued rearrangement of the fetal Vgamma3 gene segment in E2A-deficient adult thymocytes correlates with increased levels of Vgamma3 germline transcripts and increased levels of double-stranded DNA breaks at the recombination signal sequence bordering Vgamma3. Additionally, rearrangements to a number of Vgamma and Vdelta gene segments used predominantly during adult development are significantly reduced in E2A-deficient thymocytes. Interestingly, at distinct stages of T lineage development, both the increased and decreased rearrangement of particular Vdelta gene segments is highly sensitive to the dosage of the E2A gene products, suggesting that the concentration of the E2A proteins is rate limiting for the recombination reaction involving these Vdelta regions.

A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

PubMed

Zhao, Xiaomei; Wu, Yihong; Song, Guidong; Li, Zhenye; Zhang, Yazhuo; Fan, Yong

2018-01-01

Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices. Particularly, we train 3 segmentation models using 2D image patches and slices obtained in axial, coronal and sagittal views respectively, and combine them to segment brain tumors using a voting based fusion strategy. Our method could segment brain images slice-by-slice, much faster than those based on image patches. We have evaluated our method based on imaging data provided by the Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015 and BRATS 2016. The experimental results have demonstrated that our method could build a segmentation model with Flair, T1c, and T2 scans and achieve competitive performance as those built with Flair, T1, T1c, and T2 scans. Copyright © 2017 Elsevier B.V. All rights reserved.

Sagittal and transversal plane deformity in thoracic scoliosis.

PubMed

Kotwicki, Tomasz

2002-01-01

The aim of the study was to assess the sagittal and transversal plane deformity of the spine in thoracic scoliosis by the mean of 3-D radiographic analysis. 46 patients admitted for surgery for thoracic idiopathic scoliosis underwent preoperative radiographic assessment. All patients presented the same pattern of the coronal plane deformity: single right thoracic curve (Lenke 1, King 3). Neither lumbar nor proximal thoracic structural curve were present. The Cobb angle varied from 41gamma to 77 gamma (mean 55,4 gamma +/- 8,6 gamma). Long cassette standing antero-posterior and lateral radiographs were analysed. Three-dimensional reconstruction with Rachis 91TM software was performed for each pair of radiographs. The following parameters were assessed: sagittal thoracic Cobb angle (Th4-Th12), upper thoracic kyphosis angle (Th5-Th8), lower thoracic kyphosis angle (Th9-Th12), superior and inferior hemi-curve sagittal angles, lumbar lordosis, sacral slope, sacral incidence, vertebral plate index, segmental vertebral axial rotation throughout the thoracic and lumbar spine. Results showed great variability of parameters assessed. The non-harmonious distribution of kyphosis was demonstrated in the thoracic spine. Local Th9-Th12 hypokyphosis and adjacent local Th5-Th8 hyperkyphosis constitute the most typical sagittal pathologies. So called normokyphotic curves were composed of one hyperkyphotic and one hypokyphotic zone. Th1-Th4 segment revealed two patterns of segmental rotation distribution: a purely compensatory curve with no vertebral axial rotation or a rotated curve presenting the morphology intermediate between Lenke 1 and Lenke 2 types (or King 3 and King 5). curves presenting the same coronal plane deformity differ in their morphology assessed in the two other planes; global thoracic kyphosis angle is a misleading parameter because it covers hypo- and hyperkyphotic zones; local distal thoracic (Th9-Th12) hypokyphosis is present in idiopathic thoracic scoliosis.

Automatic detection of new tumors and tumor burden evaluation in longitudinal liver CT scan studies.

PubMed

Vivanti, R; Szeskin, A; Lev-Cohain, N; Sosna, J; Joskowicz, L

2017-11-01

Radiological longitudinal follow-up of liver tumors in CT scans is the standard of care for disease progression assessment and for liver tumor therapy. Finding new tumors in the follow-up scan is essential to determine malignancy, to evaluate the total tumor burden, and to determine treatment efficacy. Since new tumors are typically small, they may be missed by examining radiologists. We describe a new method for the automatic detection and segmentation of new tumors in longitudinal liver CT studies and for liver tumors burden quantification. Its inputs are the baseline and follow-up CT scans, the baseline tumors delineation, and a tumor appearance prior model. Its outputs are the new tumors segmentations in the follow-up scan, the tumor burden quantification in both scans, and the tumor burden change. Our method is the first comprehensive method that is explicitly designed to find new liver tumors. It integrates information from the scans, the baseline known tumors delineations, and a tumor appearance prior model in the form of a global convolutional neural network classifier. Unlike other deep learning-based methods, it does not require large tagged training sets. Our experimental results on 246 tumors, of which 97 were new tumors, from 37 longitudinal liver CT studies with radiologist approved ground-truth segmentations, yields a true positive new tumors detection rate of 86 versus 72% with stand-alone detection, and a tumor burden volume overlap error of 16%. New tumors detection and tumor burden volumetry are important for diagnosis and treatment. Our new method enables a simplified radiologist-friendly workflow that is potentially more accurate and reliable than the existing one by automatically and accurately following known tumors and detecting new tumors in the follow-up scan.

TU-A-12A-01: Consistency of Lung Expansion and Contraction During Respiration: Implications for Quantitative Imaging

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

Patton, T; Du, K; Bayouth, J

Purpose: Four-dimensional computed tomography (4DCT) can be used to evaluate longitudinal changes in pulmonary function. The sensitivity of such measurements to identify function change may be improved with reproducible breathing patterns. The purpose of this study was to determine if inhale was more consistent than exhale, i.e., lung expansion during inhalation compared to lung contraction during exhalation. Methods: Repeat 4DCT image data acquired within a short time interval from 8 patients. Using a tissue volume preserving deformable image registration algorithm, Jacobian ventilation maps in two scanning sessions were computed and compared on the same coordinate for reproducibility analysis. Equivalent lungmore » volumes (ELV) were used for 5 subjects and equivalent title volumes (ETV) for the 3 subjects who experienced a baseline shift between scans. In addition, gamma pass rate was calculated from a modified gamma index evaluation between two ventilation maps, using acceptance criterions of 2mm distance-to-agreement and 5% ventilation difference. The gamma pass rates were then compared using paired t-test to determine if there was a significant difference. Results: Inhalation was more reproducible than exhalation. In the 5 ELV subjects 78.5% of the lung voxels met the gamma criteria for expansion during inhalation when comparing the two scans, while significantly fewer (70.9% of the lung voxels) met the gamma criteria for contraction during exhalation (p = .027). In the 8 total subjects analyzed the average gamma pass rate for expansion during inhalation was 75.2% while for contraction during exhalation it was 70.3%; which trended towards significant (p = .064). Conclusion: This work implies inhalation is more reproducible than exhalation, when equivalent respiratory volumes are considered. The reason for this difference is unknown. Longitudinal investigation of pulmonary function change based on inhalation images appears appropriate for Jacobian-based measure of lung tissue expansion. NIH Grant: R01 CA166703.« less

Anterior Eye Imaging with Optical Coherence Tomography

NASA Astrophysics Data System (ADS)

Huang, David; Li, Yan; Tang, Maolong

The development of corneal and anterior segment optical coherence tomography (OCT) technology has advanced rapidly in recently years. The scan geometry and imaging wavelength are both important choices to make in designing anterior segment OCT systems. Rectangular scan geometry offers the least image distortion and is now used in most anterior OCT systems. The wavelength of OCT light source affects resolution and penetration. An optimal choice of the OCT imaging wavelength (840, 1,050, or 1,310 nm) depends on the application of interest. Newer generation Fourier-domain OCT technology can provide scan speed 100-1000 times faster than the time-domain technology. Various commercial anterior OCT systems are available on the market. A wide spectrum of diagnostic and surgical applications using anterior segment OCT had been investigated, including mapping of corneal and epithelial thicknesses, keratoconus screening, measuring corneal refractive power, corneal surgery planning and evaluation in LASIK, intracorneal ring implantation, assessment of angle closure glaucoma, anterior chamber biometry and intraocular lens implants, intraocular lens power calculation, and eye bank donor cornea screening.

Hierarchical parsing and semantic navigation of full body CT data

NASA Astrophysics Data System (ADS)

Seifert, Sascha; Barbu, Adrian; Zhou, S. Kevin; Liu, David; Feulner, Johannes; Huber, Martin; Suehling, Michael; Cavallaro, Alexander; Comaniciu, Dorin

2009-02-01

Whole body CT scanning is a common diagnosis technique for discovering early signs of metastasis or for differential diagnosis. Automatic parsing and segmentation of multiple organs and semantic navigation inside the body can help the clinician in efficiently obtaining accurate diagnosis. However, dealing with the large amount of data of a full body scan is challenging and techniques are needed for the fast detection and segmentation of organs, e.g., heart, liver, kidneys, bladder, prostate, and spleen, and body landmarks, e.g., bronchial bifurcation, coccyx tip, sternum, lung tips. Solving the problem becomes even more challenging if partial body scans are used, where not all organs are present. We propose a new approach to this problem, in which a network of 1D and 3D landmarks is trained to quickly parse the 3D CT data and estimate which organs and landmarks are present as well as their most probable locations and boundaries. Using this approach, the segmentation of seven organs and detection of 19 body landmarks can be obtained in about 20 seconds with state-of-the-art accuracy and has been validated on 80 CT full or partial body scans.

Breast segmentation in MR images using three-dimensional spiral scanning and dynamic programming

NASA Astrophysics Data System (ADS)

Jiang, Luan; Lian, Yanyun; Gu, Yajia; Li, Qiang

2013-03-01

Magnetic resonance (MR) imaging has been widely used for risk assessment and diagnosis of breast cancer in clinic. To develop a computer-aided diagnosis (CAD) system, breast segmentation is the first important and challenging task. The accuracy of subsequent quantitative measurement of breast density and abnormalities depends on accurate definition of the breast area in the images. The purpose of this study is to develop and evaluate a fully automated method for accurate segmentation of breast in three-dimensional (3-D) MR images. A fast method was developed to identify bounding box, i.e., the volume of interest (VOI), for breasts. A 3-D spiral scanning method was used to transform the VOI of each breast into a single two-dimensional (2-D) generalized polar-coordinate image. Dynamic programming technique was applied to the transformed 2-D image for delineating the "optimal" contour of the breast. The contour of the breast in the transformed 2-D image was utilized to reconstruct the segmentation results in the 3-D MR images using interpolation and lookup table. The preliminary results on 17 cases show that the proposed method can obtain accurate segmentation of the breast based on subjective observation. By comparing with the manually delineated region of 16 breasts in 8 cases, an overlap index of 87.6% +/- 3.8% (mean +/- SD), and a volume agreement of 93.4% +/- 4.5% (mean +/- SD) were achieved, respectively. It took approximately 3 minutes for our method to segment the breast in an MR scan of 256 slices.

A group contribution method for associating chain molecules based on the statistical associating fluid theory (SAFT-gamma).

PubMed

Lymperiadis, Alexandros; Adjiman, Claire S; Galindo, Amparo; Jackson, George

2007-12-21

A predictive group-contribution statistical associating fluid theory (SAFT-gamma) is developed by extending the molecular-based SAFT-VR equation of state [A. Gil-Villegas et al. J. Chem. Phys. 106, 4168 (1997)] to treat heteronuclear molecules which are formed from fused segments of different types. Our models are thus a heteronuclear generalization of the standard models used within SAFT, comparable to the optimized potentials for the liquid state OPLS models commonly used in molecular simulation; an advantage of our SAFT-gamma over simulation is that an algebraic description for the thermodynamic properties of the model molecules can be developed. In our SAFT-gamma approach, each functional group in the molecule is modeled as a united-atom spherical (square-well) segment. The different groups are thus characterized by size (diameter), energy (well depth) and range parameters representing the dispersive interaction, and by shape factor parameters (which denote the extent to which each group contributes to the overall molecular properties). For associating groups a number of bonding sites are included on the segment: in this case the site types, the number of sites of each type, and the appropriate association energy and range parameters also have to be specified. A number of chemical families (n-alkanes, branched alkanes, n-alkylbenzenes, mono- and diunsaturated hydrocarbons, and n-alkan-1-ols) are treated in order to assess the quality of the SAFT-gamma description of the vapor-liquid equilibria and to estimate the parameters of various functional groups. The group parameters for the functional groups present in these compounds (CH(3), CH(2), CH(3)CH, ACH, ACCH(2), CH(2)=, CH=, and OH) together with the unlike energy parameters between groups of different types are obtained from an optimal description of the pure component phase equilibria. The approach is found to describe accurately the vapor-liquid equilibria with an overall %AAD of 3.60% for the vapor pressure and 0.86% for the saturated liquid density. The fluid phase equilibria of some larger compounds comprising these groups, which are not included in the optimization database and some binary mixtures are examined to confirm the predictive capability of the SAFT-gamma approach. A key advantage of our method is that the binary interaction parameters between groups can be estimated directly from an examination of pure components alone. This means that as a first approximation the fluid-phase equilibria of mixtures of compounds comprising the groups considered can be predicted without the need for any adjustment of the binary interaction parameters (which is common in other approaches). The special case of molecular models comprising tangentially bonded (all-atom and united-atom) segments is considered separately; we comment on the adequacy of such models in representing the properties of real molecules.

Effects of MAR-M247 substrate (modified) composition on coating oxidation coating/substrate interdiffusion. M.S. Thesis. Final Report; [protective coatings for hot section components of gas turbine engines

NASA Technical Reports Server (NTRS)

Pilsner, B. H.

1985-01-01

The effects of gamma+gamma' Mar-M247 substrate composition on gamma+beta Ni-Cr-Al-Zr coating oxidation and coating/substrate interdiffusion were evaluated. These results were also compared to a prior study for a Ni-Cr-Al-Zr coated gamma Ni-Cr-Al substrate with equivalent Al and Cr atomic percentages. Cyclic oxidation behavior at 1130 C was investigated using change in weight curves. Concentration/distance profiles were measured for Al, Cr, Co, W, and Ta. The surface oxides were examined by X-ray diffraction and scanning electron microscopy. The results indicate that variations of Ta and C concentrations in the substrate do not affect oxidation resistance, while additions of grain boundary strengthening elements (Zr, Hf, B) increase oxidation resistance. In addition, the results indicate that oxidation phenomena in gamma+beta/gamma+gamma' Mar-M247 systems have similar characteristics to the l gamma+beta/gamma Ni-Cr-Al system.

Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras

PubMed Central

Morris, Mark; Sellers, William I.

2015-01-01

Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints. PMID:25780778

Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras.

PubMed

Peyer, Kathrin E; Morris, Mark; Sellers, William I

2015-01-01

Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints.

A statistical pixel intensity model for segmentation of confocal laser scanning microscopy images.

PubMed

Calapez, Alexandre; Rosa, Agostinho

2010-09-01

Confocal laser scanning microscopy (CLSM) has been widely used in the life sciences for the characterization of cell processes because it allows the recording of the distribution of fluorescence-tagged macromolecules on a section of the living cell. It is in fact the cornerstone of many molecular transport and interaction quantification techniques where the identification of regions of interest through image segmentation is usually a required step. In many situations, because of the complexity of the recorded cellular structures or because of the amounts of data involved, image segmentation either is too difficult or inefficient to be done by hand and automated segmentation procedures have to be considered. Given the nature of CLSM images, statistical segmentation methodologies appear as natural candidates. In this work we propose a model to be used for statistical unsupervised CLSM image segmentation. The model is derived from the CLSM image formation mechanics and its performance is compared to the existing alternatives. Results show that it provides a much better description of the data on classes characterized by their mean intensity, making it suitable not only for segmentation methodologies with known number of classes but also for use with schemes aiming at the estimation of the number of classes through the application of cluster selection criteria.

Abdomen and spinal cord segmentation with augmented active shape models

PubMed Central

Xu, Zhoubing; Conrad, Benjamin N.; Baucom, Rebeccah B.; Smith, Seth A.; Poulose, Benjamin K.; Landman, Bennett A.

2016-01-01

Abstract. Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework. Using AASM, landmark updates are optimized globally via a region-based LS evolution applied on the probability map generated from MALF. This augmentation effectively extends the searching range of correspondent landmarks while reducing sensitivity to the image contexts and improves the segmentation robustness. We propose the AASM framework as a two-dimensional segmentation technique targeting structures with one axis of regularity. We apply AASM approach to abdomen CT and spinal cord (SC) MR segmentation challenges. On 20 CT scans, the AASM segmentation of the whole abdominal wall enables the subcutaneous/visceral fat measurement, with high correlation to the measurement derived from manual segmentation. On 28 3T MR scans, AASM yields better performances than other state-of-the-art approaches in segmenting white/gray matter in SC. PMID:27610400

Novel multimodality segmentation using level sets and Jensen-Rényi divergence

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

Markel, Daniel, E-mail: daniel.markel@mail.mcgill.ca; Zaidi, Habib; Geneva Neuroscience Center, Geneva University, CH-1205 Geneva

2013-12-15

Purpose: Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography. Methods: A steepest gradient ascent optimization method is used in conjunction with the JRD and a level set activemore » contour to iteratively evolve a contour to partition an image based on statistical divergence of the intensity histograms. The algorithm is evaluated using PET scans of pharyngolaryngeal squamous cell carcinoma with the corresponding histological reference. The multimodality extension of the algorithm is evaluated using 22 PET/CT scans of patients with lung carcinoma and a physical phantom scanned under varying image quality conditions. Results: The average concordance index (CI) of the JRD segmentation of the PET images was 0.56 with an average classification error of 65%. The segmentation of the lung carcinoma images had a maximum diameter relative error of 63%, 19.5%, and 14.8% when using CT, PET, and combined PET/CT images, respectively. The estimated maximal diameters of the gross tumor volume (GTV) showed a high correlation with the macroscopically determined maximal diameters, with aR{sup 2} value of 0.85 and 0.88 using the PET and PET/CT images, respectively. Results from the physical phantom show that the JRD is more robust to image noise compared to mutual information and region growing. Conclusions: The JRD has shown improved noise tolerance compared to mutual information for the purpose of PET image segmentation. Presented is a flexible framework for multimodal image segmentation that can incorporate a large number of inputs efficiently for IGART.« less

Novel multimodality segmentation using level sets and Jensen-Rényi divergence.

PubMed

Markel, Daniel; Zaidi, Habib; El Naqa, Issam

2013-12-01

Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography. A steepest gradient ascent optimization method is used in conjunction with the JRD and a level set active contour to iteratively evolve a contour to partition an image based on statistical divergence of the intensity histograms. The algorithm is evaluated using PET scans of pharyngolaryngeal squamous cell carcinoma with the corresponding histological reference. The multimodality extension of the algorithm is evaluated using 22 PET/CT scans of patients with lung carcinoma and a physical phantom scanned under varying image quality conditions. The average concordance index (CI) of the JRD segmentation of the PET images was 0.56 with an average classification error of 65%. The segmentation of the lung carcinoma images had a maximum diameter relative error of 63%, 19.5%, and 14.8% when using CT, PET, and combined PET/CT images, respectively. The estimated maximal diameters of the gross tumor volume (GTV) showed a high correlation with the macroscopically determined maximal diameters, with a R(2) value of 0.85 and 0.88 using the PET and PET/CT images, respectively. Results from the physical phantom show that the JRD is more robust to image noise compared to mutual information and region growing. The JRD has shown improved noise tolerance compared to mutual information for the purpose of PET image segmentation. Presented is a flexible framework for multimodal image segmentation that can incorporate a large number of inputs efficiently for IGART.

Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images

PubMed Central

Jain, Saurabh; Sima, Diana M.; Ribbens, Annemie; Cambron, Melissa; Maertens, Anke; Van Hecke, Wim; De Mey, Johan; Barkhof, Frederik; Steenwijk, Martijn D.; Daams, Marita; Maes, Frederik; Van Huffel, Sabine; Vrenken, Hugo; Smeets, Dirk

2015-01-01

The location and extent of white matter lesions on magnetic resonance imaging (MRI) are important criteria for diagnosis, follow-up and prognosis of multiple sclerosis (MS). Clinical trials have shown that quantitative values, such as lesion volumes, are meaningful in MS prognosis. Manual lesion delineation for the segmentation of lesions is, however, time-consuming and suffers from observer variability. In this paper, we propose MSmetrix, an accurate and reliable automatic method for lesion segmentation based on MRI, independent of scanner or acquisition protocol and without requiring any training data. In MSmetrix, 3D T1-weighted and FLAIR MR images are used in a probabilistic model to detect white matter (WM) lesions as an outlier to normal brain while segmenting the brain tissue into grey matter, WM and cerebrospinal fluid. The actual lesion segmentation is performed based on prior knowledge about the location (within WM) and the appearance (hyperintense on FLAIR) of lesions. The accuracy of MSmetrix is evaluated by comparing its output with expert reference segmentations of 20 MRI datasets of MS patients. Spatial overlap (Dice) between the MSmetrix and the expert lesion segmentation is 0.67 ± 0.11. The intraclass correlation coefficient (ICC) equals 0.8 indicating a good volumetric agreement between the MSmetrix and expert labelling. The reproducibility of MSmetrix' lesion volumes is evaluated based on 10 MS patients, scanned twice with a short interval on three different scanners. The agreement between the first and the second scan on each scanner is evaluated through the spatial overlap and absolute lesion volume difference between them. The spatial overlap was 0.69 ± 0.14 and absolute total lesion volume difference between the two scans was 0.54 ± 0.58 ml. Finally, the accuracy and reproducibility of MSmetrix compare favourably with other publicly available MS lesion segmentation algorithms, applied on the same data using default parameter settings. PMID:26106562

Whole abdominal wall segmentation using augmented active shape models (AASM) with multi-atlas label fusion and level set

NASA Astrophysics Data System (ADS)

Xu, Zhoubing; Baucom, Rebeccah B.; Abramson, Richard G.; Poulose, Benjamin K.; Landman, Bennett A.

2016-03-01

The abdominal wall is an important structure differentiating subcutaneous and visceral compartments and intimately involved with maintaining abdominal structure. Segmentation of the whole abdominal wall on routinely acquired computed tomography (CT) scans remains challenging due to variations and complexities of the wall and surrounding tissues. In this study, we propose a slice-wise augmented active shape model (AASM) approach to robustly segment both the outer and inner surfaces of the abdominal wall. Multi-atlas label fusion (MALF) and level set (LS) techniques are integrated into the traditional ASM framework. The AASM approach globally optimizes the landmark updates in the presence of complicated underlying local anatomical contexts. The proposed approach was validated on 184 axial slices of 20 CT scans. The Hausdorff distance against the manual segmentation was significantly reduced using proposed approach compared to that using ASM, MALF, and LS individually. Our segmentation of the whole abdominal wall enables the subcutaneous and visceral fat measurement, with high correlation to the measurement derived from manual segmentation. This study presents the first generic algorithm that combines ASM, MALF, and LS, and demonstrates practical application for automatically capturing visceral and subcutaneous fat volumes.

Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks

PubMed Central

Huo, Yuankai; Xu, Zhoubing; Bao, Shunxing; Bermudez, Camilo; Plassard, Andrew J.; Liu, Jiaqi; Yao, Yuang; Assad, Albert; Abramson, Richard G.; Landman, Bennett A.

2018-01-01

Spleen volume estimation using automated image segmentation technique may be used to detect splenomegaly (abnormally enlarged spleen) on Magnetic Resonance Imaging (MRI) scans. In recent years, Deep Convolutional Neural Networks (DCNN) segmentation methods have demonstrated advantages for abdominal organ segmentation. However, variations in both size and shape of the spleen on MRI images may result in large false positive and false negative labeling when deploying DCNN based methods. In this paper, we propose the Splenomegaly Segmentation Network (SSNet) to address spatial variations when segmenting extraordinarily large spleens. SSNet was designed based on the framework of image-to-image conditional generative adversarial networks (cGAN). Specifically, the Global Convolutional Network (GCN) was used as the generator to reduce false negatives, while the Markovian discriminator (PatchGAN) was used to alleviate false positives. A cohort of clinically acquired 3D MRI scans (both T1 weighted and T2 weighted) from patients with splenomegaly were used to train and test the networks. The experimental results demonstrated that a mean Dice coefficient of 0.9260 and a median Dice coefficient of 0.9262 using SSNet on independently tested MRI volumes of patients with splenomegaly.

Performance of a segmented HPGe detector at KRISS.

PubMed

Han, Jubong; Lee, K B; Lee, Jong-Man; Lee, S H; Park, Tae Soon; Oh, J S

2018-04-01

A 24 segmented HPGe coaxial detector was set up with a digitized data acquisition system (DAQ). The DAQ was composed of a digitizer (5 × 10 7 sampling/s), a Field-Programmable Gate Array (FPGA), and a real time operating system. The Full Width Half Maximum (FWHM), rise time, signal characteristics, and spectra of a 137 Cs source were evaluated. The data were processed using an in-house developed gamma-ray tracking system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Longitudinal Analysis of Mouse SDOCT Volumes

PubMed Central

Antony, Bhavna J.; Carass, Aaron; Lang, Andrew; Kim, Byung-Jin; Zack, Donald J.; Prince, Jerry L.

2017-01-01

Spectral-domain optical coherence tomography (SDOCT), in addition to its routine clinical use in the diagnosis of ocular diseases, has begun to find increasing use in animal studies. Animal models are frequently used to study disease mechanisms as well as to test drug efficacy. In particular, SDOCT provides the ability to study animals longitudinally and non-invasively over long periods of time. However, the lack of anatomical landmarks makes the longitudinal scan acquisition prone to inconsistencies in orientation. Here, we propose a method for the automated registration of mouse SDOCT volumes. The method begins by accurately segmenting the blood vessels and the optic nerve head region in the scans using a pixel classification approach. The segmented vessel maps from follow-up scans were registered using an iterative closest point (ICP) algorithm to the baseline scan to allow for the accurate longitudinal tracking of thickness changes. Eighteen SDOCT volumes from a light damage model study were used to train a random forest utilized in the pixel classification step. The area under the curve (AUC) in a leave-one-out study for the retinal blood vessels and the optic nerve head (ONH) was found to be 0.93 and 0.98, respectively. The complete proposed framework, the retinal vasculature segmentation and the ICP registration, was applied to a secondary set of scans obtained from a light damage model. A qualitative assessment of the registration showed no registration failures. PMID:29138527

Longitudinal analysis of mouse SDOCT volumes

NASA Astrophysics Data System (ADS)

Antony, Bhavna J.; Carass, Aaron; Lang, Andrew; Kim, Byung-Jin; Zack, Donald J.; Prince, Jerry L.

2017-03-01

Spectral-domain optical coherence tomography (SDOCT), in addition to its routine clinical use in the diagnosis of ocular diseases, has begun to fund increasing use in animal studies. Animal models are frequently used to study disease mechanisms as well as to test drug efficacy. In particular, SDOCT provides the ability to study animals longitudinally and non-invasively over long periods of time. However, the lack of anatomical landmarks makes the longitudinal scan acquisition prone to inconsistencies in orientation. Here, we propose a method for the automated registration of mouse SDOCT volumes. The method begins by accurately segmenting the blood vessels and the optic nerve head region in the scans using a pixel classification approach. The segmented vessel maps from follow-up scans were registered using an iterative closest point (ICP) algorithm to the baseline scan to allow for the accurate longitudinal tracking of thickness changes. Eighteen SDOCT volumes from a light damage model study were used to train a random forest utilized in the pixel classification step. The area under the curve (AUC) in a leave-one-out study for the retinal blood vessels and the optic nerve head (ONH) was found to be 0.93 and 0.98, respectively. The complete proposed framework, the retinal vasculature segmentation and the ICP registration, was applied to a secondary set of scans obtained from a light damage model. A qualitative assessment of the registration showed no registration failures.

Origin of coloration in beetle scales: An optical and structural investigation

NASA Astrophysics Data System (ADS)

Nagi, Ramneet Kaur

In this thesis the origin of angle-independent yellowish-green coloration of the exoskeleton of a beetle was studied. The beetle chosen was a weevil with the Latin name Eupholus chevrolati. The origin of this weevil's coloration was investigated by optical and structural characterization techniques, including optical microscopy, scanning electron microscopy imaging and focused ion beam milling, combined with three-dimensional modeling and photonic band structure calculations. Furthermore, using color theory the pixel-like coloring of the weevil's exoskeleton was investigated and an interesting additive color mixing scheme was discovered. For optical studies, a microreflectance microscopy/spectroscopy set-up was optimized. This set-up allowed not only for imaging of individual colored exoskeleton domains with sizes ˜2-10 μm, but also for obtaining reflection spectra of these micrometer-sized domains. Spectra were analyzed in terms of reflection intensity and wavelength position and shape of the reflection features. To find the origin of these colored exoskeleton spots, a combination of focused ion beam milling and scanning electron microscopy imaging was employed. A three-dimensional photonic crystal in the form of a face-centered cubic lattice of ABC-stacked air cylinders in a biopolymeric cuticle matrix was discovered. Our photonic band structure calculations revealed the existence of different sets of stop-gaps for the lattice constant of 360, 380 and 400 nm in the main lattice directions, Gamma-L, Gamma-X, Gamma-U, Gamma-W and Gamma-K. In addition, scanning electron microscopy images were compared to the specific directional-cuts through the constructed face-centered cubic lattice-based model and the optical micrographs of individual domains to determine the photonic structure corresponding to the different lattice directions. The three-dimensional model revealed stop-gaps in the Gamma-L, Gamma-W and Gamma-K directions. Finally, the coloration of the weevil as perceived by an unaided human eye was represented (mathematically) on the xy-chromaticity diagram, based on XYZ color space developed by CIE (Commission Internationale de l'Eclairage), using the micro-reflectance spectroscopy measurements. The results confirmed the additive mixing of various colors produced by differently oriented photonic crystal domains present in the weevil's exoskeleton scales, as a reason for the angle-independent dull yellowish-green coloration of the weevil E. chevrolati.

Growth, structural, optical and thermal properties of gamma-glycine crystal.

PubMed

Balakrishnan, T; Babu, R Ramesh; Ramamurthi, K

2008-04-01

Single crystals of gamma-glycine were grown from a mixture of glycine, water and lithium bromide. Single crystal X-ray diffraction analysis confirmed the growth of gamma-glycine phase. Presence of various functional groups of gamma-glycine was identified by FTIR spectrum. Optical absorbance spectrum recorded in the wavelength range of UV-vis-NIR revealed that this crystal has good optical transparency in the range 250-1500 nm. Vickers microhardness values were estimated on the prominent (100) face. Thermogravimetric and differential scanning calorimetric analyses were carried out to study the thermal properties of gamma-glycine. Second harmonic generation efficiency of the crystal measured by Kurtz's powder method using Nd:YAG laser is about three times that of KDP.

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS).

PubMed

Menze, Bjoern H; Jakab, Andras; Bauer, Stefan; Kalpathy-Cramer, Jayashree; Farahani, Keyvan; Kirby, Justin; Burren, Yuliya; Porz, Nicole; Slotboom, Johannes; Wiest, Roland; Lanczi, Levente; Gerstner, Elizabeth; Weber, Marc-André; Arbel, Tal; Avants, Brian B; Ayache, Nicholas; Buendia, Patricia; Collins, D Louis; Cordier, Nicolas; Corso, Jason J; Criminisi, Antonio; Das, Tilak; Delingette, Hervé; Demiralp, Çağatay; Durst, Christopher R; Dojat, Michel; Doyle, Senan; Festa, Joana; Forbes, Florence; Geremia, Ezequiel; Glocker, Ben; Golland, Polina; Guo, Xiaotao; Hamamci, Andac; Iftekharuddin, Khan M; Jena, Raj; John, Nigel M; Konukoglu, Ender; Lashkari, Danial; Mariz, José Antonió; Meier, Raphael; Pereira, Sérgio; Precup, Doina; Price, Stephen J; Raviv, Tammy Riklin; Reza, Syed M S; Ryan, Michael; Sarikaya, Duygu; Schwartz, Lawrence; Shin, Hoo-Chang; Shotton, Jamie; Silva, Carlos A; Sousa, Nuno; Subbanna, Nagesh K; Szekely, Gabor; Taylor, Thomas J; Thomas, Owen M; Tustison, Nicholas J; Unal, Gozde; Vasseur, Flor; Wintermark, Max; Ye, Dong Hye; Zhao, Liang; Zhao, Binsheng; Zikic, Darko; Prastawa, Marcel; Reyes, Mauricio; Van Leemput, Koen

2015-10-01

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients-manually annotated by up to four raters-and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

PubMed Central

Jakab, Andras; Bauer, Stefan; Kalpathy-Cramer, Jayashree; Farahani, Keyvan; Kirby, Justin; Burren, Yuliya; Porz, Nicole; Slotboom, Johannes; Wiest, Roland; Lanczi, Levente; Gerstner, Elizabeth; Weber, Marc-André; Arbel, Tal; Avants, Brian B.; Ayache, Nicholas; Buendia, Patricia; Collins, D. Louis; Cordier, Nicolas; Corso, Jason J.; Criminisi, Antonio; Das, Tilak; Delingette, Hervé; Demiralp, Çağatay; Durst, Christopher R.; Dojat, Michel; Doyle, Senan; Festa, Joana; Forbes, Florence; Geremia, Ezequiel; Glocker, Ben; Golland, Polina; Guo, Xiaotao; Hamamci, Andac; Iftekharuddin, Khan M.; Jena, Raj; John, Nigel M.; Konukoglu, Ender; Lashkari, Danial; Mariz, José António; Meier, Raphael; Pereira, Sérgio; Precup, Doina; Price, Stephen J.; Raviv, Tammy Riklin; Reza, Syed M. S.; Ryan, Michael; Sarikaya, Duygu; Schwartz, Lawrence; Shin, Hoo-Chang; Shotton, Jamie; Silva, Carlos A.; Sousa, Nuno; Subbanna, Nagesh K.; Szekely, Gabor; Taylor, Thomas J.; Thomas, Owen M.; Tustison, Nicholas J.; Unal, Gozde; Vasseur, Flor; Wintermark, Max; Ye, Dong Hye; Zhao, Liang; Zhao, Binsheng; Zikic, Darko; Prastawa, Marcel; Reyes, Mauricio; Van Leemput, Koen

2016-01-01

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients—manually annotated by up to four raters—and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%–85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource. PMID:25494501

Automated and real-time segmentation of suspicious breast masses using convolutional neural network

PubMed Central

Gregory, Adriana; Denis, Max; Meixner, Duane D.; Bayat, Mahdi; Whaley, Dana H.; Fatemi, Mostafa; Alizad, Azra

2018-01-01

In this work, a computer-aided tool for detection was developed to segment breast masses from clinical ultrasound (US) scans. The underlying Multi U-net algorithm is based on convolutional neural networks. Under the Mayo Clinic Institutional Review Board protocol, a prospective study of the automatic segmentation of suspicious breast masses was performed. The cohort consisted of 258 female patients who were clinically identified with suspicious breast masses and underwent clinical US scan and breast biopsy. The computer-aided detection tool effectively segmented the breast masses, achieving a mean Dice coefficient of 0.82, a true positive fraction (TPF) of 0.84, and a false positive fraction (FPF) of 0.01. By avoiding positioning of an initial seed, the algorithm is able to segment images in real time (13–55 ms per image), and can have potential clinical applications. The algorithm is at par with a conventional seeded algorithm, which had a mean Dice coefficient of 0.84 and performs significantly better (P< 0.0001) than the original U-net algorithm. PMID:29768415

Solar gamma ray monitor for OSO-H (0.3-10 MeV)

NASA Technical Reports Server (NTRS)

Chupp, E. L.; Gleske, I. U.; Forrest, D. J.

1974-01-01

A gamma ray experiment to be flown aboard the OSO-7 spacecraft is described along with a history of the development of the experiment, a description of the gamma ray detector and its operation, and a short preliminary review of the scientific information obtained during the instruments' lifetime. The gamma ray detector operated an average of 18 hours a day for approximately 15 months. The majority of the data was collected in the solar and antisolar direction, but data at right angles to the spacecraft-sun line was also accumulated. In all, at least two full scans of the celestial sphere were completed.

The Environmental Scanning Function of Public Relations Practitioners and Participation in Management Decision Making.

ERIC Educational Resources Information Center

Dozier, David M.

Focusing on the concepts of scanning (gathering information about segments of the public, their reactions to the organization, and their opinions about issues important to the organization), decision making, and roles, a study examined the relationship between environmental scanning and the participation of public relations practitioners in…

Tracheal Atresia with Segmental Esophageal Duplication: An Unusual Anatomic Arrangement.

PubMed

Gaerty, Kirsten; Thomas, Joseph T; Petersen, Scott; Tan, Edwin; Kumar, Sailesh; Gardener, Glenn; Armes, Jane

2016-01-01

An unusual anatomic configuration of segmental tracheal agenesis/atresia with esophageal duplication on autopsy in a fetus that demised in utero at 29 weeks is reported. The mother was scanned initially for a cardiac anomaly at 20 weeks and on follow-up scan at 27 weeks had polyhydramnios and underwent amnioreduction. The final autopsy diagnosis was vertebral, ano-rectal, cardiac, tracheoesophageal, renal, and limb malformations (VACTERL). We discuss the autopsy findings along with the embryological mechanisms and compare the configuration with Floyd's classification for tracheal agenesis. The difficulties in prenatal diagnosis are discussed.

Revolutionizing (robot-assisted) laparoscopic gamma tracing using a drop-in gamma probe technology

PubMed Central

van Oosterom, Matthias N; Simon, Hervé; Mengus, Laurent; Welling, Mick M; van der Poel, Henk G; van den Berg, Nynke S; van Leeuwen, Fijs WB

2016-01-01

In complex (robot-assisted) laparoscopic radioguided surgery procedures, or when low activity lesions are located nearby a high activity background, the limited maneuverability of a laparoscopic gamma probe (LGP; 4 degrees of freedom (DOF)) may hinder lesion identification. We investigated a drop-in gamma probe (DIGP) technology to be inserted via a trocar, after which the laparoscopic surgical tool at hand can pick it up and maneuver it. Phantom experiments showed that distinguishing a low objective from a high background source (1:100 ratio) was only possible with the detector faced >90° from the high background source. Signal-low-objective-to-background ratios of 3.77, 2.01 and 1.84 were found for detector angles of 90°, 135° and 180°, respectively, whereas detector angles of 0° and 45° were unable to distinguish the sources. This underlines the critical role probe positioning plays. We then focused on engineering of the gripping part for optimal DIGP pick-up with a conventional laparoscopic forceps (4 DOF) or a robotic forceps (6 DOF). DIGPs with 0°, 45°, 90°, and 135° -grip orientations were designed, and their maneuverability- and scanning direction were evaluated and compared to a conventional LGP. The maneuverability- and scanning direction of the DIGP was found highest when using the robotic forceps, with the largest effective scanning direction range obtained with the 90° -grip design (0-180° versus 0-111°, 0-140°, and 37-180° for 0°, 45° and 135° -grip designs, respectively). For the laparoscopic forceps, the scan direction directly translated from the angle of the grip design with the advantage that the 135° -gripped DIGP could be faced backwards (not possible with the conventional LGP). In the ex vivo clinical setup, the surgeon rated DIGP pick-up most convenient for the 45°-grip design. Concluding, the DIGP technology was successfully introduced. Optimization of the grip design and grasping angle of the DIGP increased its utility for (robot-assisted) laparoscopic gamma tracing. PMID:27069762

The neuromuscular system of Pycnophyes kielensis (Kinorhyncha: Allomalorhagida) investigated by confocal laser scanning microscopy.

PubMed

Altenburger, Andreas

2016-01-01

Kinorhynchs are ecdysozoan animals with a phylogenetic position close to priapulids and loriciferans. To understand the nature of segmentation within Kinorhyncha and to infer a probable ancestry of segmentation within the last common ancestor of Ecdysozoa, the musculature and the nervous system of the allomalorhagid kinorhynch Pycnophyes kielensis were investigated by use of immunohistochemistry, confocal laser scanning microscopy, and 3D reconstruction software. The kinorhynch body plan comprises 11 trunk segments. Trunk musculature consists of paired ventral and dorsal longitudinal muscles in segments 1-10 as well as dorsoventral muscles in segments 1-11. Dorsal and ventral longitudinal muscles insert on apodemes of the cuticle inside the animal within each segment. Strands of longitudinal musculature extend over segment borders in segments 1-6. In segments 7-10, the trunk musculature is confined to the segments. Musculature of the digestive system comprises a strong pharyngeal bulb with attached mouth cone muscles as well as pharyngeal bulb protractors and retractors. The musculature of the digestive system shows no sign of segmentation. Judged by the size of the pharyngeal bulb protractors and retractors, the pharyngeal bulb, as well as the introvert, is moved passively by internal pressure caused by concerted action of the dorsoventral muscles. The nervous system comprises a neuropil ring anterior to the pharyngeal bulb. Associated with the neuropil ring are flask-shaped serotonergic somata extending anteriorly and posteriorly. A ventral nerve cord is connected to the neuropil ring and runs toward the anterior until an attachment point in segment 1, and from there toward the posterior with one ganglion in segment 6. Segmentation within Kinorhyncha likely evolved from an unsegmented ancestor. This conclusion is supported by continuous trunk musculature in the anterior segments 1-6, continuous pharyngeal bulb protractors and retractors throughout the anterior segments, no sign of segmentation within the digestive system, and the absence of ganglia in most segments. The musculature shows evidence of segmentation that fit the definition of an anteroposteriorly repeated body unit only in segments 7-10.

Machine learning based brain tumour segmentation on limited data using local texture and abnormality.

PubMed

Bonte, Stijn; Goethals, Ingeborg; Van Holen, Roel

2018-05-07

Brain tumour segmentation in medical images is a very challenging task due to the large variety in tumour shape, position, appearance, scanning modalities and scanning parameters. Most existing segmentation algorithms use information from four different MRI-sequences, but since this is often not available, there is need for a method able to delineate the different tumour tissues based on a minimal amount of data. We present a novel approach using a Random Forests model combining voxelwise texture and abnormality features on a contrast-enhanced T1 and FLAIR MRI. We transform the two scans into 275 feature maps. A random forest model next calculates the probability to belong to 4 tumour classes or 5 normal classes. Afterwards, a dedicated voxel clustering algorithm provides the final tumour segmentation. We trained our method on the BraTS 2013 database and validated it on the larger BraTS 2017 dataset. We achieve median Dice scores of 40.9% (low-grade glioma) and 75.0% (high-grade glioma) to delineate the active tumour, and 68.4%/80.1% for the total abnormal region including edema. Our fully automated brain tumour segmentation algorithm is able to delineate contrast enhancing tissue and oedema with high accuracy based only on post-contrast T1-weighted and FLAIR MRI, whereas for non-enhancing tumour tissue and necrosis only moderate results are obtained. This makes the method especially suitable for high-grade glioma. Copyright © 2018 Elsevier Ltd. All rights reserved.

Automated aortic calcification detection in low-dose chest CT images

NASA Astrophysics Data System (ADS)

Xie, Yiting; Htwe, Yu Maw; Padgett, Jennifer; Henschke, Claudia; Yankelevitz, David; Reeves, Anthony P.

2014-03-01

The extent of aortic calcification has been shown to be a risk indicator for vascular events including cardiac events. We have developed a fully automated computer algorithm to segment and measure aortic calcification in low-dose noncontrast, non-ECG gated, chest CT scans. The algorithm first segments the aorta using a pre-computed Anatomy Label Map (ALM). Then based on the segmented aorta, aortic calcification is detected and measured in terms of the Agatston score, mass score, and volume score. The automated scores are compared with reference scores obtained from manual markings. For aorta segmentation, the aorta is modeled as a series of discrete overlapping cylinders and the aortic centerline is determined using a cylinder-tracking algorithm. Then the aortic surface location is detected using the centerline and a triangular mesh model. The segmented aorta is used as a mask for the detection of aortic calcification. For calcification detection, the image is first filtered, then an elevated threshold of 160 Hounsfield units (HU) is used within the aorta mask region to reduce the effect of noise in low-dose scans, and finally non-aortic calcification voxels (bony structures, calcification in other organs) are eliminated. The remaining candidates are considered as true aortic calcification. The computer algorithm was evaluated on 45 low-dose non-contrast CT scans. Using linear regression, the automated Agatston score is 98.42% correlated with the reference Agatston score. The automated mass and volume score is respectively 98.46% and 98.28% correlated with the reference mass and volume score.

Automated circumferential construction of first-order aqueous humor outflow pathways using spectral-domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Huang, Alex S.; Belghith, Akram; Dastiridou, Anna; Chopra, Vikas; Zangwill, Linda M.; Weinreb, Robert N.

2017-06-01

The purpose was to create a three-dimensional (3-D) model of circumferential aqueous humor outflow (AHO) in a living human eye with an automated detection algorithm for Schlemm's canal (SC) and first-order collector channels (CC) applied to spectral-domain optical coherence tomography (SD-OCT). Anterior segment SD-OCT scans from a subject were acquired circumferentially around the limbus. A Bayesian Ridge method was used to approximate the location of the SC on infrared confocal laser scanning ophthalmoscopic images with a cross multiplication tool developed to initiate SC/CC detection automated through a fuzzy hidden Markov Chain approach. Automatic segmentation of SC and initial CC's was manually confirmed by two masked graders. Outflow pathways detected by the segmentation algorithm were reconstructed into a 3-D representation of AHO. Overall, only <1% of images (5114 total B-scans) were ungradable. Automatic segmentation algorithm performed well with SC detection 98.3% of the time and <0.1% false positive detection compared to expert grader consensus. CC was detected 84.2% of the time with 1.4% false positive detection. 3-D representation of AHO pathways demonstrated variably thicker and thinner SC with some clear CC roots. Circumferential (360 deg), automated, and validated AHO detection of angle structures in the living human eye with reconstruction was possible.

Feasibility of Rotational Scan Ultrasound Imaging by an Angled High Frequency Transducer for the Posterior Segment of the Eye

PubMed Central

Paeng, Dong-Guk; Chang, Jin Ho; Chen, Ruimin; Humayun, Mark S.; Shung, K. Kirk

2009-01-01

High frequency ultrasound over 40 MHz has been used to image the anterior segment of the eye, but it is not suitable for the posterior segment due to the frequency-dependent attenuation of ultrasound and thus the limitation of penetration depth. This paper proposes a novel scan method to image the posterior segment of the eye with an angled high frequency (beyond 40 MHz) ultrasound needle transducer. In this method, the needle transducer is inserted into the eye through a small incision hole (∼1 mm in diameter) and rotated around the axial direction to form a cone-shaped imaging plane, allowing the spatial information of retinal vessels and diagnosis of their occlusion to be displayed. The feasibility of this novel technique was tested with images of a wire phantom, a polyimide tube, and an excised pig eye obtained by manually rotating a 40-MHz PMN-PT needle transducer with a beveled tip of 45°. From the results, we believe that rotational scan imaging will help expand the minimally invasive applications of high frequency ultrasound to other areas due to the capability of increased closeness of an angled needle transducer to structures of interest buried in other tissues. PMID:19411226

Feasibility of rotational scan ultrasound imaging by an angled high frequency transducer for the posterior segment of the eye.

PubMed

Paeng, Dong-Guk; Chang, Jin Ho; Chen, Ruimin; Humayun, Mark S; Shung, K Kirk

2009-03-01

High frequency ultrasound over 40 MHz has been used to image the anterior segment of the eye, but it is not suitable for the posterior segment due to the frequency dependent attenuation of ultrasound and thus the limitation of penetration depth. This paper proposes a novel scan method to image the posterior segment of the eye with an angled high frequency (beyond 40 MHz) ultrasound needle transducer. In this method, the needle transducer is inserted into the eye through a small incision hole (approximately 1 mm in diameter) and rotated around the axial direction to form a cone-shaped imaging plane, allowing the spatial information of retinal vessels and diagnosis of their occlusion to be displayed. The feasibility of this novel technique was tested with images of a wire phantom, a polyimide tube, and an excised pig eye obtained by manually rotating a 40-MHz PMN-PT needle transducer with a beveled tip of 45 degrees . From the results, we believe that rotational scan imaging will help expand the minimally invasive applications of high frequency ultrasound to other areas due to the capability of increased closeness of an angled needle transducer to structures of interest buried in other tissues.

Contruction and physical parameters of multiscan whole-body scanner (in Czech)

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

Silar, J.; Smidova, M.; Vacek, J.

The construction of a commercial whole-body scanner which permits scanning in the form of a photographic picture, and the distribution in the human body of the activity of gamma emitters having an energy of up to 1.3 MeV, at relatively short intervals are described. The results are presented of the measurement of physical parameters affecting the scanning possibilities of a Model No. 602 Multiscan, produced by Cyclotron Corporation. The resulting radiometric parameters are listed. The results of measurement show that the device can be used in the whole-body scanning of the distribution of the activity of gamma emitters applied inmore » routine procedures, such as 100 mu Ci of /sup 85/ Sr, with a position resolution of 25 to 50 mm in a tissue layer in a height of up to 100 mm above the Multiscan table. (INIS)« less

Automatic anatomical segmentation of the liver by separation planes

NASA Astrophysics Data System (ADS)

Boltcheva, Dobrina; Passat, Nicolas; Agnus, Vincent; Jacob-Da, Marie-Andrée, , Col; Ronse, Christian; Soler, Luc

2006-03-01

Surgical planning in oncological liver surgery is based on the location of the 8 anatomical segments according to Couinaud's definition and tumors inside these structures. The detection of the boundaries between the segments is then the first step of the preoperative planning. The proposed method, devoted to binary images of livers segmented from CT-scans, has been designed to delineate these segments. It automatically detects a set of landmarks using a priori anatomical knowledge and differential geometry criteria. These landmarks are then used to position the Couinaud's segments. Validations performed on 7 clinical cases tend to prove that the method is reliable for most of these separation planes.

Combined endeavor of Neutrosophic Set and Chan-Vese model to extract accurate liver image from CT scan.

PubMed

Siri, Sangeeta K; Latte, Mrityunjaya V

2017-11-01

Many different diseases can occur in the liver, including infections such as hepatitis, cirrhosis, cancer and over effect of medication or toxins. The foremost stage for computer-aided diagnosis of liver is the identification of liver region. Liver segmentation algorithms extract liver image from scan images which helps in virtual surgery simulation, speedup the diagnosis, accurate investigation and surgery planning. The existing liver segmentation algorithms try to extort exact liver image from abdominal Computed Tomography (CT) scan images. It is an open problem because of ambiguous boundaries, large variation in intensity distribution, variability of liver geometry from patient to patient and presence of noise. A novel approach is proposed to meet challenges in extracting the exact liver image from abdominal CT scan images. The proposed approach consists of three phases: (1) Pre-processing (2) CT scan image transformation to Neutrosophic Set (NS) and (3) Post-processing. In pre-processing, the noise is removed by median filter. The "new structure" is designed to transform a CT scan image into neutrosophic domain which is expressed using three membership subset: True subset (T), False subset (F) and Indeterminacy subset (I). This transform approximately extracts the liver image structure. In post processing phase, morphological operation is performed on indeterminacy subset (I) and apply Chan-Vese (C-V) model with detection of initial contour within liver without user intervention. This resulted in liver boundary identification with high accuracy. Experiments show that, the proposed method is effective, robust and comparable with existing algorithm for liver segmentation of CT scan images. Copyright © 2017 Elsevier B.V. All rights reserved.

Probe for contamination detection in recyclable materials

DOEpatents

Taleyarkhan, Rusi

2003-08-05

A neutron detection system for detection of contaminants contained within a bulk material during recycling includes at least one neutron generator for neutron bombardment of the bulk material, and at least one gamma ray detector for detection of gamma rays emitted by contaminants within the bulk material. A structure for analyzing gamma ray data is communicably connected to the gamma ray detector, the structure for analyzing gamma ray data adapted. The identity and concentration of contaminants in a bulk material can also be determined. By scanning the neutron beam, discrete locations within the bulk material having contaminants can be identified. A method for recycling bulk material having unknown levels of contaminants includes the steps of providing at least one neutron generator, at least one gamma ray detector, and structure for analyzing gamma ray data, irradiating the bulk material with neutrons, and then determining the presence of at least one contaminant in the bulk material from gamma rays emitted from the bulk material.

Status Report and Research Plan for Cables Harvested from Crystal River Unit 3 Nuclear Generating Plant

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

Fifield, Leonard S.

Harvested cables from operating or decommissioned nuclear power plants present an important opportunity to validate models, understanding material aging behavior, and validate characterization techniques. Crystal River Unit 3 Nuclear Generating Plant is a pressurized water reactor that was licensed to operate from 1976 to 2013. Cable segments were harvested and made available to the Light Water Reactor Sustainability research program through the Electric Power Research Institute. Information on the locations and circuits within the reactor from whence the cable segments came, cable construction, sourcing and installation information, and photographs of the cable locations prior to harvesting were provided. The cablemore » variations provided represent six of the ten most common cable insulations in the nuclear industry and experienced service usage for periods from 15 to 42 years. Subsequently, these cables constitute a valuable asset for research to understand aging behavior and measurement of nuclear cables. Received cables harvested from Crystal River Unit 3 Nuclear Generating Plant consist of low voltage, insulated conductor surrounded by jackets in lengths from 24 to 100 feet each. Cable materials will primarily be used to investigate aging under simultaneous thermal and gamma radiation exposure. Each cable insulation and jacket material will be characterized in its as-received condition, including determination of the temperatures associated with endothermic transitions in the material using differential scanning calorimetry and dynamic mechanical analysis. Temperatures for additional thermal exposure aging will be selected following the thermal analysis to avoid transitions in accelerated laboratory aging that do not occur in field conditions. Aging temperatures above thermal transitions may also be targeted to investigate the potential for artifacts in lifetime prediction from rapid accelerated aging. Total gamma doses and dose rates targeted for each material will be determined based on filling gaps in prior work, known limits of material classes and resource constraints. Experimental plans will be developed in the context of existing data for the insulation and jacket materials available in published Department of Energy and Electric Power Research Institute reports toward addressing identified knowledge gaps.« less

Patient-specific CT dosimetry calculation: a feasibility study.

PubMed

Fearon, Thomas; Xie, Huchen; Cheng, Jason Y; Ning, Holly; Zhuge, Ying; Miller, Robert W

2011-11-15

Current estimation of radiation dose from computed tomography (CT) scans on patients has relied on the measurement of Computed Tomography Dose Index (CTDI) in standard cylindrical phantoms, and calculations based on mathematical representations of "standard man". Radiation dose to both adult and pediatric patients from a CT scan has been a concern, as noted in recent reports. The purpose of this study was to investigate the feasibility of adapting a radiation treatment planning system (RTPS) to provide patient-specific CT dosimetry. A radiation treatment planning system was modified to calculate patient-specific CT dose distributions, which can be represented by dose at specific points within an organ of interest, as well as organ dose-volumes (after image segmentation) for a GE Light Speed Ultra Plus CT scanner. The RTPS calculation algorithm is based on a semi-empirical, measured correction-based algorithm, which has been well established in the radiotherapy community. Digital representations of the physical phantoms (virtual phantom) were acquired with the GE CT scanner in axial mode. Thermoluminescent dosimeter (TLDs) measurements in pediatric anthropomorphic phantoms were utilized to validate the dose at specific points within organs of interest relative to RTPS calculations and Monte Carlo simulations of the same virtual phantoms (digital representation). Congruence of the calculated and measured point doses for the same physical anthropomorphic phantom geometry was used to verify the feasibility of the method. The RTPS algorithm can be extended to calculate the organ dose by calculating a dose distribution point-by-point for a designated volume. Electron Gamma Shower (EGSnrc) codes for radiation transport calculations developed by National Research Council of Canada (NRCC) were utilized to perform the Monte Carlo (MC) simulation. In general, the RTPS and MC dose calculations are within 10% of the TLD measurements for the infant and child chest scans. With respect to the dose comparisons for the head, the RTPS dose calculations are slightly higher (10%-20%) than the TLD measurements, while the MC results were within 10% of the TLD measurements. The advantage of the algebraic dose calculation engine of the RTPS is a substantially reduced computation time (minutes vs. days) relative to Monte Carlo calculations, as well as providing patient-specific dose estimation. It also provides the basis for a more elaborate reporting of dosimetric results, such as patient specific organ dose volumes after image segmentation.

Accuracy of patient specific organ-dose estimates obtained using an automated image segmentation algorithm

NASA Astrophysics Data System (ADS)

Gilat-Schmidt, Taly; Wang, Adam; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-03-01

The overall goal of this work is to develop a rapid, accurate and fully automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using a deterministic Boltzmann Transport Equation solver and automated CT segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. The investigated algorithm uses a combination of feature-based and atlas-based methods. A multiatlas approach was also investigated. We hypothesize that the auto-segmentation algorithm is sufficiently accurate to provide organ dose estimates since random errors at the organ boundaries will average out when computing the total organ dose. To test this hypothesis, twenty head-neck CT scans were expertly segmented into nine regions. A leave-one-out validation study was performed, where every case was automatically segmented with each of the remaining cases used as the expert atlas, resulting in nineteen automated segmentations for each of the twenty datasets. The segmented regions were applied to gold-standard Monte Carlo dose maps to estimate mean and peak organ doses. The results demonstrated that the fully automated segmentation algorithm estimated the mean organ dose to within 10% of the expert segmentation for regions other than the spinal canal, with median error for each organ region below 2%. In the spinal canal region, the median error was 7% across all data sets and atlases, with a maximum error of 20%. The error in peak organ dose was below 10% for all regions, with a median error below 4% for all organ regions. The multiple-case atlas reduced the variation in the dose estimates and additional improvements may be possible with more robust multi-atlas approaches. Overall, the results support potential feasibility of an automated segmentation algorithm to provide accurate organ dose estimates.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

NASA Astrophysics Data System (ADS)

Kalinovsky, A.; Liauchuk, V.; Tarasau, A.

2017-05-01

In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For training and testing of the algorithms a domestic dataset of 338 3D CT scans of tuberculosis patients with manually labelled lesions was used. The algorithms which are based on using Deep Convolutional Networks were implemented and applied in three different ways including slice-wise lesion detection in 2D images using semantic segmentation, slice-wise lesion detection in 2D images using sliding window technique as well as straightforward detection of lesions via semantic segmentation in whole 3D CT scans. The algorithms demonstrate superior performance compared to algorithms based on conventional image analysis methods.

Morphology-based three-dimensional segmentation of coronary artery tree from CTA scans

NASA Astrophysics Data System (ADS)

Banh, Diem Phuc T.; Kyprianou, Iacovos S.; Paquerault, Sophie; Myers, Kyle J.

2007-03-01

We developed an algorithm based on a rule-based threshold framework to segment the coronary arteries from angiographic computed tomography (CTA) data. Computerized segmentation of the coronary arteries is a challenging procedure due to the presence of diverse anatomical structures surrounding the heart on cardiac CTA data. The proposed algorithm incorporates various levels of image processing and organ information including region, connectivity and morphology operations. It consists of three successive stages. The first stage involves the extraction of the three-dimensional scaffold of the heart envelope. This stage is semiautomatic requiring a reader to review the CTA scans and manually select points along the heart envelope in slices. These points are further processed using a surface spline-fitting technique to automatically generate the heart envelope. The second stage consists of segmenting the left heart chambers and coronary arteries using grayscale threshold, size and connectivity criteria. This is followed by applying morphology operations to further detach the left and right coronary arteries from the aorta. In the final stage, the 3D vessel tree is reconstructed and labeled using an Isolated Connected Threshold technique. The algorithm was developed and tested on a patient coronary artery CTA that was graciously shared by the Department of Radiology of the Massachusetts General Hospital. The test showed that our method constantly segmented the vessels above 79% of the maximum gray-level and automatically extracted 55 of the 58 coronary segments that can be seen on the CTA scan by a reader. These results are an encouraging step toward our objective of generating high resolution models of the male and female heart that will be subsequently used as phantoms for medical imaging system optimization studies.

A continuous analog of run length distributions reflecting accumulated fractionation events.

PubMed

Yu, Zhe; Sankoff, David

2016-11-11

We propose a new, continuous model of the fractionation process (duplicate gene deletion after polyploidization) on the real line. The aim is to infer how much DNA is deleted at a time, based on segment lengths for alternating deleted (invisible) and undeleted (visible) regions. After deriving a number of analytical results for "one-sided" fractionation, we undertake a series of simulations that help us identify the distribution of segment lengths as a gamma with shape and rate parameters evolving over time. This leads to an inference procedure based on observed length distributions for visible and invisible segments. We suggest extensions of this mathematical and simulation work to biologically realistic discrete models, including two-sided fractionation.

Terrestrial gamma-ray flashes in the BeppoSAX data archive

NASA Astrophysics Data System (ADS)

Ursi, A.; Guidorzi, C.; Marisaldi, M.; Sarria, D.; Frontera, F.

2017-04-01

Up to now, Terrestrial Gamma-ray Flashes (TGFs) have been mostly observed by instruments on-board satellites devoted to astrophysics: after the discovery by the BATSE/CGRO experiment in the early 90's, this elusive phenomenon has been further detected by RHESSI, by the AGILE satellite and by the Fermi space telescope. The Italian/Dutch satellite BeppoSAX (1996-2002) was one of the most important high-energy astrophysics missions, especially for what concerns the field of Gamma-Ray Bursts (GRBs). Its payload housed the Gamma-Ray Burst Monitor (GRBM), a segmented detector that could, in principle, have observed TGFs as well. Motivated by this possibility, we carried out, for the first time, a systematic search for TGFs in the BeppoSAX data archive, ending up with a sample of 12 TGF candidates. Among them, we also found a peculiar event, whose light curve characteristics may represent the signature of a mirrored Terrestrial Electron Beam (TEB).

Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Images.

PubMed

Lee, Kyungmoo; Buitendijk, Gabriëlle H S; Bogunovic, Hrvoje; Springelkamp, Henriët; Hofman, Albert; Wahle, Andreas; Sonka, Milan; Vingerling, Johannes R; Klaver, Caroline C W; Abràmoff, Michael D

2016-03-01

To automatically identify which spectral-domain optical coherence tomography (SD-OCT) scans will provide reliable automated layer segmentations for more accurate layer thickness analyses in population studies. Six hundred ninety macular SD-OCT image volumes (6.0 × 6.0 × 2.3 mm 3 ) were obtained from one eyes of 690 subjects (74.6 ± 9.7 [mean ± SD] years, 37.8% of males) randomly selected from the population-based Rotterdam Study. The dataset consisted of 420 OCT volumes with successful automated retinal nerve fiber layer (RNFL) segmentations obtained from our previously reported graph-based segmentation method and 270 volumes with failed segmentations. To evaluate the reliability of the layer segmentations, we have developed a new metric, segmentability index SI, which is obtained from a random forest regressor based on 12 features using OCT voxel intensities, edge-based costs, and on-surface costs. The SI was compared with well-known quality indices, quality index (QI), and maximum tissue contrast index (mTCI), using receiver operating characteristic (ROC) analysis. The 95% confidence interval (CI) and the area under the curve (AUC) for the QI are 0.621 to 0.805 with AUC 0.713, for the mTCI 0.673 to 0.838 with AUC 0.756, and for the SI 0.784 to 0.920 with AUC 0.852. The SI AUC is significantly larger than either the QI or mTCI AUC ( P < 0.01). The segmentability index SI is well suited to identify SD-OCT scans for which successful automated intraretinal layer segmentations can be expected. Interpreting the quantification of SD-OCT images requires the underlying segmentation to be reliable, but standard SD-OCT quality metrics do not predict which segmentations are reliable and which are not. The segmentability index SI presented in this study does allow reliable segmentations to be identified, which is important for more accurate layer thickness analyses in research and population studies.

Evaluation of Segmented Amorphous-Contact Planar Germanium Detectors for Heavy-Element Research

NASA Astrophysics Data System (ADS)

Jackson, Emily G.

The challenge of improving our understanding of the very heaviest nuclei is at the forefront of contemporary low-energy nuclear physics. In the last two decades, "in-beam" spectroscopy experiments have advanced from Z=98 to Z=104, Rutherfordium, allowing insights into the dynamics of the fission barrier, high-order deformations, and pairing correlations. However, new detector technologies are needed to advance to even heavier nuclei. This dissertation is aimed at evaluating one promising new technology; large segmented planar germanium wafers for this area of research. The current frontier in gamma-ray spectroscopy involves large-volume (>9 cm thick) coaxial detectors that are position sensitive and employ gamma-ray "tracking". In contrast, the detectors assessed in this dissertation are relatively thin (~1 cm) segmented planar wafers with amorphous-germanium strip contacts that can tolerate extremely high gamma-ray count rates, and can accommodate hostile neutron fluxes. They may be the only path to heavier "in-beam" spectroscopy with production rates below 1 nanobarn. The resiliency of these detectors against neutron-induced damage is examined. Two detectors were deliberately subjected to a non-uniform neutron fluence leading to considerable degradation of performance. The neutrons were produced using the 7Li(p, n)7Be reaction at the UMass Lowell Van-de-Graaff accelerator with a 3.7-MeV proton beam incident on a natural Li target. The energy of the neutrons emitted at zero degrees was 2.0 MeV, close to the mean energy of the fission neutron spectrum, and each detector was exposed to a fluence >3.6 x109 n/cm2. A 3-D software "trap-corrector" gain-matching algorithm considerably restored the overall performance. Other neutron damage mitigation tactics were explored including over biasing the detector and flooding the detector with a high gamma-ray count rate. Various annealing processes to remove neutron damage were investigated. An array of very large diameter (>14 cm) wafers is being considered as the next step forward in germanium detector technology. A Small Business Innovative Research (SBIR) grant is funding the construction of such a counter, the world's largest, along with research into radiation hardness. The measurements reported here are encouraging for both ultra-high gamma-ray count rates and for neutron-damage, though reliable high temperature annealing to remove neutron-induced trapping centers will be essential for success.

Fermi LAT Observations of Cosmic-Ray Electrons

NASA Technical Reports Server (NTRS)

Moiseev, Alexander

2011-01-01

Designed as a gamma-ray instrument, the LAT is a capable detector of high energy cosmic ray electrons. The LAT is composed of a 4x4 array of identical towers. Each tower has a Tracker and a Calorimeter module. Entire LAT is covered by segmented Anti-Coincidence Detector (ACD). The electron data analysis is based on that developed for photons. The main challenge is to identify and separate electrons from all other charged species, mainly CR protons (for gamma-ray analysis this is provided by the Anti-Coincidence Detector)

Computer-assisted segmentation of white matter lesions in 3D MR images using support vector machine.

PubMed

Lao, Zhiqiang; Shen, Dinggang; Liu, Dengfeng; Jawad, Abbas F; Melhem, Elias R; Launer, Lenore J; Bryan, R Nick; Davatzikos, Christos

2008-03-01

Brain lesions, especially white matter lesions (WMLs), are associated with cardiac and vascular disease, but also with normal aging. Quantitative analysis of WML in large clinical trials is becoming more and more important. In this article, we present a computer-assisted WML segmentation method, based on local features extracted from multiparametric magnetic resonance imaging (MRI) sequences (ie, T1-weighted, T2-weighted, proton density-weighted, and fluid attenuation inversion recovery MRI scans). A support vector machine classifier is first trained on expert-defined WMLs, and is then used to classify new scans. Postprocessing analysis further reduces false positives by using anatomic knowledge and measures of distance from the training set. Cross-validation on a population of 35 patients from three different imaging sites with WMLs of varying sizes, shapes, and locations tests the robustness and accuracy of the proposed segmentation method, compared with the manual segmentation results from two experienced neuroradiologists.

Segmentation of the whole breast from low-dose chest CT images

NASA Astrophysics Data System (ADS)

Liu, Shuang; Salvatore, Mary; Yankelevitz, David F.; Henschke, Claudia I.; Reeves, Anthony P.

2015-03-01

The segmentation of whole breast serves as the first step towards automated breast lesion detection. It is also necessary for automatically assessing the breast density, which is considered to be an important risk factor for breast cancer. In this paper we present a fully automated algorithm to segment the whole breast in low-dose chest CT images (LDCT), which has been recommended as an annual lung cancer screening test. The automated whole breast segmentation and potential breast density readings as well as lesion detection in LDCT will provide useful information for women who have received LDCT screening, especially the ones who have not undergone mammographic screening, by providing them additional risk indicators for breast cancer with no additional radiation exposure. The two main challenges to be addressed are significant range of variations in terms of the shape and location of the breast in LDCT and the separation of pectoral muscles from the glandular tissues. The presented algorithm achieves robust whole breast segmentation using an anatomy directed rule-based method. The evaluation is performed on 20 LDCT scans by comparing the segmentation with ground truth manually annotated by a radiologist on one axial slice and two sagittal slices for each scan. The resulting average Dice coefficient is 0.880 with a standard deviation of 0.058, demonstrating that the automated segmentation algorithm achieves results consistent with manual annotations of a radiologist.

Automated 3D renal segmentation based on image partitioning

NASA Astrophysics Data System (ADS)

Yeghiazaryan, Varduhi; Voiculescu, Irina D.

2016-03-01

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

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)

Effects of Tantalum on the Temporal Evolution of a Model Ni-Al-Cr Superalloy During Phase Decomposition

NASA Technical Reports Server (NTRS)

Booth, Morrison, Christopher; Seidman, David N.; Noebe, Ronald D.

2009-01-01

The effects of a 2.0 at.% addition of Ta to a model Ni-10.0Al-8.5Cr (at.%) superalloy aged at 1073 K are assessed using scanning electron microscopy and atom-probe tomography. The gamma'(Ll2)-precipitate morphology that develops as a result of gamma-(fcc)matrix phase decomposition is found to evolve from a bimodal distribution of spheroidal precipitates, to {001}-faceted cuboids and parallelepipeds aligned along the elastically soft {001}-type directions. The phase compositions and the widths of the gamma'-precipitate/gamma-matrix heterophase interfaces evolve temporally as the Ni-Al-Cr-Ta alloy undergoes quasi-stationary state coarsening after 1 h of aging. Tantalum is observed to partition preferentially to the gamma'-precipitate phase, and suppresses the mobility of Ni in the gamma-matrix sufficiently to cause an accumulation of Ni on the gamma-matrix side of the gamma'/gamma interface. Additionally, computational modeling, employing Thermo-Calc, Dictra and PrecipiCalc, is employed to elucidate the kinetic pathways that lead to phase decomposition in this concentrated Ni-Al-Cr-Ta alloy.

Targeted delayed scanning at CT urography: a worthwhile use of radiation?

PubMed

Hack, Kalesha; Pinto, Patricia A; Gollub, Marc J

2012-10-01

To determine whether ureteral segments not filled with contrast material at computed tomographic (CT) urography ever contain tumor detectable only by filling these segments with contrast material. In this institutional review board-approved, HIPAA-compliant retrospective study, with waiver of informed consent, databases were searched for all patients who underwent heminephroureterectomy or ureteroscopy between January 1, 2001, and December 31, 2009, with available CT urography findings in the 12 months prior to surgery or biopsy and patients who had undergone at least two CT urography procedures with a minimum 5-year follow-up between studies. One of two radiologists blinded to results of pathologic examination recorded location of unfilled segments, time of scan, subsequent filling, and pathologic or 5-year follow-up CT urography results. Tumors were considered missed in an unfilled segment if tumor was found at pathologic examination or follow-up CT urography in the same one-third of the ureter and there were no secondary signs of a mass with other index CT urography sequences. Estimated radiation dose for additional delayed sequences was calculated with a 32-cm phantom. In 59 male and 33 female patients (mean age, 66 years) undergoing heminephroureterectomy, 27 tumors were present in 41 partially nonopacified ureters in 20 patients. Six tumors were present in nonopacified segments (one multifocal, none bilateral); all were identifiable by means of secondary signs present with earlier sequences. Among 182 lesions biopsied at ureteroscopy in 124 male and 53 female patients (mean age, 69 years), 28 tumors were present in nonopacified segments in 25 patients (four multifocal, none bilateral), all with secondary imaging signs detectable without delayed scanning. In 64 male and 29 female patients (mean age, 69 years) who underwent 5-year follow-up CT urography, three new tumors were revealed in three patients; none occurred in the unfilled ureter at index CT urography. Estimated radiation dose from additional sequences was 4.3 mSv per patient. Targeted delayed scanning at CT urography yielded no additional ureteral tumors and resulted in additional radiation exposure. © RSNA, 2012.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

PubMed

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

2017-02-11

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

Brain early infarct detection using gamma correction extreme-level eliminating with weighting distribution.

PubMed

Teh, V; Sim, K S; Wong, E K

2016-11-01

According to the statistic from World Health Organization (WHO), stroke is one of the major causes of death globally. Computed tomography (CT) scan is one of the main medical diagnosis system used for diagnosis of ischemic stroke. CT scan provides brain images in Digital Imaging and Communication in Medicine (DICOM) format. The presentation of CT brain images is mainly relied on the window setting (window center and window width), which converts an image from DICOM format into normal grayscale format. Nevertheless, the ordinary window parameter could not deliver a proper contrast on CT brain images for ischemic stroke detection. In this paper, a new proposed method namely gamma correction extreme-level eliminating with weighting distribution (GCELEWD) is implemented to improve the contrast on CT brain images. GCELEWD is capable of highlighting the hypodense region for diagnosis of ischemic stroke. The performance of this new proposed technique, GCELEWD, is compared with four of the existing contrast enhancement technique such as brightness preserving bi-histogram equalization (BBHE), dualistic sub-image histogram equalization (DSIHE), extreme-level eliminating histogram equalization (ELEHE), and adaptive gamma correction with weighting distribution (AGCWD). GCELEWD shows better visualization for ischemic stroke detection and higher values with image quality assessment (IQA) module. SCANNING 38:842-856, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

A novel fibrinogen variant--Liberec: dysfibrinogenaemia associated with gamma Tyr262Cys substitution.

PubMed

Kotlín, Roman; Sobotková, Alzbeta; Suttnar, Jirí; Salaj, Peter; Walterová, Lenka; Riedel, Tomás; Reicheltová, Zuzana; Dyr, Jan Evangelista

2008-08-01

A 22-yr-old woman had abnormal preoperative coagulation test results and congenital dysfibrinogenaemia was suspected. The patient from Liberec (Czech Republic) had a low fibrinogen plasma level as determined by Clauss method, normal fibrinogen level as determined by immunoturbidimetrical method, and prolonged thrombin time. To identify the genetic mutation responsible for this dysfibrinogen, genomic DNA extracted from the blood was analysed. Fibrin polymerisation measurement, kinetics of fibrinopeptide release, fibrinogen clottability measurement and scanning electron microscopy were performed. DNA sequencing showed the heterozygous fibrinogen gamma Y262C mutation. Kinetics of fibrinopeptide release was normal, however fibrin polymerisation was impaired. Fibrinogen clottability measurement showed that only about 45% molecules of fibrinogen are involved in the clot formation. Scanning electron microscopy revealed thicker fibres, which were significantly different from the normal control. A case of dysfibrinogenaemia, found by routine coagulation testing, was genetically identified as a novel fibrinogen variant (gamma Y262C) that has been named Liberec.

Development of the instruments for the Gamma Ray Observatory

NASA Technical Reports Server (NTRS)

Madden, J. J.; Kniffen, D. A.

1986-01-01

The Gamma Ray Observatory (GRO) is to be launched in 1988 by the STS. The GRO will feature four very large instruments: the Oriented Scintillation Spectrometer Experiment (OSSE), the Imaging Compton Telescope (COMPTEL), the Energetic Gamma Ray Experiment Telescope (EGRET) and the Burst and Transient Source Experiment (BATSE). The instruments weigh from 900-1200 kg each, and required the development of specialized lifting and dolly devices to permit their assembly, manipulation and testing. The GRO is intended a{s a tool for studying discrete celestial objects such as black holes, neutron stars and other gamma-ray emitting objects, scanning for nucleosynthesis processes, mapping the Galaxy and other, high energy galaxies in terms of gamma rays, searching for cosmological effects and observing gamma ray bursts. The instruments will be sensitive from the upper end mof X-rya wavelengths to the highest energies possible. Details of the hardware and performance specifications of each of the instruments are discussed.

Evaluation of stability of stereotactic space defined by cone-beam CT for the Leksell Gamma Knife Icon.

PubMed

AlDahlawi, Ismail; Prasad, Dheerendra; Podgorsak, Matthew B

2017-05-01

The Gamma Knife Icon comes with an integrated cone-beam CT (CBCT) for image-guided stereotactic treatment deliveries. The CBCT can be used for defining the Leksell stereotactic space using imaging without the need for the traditional invasive frame system, and this allows also for frameless thermoplastic mask stereotactic treatments (single or fractionated) with the Gamma Knife unit. In this study, we used an in-house built marker tool to evaluate the stability of the CBCT-based stereotactic space and its agreement with the standard frame-based stereotactic space. We imaged the tool with a CT indicator box using our CT-simulator at the beginning, middle, and end of the study period (6 weeks) for determining the frame-based stereotactic space. The tool was also scanned with the Icon's CBCT on a daily basis throughout the study period, and the CBCT images were used for determining the CBCT-based stereotactic space. The coordinates of each marker were determined in each CT and CBCT scan using the Leksell GammaPlan treatment planning software. The magnitudes of vector difference between the means of each marker in frame-based and CBCT-based stereotactic space ranged from 0.21 to 0.33 mm, indicating good agreement of CBCT-based and frame-based stereotactic space definition. Scanning 4-month later showed good prolonged stability of the CBCT-based stereotactic space definition. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

A search for spectral lines in gamma-ray bursts using TGRS

NASA Astrophysics Data System (ADS)

Kurczynski, P.; Palmer, D.; Seifert, H.; Teegarden, B. J.; Gehrels, N.; Cline, T. L.; Ramaty, R.; Hurley, K.; Madden, N. W.; Pehl, R. H.

1998-05-01

We present the results of an ongoing search for narrow spectral lines in gamma-ray burst data. TGRS, the Transient Gamma-Ray Spectrometer aboard the Wind satellite is a high energy-resolution Ge device. Thus it is uniquely situated among the array of space-based, burst sensitive instruments to look for line features in gamma-ray burst spectra. Our search strategy adopts a two tiered approach. An automated `quick look' scan searches spectra for statistically significant deviations from the continuum. We analyzed all possible time accumulations of spectra as well as individual spectra for each burst. Follow-up analysis of potential line candidates uses model fitting with F-test and χ2 tests for statistical significance.

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

Wilcox, Ellen; Daskalov, George; Nedialkova, Lucy

Intensity-modulated radiotherapy (IMRT) treatment plan verification is often done using Kodak EDR2 film and a Vidar Dosimetry PRO trade mark sign film digitizer. However, since many hospitals are moving towards a filmless environment, access to a film processor may not be available. Therefore, we have investigated a newly available Gafchromic[reg] EBT film for IMRT dosimetry. Planar IMRT dose distributions are delivered to both EBT and EDR2 film and scanned with the Vidar VXR-16 as well as an Epson Expression 1680 flatbed scanner. The measured dose distributions are then compared to those calculated with a Pinnacle treatment planning system. The IMRTmore » treatments consisted of 7-9 6 MV beams for treatment of prostate, head and neck, and a few other sites. The films were analyzed using FilmQA trade mark sign (3cognition LLC) software. Comparisons between measured and calculated dose distributions are reported as dose difference (DD) (pixels within {+-}5%), distance to agreement (DTA) (3 mm), as well as gamma values ({gamma}) (dose={+-}3%, dist.=2 mm). Using EDR2 with the Vidar scanner is an established technique and agreement between calculated and measured dose distributions was better than 90% in all indices (DD, DTA, and {gamma}). However, agreement with calculations deteriorated reaching the lower 80% for EBT film scans with the Vidar scanner in logarithmic mode. The EBT Vidar scans obtained in linear mode showed an improved agreement to the upper 80% range, but artifacts were still observed across the scan. These artifacts were very distinct in all EBT scans and can be attributed to the way the film is transported through the scanner. In the Epson scanner both films are rigidly immobilized and the light source scans over the film. It was found that the Epson scanner performed equally well with both types of film giving agreement to better than 90% in all indices.« less

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

NASA Astrophysics Data System (ADS)

Goswami, Subhra Sundar

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

Gradient Echo MRI Characterization of Development of Atherosclerosis in the Abdominal Aorta in Watanabe Heritable Hyperlipidemic Rabbits

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

Wang, Yi-Xiang J., E-mail: yi-xiang.wang@astrazeneca.com; Kuribayashi, Hideto; Wagberg, Maria

Purpose. The Watanabe Heritable Hyperlipidemic (WHHL) rabbit provides an important model of spontaneous atherosclerosis. With a strain of WHHL rabbits which do not develop abdominal aorta lumen stenosis even with advanced atherosclerosis, we studied the MRI-histology correlation, and the natural progression of atherosclerosis in the abdominal aorta. In addition, intra-reader segmentation repeatability and scan-rescan reproducibility were assessed. Methods. Two batches of female WHHL rabbits were used. The first batch of 6 rabbits was scanned at 20 weeks old. A second batch of 17 rabbits was scanned at 50 weeks old and then randomly divided into two subgroups: 8 were killedmore » for histologic investigation; 9 were kept alive for follow-up, with repeat scanning a week later to assess scan-rescan reproducibility, and again at 73 weeks old to assess disease progression. MR images were acquired at 4.7 T using a chemical shift selective fat suppression gradient echo with a saturation band suppressing blood signal within the aortic lumen. Five slices per animal were acquired, centered around the renal artery region of the abdominal aorta, with in-plane resolution of 0.195 mm and slice thickness of 3 mm. Results. The coefficient of variation for intra-reader reproducibility for aortic wall thickness measurements was 2.5% for repeat segmentations of the same scans on the same day, but segmentations of these same scans made 8 months later showed a systematic change, suggesting that intra-reader bias as well as increased variability could compromise assessments made over time. Comparative analyses were therefore performed in one postprocessing session. The coefficient of variation for scan-rescan reproducibility for aortic wall thickness was 5.5% for nine pairs of scans acquired a week apart and segmented on the same day. Good MRI-histology correlation was obtained. The MRI-measured mean aortic wall thickness of animals at 20 weeks of age was 76% that of animals at 50 weeks of age (p < 0.001). There was a small increase in aortic wall thickness between 50 and 73 weeks of age, but this was not significant (p > 0.05). The corresponding differences in lumen cross-sectional areas at 20, 50, and 73 weeks of age were not significant. These results were consistent with in-house historical histology data on this strain of rabbits. Conclusions. High-resolution gradient echo MRI can follow disease progression in the WHHL rabbit spontaneous atherosclerosis disease model.« less

White matter lesion extension to automatic brain tissue segmentation on MRI.

PubMed

de Boer, Renske; Vrooman, Henri A; van der Lijn, Fedde; Vernooij, Meike W; Ikram, M Arfan; van der Lugt, Aad; Breteler, Monique M B; Niessen, Wiro J

2009-05-01

A fully automated brain tissue segmentation method is optimized and extended with white matter lesion segmentation. Cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM) are segmented by an atlas-based k-nearest neighbor classifier on multi-modal magnetic resonance imaging data. This classifier is trained by registering brain atlases to the subject. The resulting GM segmentation is used to automatically find a white matter lesion (WML) threshold in a fluid-attenuated inversion recovery scan. False positive lesions are removed by ensuring that the lesions are within the white matter. The method was visually validated on a set of 209 subjects. No segmentation errors were found in 98% of the brain tissue segmentations and 97% of the WML segmentations. A quantitative evaluation using manual segmentations was performed on a subset of 6 subjects for CSF, GM and WM segmentation and an additional 14 for the WML segmentations. The results indicated that the automatic segmentation accuracy is close to the interobserver variability of manual segmentations.

The Copernicus ultraviolet spectral atlas of Gamma Pegasi

NASA Technical Reports Server (NTRS)

Rogerson, J. B., Jr.

1985-01-01

An ultraviolet spectral atlas is presented for the B2 IV star Gamma Pegasi, which has been scanned from 970 to 1501 A by the Princeton spectrometer aboard the Copernicus satellite. From 970 to 1430 A the observations have a nominal resolution of 0.05 A. At the longer wavelengths the resolution is 0.1 A. The atlas is presented in graphs. Line identifications are also listed.

Stellar and interstellar K lines - Gamma Pegasi and iota Herculis.

NASA Technical Reports Server (NTRS)

Hobbs, L. M.

1973-01-01

High-resolution scans show that the relatively strong (about 90 mA) K lines of Ca II in the early B stars gamma-Peg and iota-Her are almost entirely stellar in origin, although the latter case includes a small interstellar contribution. Such stellar lines can be of great importance in augmenting the interstellar absorption, up through the earliest of the B stars.

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

PubMed

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

2017-03-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2009-10-01

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

Control Measurements of Crane Rails Performed by Terrestrial Laser Scanning

PubMed Central

Kregar, Klemen; Možina, Jan; Ambrožič, Tomaž; Kogoj, Dušan; Marjetič, Aleš; Štebe, Gašper; Savšek, Simona

2017-01-01

This article presents a method for measuring the geometry of crane rails with terrestrial laser scanning (TLS). Two sets of crane rails were divided into segments, their planes were adjusted, and the characteristic rail lines were defined. We used their profiles to define the positional and altitude deviations of the rails, the span and height difference between the two rails, and we also verified that they complied with the Eurocode 3 standard. We tested the method on crane rails at the hydroelectric power plant in Krško and the thermal power plant in Brestanica. We used two scanning techniques: “pure” TLS (Riegel VZ-400) and “hybrid” TLS (Leica MS50) scanning. This article’s original contribution lies in the detailed presentation of the computations used to define the characteristic lines of the rails without using the numeric procedures from existing software packages. We also analysed the influence of segment length and point density on the rail geometry results, and compared the two laser scanning techniques. We also compared the results obtained by terrestrial laser scanning with the results obtained from the classic polar method, which served as a reference point for its precision. PMID:28726755

Automated circumferential construction of first-order aqueous humor outflow pathways using spectral-domain optical coherence tomography.

PubMed

Huang, Alex S; Belghith, Akram; Dastiridou, Anna; Chopra, Vikas; Zangwill, Linda M; Weinreb, Robert N

2017-06-01

The purpose was to create a three-dimensional (3-D) model of circumferential aqueous humor outflow (AHO) in a living human eye with an automated detection algorithm for Schlemm’s canal (SC) and first-order collector channels (CC) applied to spectral-domain optical coherence tomography (SD-OCT). Anterior segment SD-OCT scans from a subject were acquired circumferentially around the limbus. A Bayesian Ridge method was used to approximate the location of the SC on infrared confocal laser scanning ophthalmoscopic images with a cross multiplication tool developed to initiate SC/CC detection automated through a fuzzy hidden Markov Chain approach. Automatic segmentation of SC and initial CC’s was manually confirmed by two masked graders. Outflow pathways detected by the segmentation algorithm were reconstructed into a 3-D representation of AHO. Overall, only <1% of images (5114 total B-scans) were ungradable. Automatic segmentation algorithm performed well with SC detection 98.3% of the time and <0.1% false positive detection compared to expert grader consensus. CC was detected 84.2% of the time with 1.4% false positive detection. 3-D representation of AHO pathways demonstrated variably thicker and thinner SC with some clear CC roots. Circumferential (360 deg), automated, and validated AHO detection of angle structures in the living human eye with reconstruction was possible.

[Automated detection and volumetric segmentation of the spleen in CT scans].

PubMed

Hammon, M; Dankerl, P; Kramer, M; Seifert, S; Tsymbal, A; Costa, M J; Janka, R; Uder, M; Cavallaro, A

2012-08-01

To introduce automated detection and volumetric segmentation of the spleen in spiral CT scans with the THESEUS-MEDICO software. The consistency between automated volumetry (aV), estimated volume determination (eV) and manual volume segmentation (mV) was evaluated. Retrospective evaluation of the CAD system based on methods like "marginal space learning" and "boosting algorithms". 3 consecutive spiral CT scans (thoraco-abdominal; portal-venous contrast agent phase; 1 or 5 mm slice thickness) of 15 consecutive lymphoma patients were included. The eV: 30 cm³ + 0.58 (width × length × thickness of the spleen) and the mV as the reference standard were determined by an experienced radiologist. The aV could be performed in all CT scans within 15.2 (± 2.4) seconds. The average splenic volume measured by aV was 268.21 ± 114.67 cm³ compared to 281.58 ± 130.21 cm³ in mV and 268.93 ± 104.60 cm³ in eV. The correlation coefficient was 0.99 (coefficient of determination (R²) = 0.98) for aV and mV, 0.91 (R² = 0.83) for mV and eV and 0.91 (R² = 0.82) for aV and eV. There was an almost perfect correlation of the changes in splenic volume measured with the new aV and mV (0.92; R² = 0.84), mV and eV (0.95; R² = 0.91) and aV and eV (0.83; R² = 0.69) between two time points. The automated detection and volumetric segmentation software rapidly provides an accurate measurement of the splenic volume in CT scans. Knowledge about splenic volume and its change between two examinations provides valuable clinical information without effort for the radiologist. © Georg Thieme Verlag KG Stuttgart · New York.

3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion

PubMed Central

Dou, Qingxu; Wei, Lijun; Magee, Derek R.; Atkins, Phil R.; Chapman, David N.; Curioni, Giulio; Goddard, Kevin F.; Hayati, Farzad; Jenks, Hugo; Metje, Nicole; Muggleton, Jennifer; Pennock, Steve R.; Rustighi, Emiliano; Swingler, Steven G.; Rogers, Christopher D. F.; Cohn, Anthony G.

2016-01-01

We address the problem of accurately locating buried utility segments by fusing data from multiple sensors using a novel Marching-Cross-Section (MCS) algorithm. Five types of sensors are used in this work: Ground Penetrating Radar (GPR), Passive Magnetic Fields (PMF), Magnetic Gradiometer (MG), Low Frequency Electromagnetic Fields (LFEM) and Vibro-Acoustics (VA). As part of the MCS algorithm, a novel formulation of the extended Kalman Filter (EKF) is proposed for marching existing utility tracks from a scan cross-section (scs) to the next one; novel rules for initializing utilities based on hypothesized detections on the first scs and for associating predicted utility tracks with hypothesized detections in the following scss are introduced. Algorithms are proposed for generating virtual scan lines based on given hypothesized detections when different sensors do not share common scan lines, or when only the coordinates of the hypothesized detections are provided without any information of the actual survey scan lines. The performance of the proposed system is evaluated with both synthetic data and real data. The experimental results in this work demonstrate that the proposed MCS algorithm can locate multiple buried utility segments simultaneously, including both straight and curved utilities, and can separate intersecting segments. By using the probabilities of a hypothesized detection being a pipe or a cable together with its 3D coordinates, the MCS algorithm is able to discriminate a pipe and a cable close to each other. The MCS algorithm can be used for both post- and on-site processing. When it is used on site, the detected tracks on the current scs can help to determine the location and direction of the next scan line. The proposed “multi-utility multi-sensor” system has no limit to the number of buried utilities or the number of sensors, and the more sensor data used, the more buried utility segments can be detected with more accurate location and orientation. PMID:27827836

3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion.

PubMed

Dou, Qingxu; Wei, Lijun; Magee, Derek R; Atkins, Phil R; Chapman, David N; Curioni, Giulio; Goddard, Kevin F; Hayati, Farzad; Jenks, Hugo; Metje, Nicole; Muggleton, Jennifer; Pennock, Steve R; Rustighi, Emiliano; Swingler, Steven G; Rogers, Christopher D F; Cohn, Anthony G

2016-11-02

We address the problem of accurately locating buried utility segments by fusing data from multiple sensors using a novel Marching-Cross-Section (MCS) algorithm. Five types of sensors are used in this work: Ground Penetrating Radar (GPR), Passive Magnetic Fields (PMF), Magnetic Gradiometer (MG), Low Frequency Electromagnetic Fields (LFEM) and Vibro-Acoustics (VA). As part of the MCS algorithm, a novel formulation of the extended Kalman Filter (EKF) is proposed for marching existing utility tracks from a scan cross-section (scs) to the next one; novel rules for initializing utilities based on hypothesized detections on the first scs and for associating predicted utility tracks with hypothesized detections in the following scss are introduced. Algorithms are proposed for generating virtual scan lines based on given hypothesized detections when different sensors do not share common scan lines, or when only the coordinates of the hypothesized detections are provided without any information of the actual survey scan lines. The performance of the proposed system is evaluated with both synthetic data and real data. The experimental results in this work demonstrate that the proposed MCS algorithm can locate multiple buried utility segments simultaneously, including both straight and curved utilities, and can separate intersecting segments. By using the probabilities of a hypothesized detection being a pipe or a cable together with its 3D coordinates, the MCS algorithm is able to discriminate a pipe and a cable close to each other. The MCS algorithm can be used for both post- and on-site processing. When it is used on site, the detected tracks on the current scs can help to determine the location and direction of the next scan line. The proposed "multi-utility multi-sensor" system has no limit to the number of buried utilities or the number of sensors, and the more sensor data used, the more buried utility segments can be detected with more accurate location and orientation.

Mössbauer Magnetic Scan experiments

NASA Astrophysics Data System (ADS)

Pasquevich, G. A.; Mendoza Zélis, P.; Lencina, A.; Veiga, A.; Fernández van Raap, M. B.; Sánchez, F. H.

2014-06-01

We report an application of the Mössbauer Effect designed to retrieve specific information on the magnetic response of iron-containing materials. It consists in the measurement of the nuclear absorption of gamma-rays as a function of an external magnetic field for a specific nuclear transition between magnetically-split nuclear levels. The experiments, here termed Mössbauer Magnetic Scan experiments, were carried out recording the absorption of 57Fe 14.4 keV gamma-ray in α-Fe at constant Doppler energies coincident with some of the spectral lines of the magnetically split Mössbauer spectrum. Due to the dependence of the transition probabilities on the relative orientation between the nuclear magnetic moment and the gamma-ray direction, the present application results in a useful method to study the magnetic-field evolution of the distribution of atomic-magnetic-moment orientations. The proposed technique inherit from the Mössbauer Spectroscopy the chemical-element selectiveness as well as the ability to differentiate responses from iron atoms located at inequivalent site or at different phases. In this work, we show that the data analysis for these experiments depends on the sample thickness that the gamma-ray has to cross. For thin samples (i.e.samples with Mössbauer effective thicknesses lower than one) the magnetic-field dependence of the second-order-moment of the orientation distribution in the direction of the gamma ray is obtained. On the other hand, for thicker samples, although the data analysis is more complex, the dependences of the three second-order-moments of the orientation distribution are obtained. The experiments were performed on two α-Fe foils of different Mössbauer effective thicknesses. They were chosen to represent the cases of thin and thick Mössbauer absorbers. The magnetic evolution of the orientations distribution is compared with results obtained from magnetometric measurements showing a good agreement as well indicating the complementarity of both techniques. A complete description of the experimental set up and the formalism for Mössbauer Magnetic Scan data analysis are presented.

A segmentation algorithm based on image projection for complex text layout

NASA Astrophysics Data System (ADS)

Zhu, Wangsheng; Chen, Qin; Wei, Chuanyi; Li, Ziyang

2017-10-01

Segmentation algorithm is an important part of layout analysis, considering the efficiency advantage of the top-down approach and the particularity of the object, a breakdown of projection layout segmentation algorithm. Firstly, the algorithm will algorithm first partitions the text image, and divided into several columns, then for each column scanning projection, the text image is divided into several sub regions through multiple projection. The experimental results show that, this method inherits the projection itself and rapid calculation speed, but also can avoid the effect of arc image information page segmentation, and also can accurate segmentation of the text image layout is complex.

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.

An Analysis of the Utility of Handheld PET Probes for the Intraoperative Localization of Malignant Tissue

PubMed Central

González, Segundo Jaime; González, Lorena; Wong, Joyce; Brader, Peter; Zakowski, Maureen; Gönen, Mithat; Daghighian, Farhad; Fong, Yuman

2012-01-01

Introduction The intraoperative localization of suspicious lesions detected by positron emission tomography (PET) scan remains a challenge. To solve this, two novel probes have been created to accurately detect the 18F-FDG radiotracer intraoperatively. Methods Nude rats were inoculated with mesothelioma. When PET scans detected 10-mm tumors, animals were dissected and the PET probes analyzed the intraoperative radiotracer uptake of these lesions as tumor to background ratio (TBR). Results The 17 suspicious lesions seen on PET scan were localized intraoperatively (by their high TBR) using the PET probes and found malignant on pathology. Interestingly, smaller tumors not visualized on PET scan were detected intraoperatively by their high TBR and found malignant on pathology. Furthermore, using a TBR threshold as low as 2.0, both gamma (sensitivity, 100%; specificity, 80%; positive predictive value (PPV), 96%; and negative predictive value (NPV), 100%) and beta (sensitivity, 100%; specificity, 60%; PPV, 93%; and NPV, 100%) probes reliably detected suspicious lesions on PET scan imaging. They also showed an excellent area under the curve of 0.9 and 0.97 (95% CI of 0.81–0.99 and 0.93–1.0) for gamma and beta probes, respectively, in the receiver operating characteristic analysis for detecting malignancy. Conclusion This novel tool could be used synergistically with a PET scan imaging to maximize tissue selection intraoperatively. PMID:21108016

Technical report on semiautomatic segmentation using the Adobe Photoshop.

PubMed

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

2005-12-01

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

Thoracic cavity definition for 3D PET/CT analysis and visualization.

PubMed

Cheirsilp, Ronnarit; Bascom, Rebecca; Allen, Thomas W; Higgins, William E

2015-07-01

X-ray computed tomography (CT) and positron emission tomography (PET) serve as the standard imaging modalities for lung-cancer management. CT gives anatomical details on diagnostic regions of interest (ROIs), while PET gives highly specific functional information. During the lung-cancer management process, a patient receives a co-registered whole-body PET/CT scan pair and a dedicated high-resolution chest CT scan. With these data, multimodal PET/CT ROI information can be gleaned to facilitate disease management. Effective image segmentation of the thoracic cavity, however, is needed to focus attention on the central chest. We present an automatic method for thoracic cavity segmentation from 3D CT scans. We then demonstrate how the method facilitates 3D ROI localization and visualization in patient multimodal imaging studies. Our segmentation method draws upon digital topological and morphological operations, active-contour analysis, and key organ landmarks. Using a large patient database, the method showed high agreement to ground-truth regions, with a mean coverage=99.2% and leakage=0.52%. Furthermore, it enabled extremely fast computation. For PET/CT lesion analysis, the segmentation method reduced ROI search space by 97.7% for a whole-body scan, or nearly 3 times greater than that achieved by a lung mask. Despite this reduction, we achieved 100% true-positive ROI detection, while also reducing the false-positive (FP) detection rate by >5 times over that achieved with a lung mask. Finally, the method greatly improved PET/CT visualization by eliminating false PET-avid obscurations arising from the heart, bones, and liver. In particular, PET MIP views and fused PET/CT renderings depicted unprecedented clarity of the lesions and neighboring anatomical structures truly relevant to lung-cancer assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Thoracic Cavity Definition for 3D PET/CT Analysis and Visualization

PubMed Central

Cheirsilp, Ronnarit; Bascom, Rebecca; Allen, Thomas W.; Higgins, William E.

2015-01-01

X-ray computed tomography (CT) and positron emission tomography (PET) serve as the standard imaging modalities for lung-cancer management. CT gives anatomical detail on diagnostic regions of interest (ROIs), while PET gives highly specific functional information. During the lung-cancer management process, a patient receives a co-registered whole-body PET/CT scan pair and a dedicated high-resolution chest CT scan. With these data, multimodal PET/CT ROI information can be gleaned to facilitate disease management. Effective image segmentation of the thoracic cavity, however, is needed to focus attention on the central chest. We present an automatic method for thoracic cavity segmentation from 3D CT scans. We then demonstrate how the method facilitates 3D ROI localization and visualization in patient multimodal imaging studies. Our segmentation method draws upon digital topological and morphological operations, active-contour analysis, and key organ landmarks. Using a large patient database, the method showed high agreement to ground-truth regions, with a mean coverage = 99.2% and leakage = 0.52%. Furthermore, it enabled extremely fast computation. For PET/CT lesion analysis, the segmentation method reduced ROI search space by 97.7% for a whole-body scan, or nearly 3 times greater than that achieved by a lung mask. Despite this reduction, we achieved 100% true-positive ROI detection, while also reducing the false-positive (FP) detection rate by >5 times over that achieved with a lung mask. Finally, the method greatly improved PET/CT visualization by eliminating false PET-avid obscurations arising from the heart, bones, and liver. In particular, PET MIP views and fused PET/CT renderings depicted unprecedented clarity of the lesions and neighboring anatomical structures truly relevant to lung-cancer assessment. PMID:25957746

Evaluation of Retinal and Choroidal Thickness by Swept-Source Optical Coherence Tomography: Repeatability and Assessment of Artifacts

PubMed Central

Mansouri, Kaweh; Medeiros, Felipe A.; Tatham, Andrew J.; Marchase, Nicholas; Weinreb, Robert N.

2017-01-01

PURPOSE To determine the repeatability of automated retinal and choroidal thickness measurements with swept-source optical coherence tomography (SS OCT) and the frequency and type of scan artifacts. DESIGN Prospective evaluation of new diagnostic technology. METHODS Thirty healthy subjects were recruited prospectively and underwent imaging with a prototype SS OCT instrument. Undilated scans of 54 eyes of 27 subjects (mean age, 35.1 ± 9.3 years) were obtained. Each subject had 4 SS OCT protocols repeated 3 times: 3-dimensional (3D) 6 × 6-mm raster scan of the optic disc and macula, radial, and line scan. Automated measurements were obtained through segmentation software. Interscan repeatability was assessed by intraclass correlation coefficients (ICCs). RESULTS ICCs for choroidal measurements were 0.92, 0.98, 0.80, and 0.91, respectively, for 3D macula, 3D optic disc, radial, and line scans. ICCs for retinal measurements were 0.39, 0.49, 0.71, and 0.69, respectively. Artifacts were present in up to 9% scans. Signal loss because of blinking was the most common artifact on 3D scans (optic disc scan, 7%; macula scan, 9%), whereas segmentation failure occurred in 4% of radial and 3% of line scans. When scans with image artifacts were excluded, ICCs for choroidal thickness increased to 0.95, 0.99, 0.87, and 0.93 for 3D macula, 3D optic disc, radial, and line scans, respectively. ICCs for retinal thickness increased to 0.88, 0.83, 0.89, and 0.76, respectively. CONCLUSIONS Improved repeatability of automated choroidal and retinal thickness measurements was found with the SS OCT after correction of scan artifacts. Recognition of scan artifacts is important for correct interpretation of SS OCT measurements. PMID:24531020

Individual Rocks Segmentation in Terrestrial Laser Scanning Point Cloud Using Iterative Dbscan Algorithm

NASA Astrophysics Data System (ADS)

Walicka, A.; Jóźków, G.; Borkowski, A.

2018-05-01

The fluvial transport is an important aspect of hydrological and geomorphologic studies. The knowledge about the movement parameters of different-size fractions is essential in many applications, such as the exploration of the watercourse changes, the calculation of the river bed parameters or the investigation of the frequency and the nature of the weather events. Traditional techniques used for the fluvial transport investigations do not provide any information about the long-term horizontal movement of the rocks. This information can be gained by means of terrestrial laser scanning (TLS). However, this is a complex issue consisting of several stages of data processing. In this study the methodology for individual rocks segmentation from TLS point cloud has been proposed, which is the first step for the semi-automatic algorithm for movement detection of individual rocks. The proposed algorithm is executed in two steps. Firstly, the point cloud is classified as rocks or background using only geometrical information. Secondly, the DBSCAN algorithm is executed iteratively on points classified as rocks until only one stone is detected in each segment. The number of rocks in each segment is determined using principal component analysis (PCA) and simple derivative method for peak detection. As a result, several segments that correspond to individual rocks are formed. Numerical tests were executed on two test samples. The results of the semi-automatic segmentation were compared to results acquired by manual segmentation. The proposed methodology enabled to successfully segment 76 % and 72 % of rocks in the test sample 1 and test sample 2, respectively.

Infrared scanning laser ophthalmoscope imaging of the macula and its correlation with functional loss and structural changes in patients with stargardt disease.

PubMed

Anastasakis, Anastasios; Fishman, Gerald A; Lindeman, Martin; Genead, Mohamed A; Zhou, Wensheng

2011-05-01

To correlate the degree of functional loss with structural changes in patients with Stargardt disease. Eighteen eyes of 10 patients with Stargardt disease were studied. Scanning laser ophthalmoscope infrared images were compared with corresponding spectral-domain optical coherence tomography scans. Additionally, scanning laser ophthalmoscope microperimetry was performed, and results were superimposed on scanning laser ophthalmoscope infrared images and in selected cases on fundus autofluorescence images. Seventeen of 18 eyes showed a distinct hyporeflective foveal and/or perifoveal area with distinct borders on scanning laser ophthalmoscope infrared images, which was less evident on funduscopy and incompletely depicted in fundus autofluorescence images. This hyporeflective zone corresponded to areas of significantly elevated psychophysical thresholds on microperimetry testing, in addition to thinning of the retinal pigment epithelium and disorganization or loss of the photoreceptor cell inner segment-outer segment junction and external-limiting membrane on spectral-domain optical coherence tomography. Scanning laser ophthalmoscope infrared fundus images are useful for depicting retinal structural changes in patients with Stargardt disease. A spectral-domain optical coherence tomography/scanning laser ophthalmoscope microperimetry device allows for a direct correlation of structural abnormalities with functional defects that will likely be applicable for the determination of retinal areas for potential improvement of retinal function in these patients during future clinical trials and for the monitoring of the diseases' natural history.

New method for scanning spacecraft and balloon-borne/space-based experiments

NASA Technical Reports Server (NTRS)

Polites, Michael E.

1991-01-01

A new method is presented for scanning balloon-borne experiments, free-flying spacecraft, and gimballed experiments mounted to the space shuttle or the space station. It uses rotating-unbalanced-mass (RUM) devices for generating circular, line, or raster scan patterns and an auxiliary control system for target acquisition, keeping the scan centered on the target, and producing complementary motion for raster scanning. It is ideal for applications where the only possible way to accomplish the required scan is to physically scan the entire experiment or spacecraft as in X-ray and gamma ray experiments. In such cases, this new method should have advantages over prior methods in terms of either power, weight, cost, performance, stability, or a combination of these.

Automated segmentation of 3D anatomical structures on CT images by using a deep convolutional network based on end-to-end learning approach

NASA Astrophysics Data System (ADS)

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

2017-02-01

We have proposed an end-to-end learning approach that trained a deep convolutional neural network (CNN) for automatic CT image segmentation, which accomplished a voxel-wised multiple classification to directly map each voxel on 3D CT images to an anatomical label automatically. The novelties of our proposed method were (1) transforming the anatomical structures segmentation on 3D CT images into a majority voting of the results of 2D semantic image segmentation on a number of 2D-slices from different image orientations, and (2) using "convolution" and "deconvolution" networks to achieve the conventional "coarse recognition" and "fine extraction" functions which were integrated into a compact all-in-one deep CNN for CT image segmentation. The advantage comparing to previous works was its capability to accomplish real-time image segmentations on 2D slices of arbitrary CT-scan-range (e.g. body, chest, abdomen) and produced correspondingly-sized output. In this paper, we propose an improvement of our proposed approach by adding an organ localization module to limit CT image range for training and testing deep CNNs. A database consisting of 240 3D CT scans and a human annotated ground truth was used for training (228 cases) and testing (the remaining 12 cases). We applied the improved method to segment pancreas and left kidney regions, respectively. The preliminary results showed that the accuracies of the segmentation results were improved significantly (pancreas was 34% and kidney was 8% increased in Jaccard index from our previous results). The effectiveness and usefulness of proposed improvement for CT image segmentations were confirmed.

Segmentation of large periapical lesions toward dental computer-aided diagnosis in cone-beam CT scans

NASA Astrophysics Data System (ADS)

Rysavy, Steven; Flores, Arturo; Enciso, Reyes; Okada, Kazunori

2008-03-01

This paper presents an experimental study for assessing the applicability of general-purpose 3D segmentation algorithms for analyzing dental periapical lesions in cone-beam computed tomography (CBCT) scans. In the field of Endodontics, clinical studies have been unable to determine if a periapical granuloma can heal with non-surgical methods. Addressing this issue, Simon et al. recently proposed a diagnostic technique which non-invasively classifies target lesions using CBCT. Manual segmentation exploited in their study, however, is too time consuming and unreliable for real world adoption. On the other hand, many technically advanced algorithms have been proposed to address segmentation problems in various biomedical and non-biomedical contexts, but they have not yet been applied to the field of dentistry. Presented in this paper is a novel application of such segmentation algorithms to the clinically-significant dental problem. This study evaluates three state-of-the-art graph-based algorithms: a normalized cut algorithm based on a generalized eigen-value problem, a graph cut algorithm implementing energy minimization techniques, and a random walks algorithm derived from discrete electrical potential theory. In this paper, we extend the original 2D formulation of the above algorithms to segment 3D images directly and apply the resulting algorithms to the dental CBCT images. We experimentally evaluate quality of the segmentation results for 3D CBCT images, as well as their 2D cross sections. The benefits and pitfalls of each algorithm are highlighted.

An Efficient, Hierarchical Viewpoint Planning Strategy for Terrestrial Laser Scanner Networks

NASA Astrophysics Data System (ADS)

Jia, F.; Lichti, D. D.

2018-05-01

Terrestrial laser scanner (TLS) techniques have been widely adopted in a variety of applications. However, unlike in geodesy or photogrammetry, insufficient attention has been paid to the optimal TLS network design. It is valuable to develop a complete design system that can automatically provide an optimal plan, especially for high-accuracy, large-volume scanning networks. To achieve this goal, one should look at the "optimality" of the solution as well as the computational complexity in reaching it. In this paper, a hierarchical TLS viewpoint planning strategy is developed to solve the optimal scanner placement problems. If one targeted object to be scanned is simplified as discretized wall segments, any possible viewpoint can be evaluated by a score table representing its visible segments under certain scanning geometry constraints. Thus, the design goal is to find a minimum number of viewpoints that achieves complete coverage of all wall segments. The efficiency is improved by densifying viewpoints hierarchically, instead of a "brute force" search within the entire workspace. The experiment environments in this paper were simulated from two buildings located on University of Calgary campus. Compared with the "brute force" strategy in terms of the quality of the solutions and the runtime, it is shown that the proposed strategy can provide a scanning network with a compatible quality but with more than a 70 % time saving.

Gamma-Ray Spectroscopy at TRIUMF-ISAC: the New Frontier of Radioactive Ion Beam Research

NASA Astrophysics Data System (ADS)

Ball, G. C.; Andreoiu, C.; Austin, R. A. E.; Bandyopadhyay, D.; Becker, J. A.; Bricault, P.; Brown, N.; Chan, S.; Churchman, R.; Colosimo, S.; Coombes, H.; Cross, D.; Demand, G.; Drake, T. E.; Dombsky, M.; Ettenauer, S.; Finlay, P.; Furse, D.; Garnsworthy, A.; Garrett, P. E.; Green, K. L.; Grinyer, G. F.; Hyland, B.; Hackman, G.; Kanungo, R.; Kulp, W. D.; Lassen, J.; Leach, K. G.; Leslie, J. R.; Mattoon, C.; Melconian, D.; Morton, A. C.; Pearson, C. J.; Phillips, A. A.; Rand, E.; Sarazin, F.; Svensson, C. E.; Sumithrarachchi, S.; Schumaker, M. A.; Triambak, S.; Waddington, J. C.; Walker, P. M.; Williams, S. J.; Wood, J. L.; Wong, J.; Zganjar, E. F.

2009-03-01

High-resolution gamma-ray spectroscopy is essential to fully exploit the unique scientific opportunities at the next generation radioactive ion beam facilities such as the TRIUMF Isotope Separator and Accelerator (ISAC). At ISAC the 8π spectrometer and its associated auxiliary detectors is optimize for β-decay studies while TIGRESS an array of segmented clover HPGe detectors has been designed for studies with accelerated beams. This paper gives a brief overview of these facilities and also presents recent examples of the diverse experimental program carried out at the 8π spectrometer.

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

ADAMS, WADE C

The objectives of the confirmatory activities were to provide independent contractor field data reviews and to generate independent radiological data for use by the NRC in evaluating the adequacy and accuracy of the contractor's procedures and FSS results. ORAU reviewed ABB CE's decommissioning plan, final status survey plan, and the applicable soil DCGLs, which were developed based on an NRC-approved radiation dose assessment. The surveys include gamma surface scans, gamma direct measurements, and soil sampling.

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

ADAMS, WADE C

The objectives of the confirmatory activities were to provide independent contractor field data reviews and to generate independent radiological data for use by the NRC in evaluating the adequacy and accuracy of the contractor's procedures and FSS results. ORAU reviewed ABB CE's decommissioning plan, final status survey plan, and the applicable soil DCGLs, which were developed based on an NRC-approved radiation dose assessment. The surveys included gamma surface scans, gamma direct measurements, and soil sampling.

Detecting Cavitation Pitting Without Disassembly

NASA Technical Reports Server (NTRS)

Barkhoudarian, S.

1986-01-01

Technique for detecting cavitation pitting in pumps, turbines, and other machinery uses low-level nuclear irradiation. Isotopes concentrated below surface emit gamma radiation, a portion of which is attenuated by overlying material. Where there are cavitation pits, output of gamma-ray detector fluctuates as detector is scanned near pits. Important to detect cavitation pits because nozzle, turbine blade, or other pump component weakened by cavitation could fail catastrophically and cause machine to explode.

Real time automated inspection

DOEpatents

Fant, Karl M.; Fundakowski, Richard A.; Levitt, Tod S.; Overland, John E.; Suresh, Bindinganavle R.; Ulrich, Franz W.

1985-01-01

A method and apparatus relating to the real time automatic detection and classification of characteristic type surface imperfections occurring on the surfaces of material of interest such as moving hot metal slabs produced by a continuous steel caster. A data camera transversely scans continuous lines of such a surface to sense light intensities of scanned pixels and generates corresponding voltage values. The voltage values are converted to corresponding digital values to form a digital image of the surface which is subsequently processed to form an edge-enhanced image having scan lines characterized by intervals corresponding to the edges of the image. The edge-enhanced image is thresholded to segment out the edges and objects formed by the edges are segmented out by interval matching and bin tracking. Features of the objects are derived and such features are utilized to classify the objects into characteristic type surface imperfections.

Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion SPECT interpretation.

PubMed

Berman, Daniel S; Abidov, Aiden; Kang, Xingping; Hayes, Sean W; Friedman, John D; Sciammarella, Maria G; Cohen, Ishac; Gerlach, James; Waechter, Parker B; Germano, Guido; Hachamovitch, Rory

2004-01-01

Recently, a 17-segment model of the left ventricle has been recommended as an optimally weighted approach for interpreting myocardial perfusion single photon emission computed tomography (SPECT). Methods to convert databases from previous 20- to new 17-segment data and criteria for abnormality for the 17-segment scores are needed. Initially, for derivation of the conversion algorithm, 65 patients were studied (algorithm population) (pilot group, n = 28; validation group, n = 37). Three conversion algorithms were derived: algorithm 1, which used mid, distal, and apical scores; algorithm 2, which used distal and apical scores alone; and algorithm 3, which used maximal scores of the distal septal, lateral, and apical segments in the 20-segment model for 3 corresponding segments of the 17-segment model. The prognosis population comprised 16,020 consecutive patients (mean age, 65 +/- 12 years; 41% women) who had exercise or vasodilator stress technetium 99m sestamibi myocardial perfusion SPECT and were followed up for 2.1 +/- 0.8 years. In this population, 17-segment scores were derived from 20-segment scores by use of algorithm 2, which demonstrated the best agreement with expert 17-segment reading in the algorithm population. The prognostic value of the 20- and 17-segment scores was compared by converting the respective summed scores into percent myocardium abnormal. Conversion algorithm 2 was found to be highly concordant with expert visual analysis by the 17-segment model (r = 0.982; kappa = 0.866) in the algorithm population. In the prognosis population, 456 cardiac deaths occurred during follow-up. When the conversion algorithm was applied, extent and severity of perfusion defects were nearly identical by 20- and derived 17-segment scores. The receiver operating characteristic curve areas by 20- and 17-segment perfusion scores were identical for predicting cardiac death (both 0.77 +/- 0.02, P = not significant). The optimal prognostic cutoff value for either 20- or derived 17-segment models was confirmed to be 5% myocardium abnormal, corresponding to a summed stress score greater than 3. Of note, the 17-segment model demonstrated a trend toward fewer mildly abnormal scans and more normal and severely abnormal scans. An algorithm for conversion of 20-segment perfusion scores to 17-segment scores has been developed that is highly concordant with expert visual analysis by the 17-segment model and provides nearly identical prognostic information. This conversion model may provide a mechanism for comparison of studies analyzed by the 17-segment system with previous studies analyzed by the 20-segment approach.

Automated Agatston score computation in non-ECG gated CT scans using deep learning

NASA Astrophysics Data System (ADS)

Cano-Espinosa, Carlos; González, Germán.; Washko, George R.; Cazorla, Miguel; San José Estépar, Raúl

2018-03-01

Introduction: The Agatston score is a well-established metric of cardiovascular disease related to clinical outcomes. It is computed from CT scans by a) measuring the volume and intensity of the atherosclerotic plaques and b) aggregating such information in an index. Objective: To generate a convolutional neural network that inputs a non-contrast chest CT scan and outputs the Agatston score associated with it directly, without a prior segmentation of Coronary Artery Calcifications (CAC). Materials and methods: We use a database of 5973 non-contrast non-ECG gated chest CT scans where the Agatston score has been manually computed. The heart of each scan is cropped automatically using an object detector. The database is split in 4973 cases for training and 1000 for testing. We train a 3D deep convolutional neural network to regress the Agatston score directly from the extracted hearts. Results: The proposed method yields a Pearson correlation coefficient of r = 0.93; p <= 0.0001 against manual reference standard in the 1000 test cases. It further stratifies correctly 72.6% of the cases with respect to standard risk groups. This compares to more complex state-of-the-art methods based on prior segmentations of the CACs, which achieve r = 0.94 in ECG-gated pulmonary CT. Conclusions: A convolutional neural network can regress the Agatston score from the image of the heart directly, without a prior segmentation of the CACs. This is a new and simpler paradigm in the Agatston score computation that yields similar results to the state-of-the-art literature.

Determination of lung segments in computed tomography images using the Euclidean distance to the pulmonary artery

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

Stoecker, Christina; Moltz, Jan H.; Lassen, Bianca

Purpose: Computed tomography (CT) imaging is the modality of choice for lung cancer diagnostics. With the increasing number of lung interventions on sublobar level in recent years, determining and visualizing pulmonary segments in CT images and, in oncological cases, reliable segment-related information about the location of tumors has become increasingly desirable. Computer-assisted identification of lung segments in CT images is subject of this work.Methods: The authors present a new interactive approach for the segmentation of lung segments that uses the Euclidean distance of each point in the lung to the segmental branches of the pulmonary artery. The aim is tomore » analyze the potential of the method. Detailed manual pulmonary artery segmentations are used to achieve the best possible segment approximation results. A detailed description of the method and its evaluation on 11 CT scans from clinical routine are given.Results: An accuracy of 2–3 mm is measured for the segment boundaries computed by the pulmonary artery-based method. On average, maximum deviations of 8 mm are observed. 135 intersegmental pulmonary veins detected in the 11 test CT scans serve as reference data. Furthermore, a comparison of the presented pulmonary artery-based approach to a similar approach that uses the Euclidean distance to the segmental branches of the bronchial tree is presented. It shows a significantly higher accuracy for the pulmonary artery-based approach in lung regions at least 30 mm distal to the lung hilum.Conclusions: A pulmonary artery-based determination of lung segments in CT images is promising. In the tests, the pulmonary artery-based determination has been shown to be superior to the bronchial tree-based determination. The suitability of the segment approximation method for application in the planning of segment resections in clinical practice has already been verified in experimental cases. However, automation of the method accompanied by an evaluation on a larger number of test cases is required before application in the daily clinical routine.« less

Characterization of Human Torso Vascular Morphometry in Normotensive and Hypotensive Trauma Patients

DTIC Science & Technology

2015-07-01

Aorta Wall Measures Merged for Analysis Landmarks & User-aided Segmentation 5cm Volume...with Centerline Measures AORTA PROCESSING VENA CAVA PROCESSING Basic Morphomics Scan Identification Aorta Centerline Segmented Aorta and Vena...Analysis 49 Data Presentation Aorta  Radius  Popula/on       Normotensive   Hypotensive  

Segmenting Images for a Better Diagnosis

NASA Technical Reports Server (NTRS)

2004-01-01

NASA's Hierarchical Segmentation (HSEG) software has been adapted by Bartron Medical Imaging, LLC, for use in segmentation feature extraction, pattern recognition, and classification of medical images. Bartron acquired licenses from NASA Goddard Space Flight Center for application of the HSEG concept to medical imaging, from the California Institute of Technology/Jet Propulsion Laboratory to incorporate pattern-matching software, and from Kennedy Space Center for data-mining and edge-detection programs. The Med-Seg[TM] united developed by Bartron provides improved diagnoses for a wide range of medical images, including computed tomography scans, positron emission tomography scans, magnetic resonance imaging, ultrasound, digitized Z-ray, digitized mammography, dental X-ray, soft tissue analysis, and moving object analysis. It also can be used in analysis of soft-tissue slides. Bartron's future plans include the application of HSEG technology to drug development. NASA is advancing it's HSEG software to learn more about the Earth's magnetosphere.

Optimization of the scan protocols for CT-based material extraction in small animal PET/CT studies

NASA Astrophysics Data System (ADS)

Yang, Ching-Ching; Yu, Jhih-An; Yang, Bang-Hung; Wu, Tung-Hsin

2013-12-01

We investigated the effects of scan protocols on CT-based material extraction to minimize radiation dose while maintaining sufficient image information in small animal studies. The phantom simulation experiments were performed with the high dose (HD), medium dose (MD) and low dose (LD) protocols at 50, 70 and 80 kVp with varying mA s. The reconstructed CT images were segmented based on Hounsfield unit (HU)-physical density (ρ) calibration curves and the dual-energy CT-based (DECT) method. Compared to the (HU;ρ) method performed on CT images acquired with the 80 kVp HD protocol, a 2-fold improvement in segmentation accuracy and a 7.5-fold reduction in radiation dose were observed when the DECT method was performed on CT images acquired with the 50/80 kVp LD protocol, showing the possibility to reduce radiation dose while achieving high segmentation accuracy.

Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning

NASA Astrophysics Data System (ADS)

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

2017-02-01

In developing treatment of cardiovascular diseases, short axis cine MRI has been used as a standard technique for understanding the global structural and functional characteristics of the heart, e.g. ventricle dimensions, stroke volume and ejection fraction. To conduct an accurate assessment, heart structures need to be segmented from the cine MRI images with high precision, which could be a laborious task when performed manually. Herein a fully automatic framework is proposed for the segmentation of the left ventricle from the slices of short axis cine MRI scans of porcine subjects using a deep learning approach. For training the deep learning models, which generally requires a large set of data, a public database of human cine MRI scans is used. Experiments on the 3150 cine slices of 7 porcine subjects have shown that when comparing the automatic and manual segmentations the mean slice-wise Dice coefficient is about 0.930, the point-to-curve error is 1.07 mm, and the mean slice-wise Hausdorff distance is around 3.70 mm, which demonstrates the accuracy and robustness of the proposed inter-species translational approach.

Grammar-based Automatic 3D Model Reconstruction from Terrestrial Laser Scanning Data

NASA Astrophysics Data System (ADS)

Yu, Q.; Helmholz, P.; Belton, D.; West, G.

2014-04-01

The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules. Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account.

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.

Segmentation of 830- and 1310-nm LASIK corneal optical coherence tomography images

NASA Astrophysics Data System (ADS)

Li, Yan; Shekhar, Raj; Huang, David

2002-05-01

Optical coherence tomography (OCT) provides a non-contact and non-invasive means to visualize the corneal anatomy at micron scale resolution. We obtained corneal images from an arc-scanning (converging) OCT system operating at a wavelength of 830nm and a fan-shaped-scanning high-speed OCT system with an operating wavelength of 1310nm. Different scan protocols (arc/fan) and data acquisition rates, as well as wavelength dependent bio-tissue backscatter contrast and optical absorption, make the images acquired using the two systems different. We developed image-processing algorithms to automatically detect the air-tear interface, epithelium-Bowman's layer interface, laser in-situ keratomileusis (LASIK) flap interface, and the cornea-aqueous interface in both kinds of images. The overall segmentation scheme for 830nm and 1310nm OCT images was similar, although different strategies were adopted for specific processing approaches. Ultrasound pachymetry measurements of the corneal thickness and Placido-ring based corneal topography measurements of the corneal curvature were made on the same day as the OCT examination. Anterior/posterior corneal surface curvature measurement with OCT was also investigated. Results showed that automated segmentation of OCT images could evaluate anatomic outcome of LASIK surgery.

GRAPhEME: a setup to measure (n, xn γ) reaction cross sections

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

Henning, Greg; Bacquias, A.; Capdevielle, O.

2015-07-01

Most of nuclear reactor developments are using evaluated data base for numerical simulations. However, the considered databases present still large uncertainties and disagreements. To improve their level of precision, new measurements are needed, in particular for (n, xn) reactions, which are of great importance as they modify the neutron spectrum, the neutron population, and produce radioactive species. The IPHC group started an experimental program to measure (n, xn gamma) reaction cross sections using prompt gamma spectroscopy and neutron energy determination by time of flight. Measurements of (n, xn gamma) cross section have been performed for {sup 235,238}U, {sup 232}Th, {supmore » nat,182,183,184,186}W, {sup nat}Zr. The experimental setup is installed at the neutron beam at GELINA (Geel, Belgium). The setup has recently been upgraded with the addition of a highly segmented 36 pixels planar HPGe detector. Significant efforts have been made to reduce radiation background and electromagnetic perturbations. The setup is equipped with a high rate digital acquisition system. The analysis of the segmented detector data requires a specific procedure to account for cross signals between pixels. An overall attention is paid to the precision of the measurement. The setup characteristic and the analysis procedure will be presented along with the acquisition and analysis challenges. Examples of results and their impact on models will be discussed. (authors)« less

SU-F-SPS-10: The Dosimetric Comparison of GammaKnife and Cyberknife Treatment Plans for Brain SRS Treatment

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

Sanli, E; Mabhouti, H; Cebe, M

Purpose: Brain stereotactic radiosurgery (SRS) involves the use of precisely directed, single session radiation to create a desired radiobiologic response within the brain target with acceptable minimal effects on surrounding structures or tissues. In this study, the dosimetric comparison of GammaKnife perfection and Cyberknife M6 treatment plans were made. Methods: Treatment plannings were done for GammaKnife perfection unit using Gammaplan treatment planning system (TPS) on the CT scan of head and neck randophantom simulating the treatment of sterotactic treatments for one brain metastasis. The dose distribution were calculated using TMR 10 algorithm. The treatment planning for the same target weremore » also done for Cyberknife M6 machine using Multiplan (TPS) with Monte Carlo algorithm. Using the same film batch, the net OD to dose calibration curve was obtained using both machine by delivering 0- 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. Dose distribution were measured using EBT3 film dosimeter. The measured and calculated doses were compared. Results: The dose distribution in the target and 2 cm beyond the target edge were calculated on TPSs and measured using EBT3 film. For cyberknife treatment plans, the gamma analysis passing rates between measured and calculated dose distributions were 99.2% and 96.7% for target and peripheral region of target respectively. For gammaknife treatment plans, the gamma analysis passing rates were 98.9% and 93.2% for target and peripheral region of target respectively. Conclusion: The study shows that dosimetrically comparable plans are achievable with Cyberknife and GammaKnife. Although TMR 10 algorithm predicts the target dose.« less

A Set of Image Processing Algorithms for Computer-Aided Diagnosis in Nuclear Medicine Whole Body Bone Scan Images

NASA Astrophysics Data System (ADS)

Huang, Jia-Yann; Kao, Pan-Fu; Chen, Yung-Sheng

2007-06-01

Adjustment of brightness and contrast in nuclear medicine whole body bone scan images may confuse nuclear medicine physicians when identifying small bone lesions as well as making the identification of subtle bone lesion changes in sequential studies difficult. In this study, we developed a computer-aided diagnosis system, based on the fuzzy sets histogram thresholding method and anatomical knowledge-based image segmentation method that was able to analyze and quantify raw image data and identify the possible location of a lesion. To locate anatomical reference points, the fuzzy sets histogram thresholding method was adopted as a first processing stage to suppress the soft tissue in the bone images. Anatomical knowledge-based image segmentation method was then applied to segment the skeletal frame into different regions of homogeneous bones. For the different segmented bone regions, the lesion thresholds were set at different cut-offs. To obtain lesion thresholds in different segmented regions, the ranges and standard deviations of the image's gray-level distribution were obtained from 100 normal patients' whole body bone images and then, another 62 patients' images were used for testing. The two groups of images were independent. The sensitivity and the mean number of false lesions detected were used as performance indices to evaluate the proposed system. The overall sensitivity of the system is 92.1% (222 of 241) and 7.58 false detections per patient scan image. With a high sensitivity and an acceptable false lesions detection rate, this computer-aided automatic lesion detection system is demonstrated as useful and will probably in the future be able to help nuclear medicine physicians to identify possible bone lesions.

Effect of Emphysema on CT Scan Measures of Airway Dimensions in Smokers

PubMed Central

Han, MeiLan K.; Come, Carolyn E.; San José Estépar, Raúl; Ross, James C.; Kim, Victor; Dransfield, Mark T.; Curran-Everett, Douglas; Schroeder, Joyce D.; Lynch, David A.; Tschirren, Juerg; Silverman, Edwin K.; Washko, George R.

2013-01-01

Background: In CT scans of smokers with COPD, the subsegmental airway wall area percent (WA%) is greater and more strongly correlated with FEV1 % predicted than WA% obtained in the segmental airways. Because emphysema is linked to loss of airway tethering and may limit airway expansion, increases in WA% may be related to emphysema and not solely to remodeling. We aimed to first determine whether the stronger association of subsegmental vs segmental WA% with FEV1 % predicted is mitigated by emphysema and, second, to assess the relationships among emphysema, WA%, and total bronchial area (TBA). Methods: We analyzed CT scan segmental and subsegmental WA% (WA% = 100 × wall area/TBA) of six bronchial paths and corresponding lobar emphysema, lung function, and clinical data in 983 smokers with COPD. Results: Compared with segmental WA%, the subsegmental WA% had a greater effect on FEV1% predicted (−0.8% to −1.7% vs −1.9% to −2.6% per 1-unit increase in WA%, respectively; P < .05 for most bronchial paths). After adjusting for emphysema, the association between subsegmental WA% and FEV1 % predicted was weakened in two bronchial paths. Increases in WA% between bronchial segments correlated directly with emphysema in all bronchial paths (P < .05). In multivariate regression models, emphysema was directly related to subsegmental WA% in most bronchial paths and inversely related to subsegmental TBA in all bronchial paths. Conclusion: The greater effect of subsegmental WA% on airflow obstruction is mitigated by emphysema. Part of the emphysema effect might be due to loss of airway tethering, leading to a reduction in TBA and an increase in WA%. Trial registry: ClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov PMID:23460155

Primary gamma rays. [resulting from cosmic ray interaction with interstellar matter

NASA Technical Reports Server (NTRS)

Fichtel, C. E.

1974-01-01

Within this galaxy, cosmic rays reveal their presence in interstellar space and probably in source regions by their interactions with interstellar matter which lead to gamma rays with a very characteristic energy spectrum. From the study of the intensity of the high energy gamma radiation as a function of galactic longitude, it is already clear that cosmic rays are almost certainly not uniformly distributed in the galaxy and are not concentrated in the center of the galaxy. The galactic cosmic rays appear to be tied to galactic structural features, presumably by the galactic magnetic fields which are in turn held by the matter in the arm segments and the clouds. On the extragalactic scale, it is now possible to say that cosmic rays are not universal at the density seen near the earth. The diffuse celestial gamma ray spectrum that is observed presents the interesting possibility of cosmological studies and possible evidence for a residual universal cosmic ray density, which is much lower than the present galactic cosmic ray density.

Predicting Future Morphological Changes of Lesions from Radiotracer Uptake in 18F-FDG-PET Images

PubMed Central

Bagci, Ulas; Yao, Jianhua; Miller-Jaster, Kirsten; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on 18F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 18F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75±1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUVmax (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUVmax. We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16). PMID:23431398

Local SIMPLE multi-atlas-based segmentation applied to lung lobe detection on chest CT

NASA Astrophysics Data System (ADS)

Agarwal, M.; Hendriks, E. A.; Stoel, B. C.; Bakker, M. E.; Reiber, J. H. C.; Staring, M.

2012-02-01

For multi atlas-based segmentation approaches, a segmentation fusion scheme which considers local performance measures may be more accurate than a method which uses a global performance measure. We improve upon an existing segmentation fusion method called SIMPLE and extend it to be localized and suitable for multi-labeled segmentations. We demonstrate the algorithm performance on 23 CT scans of COPD patients using a leave-one- out experiment. Our algorithm performs significantly better (p < 0.01) than majority voting, STAPLE, and SIMPLE, with a median overlap of the fissure of 0.45, 0.48, 0.55 and 0.6 for majority voting, STAPLE, SIMPLE, and the proposed algorithm, respectively.

Solubility Enhancement of Steviol Glycosides and Characterization of Their Inclusion Complexes with Gamma-Cyclodextrin

PubMed Central

Upreti, Mani; Strassburger, Ken; Chen, You L.; Wu, Shaoxiong; Prakash, Indra

2011-01-01

Steviol glycosidesrebaudioside (reb) A, C and D have low aqueous solubilities. To improve their aqueous solubilities, inclusion complex of steviol glycosides, reb A, C and D and gamma cyclodextrin were prepared by freeze drying method and further characterized by means of differential scanning calorimetry, Fourier transform infrared spectroscopy and Raman spectroscopy. The effect of gamma cyclodextrin on chemical shifts of the steviol glycosides was also studied in proton NMR experiments as well as in solid state 13C CP/MAS NMR experiments. These results indicated that the steviol glycosides were clearly in inclusion complex formation with the gamma cyclodextrin which also results in solubility enhancement of these steviol glycosides. Phase solubility studies showed that amounts of soluble reb A, C and D increased with increasing amounts of gamma cyclodextrin indicating formation of 1:1 stoichiometric and higher order inclusion complexes. PMID:22174615

Effects of cobalt on the microstructure of Udimet 700. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Engel, M. A.

1982-01-01

Cobalt, a critical and "strategic" alloying element in many superalloys, was systematically substituted by nickel in experimental alloys Udimet 700 containing 0.1, 4.3, 8.6, 12.8 and the standard 17.0 wt.% cobalt. Electrolytic and chemical extraction techniques, X-ray diffraction, scanning electron and optical microscopy were used for the microstructural studies. The total weight fraction of gamma' was not significantly affected by the cobalt content, although a difference in the size and quantities of the primary and secondary gamma' phases was apparent. The lattice parameters of the gamma' were found to increase with increasing cobalt content while the lattice mismatch between the gamma matrix and gamma' phases decreased. Other significant effects of cobalt on the weight fraction, distribution and formation of the carbide and boride phases as well as the relative stability of the experimental alloys during long-time aging are also discussed.

Stacked search for time shifted high energy neutrinos from gamma ray bursts with the Antares neutrino telescope

NASA Astrophysics Data System (ADS)

Adrián-Martínez, S.; Albert, A.; André, M.; Anghinolfi, M.; Anton, G.; Ardid, M.; Aubert, J.-J.; Baret, B.; Barrios-Marti, J.; Basa, S.; Bertin, V.; Biagi, S.; Bormuth, R.; Bouwhuis, M. C.; Bruijn, R.; Brunner, J.; Busto, J.; Capone, A.; Caramete, L.; Carr, J.; Chiarusi, T.; Circella, M.; Coniglione, R.; Costantini, H.; Coyle, P.; Creusot, A.; Dekeyser, I.; Deschamps, A.; De Bonis, G.; Distefano, C.; Donzaud, C.; Dornic, D.; Drouhin, D.; Dumas, A.; Eberl, T.; Elsässer, D.; Enzenhöfer, A.; Fehn, K.; Felis, I.; Fermani, P.; Folger, F.; Fusco, L. A.; Galatà, S.; Gay, P.; Geißelsöder, S.; Geyer, K.; Giordano, V.; Gleixner, A.; Gracia-Ruiz, R.; Graf, K.; Hallmann, S.; van Haren, H.; Heijboer, A. J.; Hello, Y.; Hernández-Rey, J. J.; Hößl, J.; Hofestädt, J.; Hugon, C.; James, C. W.; de Jong, M.; Kadler, M.; Kalekin, O.; Katz, U.; Kießling, D.; Kooijman, P.; Kouchner, A.; Kreter, M.; Kreykenbohm, I.; Kulikovskiy, V.; Lahmann, R.; Lefèvre, D.; Leonora, E.; Loucatos, S.; Marcelin, M.; Margiotta, A.; Marinelli, A.; Martínez-Mora, J. A.; Mathieu, A.; Michael, T.; Migliozzi, P.; Moussa, A.; Müller, C.; Nezri, E.; Păvălaş, G. E.; Pellegrino, C.; Perrina, C.; Piattelli, P.; Popa, V.; Pradier, T.; Racca, C.; Riccobene, G.; Richter, R.; Roensch, K.; Saldaña, M.; Samtleben, D. F. E.; Sánchez-Losa, A.; Sanguineti, M.; Sapienza, P.; Schmid, J.; Schnabel, J.; Schüssler, F.; Seitz, T.; Sieger, C.; Spurio, M.; Steijger, J. J. M.; Stolarczyk, Th.; Taiuti, M.; Tamburini, C.; Trovato, A.; Tselengidou, M.; Tönnis, C.; Vallage, B.; Vallée, C.; Van Elewyck, V.; Visser, E.; Vivolo, D.; Wagner, S.; Wilms, J.; Zornoza, J. D.; Zúñiga, J.

2017-01-01

A search for high-energy neutrino emission correlated with gamma-ray bursts outside the electromagnetic prompt-emission time window is presented. Using a stacking approach of the time delays between reported gamma-ray burst alerts and spatially coincident muon-neutrino signatures, data from the Antares neutrino telescope recorded between 2007 and 2012 are analysed. One year of public data from the IceCube detector between 2008 and 2009 have been also investigated. The respective timing profiles are scanned for statistically significant accumulations within 40 days of the Gamma Ray Burst, as expected from Lorentz Invariance Violation effects and some astrophysical models. No significant excess over the expected accidental coincidence rate could be found in either of the two data sets. The average strength of the neutrino signal is found to be fainter than one detectable neutrino signal per hundred gamma-ray bursts in the Antares data at 90% confidence level.

Helios-2 Vela-Ariel-5 gamma-ray burst source position

NASA Technical Reports Server (NTRS)

Cline, T. L.; Trainor, J. H.; Desai, U. D.; Klebesadel, R. W.; Ricketts, M.; Heluken, H.

1979-01-01

The gamma-ray burst of 28 January 1976, one of 18 events thus far detected in interplanetary space with Helios-2, was also observed with the Vela-5A, -6A and the Ariel-5 satellites. A small source field is obtained from the intersection of the region derived from the observed time delays between Helios-2 and Vela-5A and -6A with the source region independently found with the Ariel-5 X-ray detector. This area contains neither any steady X-ray source as scanned by HEAO-A nor any previously catalogued X-ray, radio or infrared sources, X-ray transients, quasars, seyferts, globular clusters, flare stars, pulsars, white dwarfs or high energy gamma-ray sources. The region is however, within the source field of a gamma-ray transient observed in 1974, which exhibited nuclear gamma-ray line structure.

A novel fibrinogen variant--Praha I: hypofibrinogenemia associated with gamma Gly351Ser substitution.

PubMed

Kotlín, Roman; Chytilová, Martina; Suttnar, Jirí; Salaj, Peter; Riedel, Tomás; Santrůcek, Jirí; Klener, Pavel; Dyr, Jan Evangelista

2007-05-01

A 25-yr-old man from Prague had abnormal bleeding after several surgical operations with low fibrinogen level and hypofibrinogenemia was suspected. The patient, 25 yr-old male had a low fibrinogen concentration as determined by the thrombin time and immunoturbidimetrical method. His 48-yr-old mother presented with normal coagulation tests, normal fibrinogen level and reported no history of bleeding. To identify the genetic mutation responsible for this hypofibrinogen, genomic DNA extracted from the blood was analyzed. Fibrin polymerization measurement, kinetics of fibrinopeptide release, fibrinogen clottability measurement, mass spectroscopy, and scanning electron microscopy were performed. DNA sequencing showed heterogeneous fibrinogen gammaG351S mutation in the propositus. The mutant chain was found not to be expressed to the circulation by matrix-assisted laser desorption/ionization time of flight mass spectrometry. Scanning electron micrographs of the patient's fibrin clot as well as kinetics of fibrinopeptide release and fibrin polymerization were found to be normal. A case of hypofibrinogenemia gammaG351S was found by routine coagulation testing and was genetically identified.

Crystalline gamma-Al2O3 physical vapour deposition-coating for steel thixoforging tools.

PubMed

Bobzin, K; Hirt, G; Bagcivan, N; Khizhnyakova, L; Ewering, M

2011-10-01

The process of thixoforming, which has been part of many researches during the last decades, combines the advantages of forging and casting for the shaping of metallic components. But due to the high temperatures of semi-solid steel alloys high demands on the tools are requested. To resists the thermal and mechanical loads (wear, friction, thermal and thermomechanical fatigue) protecting thin films are necessary. In this regard crystalline gamma-Al2O3 deposited via Physical Vapour Deposition (PVD) is a promising candidate: It exhibits high thermal stability, high oxidation resistance and high hot hardness. In the present work the application of a (Ti, Al)N/gamma-Al2O3 coating deposited by means of Magnetron Sputter Ion Plating in an industrial coating unit is presented. The coating was analysed by means of Rockwell test, nanoindentation, and Scanning Electron Microscopy (SEM). The coated tool was tested in thixoforging experiments with steel grade X210CrW12 (AlSI D6). The surface of the coated dies was examined with Scanning Electron Microscope (SEM) after 22, 42, 90 and 170 forging cycles.

Helicopter Electro-Optical System Display Requirements. 1. The Effects of CRT Display Size, System Gamma Function, and Terrain Type on Pilots’ Required Display Luminance

DTIC Science & Technology

1980-03-01

full-color terrain model designed to 6 ,. .. ., CINE MA ICiINE h MRO FILM To’ N U Ix v M C CTMIRROR MONITOR FRESNEL REAR- PROJECTION SCREEN Z...ments of NOE flight, recorded on videotape. One segment was filmed at the Hunter-Liggett, Calif., ntilitary reservation, and the other segment was... filmed near Fort Rucker, Ala. The tapes were viewed by each participant pilot on the 13-cm and the 26-cm CRT displays. They could attenuate the display

Influence of gamma irradiation on the surface morphology, XRD and thermophysical properties of silicide hexoboride

NASA Astrophysics Data System (ADS)

Mirzayev, Matlab N.; Mehdiyeva, Ravan N.; Garibov, Ramin G.; Ismayilova, Narmin A.; Jabarov, Sakin H.

2018-05-01

In this study, compounds of B6Si were irradiated using a 60Co gamma source that have an energy line of 1.25 MeV at the absorbed dose rates from 14.6 kGy to 194.4 kGy. Surface morphology images of the sample obtained by Scanning Electron Microscope (SEM) show that the crystal structure at a high absorbed doses (D ≥ 145.8kGy) starts to be destroyed. X-ray diffraction studies revealed that with increasing radiation absorption dose, the spectrum intensity of the sample was decreased 1.96 times compared with the initial value. Thermal properties were studied by Differential scanning calorimetry (DSC) method in the temperature range of 30-1000∘C.

Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds.

PubMed

Hamraz, Hamid; Contreras, Marco A; Zhang, Jun

2017-07-28

Airborne laser scanning (LiDAR) point clouds over large forested areas can be processed to segment individual trees and subsequently extract tree-level information. Existing segmentation procedures typically detect more than 90% of overstory trees, yet they barely detect 60% of understory trees because of the occlusion effect of higher canopy layers. Although understory trees provide limited financial value, they are an essential component of ecosystem functioning by offering habitat for numerous wildlife species and influencing stand development. Here we model the occlusion effect in terms of point density. We estimate the fractions of points representing different canopy layers (one overstory and multiple understory) and also pinpoint the required density for reasonable tree segmentation (where accuracy plateaus). We show that at a density of ~170 pt/m² understory trees can likely be segmented as accurately as overstory trees. Given the advancements of LiDAR sensor technology, point clouds will affordably reach this required density. Using modern computational approaches for big data, the denser point clouds can efficiently be processed to ultimately allow accurate remote quantification of forest resources. The methodology can also be adopted for other similar remote sensing or advanced imaging applications such as geological subsurface modelling or biomedical tissue analysis.

Identification of amino acids in the nicotinic acetylcholine receptor agonist binding site and ion channel photolabeled by 4-[(3-trifluoromethyl)-3H-diazirin-3-yl]benzoylcholine, a novel photoaffinity antagonist.

PubMed

Chiara, David C; Trinidad, Jonathan C; Wang, Dong; Ziebell, Michael R; Sullivan, Deirdre; Cohen, Jonathan B

2003-01-21

[(3)H]4-[(3-trifluoromethyl)-3H-diazirin-3-yl]benzoylcholine (TDBzcholine) was synthesized and used as a photoaffinity probe to map the orientation of an aromatic choline ester within the agonist binding sites of the Torpedo nicotinic acetylcholine receptor (nAChR). TDBzcholine acts as a nAChR competitive antagonist that binds at equilibrium with equal affinity to both agonist sites (K(D) approximately 10 microM). Upon UV irradiation (350 nm), nAChR-rich membranes equilibrated with [(3)H]TDBzcholine incorporate (3)H into the alpha, gamma, and delta subunits in an agonist-inhibitable manner. The specific residues labeled by [(3)H]TDBzcholine were determined by N-terminal sequence analysis of subunit fragments produced by enzymatic cleavage and purified by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and/or reversed-phase high-performance liquid chromatography. For the alpha subunit, [(3)H]TDBzcholine photoincorporated into alphaCys-192, alphaCys-193, and alphaPro-194. For the gamma and delta subunits, [(3)H]TDBzcholine incorporated into homologous leucine residues, gammaLeu-109 and deltaLeu-111. The photolabeling of these amino acids suggests that when the antagonist TDBzcholine occupies the agonist binding sites, the Cys-192-193 disulfide and Pro-194 from the alpha subunit Segment C are oriented toward the agonist site and are in proximity to gammaLeu-109/deltaLeu-111 in Segment E, a conclusion consistent with the structure of the binding site in the molluscan acetylcholine binding protein, a soluble protein that is homologous to the nAChR extracellular domain.

SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

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

Gupta, V; Wang, Y; Romero, A

2014-06-01

Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain groundmore » truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation method overcomes an important hurdle to the clinical implementation of online adaptive radiotherapy. Partial funding for this work was provided by Accuray Incorporated as part of a research collaboration with Erasmus MC Cancer Institute.« less

High-resolution radiography by means of a hodoscope

DOEpatents

De Volpi, Alexander

1978-01-01

The fast neutron hodoscope, a device that produces neutron radiographs with coarse space resolution in a short time, is modified to produce neutron or gamma radiographs of relatively thick samples and with high space resolution. The modification comprises motorizing a neutron and gamma collimator to permit a controlled scanning pattern, simultaneous collection of data in a number of hodoscope channels over a period of time, and computerized image reconstruction of the data thus gathered.

Computational efficient segmentation of cell nuclei in 2D and 3D fluorescent micrographs

NASA Astrophysics Data System (ADS)

De Vylder, Jonas; Philips, Wilfried

2011-02-01

This paper proposes a new segmentation technique developed for the segmentation of cell nuclei in both 2D and 3D fluorescent micrographs. The proposed method can deal with both blurred edges as with touching nuclei. Using a dual scan line algorithm its both memory as computational efficient, making it interesting for the analysis of images coming from high throughput systems or the analysis of 3D microscopic images. Experiments show good results, i.e. recall of over 0.98.

Assessment of a Microsoft Kinect-based 3D scanning system for taking body segment girth measurements: a comparison to ISAK and ISO standards.

PubMed

Clarkson, Sean; Wheat, Jon; Heller, Ben; Choppin, Simon

2016-01-01

Use of anthropometric data to infer sporting performance is increasing in popularity, particularly within elite sport programmes. Measurement typically follows standards set by the International Society for the Advancement of Kinanthropometry (ISAK). However, such techniques are time consuming, which reduces their practicality. Schranz et al. recently suggested 3D body scanners could replace current measurement techniques; however, current systems are costly. Recent interest in natural user interaction has led to a range of low-cost depth cameras capable of producing 3D body scans, from which anthropometrics can be calculated. A scanning system comprising 4 depth cameras was used to scan 4 cylinders, representative of the body segments. Girth measurements were calculated from the 3D scans and compared to gold standard measurements. Requirements of a Level 1 ISAK practitioner were met in all 4 cylinders, and ISO standards for scan-derived girth measurements were met in the 2 larger cylinders only. A fixed measurement bias was identified that could be corrected with a simple offset factor. Further work is required to determine comparable performance across a wider range of measurements performed upon living participants. Nevertheless, findings of the study suggest such a system offers many advantages over current techniques, having a range of potential applications.

Rotating-unbalanced-mass Devices for Scanning Balloon-borne Experiments, Free-flying Spacecraft, and Space Shuttle/space Station Experiments

NASA Technical Reports Server (NTRS)

Polites, Michael E.

1990-01-01

A new method is presented for scanning balloon-borne experiments, free-flying spacecraft, and gimballed experiments mounted to the space shuttle or the space station. It uses rotating-unbalanced-mass (RUM) devices for generating circular, line, or raster scan patterns and an auxiliary control system for target acquisition, keeping the scan centered on the target, and producing complementary motion for raster scanning. It is ideal for applications where the only possible way to accomplish the required scan is to physically scan the entire experiment or spacecraft as in x ray and gamma ray experiments. In such cases, this new method should have advantages over prior methods in terms of either power, weight, cost, performance, stability, or a combination of these.

Glioblastoma Segmentation: Comparison of Three Different Software Packages.

PubMed

Fyllingen, Even Hovig; Stensjøen, Anne Line; Berntsen, Erik Magnus; Solheim, Ole; Reinertsen, Ingerid

2016-01-01

To facilitate a more widespread use of volumetric tumor segmentation in clinical studies, there is an urgent need for reliable, user-friendly segmentation software. The aim of this study was therefore to compare three different software packages for semi-automatic brain tumor segmentation of glioblastoma; namely BrainVoyagerTM QX, ITK-Snap and 3D Slicer, and to make data available for future reference. Pre-operative, contrast enhanced T1-weighted 1.5 or 3 Tesla Magnetic Resonance Imaging (MRI) scans were obtained in 20 consecutive patients who underwent surgery for glioblastoma. MRI scans were segmented twice in each software package by two investigators. Intra-rater, inter-rater and between-software agreement was compared by using differences of means with 95% limits of agreement (LoA), Dice's similarity coefficients (DSC) and Hausdorff distance (HD). Time expenditure of segmentations was measured using a stopwatch. Eighteen tumors were included in the analyses. Inter-rater agreement was highest for BrainVoyager with difference of means of 0.19 mL and 95% LoA from -2.42 mL to 2.81 mL. Between-software agreement and 95% LoA were very similar for the different software packages. Intra-rater, inter-rater and between-software DSC were ≥ 0.93 in all analyses. Time expenditure was approximately 41 min per segmentation in BrainVoyager, and 18 min per segmentation in both 3D Slicer and ITK-Snap. Our main findings were that there is a high agreement within and between the software packages in terms of small intra-rater, inter-rater and between-software differences of means and high Dice's similarity coefficients. Time expenditure was highest for BrainVoyager, but all software packages were relatively time-consuming, which may limit usability in an everyday clinical setting.

Automated assessment of aortic and main pulmonary arterial diameters using model-based blood vessel segmentation for predicting chronic thromboembolic pulmonary hypertension in low-dose CT lung screening

NASA Astrophysics Data System (ADS)

Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Sugiura, Toshihiko; Tanabe, Nobuhiro; Kusumoto, Masahiko; Eguchi, Kenji; Kaneko, Masahiro

2018-02-01

Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by obstruction of the pulmonary vasculature by residual organized thrombi. A morphological abnormality inside mediastinum of CTEPH patient is enlargement of pulmonary artery. This paper presents an automated assessment of aortic and main pulmonary arterial diameters for predicting CTEPH in low-dose CT lung screening. The distinctive feature of our method is to segment aorta and main pulmonary artery using both of prior probability and vascular direction which were estimated from mediastinal vascular region using principal curvatures of four-dimensional hyper surface. The method was applied to two datasets, 64 lowdose CT scans of lung cancer screening and 19 normal-dose CT scans of CTEPH patients through the training phase with 121 low-dose CT scans. This paper demonstrates effectiveness of our method for predicting CTEPH in low-dose CT screening.

Effect of gamma irradiation on ethylene propylene diene terpolymer rubber composites

NASA Astrophysics Data System (ADS)

Abou Zeid, M. M.; Rabie, S. T.; Nada, A. A.; Khalil, A. M.; Hilal, R. H.

2008-01-01

Composites of ethylene propylene dine terpolymer rubber (EPDM), high density polyethylene (HDPE) and ground tire rubber powder (GTR) at different ratios were subjected to gamma irradiation at various doses up to 250 kGy. The physical, mechanical and thermal properties were investigated as a function of irradiation dose and blend composition. Gamma irradiation led to a significant improvement in the properties for all blend compositions. The results indicate that the improvement in properties is inversely proportional to the substituted ratio of GTR, attributed to the development of an interfacial adhesion between GTR and blend components. The results were confirmed by examining the fracture surfaces by scanning electron microscopy.

Automated brain tumor segmentation in magnetic resonance imaging based on sliding-window technique and symmetry analysis.

PubMed

Lian, Yanyun; Song, Zhijian

2014-01-01

Brain tumor segmentation from magnetic resonance imaging (MRI) is an important step toward surgical planning, treatment planning, monitoring of therapy. However, manual tumor segmentation commonly used in clinic is time-consuming and challenging, and none of the existed automated methods are highly robust, reliable and efficient in clinic application. An accurate and automated tumor segmentation method has been developed for brain tumor segmentation that will provide reproducible and objective results close to manual segmentation results. Based on the symmetry of human brain, we employed sliding-window technique and correlation coefficient to locate the tumor position. At first, the image to be segmented was normalized, rotated, denoised, and bisected. Subsequently, through vertical and horizontal sliding-windows technique in turn, that is, two windows in the left and the right part of brain image moving simultaneously pixel by pixel in two parts of brain image, along with calculating of correlation coefficient of two windows, two windows with minimal correlation coefficient were obtained, and the window with bigger average gray value is the location of tumor and the pixel with biggest gray value is the locating point of tumor. At last, the segmentation threshold was decided by the average gray value of the pixels in the square with center at the locating point and 10 pixels of side length, and threshold segmentation and morphological operations were used to acquire the final tumor region. The method was evaluated on 3D FSPGR brain MR images of 10 patients. As a result, the average ratio of correct location was 93.4% for 575 slices containing tumor, the average Dice similarity coefficient was 0.77 for one scan, and the average time spent on one scan was 40 seconds. An fully automated, simple and efficient segmentation method for brain tumor is proposed and promising for future clinic use. Correlation coefficient is a new and effective feature for tumor location.

Expression of peroxisome proliferator-activated receptor gamma (PPAR-gamma) in canine nasal carcinomas.

PubMed

Paciello, O; Borzacchiello, G; Varricchio, E; Papparella, S

2007-10-01

Peroxisome proliferator-activated receptor gamma (PPAR-gamma) is a ligand-activated transcriptional factor belonging to the steroid receptor superfamily. PPAR-gamma is expressed in multiple normal and neoplastic tissues, such as the breast, colon, lung, ovary and placenta. In addition to adipogenic and anti-inflammatory effects, PPAR-gamma activation has been shown to be anti-proliferative by its differentiation-promoting effect, suggesting that activation of PPAR-gamma may be useful in slowing or arresting the proliferation of de-differentiated tumour cells. In this study, we investigated the expression of PPAR-gamma in normal and neoplastic canine nasal epithelium. Twenty-five samples composed of five normal nasal epithelia and 20 canine nasal carcinomas, were immunohistochemically stained for PPAR-gamma. The specificity of the antibody was verified by Western Blot analysis. Confocal laser scanning microscopical investigation was also performed. In normal epithelium, the staining pattern was cytoplasmic and polarized at the cellular free edge. In carcinomas, the neoplastic cells showed mainly strong cytoplasmatic PPAR-gamma expression; moreover, perinuclear immunoreactivity was also detected and few neoplastic cells exhibited a nuclear positivity. Our results demonstrate different patterns of PPAR-gamma expression in normal canine nasal epithelium when compared with canine nasal carcinoma. The importance of this transcription factor in the pathophysiology of several different tumours has stimulated much research in this field and has opened new opportunities for the treatment of the tumours.

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.

Development of representative magnetic resonance imaging-based atlases of the canine brain and evaluation of three methods for atlas-based segmentation.

PubMed

Milne, Marjorie E; Steward, Christopher; Firestone, Simon M; Long, Sam N; O'Brien, Terrence J; Moffat, Bradford A

2016-04-01

To develop representative MRI atlases of the canine brain and to evaluate 3 methods of atlas-based segmentation (ABS). 62 dogs without clinical signs of epilepsy and without MRI evidence of structural brain disease. The MRI scans from 44 dogs were used to develop 4 templates on the basis of brain shape (brachycephalic, mesaticephalic, dolichocephalic, and combined mesaticephalic and dolichocephalic). Atlas labels were generated by segmenting the brain, ventricular system, hippocampal formation, and caudate nuclei. The MRI scans from the remaining 18 dogs were used to evaluate 3 methods of ABS (manual brain extraction and application of a brain shape-specific template [A], automatic brain extraction and application of a brain shape-specific template [B], and manual brain extraction and application of a combined template [C]). The performance of each ABS method was compared by calculation of the Dice and Jaccard coefficients, with manual segmentation used as the gold standard. Method A had the highest mean Jaccard coefficient and was the most accurate ABS method assessed. Measures of overlap for ABS methods that used manual brain extraction (A and C) ranged from 0.75 to 0.95 and compared favorably with repeated measures of overlap for manual extraction, which ranged from 0.88 to 0.97. Atlas-based segmentation was an accurate and repeatable method for segmentation of canine brain structures. It could be performed more rapidly than manual segmentation, which should allow the application of computer-assisted volumetry to large data sets and clinical cases and facilitate neuroimaging research and disease diagnosis.

Fast-neutron and gamma-ray imaging with a capillary liquid xenon converter coupled to a gaseous photomultiplier

NASA Astrophysics Data System (ADS)

Israelashvili, I.; Coimbra, A. E. C.; Vartsky, D.; Arazi, L.; Shchemelinin, S.; Caspi, E. N.; Breskin, A.

2017-09-01

Gamma-ray and fast-neutron imaging was performed with a novel liquid xenon (LXe) scintillation detector read out by a Gaseous Photomultiplier (GPM). The 100 mm diameter detector prototype comprised a capillary-filled LXe converter/scintillator, coupled to a triple-THGEM imaging-GPM, with its first electrode coated by a CsI UV-photocathode, operated in Ne/5%CH4 at cryogenic temperatures. Radiation localization in 2D was derived from scintillation-induced photoelectron avalanches, measured on the GPM's segmented anode. The localization properties of 60Co gamma-rays and a mixed fast-neutron/gamma-ray field from an AmBe neutron source were derived from irradiation of a Pb edge absorber. Spatial resolutions of 12± 2 mm and 10± 2 mm (FWHM) were reached with 60Co and AmBe sources, respectively. The experimental results are in good agreement with GEANT4 simulations. The calculated ultimate expected resolutions for our application-relevant 4.4 and 15.1 MeV gamma-rays and 1-15 MeV neutrons are 2-4 mm and ~ 2 mm (FWHM), respectively. These results indicate the potential applicability of the new detector concept to Fast-Neutron Resonance Radiography (FNRR) and Dual-Discrete-Energy Gamma Radiography (DDEGR) of large objects.

Contour maps of lunar remanent magnetic fields

NASA Technical Reports Server (NTRS)

Hood, L. L.; Russell, C. T.; Coleman, P. J., Jr.

1981-01-01

The 2605 usable orbits of Apollo 15 and 16 subsatellite magnetometer data have been reexamined for intervals suitable for analysis of crustal magnetic anomalies. To minimize plasma-related disturbances, segments from 274 of these orbits were selected from times when the moon was either in a lobe of the geomagnetic tail or in the solar wind with the subsatellites in the lunar wake. External field contributions which remained in the selected intervals were minimized by (1) quadratic detrending of individual orbit segments with lengths much greater than anomaly wavelengths and (2) two-dimensional filtering with minimum passed wavelengths less than or equal to anomaly wavelengths. Improvements in coverage, accuracy, and resolution of previously published anomaly maps produced from these data are obtained. In addition to improved maps of the Reiner Gamma and Van de Graaff-Aitken anomalies studied previously, a third region of relatively high-amplitude anomalies centered near the crater Gerasimovich on the southeastern far side has been mapped. Both the Van de Graaff-Aitken region and the Gerasimovich region are marked by the general occurrence of extensive groups of Reiner Gamma-type swirls.

TCR gamma chain diversity in the spleen of the duckbill platypus (Ornithorhynchus anatinus).

PubMed

Parra, Zuly E; Arnold, Tamara; Nowak, Melissa A; Hellman, Lars; Miller, Robert D

2006-01-01

TCR gamma (TRG) chain diversity in splenic gammadelta T cells was determined for an egg-laying mammal (or monotreme), the duckbill platypus. Three distinct V subgroups were found in the expressed TRG chains and these three subgroups are members of a clade not found so far in eutherian mammals or birds. Each subgroup contains approximately five V gene segments, and their overall divergence is much less than is found in eutherians and birds, consistent with their recent evolution from an ancestral V gene segment. The platypus TRG locus also contains three C region genes and many of the residues involved in TCR function, such as interactions with CD3, were conserved in the monotreme C regions. All non-eutherian mammals (monotremes and marsupials) lacked the second cysteine residue necessary to form the intradomain disulfide bond in the C region, a loss apparently due to independent mutations in marsupials and monotremes. Monotreme TRGC regions also had among the most variation in the length of the connecting peptide region described for any species due to repeated motifs.

Automatic detection of axillary lymphadenopathy on CT scans of untreated chronic lymphocytic leukemia patients

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Hua, Jeremy; Chellappa, Vivek; Petrick, Nicholas; Sahiner, Berkman; Farooqui, Mohammed; Marti, Gerald; Wiestner, Adrian; Summers, Ronald M.

2012-03-01

Patients with chronic lymphocytic leukemia (CLL) have an increased frequency of axillary lymphadenopathy. Pretreatment CT scans can be used to upstage patients at the time of presentation and post-treatment CT scans can reduce the number of complete responses. In the current clinical workflow, the detection and diagnosis of lymph nodes is usually performed manually by examining all slices of CT images, which can be time consuming and highly dependent on the observer's experience. A system for automatic lymph node detection and measurement is desired. We propose a computer aided detection (CAD) system for axillary lymph nodes on CT scans in CLL patients. The lung is first automatically segmented and the patient's body in lung region is extracted to set the search region for lymph nodes. Multi-scale Hessian based blob detection is then applied to detect potential lymph nodes within the search region. Next, the detected potential candidates are segmented by fast level set method. Finally, features are calculated from the segmented candidates and support vector machine (SVM) classification is utilized for false positive reduction. Two blobness features, Frangi's and Li's, are tested and their free-response receiver operating characteristic (FROC) curves are generated to assess system performance. We applied our detection system to 12 patients with 168 axillary lymph nodes measuring greater than 10 mm. All lymph nodes are manually labeled as ground truth. The system achieved sensitivities of 81% and 85% at 2 false positives per patient for Frangi's and Li's blobness, respectively.

Initial Gamma Spectrometry Examination of the AGR-3/4 Irradiation

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

Harp, Jason M.; Demkowicz, Paul A.; Stempien, John D.

2016-11-01

The initial results from gamma spectrometry examination of the different components from the combined third and fourth US Advanced Gas Reactor Fuel Development TRISO-coated particle fuel irradiation tests (AGR-3/4) have been analyzed. This experiment was designed to provide information about in-pile fission product migration. In each of the 12 capsules, a single stack of four compacts with designed-to-fail particles surrounded by two graphitic diffusion rings (inner and outer) and a graphite sink were irradiated in the Idaho National Laboratory’s Advanced Test Reactor. Gamma spectrometry has been used to evaluate the gamma-emitting fission product inventory of compacts from the irradiation andmore » evaluate the burnup of these compacts based on the activity of the radioactive cesium isotopes (Cs-134 and Cs-137) in the compacts. Burnup from gamma spectrometry compares well with predicted burnup from simulations. Additionally, inner and outer rings were also examined by gamma spectrometry both to evaluate the fission product inventory and the distribution of gamma-emitting fission products within the rings using gamma emission computed tomography. The cesium inventory of the scanned rings compares acceptably well with the expected inventory from fission product transport modeling. The inventory of the graphite fission product sinks is also being evaluated by gamma spectrometry.« less

Effects of CT-based attenuation correction of rat microSPECT images on relative myocardial perfusion and quantitative tracer uptake

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

Strydhorst, Jared H., E-mail: jared.strydhorst@gmail.com; Ruddy, Terrence D.; Wells, R. Glenn

2015-04-15

Purpose: Our goal in this work was to investigate the impact of CT-based attenuation correction on measurements of rat myocardial perfusion with {sup 99m}Tc and {sup 201}Tl single photon emission computed tomography (SPECT). Methods: Eight male Sprague-Dawley rats were injected with {sup 99m}Tc-tetrofosmin and scanned in a small animal pinhole SPECT/CT scanner. Scans were repeated weekly over a period of 5 weeks. Eight additional rats were injected with {sup 201}Tl and also scanned following a similar protocol. The images were reconstructed with and without attenuation correction, and the relative perfusion was analyzed with the commercial cardiac analysis software. The absolutemore » uptake of {sup 99m}Tc in the heart was also quantified with and without attenuation correction. Results: For {sup 99m}Tc imaging, relative segmental perfusion changed by up to +2.1%/−1.8% as a result of attenuation correction. Relative changes of +3.6%/−1.0% were observed for the {sup 201}Tl images. Interscan and inter-rat reproducibilities of relative segmental perfusion were 2.7% and 3.9%, respectively, for the uncorrected {sup 99m}Tc scans, and 3.6% and 4.3%, respectively, for the {sup 201}Tl scans, and were not significantly affected by attenuation correction for either tracer. Attenuation correction also significantly increased the measured absolute uptake of tetrofosmin and significantly altered the relationship between the rat weight and tracer uptake. Conclusions: Our results show that attenuation correction has a small but statistically significant impact on the relative perfusion measurements in some segments of the heart and does not adversely affect reproducibility. Attenuation correction had a small but statistically significant impact on measured absolute tracer uptake.« less

High pitch third generation dual-source CT: Coronary and Cardiac Visualization on Routine Chest CT

PubMed Central

Sandfort, Veit; Ahlman, Mark; Jones, Elizabeth; Selwaness, Mariana; Chen, Marcus; Folio, Les; Bluemke, David A.

2016-01-01

Background Chest CT scans are frequently performed in radiology departments but have not previously contained detailed depiction of cardiac structures. Objectives To evaluate myocardial and coronary visualization on high-pitch non-gated CT of the chest using 3rd generation dual-source computed tomography (CT). Methods Cardiac anatomy of patients who had 3rd generation, non-gated high pitch contrast enhanced chest CT and who also had prior conventional (low pitch) chest CT as part of a chest abdomen pelvis exam was evaluated. Cardiac image features were scored by reviewers blinded to diagnosis and pitch. Paired analysis was performed. Results 3862 coronary segments and 2220 cardiac structures were evaluated by two readers in 222 CT scans. Most patients (97.2%) had chest CT for oncologic evaluation. The median pitch was 2.34 (IQR 2.05, 2.65) in high pitch and 0.8 (IQR 0.8, 0.8) in low pitch scans (p<0.001). High pitch CT showed higher image visualization scores for all cardiovascular structures compared with conventional pitch scans (p<0.0001). Coronary arteries were visualized in 9 coronary segments per exam in high pitch scans versus 2 segments for conventional pitch (p<0.0001). Radiation exposure was lower in the high pitch group compared with the conventional pitch group (median CTDIvol 10.83 vs. 12.36 mGy and DLP 790 vs. 827 mGycm respectively, p <0.01 for both) with comparable image noise (p=0.43). Conclusion Myocardial structure and coronary arteries are frequently visualized on non-gated 3rd generation chest CT. These results raise the question of whether the heart and coronary arteries should be routinely interpreted on routine chest CT that is otherwise obtained for non-cardiac indications. PMID:27133589

Patient‐specific CT dosimetry calculation: a feasibility study

PubMed Central

Xie, Huchen; Cheng, Jason Y.; Ning, Holly; Zhuge, Ying; Miller, Robert W.

2011-01-01

Current estimation of radiation dose from computed tomography (CT) scans on patients has relied on the measurement of Computed Tomography Dose Index (CTDI) in standard cylindrical phantoms, and calculations based on mathematical representations of “standard man”. Radiation dose to both adult and pediatric patients from a CT scan has been a concern, as noted in recent reports. The purpose of this study was to investigate the feasibility of adapting a radiation treatment planning system (RTPS) to provide patient‐specific CT dosimetry. A radiation treatment planning system was modified to calculate patient‐specific CT dose distributions, which can be represented by dose at specific points within an organ of interest, as well as organ dose‐volumes (after image segmentation) for a GE Light Speed Ultra Plus CT scanner. The RTPS calculation algorithm is based on a semi‐empirical, measured correction‐based algorithm, which has been well established in the radiotherapy community. Digital representations of the physical phantoms (virtual phantom) were acquired with the GE CT scanner in axial mode. Thermoluminescent dosimeter (TLDs) measurements in pediatric anthropomorphic phantoms were utilized to validate the dose at specific points within organs of interest relative to RTPS calculations and Monte Carlo simulations of the same virtual phantoms (digital representation). Congruence of the calculated and measured point doses for the same physical anthropomorphic phantom geometry was used to verify the feasibility of the method. The RTPS algorithm can be extended to calculate the organ dose by calculating a dose distribution point‐by‐point for a designated volume. Electron Gamma Shower (EGSnrc) codes for radiation transport calculations developed by National Research Council of Canada (NRCC) were utilized to perform the Monte Carlo (MC) simulation. In general, the RTPS and MC dose calculations are within 10% of the TLD measurements for the infant and child chest scans. With respect to the dose comparisons for the head, the RTPS dose calculations are slightly higher (10%–20%) than the TLD measurements, while the MC results were within 10% of the TLD measurements. The advantage of the algebraic dose calculation engine of the RTPS is a substantially reduced computation time (minutes vs. days) relative to Monte Carlo calculations, as well as providing patient‐specific dose estimation. It also provides the basis for a more elaborate reporting of dosimetric results, such as patient specific organ dose volumes after image segmentation. PACS numbers: 87.55.D‐, 87.57.Q‐, 87.53.Bn, 87.55.K‐ PMID:22089016

A comparison of two prompt gamma imaging techniques with collimator-based cameras for range verification in proton therapy

NASA Astrophysics Data System (ADS)

Lin, Hsin-Hon; Chang, Hao-Ting; Chao, Tsi-Chian; Chuang, Keh-Shih

2017-08-01

In vivo range verification plays an important role in proton therapy to fully utilize the benefits of the Bragg peak (BP) for delivering high radiation dose to tumor, while sparing the normal tissue. For accurately locating the position of BP, camera equipped with collimators (multi-slit and knife-edge collimator) to image prompt gamma (PG) emitted along the proton tracks in the patient have been proposed for range verification. The aim of the work is to compare the performance of multi-slit collimator and knife-edge collimator for non-invasive proton beam range verification. PG imaging was simulated by a validated GATE/GEANT4 Monte Carlo code to model the spot-scanning proton therapy and cylindrical PMMA phantom in detail. For each spot, 108 protons were simulated. To investigate the correlation between the acquired PG profile and the proton range, the falloff regions of PG profiles were fitted with a 3-line-segment curve function as the range estimate. Factors including the energy window setting, proton energy, phantom size, and phantom shift that may influence the accuracy of detecting range were studied. Results indicated that both collimator systems achieve reasonable accuracy and good response to the phantom shift. The accuracy of range predicted by multi-slit collimator system is less affected by the proton energy, while knife-edge collimator system can achieve higher detection efficiency that lead to a smaller deviation in predicting range. We conclude that both collimator systems have potentials for accurately range monitoring in proton therapy. It is noted that neutron contamination has a marked impact on range prediction of the two systems, especially in multi-slit system. Therefore, a neutron reduction technique for improving the accuracy of range verification of proton therapy is needed.

Identification of the gamma subunit-interacting residues on photoreceptor cGMP phosphodiesterase, PDE6alpha '.

PubMed

Granovsky, A E; Artemyev, N O

2000-12-29

Photoreceptor cGMP phosphodiesterase (PDE6) is the effector enzyme in the G protein-mediated visual transduction cascade. In the dark, the activity of PDE6 is shut off by the inhibitory gamma subunit (Pgamma). Chimeric proteins between cone PDE6alpha' and cGMP-binding and cGMP-specific PDE (PDE5) have been constructed and expressed in Sf9 cells to study the mechanism of inhibition of PDE6 catalytic activity by Pgamma. Substitution of the segment PDE5-(773-820) by the corresponding PDE6alpha'-(737-784) sequence in the wild-type PDE5 or in a PDE5/PDE6alpha' chimera containing the catalytic domain of PDE5 results in chimeric enzymes capable of inhibitory interaction with Pgamma. The catalytic properties of the chimeric PDEs remained similar to those of PDE5. Ala-scanning mutational analysis of the Pgamma-binding region, PDE6alpha'-(750-760), revealed PDE6alpha' residues essential for the interaction. The M758A mutation markedly impaired and the Q752A mutation moderately impaired the inhibition of chimeric PDE by Pgamma. The analysis of the catalytic properties of mutant PDEs and a model of the PDE6 catalytic domain suggest that residues Met(758) and Gln(752) directly bind Pgamma. A model of the PDE6 catalytic site shows that PDE6alpha'-(750-760) forms a loop at the entrance to the cGMP-binding pocket. Binding of Pgamma to Met(758) would effectively block access of cGMP to the catalytic cavity, providing a structural basis for the mechanism of PDE6 inhibition.

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

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

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.

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

PubMed

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

2016-05-01

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

ARIES NDA Robot operators` manual

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

Scheer, N.L.; Nelson, D.C.

1998-05-01

The ARIES NDA Robot is an automation device for servicing the material movements for a suite of Non-destructive assay (NDA) instruments. This suite of instruments includes a calorimeter, a gamma isotopic system, a segmented gamma scanner (SGS), and a neutron coincidence counter (NCC). Objects moved by the robot include sample cans, standard cans, and instrument plugs. The robot computer has an RS-232 connection with the NDA Host computer, which coordinates robot movements and instrument measurements. The instruments are expected to perform measurements under the direction of the Host without operator intervention. This user`s manual describes system startup, using the mainmore » menu, manual operation, and error recovery.« less

In vivo imaging of the rodent eye with swept source/Fourier domain OCT

PubMed Central

Liu, Jonathan J.; Grulkowski, Ireneusz; Kraus, Martin F.; Potsaid, Benjamin; Lu, Chen D.; Baumann, Bernhard; Duker, Jay S.; Hornegger, Joachim; Fujimoto, James G.

2013-01-01

Swept source/Fourier domain OCT is demonstrated for in vivo imaging of the rodent eye. Using commercial swept laser technology, we developed a prototype OCT imaging system for small animal ocular imaging operating in the 1050 nm wavelength range at an axial scan rate of 100 kHz with ~6 µm axial resolution. The high imaging speed enables volumetric imaging with high axial scan densities, measuring high flow velocities in vessels, and repeated volumetric imaging over time. The 1050 nm wavelength light provides increased penetration into tissue compared to standard commercial OCT systems at 850 nm. The long imaging range enables multiple operating modes for imaging the retina, posterior eye, as well as anterior eye and full eye length. A registration algorithm using orthogonally scanned OCT volumetric data sets which can correct motion on a per A-scan basis is applied to compensate motion and merge motion corrected volumetric data for enhanced OCT image quality. Ultrahigh speed swept source OCT is a promising technique for imaging the rodent eye, proving comprehensive information on the cornea, anterior segment, lens, vitreous, posterior segment, retina and choroid. PMID:23412778

Earth Observatory Satellite system definition study. Report 5: System design and specifications. Volume 4: Mission peculiar spacecraft segment and module specifications

NASA Technical Reports Server (NTRS)

1974-01-01

The specifications for the Earth Observatory Satellite (EOS) peculiar spacecraft segment and associated subsystems and modules are presented. The specifications considered include the following: (1) wideband communications subsystem module, (2) mission peculiar software, (3) hydrazine propulsion subsystem module, (4) solar array assembly, and (5) the scanning spectral radiometer.

Radiation dose in 320-slice multidetector cardiac CT: a single center experience of evolving dose minimization.

PubMed

Tung, Matthew K; Cameron, James D; Casan, Joshua M; Crossett, Marcus; Troupis, John M; Meredith, Ian T; Seneviratne, Sujith K

2013-01-01

Minimization of radiation exposure remains an important subject that occurs in parallel with advances in scanner technology. We report our experience of evolving radiation dose and its determinants after the introduction of 320-multidetector row cardiac CT within a single tertiary cardiology referral service. Four cohorts of consecutive patients (total 525 scans), who underwent cardiac CT at defined time points as early as 2008, are described. These include a cohort just after scanner installation, after 2 upgrades of the operating system, and after introduction of an adaptive iterative image reconstruction algorithm. The proportions of nondiagnostic coronary artery segments and studies with nondiagnostic segments were compared between cohorts. Significant reductions were observed in median radiation doses in all cohorts compared with the initial cohort (P < .001). Median dose-length product fell from 944 mGy · cm (interquartile range [IQR], 567.3-1426.5 mGy · cm) to 156 mGy · cm (IQR, 99.2-265.0 mGy · cm). Although the proportion of prospectively triggered scans has increased, reductions in radiation dose have occurred independently of distribution of scan formats. In multiple regression that combined all groups, determinants of dose-length product were tube output, the number of cardiac cycles scanned, tube voltage, scan length, scan format, body mass index, phase width, and heart rate (adjusted R(2) = 0.85, P < .001). The proportion of nondiagnostic coronary artery segments was slightly increased in group 4 (2.9%; P < .01). While maintaining diagnostic quality in 320-multidetector row cardiac CT, the radiation dose has decreased substantially because of a combination of dose-reduction protocols and technical improvements. Continued minimization of radiation dose will increase the potential for cardiac CT to expand as a cardiac imaging modality. Copyright © 2013 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Validation of Body Volume Acquisition by Using Elliptical Zone Method.

PubMed

Chiu, C-Y; Pease, D L; Fawkner, S; Sanders, R H

2016-12-01

The elliptical zone method (E-Zone) can be used to obtain reliable body volume data including total body volume and segmental volumes with inexpensive and portable equipment. The purpose of this research was to assess the accuracy of body volume data obtained from E-Zone by comparing them with those acquired from the 3D photonic scanning method (3DPS). 17 male participants with diverse somatotypes were recruited. Each participant was scanned twice on the same day by a 3D whole-body scanner and photographed twice for the E-Zone analysis. The body volume data acquired from 3DPS was regarded as the reference against which the accuracy of the E-Zone was assessed. The relative technical error of measurement (TEM) of total body volume estimations was around 3% for E-Zone. E-Zone can estimate the segmental volumes of upper torso, lower torso, thigh, shank, upper arm and lower arm accurately (relative TEM<10%) but the accuracy for small segments including the neck, hand and foot were poor. In summary, E-Zone provides a reliable, inexpensive, portable, and simple method to obtain reasonable estimates of total body volume and to indicate segmental volume distribution. © Georg Thieme Verlag KG Stuttgart · New York.

Hierarchical extraction of urban objects from mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Zhao, Gang; Dai, Wenxia

2015-01-01

Point clouds collected in urban scenes contain a huge number of points (e.g., billions), numerous objects with significant size variability, complex and incomplete structures, and variable point densities, raising great challenges for the automated extraction of urban objects in the field of photogrammetry, computer vision, and robotics. This paper addresses these challenges by proposing an automated method to extract urban objects robustly and efficiently. The proposed method generates multi-scale supervoxels from 3D point clouds using the point attributes (e.g., colors, intensities) and spatial distances between points, and then segments the supervoxels rather than individual points by combining graph based segmentation with multiple cues (e.g., principal direction, colors) of the supervoxels. The proposed method defines a set of rules for merging segments into meaningful units according to types of urban objects and forms the semantic knowledge of urban objects for the classification of objects. Finally, the proposed method extracts and classifies urban objects in a hierarchical order ranked by the saliency of the segments. Experiments show that the proposed method is efficient and robust for extracting buildings, streetlamps, trees, telegraph poles, traffic signs, cars, and enclosures from mobile laser scanning (MLS) point clouds, with an overall accuracy of 92.3%.

Interactive Volumetry Of Liver Ablation Zones.

PubMed

Egger, Jan; Busse, Harald; Brandmaier, Philipp; Seider, Daniel; Gawlitza, Matthias; Strocka, Steffen; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Kainz, Bernhard; Hann, Alexander; Chen, Xiaojun; Alhonnoro, Tuomas; Pollari, Mika; Schmalstieg, Dieter; Moche, Michael

2015-10-20

Percutaneous radiofrequency ablation (RFA) is a minimally invasive technique that destroys cancer cells by heat. The heat results from focusing energy in the radiofrequency spectrum through a needle. Amongst others, this can enable the treatment of patients who are not eligible for an open surgery. However, the possibility of recurrent liver cancer due to incomplete ablation of the tumor makes post-interventional monitoring via regular follow-up scans mandatory. These scans have to be carefully inspected for any conspicuousness. Within this study, the RF ablation zones from twelve post-interventional CT acquisitions have been segmented semi-automatically to support the visual inspection. An interactive, graph-based contouring approach, which prefers spherically shaped regions, has been applied. For the quantitative and qualitative analysis of the algorithm's results, manual slice-by-slice segmentations produced by clinical experts have been used as the gold standard (which have also been compared among each other). As evaluation metric for the statistical validation, the Dice Similarity Coefficient (DSC) has been calculated. The results show that the proposed tool provides lesion segmentation with sufficient accuracy much faster than manual segmentation. The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow.

Interactive Volumetry Of Liver Ablation Zones

PubMed Central

Egger, Jan; Busse, Harald; Brandmaier, Philipp; Seider, Daniel; Gawlitza, Matthias; Strocka, Steffen; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Kainz, Bernhard; Hann, Alexander; Chen, Xiaojun; Alhonnoro, Tuomas; Pollari, Mika; Schmalstieg, Dieter; Moche, Michael

2015-01-01

Percutaneous radiofrequency ablation (RFA) is a minimally invasive technique that destroys cancer cells by heat. The heat results from focusing energy in the radiofrequency spectrum through a needle. Amongst others, this can enable the treatment of patients who are not eligible for an open surgery. However, the possibility of recurrent liver cancer due to incomplete ablation of the tumor makes post-interventional monitoring via regular follow-up scans mandatory. These scans have to be carefully inspected for any conspicuousness. Within this study, the RF ablation zones from twelve post-interventional CT acquisitions have been segmented semi-automatically to support the visual inspection. An interactive, graph-based contouring approach, which prefers spherically shaped regions, has been applied. For the quantitative and qualitative analysis of the algorithm’s results, manual slice-by-slice segmentations produced by clinical experts have been used as the gold standard (which have also been compared among each other). As evaluation metric for the statistical validation, the Dice Similarity Coefficient (DSC) has been calculated. The results show that the proposed tool provides lesion segmentation with sufficient accuracy much faster than manual segmentation. The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow. PMID:26482818

Interactive Volumetry Of Liver Ablation Zones

NASA Astrophysics Data System (ADS)

Egger, Jan; Busse, Harald; Brandmaier, Philipp; Seider, Daniel; Gawlitza, Matthias; Strocka, Steffen; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Kainz, Bernhard; Hann, Alexander; Chen, Xiaojun; Alhonnoro, Tuomas; Pollari, Mika; Schmalstieg, Dieter; Moche, Michael

2015-10-01

Percutaneous radiofrequency ablation (RFA) is a minimally invasive technique that destroys cancer cells by heat. The heat results from focusing energy in the radiofrequency spectrum through a needle. Amongst others, this can enable the treatment of patients who are not eligible for an open surgery. However, the possibility of recurrent liver cancer due to incomplete ablation of the tumor makes post-interventional monitoring via regular follow-up scans mandatory. These scans have to be carefully inspected for any conspicuousness. Within this study, the RF ablation zones from twelve post-interventional CT acquisitions have been segmented semi-automatically to support the visual inspection. An interactive, graph-based contouring approach, which prefers spherically shaped regions, has been applied. For the quantitative and qualitative analysis of the algorithm’s results, manual slice-by-slice segmentations produced by clinical experts have been used as the gold standard (which have also been compared among each other). As evaluation metric for the statistical validation, the Dice Similarity Coefficient (DSC) has been calculated. The results show that the proposed tool provides lesion segmentation with sufficient accuracy much faster than manual segmentation. The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow.

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

PubMed Central

Guo, Wei; Li, Qiang

2014-01-01

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

Temporally consistent probabilistic detection of new multiple sclerosis lesions in brain MRI.

PubMed

Elliott, Colm; Arnold, Douglas L; Collins, D Louis; Arbel, Tal

2013-08-01

Detection of new Multiple Sclerosis (MS) lesions on magnetic resonance imaging (MRI) is important as a marker of disease activity and as a potential surrogate for relapses. We propose an approach where sequential scans are jointly segmented, to provide a temporally consistent tissue segmentation while remaining sensitive to newly appearing lesions. The method uses a two-stage classification process: 1) a Bayesian classifier provides a probabilistic brain tissue classification at each voxel of reference and follow-up scans, and 2) a random-forest based lesion-level classification provides a final identification of new lesions. Generative models are learned based on 364 scans from 95 subjects from a multi-center clinical trial. The method is evaluated on sequential brain MRI of 160 subjects from a separate multi-center clinical trial, and is compared to 1) semi-automatically generated ground truth segmentations and 2) fully manual identification of new lesions generated independently by nine expert raters on a subset of 60 subjects. For new lesions greater than 0.15 cc in size, the classifier has near perfect performance (99% sensitivity, 2% false detection rate), as compared to ground truth. The proposed method was also shown to exceed the performance of any one of the nine expert manual identifications.

HNF-1B specifically regulates the transcription of the {gamma}a-subunit of the Na{sup +}/K{sup +}-ATPase

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

Ferre, Silvia; Veenstra, Gert Jan C.; Bouwmeester, Rianne

2011-01-07

Research highlights: {yields} Defects in HNF-1B transcription factor affect Mg{sup 2+} handling in the distal kidney. {yields} {gamma}a- and {gamma}b- subunits of the Na{sup +}/K{sup +}-ATPase colocalize in the distal convoluted tubule of the nephron. {yields} HNF-1B specifically activates {gamma}a expression. {yields} HNF-1B mutants have a dominant negative effect on wild type HNF-1B activity. {yields} Defective transcription of {gamma}a may promote renal Mg{sup 2+} wasting. -- Abstract: Hepatocyte nuclear factor-1B (HNF-1B) is a transcription factor involved in embryonic development and tissue-specific gene expression in several organs, including the kidney. Recently heterozygous mutations in the HNF1B gene have been identified inmore » patients with hypomagnesemia due to renal Mg{sup 2+} wasting. Interestingly, ChIP-chip data revealed HNF-1B binding sites in the FXYD2 gene, encoding the {gamma}-subunit of the Na{sup +}/K{sup +}-ATPase. The {gamma}-subunit has been described as one of the molecular players in the renal Mg{sup 2+} reabsorption in the distal convoluted tubule (DCT). Of note, the FXYD2 gene can be alternatively transcribed into two main variants, namely {gamma}a and {gamma}b. In the present study, we demonstrated via two different reporter gene assays that HNF-1B specifically acts as an activator of the {gamma}a-subunit, whereas the {gamma}b-subunit expression was not affected. Moreover, the HNF-1B mutations H69fsdelAC, H324S325fsdelCA, Y352finsA and K156E, previously identified in patients with hypomagnesemia, prevented transcription activation of {gamma}a-subunit via a dominant negative effect on wild type HNF1-B. By immunohistochemistry, it was shown that the {gamma}a- and {gamma}b-subunits colocalize at the basolateral membrane of the DCT segment of mouse kidney. On the basis of these data, we suggest that abnormalities involving the HNF-1B gene may impair the relative abundance of {gamma}a and {gamma}b, thus affecting the transcellular Mg{sup 2+} reabsorption in the DCT.« less

Review methods for image segmentation from computed tomography images

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

Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik

Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affectmore » the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan.« less

RFA-cut: Semi-automatic segmentation of radiofrequency ablation zones with and without needles via optimal s-t-cuts.

PubMed

Egger, Jan; Busse, Harald; Brandmaier, Philipp; Seider, Daniel; Gawlitza, Matthias; Strocka, Steffen; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Kainz, Bernhard; Chen, Xiaojun; Hann, Alexander; Boechat, Pedro; Yu, Wei; Freisleben, Bernd; Alhonnoro, Tuomas; Pollari, Mika; Moche, Michael; Schmalstieg, Dieter

2015-01-01

In this contribution, we present a semi-automatic segmentation algorithm for radiofrequency ablation (RFA) zones via optimal s-t-cuts. Our interactive graph-based approach builds upon a polyhedron to construct the graph and was specifically designed for computed tomography (CT) acquisitions from patients that had RFA treatments of Hepatocellular Carcinomas (HCC). For evaluation, we used twelve post-interventional CT datasets from the clinical routine and as evaluation metric we utilized the Dice Similarity Coefficient (DSC), which is commonly accepted for judging computer aided medical segmentation tasks. Compared with pure manual slice-by-slice expert segmentations from interventional radiologists, we were able to achieve a DSC of about eighty percent, which is sufficient for our clinical needs. Moreover, our approach was able to handle images containing (DSC=75.9%) and not containing (78.1%) the RFA needles still in place. Additionally, we found no statistically significant difference (p<;0.423) between the segmentation results of the subgroups for a Mann-Whitney test. Finally, to the best of our knowledge, this is the first time a segmentation approach for CT scans including the RFA needles is reported and we show why another state-of-the-art segmentation method fails for these cases. Intraoperative scans including an RFA probe are very critical in the clinical practice and need a very careful segmentation and inspection to avoid under-treatment, which may result in tumor recurrence (up to 40%). If the decision can be made during the intervention, an additional ablation can be performed without removing the entire needle. This decreases the patient stress and associated risks and costs of a separate intervention at a later date. Ultimately, the segmented ablation zone containing the RFA needle can be used for a precise ablation simulation as the real needle position is known.

Automated choroid segmentation of three-dimensional SD-OCT images by incorporating EDI-OCT images.

PubMed

Chen, Qiang; Niu, Sijie; Fang, Wangyi; Shuai, Yuanlu; Fan, Wen; Yuan, Songtao; Liu, Qinghuai

2018-05-01

The measurement of choroidal volume is more related with eye diseases than choroidal thickness, because the choroidal volume can reflect the diseases comprehensively. The purpose is to automatically segment choroid for three-dimensional (3D) spectral domain optical coherence tomography (SD-OCT) images. We present a novel choroid segmentation strategy for SD-OCT images by incorporating the enhanced depth imaging OCT (EDI-OCT) images. The down boundary of the choroid, namely choroid-sclera junction (CSJ), is almost invisible in SD-OCT images, while visible in EDI-OCT images. During the SD-OCT imaging, the EDI-OCT images can be generated for the same eye. Thus, we present an EDI-OCT-driven choroid segmentation method for SD-OCT images, where the choroid segmentation results of the EDI-OCT images are used to estimate the average choroidal thickness and to improve the construction of the CSJ feature space of the SD-OCT images. We also present a whole registration method between EDI-OCT and SD-OCT images based on retinal thickness and Bruch's Membrane (BM) position. The CSJ surface is obtained with a 3D graph search in the CSJ feature space. Experimental results with 768 images (6 cubes, 128 B-scan images for each cube) from 2 healthy persons, 2 age-related macular degeneration (AMD) and 2 diabetic retinopathy (DR) patients, and 210 B-scan images from other 8 healthy persons and 21 patients demonstrate that our method can achieve high segmentation accuracy. The mean choroid volume difference and overlap ratio for 6 cubes between our proposed method and outlines drawn by experts were -1.96µm3 and 88.56%, respectively. Our method is effective for the 3D choroid segmentation of SD-OCT images because the segmentation accuracy and stability are compared with the manual segmentation. Copyright © 2017. Published by Elsevier B.V.

The structure of control and data transfer management system for the GAMMA-400 scientific complex

NASA Astrophysics Data System (ADS)

Arkhangelskiy, A. I.; Bobkov, S. G.; Serdin, O. V.; Gorbunov, M. S.; Topchiev, N. P.

2016-02-01

A description of the control and data transfer management system for scientific instrumentation involved in the GAMMA-400 space project is given. The technical capabilities of all specialized equipment to provide the functioning of the scientific instrumentation and satellite support systems are unified in a single structure. Control of the scientific instruments is maintained using one-time pulse radio commands, as well as program commands in the form of 16-bit code words, which are transmitted via onboard control system and scientific data acquisition system. Up to 100 GByte of data per day can be transferred to the ground segment of the project. The correctness of the proposed and implemented structure, engineering solutions and electronic elemental base selection has been verified by the experimental working-off of the prototype of the GAMMA-400 scientific complex in laboratory conditions.

Assessing Temporal Behavior in LIDAR Point Clouds of Urban Environments

NASA Astrophysics Data System (ADS)

Schachtschneider, J.; Schlichting, A.; Brenner, C.

2017-05-01

Self-driving cars and robots that run autonomously over long periods of time need high-precision and up-to-date models of the changing environment. The main challenge for creating long term maps of dynamic environments is to identify changes and adapt the map continuously. Changes can occur abruptly, gradually, or even periodically. In this work, we investigate how dense mapping data of several epochs can be used to identify the temporal behavior of the environment. This approach anticipates possible future scenarios where a large fleet of vehicles is equipped with sensors which continuously capture the environment. This data is then being sent to a cloud based infrastructure, which aligns all datasets geometrically and subsequently runs scene analysis on it, among these being the analysis for temporal changes of the environment. Our experiments are based on a LiDAR mobile mapping dataset which consists of 150 scan strips (a total of about 1 billion points), which were obtained in multiple epochs. Parts of the scene are covered by up to 28 scan strips. The time difference between the first and last epoch is about one year. In order to process the data, the scan strips are aligned using an overall bundle adjustment, which estimates the surface (about one billion surface element unknowns) as well as 270,000 unknowns for the adjustment of the exterior orientation parameters. After this, the surface misalignment is usually below one centimeter. In the next step, we perform a segmentation of the point clouds using a region growing algorithm. The segmented objects and the aligned data are then used to compute an occupancy grid which is filled by tracing each individual LiDAR ray from the scan head to every point of a segment. As a result, we can assess the behavior of each segment in the scene and remove voxels from temporal objects from the global occupancy grid.

Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network.

PubMed

Prasoon, Adhish; Petersen, Kersten; Igel, Christian; Lauze, François; Dam, Erik; Nielsen, Mads

2013-01-01

Segmentation of anatomical structures in medical images is often based on a voxel/pixel classification approach. Deep learning systems, such as convolutional neural networks (CNNs), can infer a hierarchical representation of images that fosters categorization. We propose a novel system for voxel classification integrating three 2D CNNs, which have a one-to-one association with the xy, yz and zx planes of 3D image, respectively. We applied our method to the segmentation of tibial cartilage in low field knee MRI scans and tested it on 114 unseen scans. Although our method uses only 2D features at a single scale, it performs better than a state-of-the-art method using 3D multi-scale features. In the latter approach, the features and the classifier have been carefully adapted to the problem at hand. That we were able to get better results by a deep learning architecture that autonomously learns the features from the images is the main insight of this study.

Scanning and transmission electron microscopic analysis of ampullary segment of oviduct during estrous cycle in caprines.

PubMed

Sharma, R K; Singh, R; Bhardwaj, J K

2015-01-01

The ampullary segment of the mammalian oviduct provides suitable milieu for fertilization and development of zygote before implantation into uterus. It is, therefore, in the present study, the cyclic changes in the morphology of ampullary segment of goat oviduct were studied during follicular and luteal phases using scanning and transmission electron microscopy techniques. Topographical analysis revealed the presence of uniformly ciliated ampullary epithelia, concealing apical processes of non-ciliated cells along with bulbous secretory cells during follicular phase. The luteal phase was marked with decline in number of ciliated cells with increased occurrence of secretory cells. The ultrastructure analysis has demonstrated the presence of indented nuclear membrane, supranuclear cytoplasm, secretory granules, rough endoplasmic reticulum, large lipid droplets, apically located glycogen masses, oval shaped mitochondria in the secretory cells. The ciliated cells were characterized by the presence of elongated nuclei, abundant smooth endoplasmic reticulum, oval or spherical shaped mitochondria with crecentric cristae during follicular phase. However, in the luteal phase, secretory cells were possessing highly indented nucleus with diffused electron dense chromatin, hyaline nucleosol, increased number of lipid droplets. The ciliated cells had numerous fibrous granules and basal bodies. The parallel use of scanning and transmission electron microscopy techniques has enabled us to examine the cyclic and hormone dependent changes occurring in the topography and fine structure of epithelium of ampullary segment and its cells during different reproductive phases that will be great help in understanding major bottle neck that limits success rate in vitro fertilization and embryo transfer technology. © Wiley Periodicals, Inc.

Safe Zone Quantification of the Third Sacral Segment in Normal and Dysmorphic Sacra.

PubMed

Hwang, John S; Reilly, Mark C; Shaath, Mohammad K; Changoor, Stuart; Eastman, Jonathan; Routt, Milton Lee Chip; Sirkin, Michael S; Adams, Mark R

2018-04-01

To quantify the osseous anatomy of the dysmorphic third sacral segment and assess its ability to accommodate internal fixation. Retrospective chart review of a trauma database. University Level 1 Trauma Center. Fifty-nine patients over the age of 18 with computed tomography scans of the pelvis separated into 2 groups: a group with normal pelvic anatomy and a group with sacral dysmorphism. The sacral osseous area was measured on computed tomography scans in the axial, coronal, and sagittal planes in normal and dysmorphic pelves. These measurements were used to determine the possibility of accommodating a transiliac transsacral screw in the third sacral segment. In the normal group, the S3 coronal transverse width averaged 7.71 mm and the S3 axial transverse width averaged 7.12 mm. The mean S3 cross-sectional area of the normal group was 55.8 mm. The dysmorphic group was found to have a mean S3 coronal transverse width of 9.49 mm, an average S3 axial transverse width of 9.14 mm, and an S3 cross-sectional area of 77.9 mm. The third sacral segment of dysmorphic sacra has a larger osseous pathway available to safely accommodate a transiliac transsacral screw when compared with normal sacra. The S3 segment of dysmorphic sacra can serve as an additional site for screw placement when treating unstable posterior pelvic ring fractures.

Fully automatic segmentation of white matter hyperintensities in MR images of the elderly.

PubMed

Admiraal-Behloul, F; van den Heuvel, D M J; Olofsen, H; van Osch, M J P; van der Grond, J; van Buchem, M A; Reiber, J H C

2005-11-15

The role of quantitative image analysis in large clinical trials is continuously increasing. Several methods are available for performing white matter hyperintensity (WMH) volume quantification. They vary in the amount of the human interaction involved. In this paper, we describe a fully automatic segmentation that was used to quantify WMHs in a large clinical trial on elderly subjects. Our segmentation method combines information from 3 different MR images: proton density (PD), T2-weighted and fluid-attenuated inversion recovery (FLAIR) images; our method uses an established artificial intelligent technique (fuzzy inference system) and does not require extensive computations. The reproducibility of the segmentation was evaluated in 9 patients who underwent scan-rescan with repositioning; an inter-class correlation coefficient (ICC) of 0.91 was obtained. The effect of differences in image resolution was tested in 44 patients, scanned with 6- and 3-mm slice thickness FLAIR images; we obtained an ICC value of 0.99. The accuracy of the segmentation was evaluated on 100 patients for whom manual delineation of WMHs was available; the obtained ICC was 0.98 and the similarity index was 0.75. Besides the fact that the approach demonstrated very high volumetric and spatial agreement with expert delineation, the software did not require more than 2 min per patient (from loading the images to saving the results) on a Pentium-4 processor (512 MB RAM).

Automatic segmentation of thoracic aorta segments in low-dose chest CT

NASA Astrophysics Data System (ADS)

Noothout, Julia M. H.; de Vos, Bob D.; Wolterink, Jelmer M.; Išgum, Ivana

2018-03-01

Morphological analysis and identification of pathologies in the aorta are important for cardiovascular diagnosis and risk assessment in patients. Manual annotation is time-consuming and cumbersome in CT scans acquired without contrast enhancement and with low radiation dose. Hence, we propose an automatic method to segment the ascending aorta, the aortic arch and the thoracic descending aorta in low-dose chest CT without contrast enhancement. Segmentation was performed using a dilated convolutional neural network (CNN), with a receptive field of 131 × 131 voxels, that classified voxels in axial, coronal and sagittal image slices. To obtain a final segmentation, the obtained probabilities of the three planes were averaged per class, and voxels were subsequently assigned to the class with the highest class probability. Two-fold cross-validation experiments were performed where ten scans were used to train the network and another ten to evaluate the performance. Dice coefficients of 0.83 +/- 0.07, 0.86 +/- 0.06 and 0.88 +/- 0.05, and Average Symmetrical Surface Distances (ASSDs) of 2.44 +/- 1.28, 1.56 +/- 0.68 and 1.87 +/- 1.30 mm were obtained for the ascending aorta, the aortic arch and the descending aorta, respectively. The results indicate that the proposed method could be used in large-scale studies analyzing the anatomical location of pathology and morphology of the thoracic aorta.

Reproducibility measurements of three methods for calculating in vivo MR-based knee kinematics.

PubMed

Lansdown, Drew A; Zaid, Musa; Pedoia, Valentina; Subburaj, Karupppasamy; Souza, Richard; Benjamin, C; Li, Xiaojuan

2015-08-01

To describe three quantification methods for magnetic resonance imaging (MRI)-based knee kinematic evaluation and to report on the reproducibility of these algorithms. T2 -weighted, fast-spin echo images were obtained of the bilateral knees in six healthy volunteers. Scans were repeated for each knee after repositioning to evaluate protocol reproducibility. Semiautomatic segmentation defined regions of interest for the tibia and femur. The posterior femoral condyles and diaphyseal axes were defined using the previously defined tibia and femur. All segmentation was performed twice to evaluate segmentation reliability. Anterior tibial translation (ATT) and internal tibial rotation (ITR) were calculated using three methods: a tibial-based registration system, a combined tibiofemoral-based registration method with all manual segmentation, and a combined tibiofemoral-based registration method with automatic definition of condyles and axes. Intraclass correlation coefficients and standard deviations across multiple measures were determined. Reproducibility of segmentation was excellent (ATT = 0.98; ITR = 0.99) for both combined methods. ATT and ITR measurements were also reproducible across multiple scans in the combined registration measurements with manual (ATT = 0.94; ITR = 0.94) or automatic (ATT = 0.95; ITR = 0.94) condyles and axes. The combined tibiofemoral registration with automatic definition of the posterior femoral condyle and diaphyseal axes allows for improved knee kinematics quantification with excellent in vivo reproducibility. © 2014 Wiley Periodicals, Inc.

Commissioning of a new SeHCAT detector and comparison with an uncollimated gamma camera.

PubMed

Taylor, Jonathan C; Hillel, Philip G; Himsworth, John M

2014-10-01

Measurements of SeHCAT (tauroselcholic [75selenium] acid) retention have been used to diagnose bile acid malabsorption for a number of years. In current UK practice the vast majority of centres calculate uptake using an uncollimated gamma camera. Because of ever-increasing demands on gamma camera time, a new 'probe' detector was designed, assembled and commissioned. To validate the system, nine patients were scanned at day 0 and day 7 with both the new probe detector and an uncollimated gamma camera. Commissioning results were largely in line with expectations. Spatial resolution (full-width 95% of maximum) at 1 m was 36.6 cm, the background count rate was 24.7 cps and sensitivity at 1 m was 720.8 cps/MBq. The patient comparison study showed a mean absolute difference in retention measurements of 0.8% between the probe and uncollimated gamma camera, and SD of ± 1.8%. The study demonstrated that it is possible to create a simple, reproducible SeHCAT measurement system using a commercially available scintillation detector. Retention results from the probe closely agreed with those from the uncollimated gamma camera.

Catalysis study for space shuttle vehicle thermal protection systems. [for vehicle surface

NASA Technical Reports Server (NTRS)

Breen, J.; Rosner, D. E.; Delgass, W. N.; Nordine, P. C.; Cibrian, R.; Krishnan, N. G.

1973-01-01

Experimental results on the problem of reducing aerodynamic heating on space shuttle orbiter surfaces are presented. Data include: (1) development of a laboratory flow reactor technique for measuring gamma sub O and gamma sub N on candidate materials at surfaces, T sub w, in the nominal range 1000 to 2000, (2) measurements of gamma sub O and gamma sub N above 1000 K for both the glass coating of a reusable surface insulation material and the siliconized surface of a reinforced pyrolyzed plastic material, (3) measurement of the ablation behavior of the coated RPP material at T sub w is greater than or equal to 2150 K, (4) X-ray photoelectron spectral studies of the chemical constituents on these surfaces before and after dissociated gas exposure, (5) scanning electron micrograph examination of as-received and reacted specimens, and (6) development and exploitation of a method of predicting the aerodynamic heating consquences of these gamma sub O(T sub w) and gamma sub N(T sub w) measurements for critical locations on a radiation cooled orbiter vehicle.

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.

DSC studies on gamma irradiated poly(vinylidene fluoride) applied to high gamma dose dosimetry

NASA Astrophysics Data System (ADS)

Batista, Adriana S. M.; Faria, Luiz O.

2017-11-01

Poly(vinylidene fluoride) homopolymer (PVDF) was investigated for use on high gamma dose dosimetry. Samples were irradiated with gamma doses ranging from 100 kGy to 3000 kGy. Differential scanning calorimetry (DSC) was used to construct an unambiguous relationship between the melting transition latent heat (LM) and the absorbed dose (D). DSC thermograms were taken immediately, 1, 2 and 8 months after the irradiation process revealing that the LMx D relationship presented no change for doses ranging from 100 to 2750 kGy. FTIR and UV-Vis spectroscopy data revealed the radio-induction of C˭O and C˭C bonds. These radio-induced bonds were responsible by the chain stiffening and chain oxidation, respectively. SEM microscopy demonstrates that the spherulitic large crystalline structures present in pristine PVDF are destroyed with doses as low as 100 kGy. The DRX analysis revealed that the main effect of high gamma doses in the crystalline structure of PVDF is to provoke a change from the pristine PVDF α-phase to the γ-phase. Both the ability to detect gamma doses in a large dose range and the low fading features make PVDF homopolymers good candidates to be investigated as high gamma dose dosimeters.

Methods for increasing the sensitivity of gamma-ray imagers

DOEpatents

Mihailescu, Lucian [Pleasanton, CA; Vetter, Kai M [Alameda, CA; Chivers, Daniel H [Fremont, CA

2012-02-07

Methods are presented that increase the position resolution and granularity of double sided segmented semiconductor detectors. These methods increase the imaging resolution capability of such detectors, either used as Compton cameras, or as position sensitive radiation detectors in imagers such as SPECT, PET, coded apertures, multi-pinhole imagers, or other spatial or temporal modulated imagers.

Systems for increasing the sensitivity of gamma-ray imagers

DOEpatents

Mihailescu, Lucian; Vetter, Kai M.; Chivers, Daniel H.

2012-12-11

Systems that increase the position resolution and granularity of double sided segmented semiconductor detectors are provided. These systems increase the imaging resolution capability of such detectors, either used as Compton cameras, or as position sensitive radiation detectors in imagers such as SPECT, PET, coded apertures, multi-pinhole imagers, or other spatial or temporal modulated imagers.

Technical Note: Development of a 3D printed subresolution sandwich phantom for validation of brain SPECT analysis

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

Negus, Ian S.; Holmes, Robin B.; Thorne, Gareth C.

Purpose: To make an adaptable, head shaped radionuclide phantom to simulate molecular imaging of the brain using clinical acquisition and reconstruction protocols. This will allow the characterization and correction of scanner characteristics, and improve the accuracy of clinical image analysis, including the application of databases of normal subjects. Methods: A fused deposition modeling 3D printer was used to create a head shaped phantom made up of transaxial slabs, derived from a simulated MRI dataset. The attenuation of the printed polylactide (PLA), measured by means of the Hounsfield unit on CT scanning, was set to match that of the brain bymore » adjusting the proportion of plastic filament and air (fill ratio). Transmission measurements were made to verify the attenuation of the printed slabs. The radionuclide distribution within the phantom was created by adding {sup 99m}Tc pertechnetate to the ink cartridge of a paper printer and printing images of gray and white matter anatomy, segmented from the same MRI data. The complete subresolution sandwich phantom was assembled from alternate 3D printed slabs and radioactive paper sheets, and then imaged on a dual headed gamma camera to simulate an HMPAO SPECT scan. Results: Reconstructions of phantom scans successfully used automated ellipse fitting to apply attenuation correction. This removed the variability inherent in manual application of attenuation correction and registration inherent in existing cylindrical phantom designs. The resulting images were assessed visually and by count profiles and found to be similar to those from an existing elliptical PMMA phantom. Conclusions: The authors have demonstrated the ability to create physically realistic HMPAO SPECT simulations using a novel head-shaped 3D printed subresolution sandwich method phantom. The phantom can be used to validate all neurological SPECT imaging applications. A simple modification of the phantom design to use thinner slabs would make it suitable for use in PET.« less

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography.

PubMed

Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

2016-07-07

Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography

NASA Astrophysics Data System (ADS)

Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

2016-07-01

Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

Simultaneous and Sequential MS/MS Scan Combinations and Permutations in a Linear Quadrupole Ion Trap.

PubMed

Snyder, Dalton T; Szalwinski, Lucas J; Cooks, R Graham

2017-10-17

Methods of performing precursor ion scans as well as neutral loss scans in a single linear quadrupole ion trap have recently been described. In this paper we report methodology for performing permutations of MS/MS scan modes, that is, ordered combinations of precursor, product, and neutral loss scans following a single ion injection event. Only particular permutations are allowed; the sequences demonstrated here are (1) multiple precursor ion scans, (2) precursor ion scans followed by a single neutral loss scan, (3) precursor ion scans followed by product ion scans, and (4) segmented neutral loss scans. (5) The common product ion scan can be performed earlier in these sequences, under certain conditions. Simultaneous scans can also be performed. These include multiple precursor ion scans, precursor ion scans with an accompanying neutral loss scan, and multiple neutral loss scans. We argue that the new capability to perform complex simultaneous and sequential MS n operations on single ion populations represents a significant step in increasing the selectivity of mass spectrometry.

Skylab S-191 spectrometer single spectral scan analysis program. [user manual

NASA Technical Reports Server (NTRS)

Downes, E. L.

1974-01-01

Documentation and user information for the S-191 single spectral scan analysis program are reported. A breakdown of the computational algorithms is supplied, followed by the program listing and examples of sample output. A copy of the flow chart which describes the driver routine in the body of the main program segment is included.

Study of the effect of gamma irradiation on a commercial polycyclooctene I. Thermal and mechanical properties

NASA Astrophysics Data System (ADS)

García-Huete, N.; Laza, J. M.; Cuevas, J. M.; Vilas, J. L.; Bilbao, E.; León, L. M.

2014-09-01

A gamma radiation process for modification of commercial polymers is a widely applied technique to promote new physical, chemical and mechanical properties. Gamma irradiation originates free radicals able to induce chain scission or recombination of radicals, which induces annihilation, branching or crosslinking processes. The aim of this work is to research the structural, thermal and mechanical changes induced on a commercial polycyclooctene (PCO) when it is irradiated with a gamma source of 60Co at different doses (25-200 kGy). After gamma irradiation, gel content was determined by Soxhlet extraction in cyclohexane. Furthermore, thermal properties were evaluated before and after Soxhlet extraction by means of Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC), as well as mechanical properties were measured by Dynamic Mechanical Thermal Analysis (DMTA). The results showed the variations of the properties depending on the irradiation dose. Finally, a first approach to evaluate qualitatively the shape memory behaviour of all irradiated PCO samples was performed by a visually monitoring shape recovery process.

A Novel Study Connecting Ultra-High Energy Cosmic Rays, Neutrinos, and Gamma-Rays

NASA Astrophysics Data System (ADS)

Coenders, Stefan; Resconi, Elisa; Padovani, Paolo; Giommi, Paolo; Caccianiga, Lorenzo

We present a novel study connecting ultra-high energy cosmic rays, neutrinos, and gamma-rays with the objective to identify common counterparts of the three astrophysical messengers. In the test presented here, we first identify potential hadronic sources by filtering gamma-ray emitters that are in spatial coincidence with IceCube neutrinos. Subsequently, these objects are correlated against ultra-high energy cosmic rays detected by the Pierre Auger Observatory and the Telescope Array, scanning in gamma-ray flux and angular separation between sources and cosmic rays. A maximal excess of 80 cosmic rays (41.9 expected) is observed for the second catalog of hard Fermi-LAT objects of blazars of the high synchrotron peak type. This corresponds to a deviation from the null-hypothesis of 2.94σ . No excess is observed for objects not in spatial connection with neutrinos. The gamma-ray sources that make up the excess are blazars of the high synchrotron peak type.

Effects of gamma radiation on hard dental tissues of albino rats using scanning electron microscope - Part 1

NASA Astrophysics Data System (ADS)

El-Faramawy, Nabil; Ameen, Reham; El-Haddad, Khaled; Maghraby, Ahmed; El-Zainy, Medhat

2011-12-01

In the present study, 40 adult male albino rats were used to study the effect of gamma radiation on the hard dental tissues (enamel surface, dentinal tubules and the cementum surface). The rats were irradiated at 0.2, 0.5, 1.0, 2.0, 4.0 and 6.0 Gy gamma doses. The effects of irradiated hard dental tissues samples were investigated using a scanning electron microscope. For doses up to 0.5 Gy, there was no evidence of the existence of cracks on the enamel surface. With 1 Gy irradiation dose, cracks were clearly observed with localized erosive areas. At 2 Gy irradiation dose, the enamel showed morphological alterations as disturbed prismatic and interprismatic areas. An increase in dentinal tubules diameter and a contemporary inter-tubular dentine volume decrease were observed with higher irradiation dose. Concerning cementum, low doses,<0.5 Gy, showed surface irregularities and with increase in the irradiation dose to≥1 Gy, noticeable surface irregularities and erosive areas with decrease in Sharpey's fiber sites were observed. These observations could shed light on the hazardous effects of irradiation fields to the functioning of the human teeth.

Quantitative Laser-Saturated Fluorescence Measurements of Nitric Oxide in a Heptane Spray Flame

NASA Technical Reports Server (NTRS)

Cooper, Clayton S.; Laurendeau, Normand M.; Lee, Chi (Technical Monitor)

1997-01-01

We report spatially resolved laser-saturated fluorescence measurements of NO concentration in a pre-heated, lean-direct injection (LDI) spray flame at atmospheric pressure. The spray is produced by a hollow-cone, pressure-atomized nozzle supplied with liquid heptane. NO is excited via the Q2(26.5) transition of the gamma(0,0) band. Detection is performed in a 2-nm region centered on the gamma(0,1) band. Because of the relatively close spectral spacing between the excitation (226 nm) and detection wavelengths (236 nm), the gamma(0,1) band of NO cannot be isolated from the spectral wings of the Mie scattering signal produced by the spray. To account for the resulting superposition of the fluorescence and scattering signals, a background subtraction method has been developed that utilizes a nearby non-resonant wavelength. Excitation scans have been performed to locate the optimum off-line wavelength. Detection scans have been performed at problematic locations in the flame to determine possible fluorescence interferences from UHCs and PAHs at both the on-line and off-line excitation wavelengths. Quantitative radial NO profiles are presented and analyzed so as to better understand the operation of lean-direct injectors for gas turbine combustors.

Polymer translocation through a nanopore: a showcase of anomalous diffusion.

PubMed

Milchev, A; Dubbeldam, Johan L A; Rostiashvili, Vakhtang G; Vilgis, Thomas A

2009-04-01

We investigate the translocation dynamics of a polymer chain threaded through a membrane nanopore by a chemical potential gradient that acts on the chain segments inside the pore. By means of diverse methods (scaling theory, fractional calculus, and Monte Carlo and molecular dynamics simulations), we demonstrate that the relevant dynamic variable, the transported number of polymer segments, s(t), displays an anomalous diffusive behavior, both with and without an external driving force being present. We show that in the absence of drag force the time tau, needed for a macromolecule of length N to thread from the cis into the trans side of a cell membrane, scales as tauN(2/alpha) with the chain length. The anomalous dynamics of the translocation process is governed by a universal exponent alpha= 2/(2nu + 2 - gamma(1)), which contains the basic universal exponents of polymer physics, nu (the Flory exponent) and gamma(1) (the surface entropic exponent). A closed analytic expression for the probability to find s translocated segments at time t in terms of chain length N and applied drag force f is derived from the fractional Fokker-Planck equation, and shown to provide analytic results for the time variation of the statistical moments and . It turns out that the average translocation time scales as tau proportional, f(-1)N(2/alpha-1). These results are tested and found to be in perfect agreement with extensive Monte Carlo and molecular dynamics computer simulations.

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

PubMed Central

2014-01-01

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

Scan-rescan reproducibility of CT densitometric measures of emphysema

NASA Astrophysics Data System (ADS)

Chong, D.; van Rikxoort, E. M.; Kim, H. J.; Goldin, J. G.; Brown, M. S.

2011-03-01

This study investigated the reproducibility of HRCT densitometric measures of emphysema in patients scanned twice one week apart. 24 emphysema patients from a multicenter study were scanned at full inspiration (TLC) and expiration (RV), then again a week later for four scans total. Scans for each patient used the same scanner and protocol, except for tube current in three patients. Lung segmentation with gross airway removal was performed on the scans. Volume, weight, mean lung density (MLD), relative area under -950HU (RA-950), and 15th percentile (PD-15) were calculated for TLC, and volume and an airtrapping mask (RA-air) between -950 and -850HU for RV. For each measure, absolute differences were computed for each scan pair, and linear regression was performed against volume difference in a subgroup with volume difference <500mL. Two TLC scan pairs were excluded due to segmentation failure. The mean lung volumes were 5802 +/- 1420mL for TLC, 3878 +/- 1077mL for RV. The mean absolute differences were 169mL for TLC volume, 316mL for RV volume, 14.5g for weight, 5.0HU for MLD, 0.66p.p. for RA-950, 2.4HU for PD-15, and 3.1p.p. for RA-air. The <500mL subgroup had 20 scan pairs for TLC and RV. The R2 values were 0.8 for weight, 0.60 for MLD, 0.29 for RA-950, 0.31 for PD-15, and 0.64 for RA-air. Our results indicate that considerable variability exists in densitometric measures over one week that cannot be attributed to breathhold or physiology. This has implications for clinical trials relying on these measures to assess emphysema treatment efficacy.

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

PubMed

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

2015-12-01

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

a New Improved Threshold Segmentation Method for Scanning Images of Reservoir Rocks Considering Pore Fractal Characteristics

NASA Astrophysics Data System (ADS)

Lin, Wei; Li, Xizhe; Yang, Zhengming; Lin, Lijun; Xiong, Shengchun; Wang, Zhiyuan; Wang, Xiangyang; Xiao, Qianhua

Based on the basic principle of the porosity method in image segmentation, considering the relationship between the porosity of the rocks and the fractal characteristics of the pore structures, a new improved image segmentation method was proposed, which uses the calculated porosity of the core images as a constraint to obtain the best threshold. The results of comparative analysis show that the porosity method can best segment images theoretically, but the actual segmentation effect is deviated from the real situation. Due to the existence of heterogeneity and isolated pores of cores, the porosity method that takes the experimental porosity of the whole core as the criterion cannot achieve the desired segmentation effect. On the contrary, the new improved method overcomes the shortcomings of the porosity method, and makes a more reasonable binary segmentation for the core grayscale images, which segments images based on the actual porosity of each image by calculated. Moreover, the image segmentation method based on the calculated porosity rather than the measured porosity also greatly saves manpower and material resources, especially for tight rocks.

Open-source software platform for medical image segmentation applications

NASA Astrophysics Data System (ADS)

Namías, R.; D'Amato, J. P.; del Fresno, M.

2017-11-01

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.

PubMed

Bakas, Spyridon; Zeng, Ke; Sotiras, Aristeidis; Rathore, Saima; Akbari, Hamed; Gaonkar, Bilwaj; Rozycki, Martin; Pati, Sarthak; Davatzikos, Christos

2016-01-01

We present an approach for segmenting low- and high-grade gliomas in multimodal magnetic resonance imaging volumes. The proposed approach is based on a hybrid generative-discriminative model. Firstly, a generative approach based on an Expectation-Maximization framework that incorporates a glioma growth model is used to segment the brain scans into tumor, as well as healthy tissue labels. Secondly, a gradient boosting multi-class classification scheme is used to refine tumor labels based on information from multiple patients. Lastly, a probabilistic Bayesian strategy is employed to further refine and finalize the tumor segmentation based on patient-specific intensity statistics from the multiple modalities. We evaluated our approach in 186 cases during the training phase of the BRAin Tumor Segmentation (BRATS) 2015 challenge and report promising results. During the testing phase, the algorithm was additionally evaluated in 53 unseen cases, achieving the best performance among the competing methods.

Statistical evaluation of manual segmentation of a diffuse low-grade glioma MRI dataset.

PubMed

Ben Abdallah, Meriem; Blonski, Marie; Wantz-Mezieres, Sophie; Gaudeau, Yann; Taillandier, Luc; Moureaux, Jean-Marie

2016-08-01

Software-based manual segmentation is critical to the supervision of diffuse low-grade glioma patients and to the optimal treatment's choice. However, manual segmentation being time-consuming, it is difficult to include it in the clinical routine. An alternative to circumvent the time cost of manual segmentation could be to share the task among different practitioners, providing it can be reproduced. The goal of our work is to assess diffuse low-grade gliomas' manual segmentation's reproducibility on MRI scans, with regard to practitioners, their experience and field of expertise. A panel of 13 experts manually segmented 12 diffuse low-grade glioma clinical MRI datasets using the OSIRIX software. A statistical analysis gave promising results, as the practitioner factor, the medical specialty and the years of experience seem to have no significant impact on the average values of the tumor volume variable.

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.

PubMed

Roth, Holger R; Lu, Le; Lay, Nathan; Harrison, Adam P; Farag, Amal; Sohn, Andrew; Summers, Ronald M

2018-04-01

Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis. Specifically, as a small, soft, and flexible abdominal organ, the pancreas demonstrates very high inter-patient anatomical variability in both its shape and volume. This inhibits traditional automated segmentation methods from achieving high accuracies, especially compared to the performance obtained for other organs, such as the liver, heart or kidneys. To fill this gap, we present an automated system from 3D computed tomography (CT) volumes that is based on a two-stage cascaded approach-pancreas localization and pancreas segmentation. For the first step, we localize the pancreas from the entire 3D CT scan, providing a reliable bounding box for the more refined segmentation step. We introduce a fully deep-learning approach, based on an efficient application of holistically-nested convolutional networks (HNNs) on the three orthogonal axial, sagittal, and coronal views. The resulting HNN per-pixel probability maps are then fused using pooling to reliably produce a 3D bounding box of the pancreas that maximizes the recall. We show that our introduced localizer compares favorably to both a conventional non-deep-learning method and a recent hybrid approach based on spatial aggregation of superpixels using random forest classification. The second, segmentation, phase operates within the computed bounding box and integrates semantic mid-level cues of deeply-learned organ interior and boundary maps, obtained by two additional and separate realizations of HNNs. By integrating these two mid-level cues, our method is capable of generating boundary-preserving pixel-wise class label maps that result in the final pancreas segmentation. Quantitative evaluation is performed on a publicly available dataset of 82 patient CT scans using 4-fold cross-validation (CV). We achieve a (mean  ±  std. dev.) Dice similarity coefficient (DSC) of 81.27 ± 6.27% in validation, which significantly outperforms both a previous state-of-the art method and a preliminary version of this work that report DSCs of 71.80 ± 10.70% and 78.01 ± 8.20%, respectively, using the same dataset. Copyright © 2018. Published by Elsevier B.V.

Moving metal artifact reduction in cone-beam CT scans with implanted cylindrical gold markers

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

Toftegaard, Jakob, E-mail: jaktofte@rm.dk; Fledelius, Walther; Worm, Esben S.

2014-12-15

Purpose: Implanted gold markers for image-guided radiotherapy lead to streaking artifacts in cone-beam CT (CBCT) scans. Several methods for metal artifact reduction (MAR) have been published, but they all fail in scans with large motion. Here the authors propose and investigate a method for automatic moving metal artifact reduction (MMAR) in CBCT scans with cylindrical gold markers. Methods: The MMAR CBCT reconstruction method has six steps. (1) Automatic segmentation of the cylindrical markers in the CBCT projections. (2) Removal of each marker in the projections by replacing the pixels within a masked area with interpolated values. (3) Reconstruction of amore » marker-free CBCT volume from the manipulated CBCT projections. (4) Reconstruction of a standard CBCT volume with metal artifacts from the original CBCT projections. (5) Estimation of the three-dimensional (3D) trajectory during CBCT acquisition for each marker based on the segmentation in Step 1, and identification of the smallest ellipsoidal volume that encompasses 95% of the visited 3D positions. (6) Generation of the final MMAR CBCT reconstruction from the marker-free CBCT volume of Step 3 by replacing the voxels in the 95% ellipsoid with the corresponding voxels of the standard CBCT volume of Step 4. The MMAR reconstruction was performed retrospectively using a half-fan CBCT scan for 29 consecutive stereotactic body radiation therapy patients with 2–3 gold markers implanted in the liver. The metal artifacts of the MMAR reconstructions were scored and compared with a standard MAR reconstruction by counting the streaks and by calculating the standard deviation of the Hounsfield units in a region around each marker. Results: The markers were found with the same autosegmentation settings in 27 CBCT scans, while two scans needed slightly changed settings to find all markers automatically in Step 1 of the MMAR method. MMAR resulted in 15 scans with no streaking artifacts, 11 scans with 1–4 streaks, and 3 scans with severe streaking artifacts. The corresponding numbers for MAR were 8 (no streaks), 1 (1–4 streaks), and 20 (severe streaking artifacts). The MMAR method was superior to MAR in scans with more than 8 mm 3D marker motion and comparable to MAR for scans with less than 8 mm motion. In addition, the MMAR method was tested on a 4D CBCT reconstruction for which it worked equally well as for the 3D case. The markers in the 4D case had very low motion blur. Conclusions: An automatic method for MMAR in CBCT scans was proposed and shown to effectively remove almost all streaking artifacts in a large set of clinical CBCT scans with implanted gold markers in the liver. Residual streaking artifacts observed in three CBCT scans may be removed with better marker segmentation.« less

Geophysical study of the East Pacific Rise 15°N-17°N: An unusually robust segment

NASA Astrophysics Data System (ADS)

Weiland, Charles M.; MacDonald, Ken C.

1996-09-01

Bathymetric, side-scan sonar, magnetic and gravity data from the East Pacific Rise (EPR) between 15° and 17°N are used to establish the spreading history and examine melt delivery to an unusually robust spreading segment. The axial ridge between the Orozco transform fault (15°30'N) and the 16°20'N overlapping spreading center (OSC) has an average elevation of 2300 m which is 300 m shallower than typical EPR depths, and its cross-sectional area is double the average value for the northern EPR. The total opening rate is 86 km/Myr, but the inflated segment appears to have spread faster to the east by more than 20% since 0.78 Ma. The orientation of magnetic isochrons and lineaments in the side-scan sonar indicates a ˜3° counterclockwise rotation of the spreading direction since 1.8 Ma (C2) and reflects a change in the Pacific-Cocos plate motion. The side-scan lineaments also show that the percentage of inward facing faults (83%) and the spacing between faults (1.5 km) are consistent with the spreading rate dependence shown by Carbotte and Macdonald [1994]. However, the mean fault length (4.8 km) is 1.5 km shorter than expected for the spreading rate and suggests that extensive off-axis volcanism has draped the faults. Gravity analysis shows that the inflated segment has a ˜12-mGal bull's eye shaped low in residual mantle Bouguer anomaly. We offer several possible end-member models for the anomaly, including a prism of 10% partial melt in the mantle and lower crust or a crustal thickness anomaly of 2.25 km. Kinematic modeling that is based on structure and magnetic data suggests that two large magmatic pulses occurred at approximately 0.8 Ma and 0.3 Ma and have reshaped the plate boundary geometry and inflated the segment.

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

Verburg, J; Bortfeld, T

Purpose: We present a new system to perform prompt gamma-ray spectroscopy during proton pencil-beam scanning treatments, which enables in vivo verification of the proton range. This system will be used for the first clinical studies of this technology. Methods: After successful pre-clinical testing of prompt gamma-ray spectroscopy, a full scale system for clinical studies is now being assembled. Prompt gamma-rays will be detected during patient treatment using an array of 8 detector modules arranged behind a tungsten collimator. Each detector module consists of a lanthanum(III) bromide scintillator, a photomultiplier tube, and custom electronics for stable high voltage supply and signalmore » amplification. A new real-time data acquisition and control system samples the signals from the detectors with analog-to-digital converters, analyses events of interest, and communicates with the beam delivery systems. The timing of the detected events was synchronized to the cyclotron radiofrequency and the pencil-beam delivery. Range verification is performed by matching measured energy- and timeresolved gamma-ray spectra to nuclear reaction models based on the clinical treatment plan. Experiments in phantoms were performed using clinical beams in order to assess the performance of the systems. Results: The experiments showed reliable real-time analysis of more than 10 million detector events per second. The individual detector modules acquired accurate energy- and time-resolved gamma-ray measurements at a rate of 1 million events per second, which is typical for beams delivered with a clinical dose rate. The data acquisition system successfully tracked the delivery of the scanned pencil-beams to determine the location of range deviations within the treatment field. Conclusion: A clinical system for proton range verification using prompt gamma-ray spectroscopy has been designed and is being prepared for use during patient treatments. We anticipate to start a first clinical study in the near future. This work was supported by the Federal Share of program income earned by Massachusetts; General Hospital on C06-CA059267, Proton Therapy Research and Treatment Center.« less

Performance of A Compact Multi-crystal High-purity Germanium Detector Array for Measuring Coincident Gamma-ray Emissions

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

Howard, Chris; Daigle, Stephen; Buckner, Matt

2015-02-18

The Multi-sensor Airborne Radiation Survey (MARS) detector is a 14-crystal array of high-purity germanium (HPGe) detectors housed in a single cryostat. The array was used to measure the astrophysical S-factor for the 14N(p,γ) 15O* reaction for several transition energies at an effective center of mass energy of 163 keV. Owing to the segmented nature of the MARS detector, the effect of gamma-ray summing was greatly reduced in comparison to past experiments which utilized large, single-crystal detectors. The new S-factor values agree within the uncertainties with the past measurements. Details of the analysis and detector performance will be presented.

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

NASA Astrophysics Data System (ADS)

Metz, Albert; Hogenbirk, Alfred

2017-09-01

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

Alluvial substrate mapping by automated texture segmentation of recreational-grade side scan sonar imagery.

PubMed

Hamill, Daniel; Buscombe, Daniel; Wheaton, Joseph M

2018-01-01

Side scan sonar in low-cost 'fishfinder' systems has become popular in aquatic ecology and sedimentology for imaging submerged riverbed sediment at coverages and resolutions sufficient to relate bed texture to grain-size. Traditional methods to map bed texture (i.e. physical samples) are relatively high-cost and low spatial coverage compared to sonar, which can continuously image several kilometers of channel in a few hours. Towards a goal of automating the classification of bed habitat features, we investigate relationships between substrates and statistical descriptors of bed textures in side scan sonar echograms of alluvial deposits. We develop a method for automated segmentation of bed textures into between two to five grain-size classes. Second-order texture statistics are used in conjunction with a Gaussian Mixture Model to classify the heterogeneous bed into small homogeneous patches of sand, gravel, and boulders with an average accuracy of 80%, 49%, and 61%, respectively. Reach-averaged proportions of these sediment types were within 3% compared to similar maps derived from multibeam sonar.

Factors affecting the appearance of the hump charge movement component in frog cut twitch fibers.

PubMed

Hui, C S

1991-08-01

Charge movement was measured in frog cut twitch fibers with the double Vaseline gap technique. Five manipulations listed below were applied to investigate their effects on the hump component (I gamma) in the ON segments of TEST minus CONTROL current traces. When external Cl-1 was replaced by MeSO3- to eliminate Cl current, I gamma peaked earlier due to a few millivolts shift of the voltage dependence of I gamma kinetics in the negative direction. The Q-V plots in the TEA.Cl and TEA.MeSO3 solutions were well fitted by a sum of two Boltzmann distribution functions. The more steeply voltage-dependent component (Q gamma) had a V approximately 6 mV more negative in the TEA.MeSO3 solution than in the TEA.Cl solution. These voltage shifts were partially reversible. When creatine phosphate in the end pool solution was removed, the I gamma hump disappeared slowly over the course of 20-30 min, partly due to a suppression of Q gamma. The hump reappeared when creatine phosphate was restored. When 0.2-1.0 mM Cd2+ was added to the center pool solution to block inward Ca current, the I gamma hump became less prominent due to a prolongation in the time course of I gamma but not to a suppression of Q gamma. When the holding potential was changed from -90 to -120 mV, the amplitude of I beta was increased, thereby obscuring the I gamma hump. Finally, when a cut fiber was stimulated repetitively, I gamma lost its hump appearance because its time course was prolonged. In an extreme case, a 5-min resting interval was insufficient for a complete recovery of the waveform. In general, a stimulation rate of once per minute had a negligible effect on the shape of I gamma. Of the five manipulations, MeSO3- has the least perturbation on the appearance of I gamma and is potentially a better substitute for Cl- than SO2-(4) in eliminating Cl current if the appearance of the I gamma hump is to be preserved.

Nurse exposure doses resulted from bone scintigraphy patient

NASA Astrophysics Data System (ADS)

Tunçman, Duygu; Kovan, Bilal; Poyraz, Leyla; ćapali, Veli; Demir, Bayram; Türkmen, Cüneyt

2016-03-01

Bone scintigraphy is used for displaying the radiologic undiagnosed bone lesions in nuclear medicine. It's general indications are researching bone metastases, detection of radiographically occult fractures, staging and follow-up in primary bone tumors, diagnosis of paget's disease, investigation of loosening and infection in orthopedic implants. It is applied with using 99mTc labeled radiopharmaceuticals (e.g 99m Tc MDP,99mTc HEDP and 99mTc HMDP). 20 -25 mCi IV radiotracer was injected into vein and radiotracer emits gamma radiation. Patient waits in isolated room for about 3 hours then a gamma camera scans radiation area and creates an image. When some patient's situation is not good, patients are hospitalized until the scanning because of patients' close contact care need. In this study, measurements were taken from ten patients using Geiger Muller counter. After these measurements, we calculated nurse's exposure radiations from patient's routine treatment, examination and emergency station.

A spatial scan statistic for survival data based on Weibull distribution.

PubMed

Bhatt, Vijaya; Tiwari, Neeraj

2014-05-20

The spatial scan statistic has been developed as a geographical cluster detection analysis tool for different types of data sets such as Bernoulli, Poisson, ordinal, normal and exponential. We propose a scan statistic for survival data based on Weibull distribution. It may also be used for other survival distributions, such as exponential, gamma, and log normal. The proposed method is applied on the survival data of tuberculosis patients for the years 2004-2005 in Nainital district of Uttarakhand, India. Simulation studies reveal that the proposed method performs well for different survival distribution functions. Copyright © 2013 John Wiley & Sons, Ltd.

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.

Results of a laboratory experiment that tests rotating unbalanced-mass devices for scanning gimbaled payloads and free-flying spacecraft

NASA Technical Reports Server (NTRS)

Alhorn, D. C.; Polites, M. E.

1994-01-01

Rotating unbalanced-mass (RUM) devices are a new way to scan space-based, balloon-borne, and ground-based gimbaled payloads, like x-ray and gamma-ray telescopes. They can also be used to scan free-flying spacecraft. Circular scans, linear scans, and raster scans can be generated. A pair of RUM devices generates the basic scan motion and an auxiliary control system using torque motors, control moment gyros, or reaction wheels keeps the scan centered on the target and produces some complementary motion for raster scanning. Previous analyses and simulation results show that this approach offers significant power savings compared to scanning only with the auxiliary control system, especially with large payloads and high scan frequencies. However, these claims have never been proven until now. This paper describes a laboratory experiment which tests the concept of scanning a gimbaled payload with RUM devices. A description of the experiment is given and test results that prove the concept are presented. The test results are compared with those from a computer simulation model of the experiment and the differences are discussed.

Influence of gamma ray irradiation on stoichiometry of hydrothermally synthesized bismuth telluride nanoparticles

NASA Astrophysics Data System (ADS)

Abishek, N. S.; Naik, K. Gopalakrishna

2018-05-01

Bismuth telluride (Bi2Te3) nanoparticles were synthesized by the hydrothermal method at 200 °C for 24 h. The synthesized Bi2Te3 nanoparticles were irradiated with gamma rays at doses of 50 kGy and 100 kGy. The structural characterization of the pre-irradiated and post-irradiated samples was carried out by X-ray diffraction technique and was found to have rhombohedral phase having R3 ¯m (166) space group. The X-ray diffraction peaks were found to shift towards lower diffraction angle with gamma ray irradiation. The morphologies and compositions of the grown Bi2Te3 nanoparticles were studied using Field Emission Scanning Electron Microscope and X-ray energy dispersive analysis, respectively. The possible cause for the shift in the X-ray diffraction peaks with gamma ray irradiation has been discussed in the present work.

Dual-stage deep learning framework for pigment epithelium detachment segmentation in polypoidal choroidal vasculopathy

PubMed Central

Xu, Yupeng; Yan, Ke; Kim, Jinman; Wang, Xiuying; Li, Changyang; Su, Li; Yu, Suqin; Xu, Xun; Feng, Dagan David

2017-01-01

Worldwide, polypoidal choroidal vasculopathy (PCV) is a common vision-threatening exudative maculopathy, and pigment epithelium detachment (PED) is an important clinical characteristic. Thus, precise and efficient PED segmentation is necessary for PCV clinical diagnosis and treatment. We propose a dual-stage learning framework via deep neural networks (DNN) for automated PED segmentation in PCV patients to avoid issues associated with manual PED segmentation (subjectivity, manual segmentation errors, and high time consumption).The optical coherence tomography scans of fifty patients were quantitatively evaluated with different algorithms and clinicians. Dual-stage DNN outperformed existing PED segmentation methods for all segmentation accuracy parameters, including true positive volume fraction (85.74 ± 8.69%), dice similarity coefficient (85.69 ± 8.08%), positive predictive value (86.02 ± 8.99%) and false positive volume fraction (0.38 ± 0.18%). Dual-stage DNN achieves accurate PED quantitative information, works with multiple types of PEDs and agrees well with manual delineation, suggesting that it is a potential automated assistant for PCV management. PMID:28966847

Dual-stage deep learning framework for pigment epithelium detachment segmentation in polypoidal choroidal vasculopathy.

PubMed

Xu, Yupeng; Yan, Ke; Kim, Jinman; Wang, Xiuying; Li, Changyang; Su, Li; Yu, Suqin; Xu, Xun; Feng, Dagan David

2017-09-01

Worldwide, polypoidal choroidal vasculopathy (PCV) is a common vision-threatening exudative maculopathy, and pigment epithelium detachment (PED) is an important clinical characteristic. Thus, precise and efficient PED segmentation is necessary for PCV clinical diagnosis and treatment. We propose a dual-stage learning framework via deep neural networks (DNN) for automated PED segmentation in PCV patients to avoid issues associated with manual PED segmentation (subjectivity, manual segmentation errors, and high time consumption).The optical coherence tomography scans of fifty patients were quantitatively evaluated with different algorithms and clinicians. Dual-stage DNN outperformed existing PED segmentation methods for all segmentation accuracy parameters, including true positive volume fraction (85.74 ± 8.69%), dice similarity coefficient (85.69 ± 8.08%), positive predictive value (86.02 ± 8.99%) and false positive volume fraction (0.38 ± 0.18%). Dual-stage DNN achieves accurate PED quantitative information, works with multiple types of PEDs and agrees well with manual delineation, suggesting that it is a potential automated assistant for PCV management.

One-dimensional Spatial Distributions of Gamma-ray Emitting Contaminants in Field Lysimeters Using a Collimated Gamma-ray Spectroscopy System.

PubMed

Erdmann, Bryan J; Powell, Brian A; Kaplan, Daniel I; DeVol, Timothy A

2018-05-01

One-dimensional scans of gamma-ray emitting contaminants were conducted on lysimeters from the RadFLEX facility at the Savannah River Nationals Laboratory (SRNL). The lysimeters each contained a contamination source that was buried in SRNL soil. A source consisted of Cs, Co, Ba, and Eu incorporated either into a solid waste form (Portland cement and reducing grout) or applied to a filter paper for direct soil exposure. The lysimeters were exposed to natural environmental conditions for 3 to 4 y. The initial contaminant activities range from 4.0 to 9.0 MBq for the solid wasteforms and 0.25 to 0.47 MBq for the soil-incorporated source. The measurements were performed using a collimated high-purity germanium gamma-ray spectrometer with a spatial resolution of 2.5 mm. These scans showed downward mobility of Co and Ba when the radionuclides were incorporated directly into the SRNL soil. When radionuclides were incorporated into the solid waste forms positioned in the SRNL soil, Cs exhibited both upward and downward dispersion while the other radionuclides showed no movement. This dispersion was more significant for the Portland cement than the reducing grout wasteform. Europium-152 was the only radionuclide of those studied that showed no movement within the spatial resolution of the scanner from the original placement within the lysimeter. Understanding radionuclide movement in the environment is important for developing strategies for waste management and disposal.

SU-C-BRA-07: Virtual Bronchoscopy-Guided IMRT Planning for Mapping and Avoiding Radiation Injury to the Airway Tree in Lung SAbR

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

Sawant, A; Modiri, A; Bland, R

Purpose: Post-treatment radiation injury to central and peripheral airways is a potentially important, yet under-investigated determinant of toxicity in lung stereotactic ablative radiotherapy (SAbR). We integrate virtual bronchoscopy technology into the radiotherapy planning process to spatially map and quantify the radiosensitivity of bronchial segments, and propose novel IMRT planning that limits airway dose through non-isotropic intermediate- and low-dose spillage. Methods: Pre- and ∼8.5 months post-SAbR diagnostic-quality CT scans were retrospectively collected from six NSCLC patients (50–60Gy in 3–5 fractions). From each scan, ∼5 branching levels of the bronchial tree were segmented using LungPoint, a virtual bronchoscopic navigation system. The pre-SAbRmore » CT and the segmented bronchial tree were imported into the Eclipse treatment planning system and deformably registered to the planning CT. The five-fraction equivalent dose from the clinically-delivered plan was calculated for each segment using the Universal Survival Curve model. The pre- and post-SAbR CTs were used to evaluate radiation-induced segmental collapse. Two of six patients exhibited significant segmental collapse with associated atelectasis and fibrosis, and were re-planned using IMRT. Results: Multivariate stepwise logistic regression over six patients (81 segments) showed that D0.01cc (minimum point dose within the 0.01cc receiving highest dose) was a significant independent factor associated with collapse (odds-ratio=1.17, p=0.010). The D0.01cc threshold for collapse was 57Gy, above which, collapse rate was 45%. In the two patients exhibiting segmental collapse, 22 out of 32 segments showed D0.01cc >57Gy. IMRT re-planning reduced D0.01cc below 57Gy in 15 of the 22 segments (68%) while simultaneously achieving the original clinical plan objectives for PTV coverage and OAR-sparing. Conclusion: Our results indicate that the administration of lung SAbR can Result in significant injury to bronchial segments, potentially impairing post-SAbR lung function. To our knowledge, this is the first investigation of functional avoidance based on mapping and minimizing dose to individual bronchial segments. The presenting author receives research funding from Varian Medical Systems, Elekta, and VisionRT.« less

Automated quantification of cerebral edema following hemispheric infarction: Application of a machine-learning algorithm to evaluate CSF shifts on serial head CTs.

PubMed

Chen, Yasheng; Dhar, Rajat; Heitsch, Laura; Ford, Andria; Fernandez-Cadenas, Israel; Carrera, Caty; Montaner, Joan; Lin, Weili; Shen, Dinggang; An, Hongyu; Lee, Jin-Moo

2016-01-01

Although cerebral edema is a major cause of death and deterioration following hemispheric stroke, there remains no validated biomarker that captures the full spectrum of this critical complication. We recently demonstrated that reduction in intracranial cerebrospinal fluid (CSF) volume (∆ CSF) on serial computed tomography (CT) scans provides an accurate measure of cerebral edema severity, which may aid in early triaging of stroke patients for craniectomy. However, application of such a volumetric approach would be too cumbersome to perform manually on serial scans in a real-world setting. We developed and validated an automated technique for CSF segmentation via integration of random forest (RF) based machine learning with geodesic active contour (GAC) segmentation. The proposed RF + GAC approach was compared to conventional Hounsfield Unit (HU) thresholding and RF segmentation methods using Dice similarity coefficient (DSC) and the correlation of volumetric measurements, with manual delineation serving as the ground truth. CSF spaces were outlined on scans performed at baseline (< 6 h after stroke onset) and early follow-up (FU) (closest to 24 h) in 38 acute ischemic stroke patients. RF performed significantly better than optimized HU thresholding (p < 10 - 4 in baseline and p < 10 - 5 in FU) and RF + GAC performed significantly better than RF (p < 10 - 3 in baseline and p < 10 - 5 in FU). Pearson correlation coefficients between the automatically detected ∆ CSF and the ground truth were r  = 0.178 (p = 0.285), r  = 0.876 (p < 10 - 6 ) and r  = 0.879 (p < 10 - 6 ) for thresholding, RF and RF + GAC, respectively, with a slope closer to the line of identity in RF + GAC. When we applied the algorithm trained from images of one stroke center to segment CTs from another center, similar findings held. In conclusion, we have developed and validated an accurate automated approach to segment CSF and calculate its shifts on serial CT scans. This algorithm will allow us to efficiently and accurately measure the evolution of cerebral edema in future studies including large multi-site patient populations.

Synthesis and Physical Properties of Poly(Perfluoroalkylether)Urethanes

DTIC Science & Technology

1989-05-30

Differential scanning calorimetry and dynamic mechanical analysis showed that the incorporation of PFEG into the soft segment phase slightly enhanced...for all the polymers, using electron spectroscopy for chemical analysis (ESCA). The dynamic contact angle results indicate that the polymer surfaces...these polymers were evaluated by a variety of techniques. Differential scanning calorimetry and dynamic mechanical analysis showed that the

Identifying Lesions on Structural Brain Images-Validation of the Method and Application to Neuropsychological Patients

ERIC Educational Resources Information Center

Stamatakis, E.A.; Tyler, L.K.

2005-01-01

The study of neuropsychological disorders has been greatly facilitated by the localization of brain lesions on MRI scans. Current popular approaches for the assessment of MRI brain scans mostly depend on the successful segmentation of the brain into grey and white matter. These methods cannot be used effectively with large lesions because lesions…

A segmental analysis of current and future scanning and optimizing technology in the hardwood sawmill industry

Treesearch

S.A. Bowe; R.L. Smith; D. Earl Kline; Philip A. Araman

2002-01-01

A nationwide survey of advanced scanning and optimizing technology in the hardwood sawmill industry was conducted in the fall of 1999. Three specific hardwood sawmill technologies were examined that included current edger-optimizer systems, future edger-optimizer systems, and future automated grading systems. The objectives of the research were to determine differences...

In vivo estimation of normal amygdala volume from structural MRI scans with anatomical-based segmentation.

PubMed

Siozopoulos, Achilleas; Thomaidis, Vasilios; Prassopoulos, Panos; Fiska, Aliki

2018-02-01

Literature includes a number of studies using structural MRI (sMRI) to determine the volume of the amygdala, which is modified in various pathologic conditions. The reported values vary widely mainly because of different anatomical approaches to the complex. This study aims at estimating of the normal amygdala volume from sMRI scans using a recent anatomical definition described in a study based on post-mortem material. The amygdala volume has been calculated in 106 healthy subjects, using sMRI and anatomical-based segmentation. The resulting volumes have been analyzed for differences related to hemisphere, sex, and age. The mean amygdalar volume was estimated at 1.42 cm 3 . The mean right amygdala volume has been found larger than the left, but the difference for the raw values was within the limits of the method error. No intersexual differences or age-related alterations have been observed. The study provides a method for determining the boundaries of the amygdala in sMRI scans based on recent anatomical considerations and an estimation of the mean normal amygdala volume from a quite large number of scans for future use in comparative studies.

Eta Sigma Gamma Members' Participation in Advocacy Activities and Opinions on Advocacy Priorities for the Organization

ERIC Educational Resources Information Center

Cox, Carol; Haidar, Salma; Brookins-Fisher, Jodi; Thompson, Amy; Deakins, Bethany; Bishop, Chaundra

2014-01-01

Advocacy for health policies and programs can impact large segments of the population with the goal of promoting and protecting the nation's health. Historically, advocacy has not been viewed as seriously as other components of health education, and involvement in public policy work has been moderate by health education practitioners and health…

A completely automated processing pipeline for lung and lung lobe segmentation and its application to the LIDC-IDRI data base

NASA Astrophysics Data System (ADS)

Blaffert, Thomas; Wiemker, Rafael; Barschdorf, Hans; Kabus, Sven; Klinder, Tobias; Lorenz, Cristian; Schadewaldt, Nicole; Dharaiya, Ekta

2010-03-01

Automated segmentation of lung lobes in thoracic CT images has relevance for various diagnostic purposes like localization of tumors within the lung or quantification of emphysema. Since emphysema is a known risk factor for lung cancer, both purposes are even related to each other. The main steps of the segmentation pipeline described in this paper are the lung detector and the lung segmentation based on a watershed algorithm, and the lung lobe segmentation based on mesh model adaptation. The segmentation procedure was applied to data sets of the data base of the Image Database Resource Initiative (IDRI) that currently contains over 500 thoracic CT scans with delineated lung nodule annotations. We visually assessed the reliability of the single segmentation steps, with a success rate of 98% for the lung detection and 90% for lung delineation. For about 20% of the cases we found the lobe segmentation not to be anatomically plausible. A modeling confidence measure is introduced that gives a quantitative indication of the segmentation quality. For a demonstration of the segmentation method we studied the correlation between emphysema score and malignancy on a per-lobe basis.

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

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen

2013-07-01

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

A Monte-Carlo study to assess the effect of 1.5 T magnetic fields on the overall robustness of pencil-beam scanning proton radiotherapy plans for prostate cancer

NASA Astrophysics Data System (ADS)

Kurz, Christopher; Landry, Guillaume; Resch, Andreas F.; Dedes, George; Kamp, Florian; Ganswindt, Ute; Belka, Claus; Raaymakers, Bas W.; Parodi, Katia

2017-11-01

Combining magnetic-resonance imaging (MRI) and proton therapy (PT) using pencil-beam scanning (PBS) may improve image-guided radiotherapy. We aimed at assessing the impact of a magnetic field on PBS-PT plan quality and robustness. Specifically, the robustness against anatomical changes and positioning errors in an MRI-guided scenario with a 30 cm radius 1.5 T magnetic field was studied for prostate PT. Five prostate cancer patients with three consecutive CT images (CT1-3) were considered. Single-field uniform dose PBS-PT plans were generated on the segmented CT1 with Monte-Carlo-based treatment planning software for inverse optimization. Plans were optimized at 90° gantry angle without B-field (no B), with  ±1.5 T B-field (B and minus B), as well as at 81° gantry angle and  +1.5 T (B G81). Plans were re-calculated on aligned CT2 and CT3 to study the impact of anatomical changes. Dose distributions were compared in terms of changes in DVH parameters, proton range and gamma-index pass-rates. To assess the impact of positioning errors, DVH parameters were compared for  ±5 mm CT1 patient shifts in anterior-posterior (AP) and left-right (LR) direction. Proton beam deflection considerably reduced robustness against inter-fractional changes for the B scenario. Range agreement, gamma-index pass-rates and PTV V95% were significantly lower compared to no B. Improved robustness was obtained for minus B and B G81, the latter showing only minor differences to no B. The magnetic field introduced slight dosimetric changes under LR shifts. The impact of AP shifts was considerably larger, and equivalent for scenarios with and without B-field. Results suggest that robustness equivalent to PT without magnetic field can be achieved by adaptation of the treatment parameters, such as B-field orientation (minus B) with respect to the patient and/or gantry angle (B G81). MRI-guided PT for prostate cancer might thus be implemented without compromising robustness compared to state-of-the-art CT-guided PT.

Polarization sensitive corneal and anterior segment swept-source optical coherence tomography

NASA Astrophysics Data System (ADS)

Lim, Yiheng; Yamanari, Masahiro; Yasuno, Yoshiaki

2010-02-01

We develop a compact polarization sensitive corneal and anterior segment swept-source optical coherence tomography (PS-CAS- OCT) for evaluating the usefulness of PS-OCT, and enabling large scale studies in the tissue properties of normal and diseased eyes using the benefits of the PS-OCT, which provides better tissue discrimination compared to the conventional OCT by visualizing the fibrous tissues in the anterior eye segment. Our polarization-sensitive interferometer is size reduced into a 19 inch box for the portability and the probe is integrated into a position adjustable scanning head for the usability of our system.

An overview of the thematic mapper geometric correction system

NASA Technical Reports Server (NTRS)

Beyer, E. P.

1983-01-01

Geometric accuracy specifications for LANDSAT 4 are reviewed and the processing concepts which form the basis of NASA's thematic mapper geometric correction system are summarized for both the flight and ground segments. The flight segment includes the thematic mapper instrument, attitude measurement devices, attitude control, and ephemeris processing. For geometric correction the ground segment uses mirror scan correction data, payload correction data, and control point information to determine where TM detector samples fall on output map projection systems. Then the raw imagery is reformatted and resampled to produce image samples on a selected output projection grid system.

Parallelized seeded region growing using CUDA.

PubMed

Park, Seongjin; Lee, Jeongjin; Lee, Hyunna; Shin, Juneseuk; Seo, Jinwook; Lee, Kyoung Ho; Shin, Yeong-Gil; Kim, Bohyoung

2014-01-01

This paper presents a novel method for parallelizing the seeded region growing (SRG) algorithm using Compute Unified Device Architecture (CUDA) technology, with intention to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared with SRG implementations on single-core CPUs, quad-core CPUs, and shader language programming, using synthetic datasets and 20 body CT scans. Based on the experimental results, the CUDA-based SRG outperforms the other three implementations, advocating that it can substantially assist the segmentation during massive CT screening tests.

Automated segmentation of cardiac visceral fat in low-dose non-contrast chest CT images

NASA Astrophysics Data System (ADS)

Xie, Yiting; Liang, Mingzhu; Yankelevitz, David F.; Henschke, Claudia I.; Reeves, Anthony P.

2015-03-01

Cardiac visceral fat was segmented from low-dose non-contrast chest CT images using a fully automated method. Cardiac visceral fat is defined as the fatty tissues surrounding the heart region, enclosed by the lungs and posterior to the sternum. It is measured by constraining the heart region with an Anatomy Label Map that contains robust segmentations of the lungs and other major organs and estimating the fatty tissue within this region. The algorithm was evaluated on 124 low-dose and 223 standard-dose non-contrast chest CT scans from two public datasets. Based on visual inspection, 343 cases had good cardiac visceral fat segmentation. For quantitative evaluation, manual markings of cardiac visceral fat regions were made in 3 image slices for 45 low-dose scans and the Dice similarity coefficient (DSC) was computed. The automated algorithm achieved an average DSC of 0.93. Cardiac visceral fat volume (CVFV), heart region volume (HRV) and their ratio were computed for each case. The correlation between cardiac visceral fat measurement and coronary artery and aortic calcification was also evaluated. Results indicated the automated algorithm for measuring cardiac visceral fat volume may be an alternative method to the traditional manual assessment of thoracic region fat content in the assessment of cardiovascular disease risk.

Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis.

PubMed

Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B

2012-01-01

The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.

An application of cascaded 3D fully convolutional networks for medical image segmentation.

PubMed

Roth, Holger R; Oda, Hirohisa; Zhou, Xiangrong; Shimizu, Natsuki; Yang, Ying; Hayashi, Yuichiro; Oda, Masahiro; Fujiwara, Michitaka; Misawa, Kazunari; Mori, Kensaku

2018-06-01

Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of volumetric images. In this work, we show that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical structures (ranging from the large organs to thin vessels) can achieve competitive segmentation results, while avoiding the need for handcrafting features or training class-specific models. To this end, we propose a two-stage, coarse-to-fine approach that will first use a 3D FCN to roughly define a candidate region, which will then be used as input to a second 3D FCN. This reduces the number of voxels the second FCN has to classify to ∼10% and allows it to focus on more detailed segmentation of the organs and vessels. We utilize training and validation sets consisting of 331 clinical CT images and test our models on a completely unseen data collection acquired at a different hospital that includes 150 CT scans, targeting three anatomical organs (liver, spleen, and pancreas). In challenging organs such as the pancreas, our cascaded approach improves the mean Dice score from 68.5 to 82.2%, achieving the highest reported average score on this dataset. We compare with a 2D FCN method on a separate dataset of 240 CT scans with 18 classes and achieve a significantly higher performance in small organs and vessels. Furthermore, we explore fine-tuning our models to different datasets. Our experiments illustrate the promise and robustness of current 3D FCN based semantic segmentation of medical images, achieving state-of-the-art results. 1 . Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluation of the Anterior Segment Angle-to-Angle Scan of Cirrus High-Definition Optical Coherence Tomography and Comparison With Gonioscopy and With the Visante OCT.

PubMed

Tun, Tin A; Baskaran, Mani; Tan, Shayne S; Perera, Shamira A; Aung, Tin; Husain, Rahat

2017-01-01

To evaluate the diagnostic performance of the anterior segment angle-to-angle scan of the Cirrus high-definition optical coherence tomography (HD-OCT) in detecting eyes with closed angles. All subjects underwent dark-room gonioscopy by an ophthalmologist. A technician performed anterior segment imaging with Cirrus (n = 202) and Visante OCT (n = 85) under dark-room conditions. All eyes were categorized by two masked graders as per number of closed quadrants. Each quadrant of anterior chamber angle was categorized as a closed angle if posterior trabecular meshwork could not be seen on gonioscopy or if there was any irido-corneal contact anterior to scleral spur in Cirrus and Visante images. An eye was graded as having a closed angle if two or more quadrants were closed. Agreement and area under the curve (AUC) were performed. There were 50 (24.8%) eyes with closed angles. The agreements of closed-angle diagnosis (by eye) between Cirrus HD-OCT and gonioscopy (k = 0.59; 95% confidence interval (CI) 0.45-0.72; AC1 = 0.76) and between Cirrus and Visante OCT (k = 0.65; 95% CI 0.48-0.82, AC1 = 0.77) were moderate. The AUC for diagnosing the eye with gonioscopic closed angle by Cirrus HD-OCT was good (AUC = 0.86; sensitivity = 83.33; specificity = 77.78). The diagnostic performance of Cirrus HD-OCT in detecting the eyes with closed angles was similar to that of Visante (AUC 0.87 vs. 0.9, respectively; P = 0.51). The anterior segment angle-to-angle scans of Cirrus HD-OCT demonstrated similar diagnostic performance as Visante in detecting gonioscopic closed angles. The agreement between Cirrus and gonioscopy for detecting eyes with closed angles was moderate.

An accurate segmentation method for volumetry of brain tumor in 3D MRI

NASA Astrophysics Data System (ADS)

Wang, Jiahui; Li, Qiang; Hirai, Toshinori; Katsuragawa, Shigehiko; Li, Feng; Doi, Kunio

2008-03-01

Accurate volumetry of brain tumors in magnetic resonance imaging (MRI) is important for evaluating the interval changes in tumor volumes during and after treatment, and also for planning of radiation therapy. In this study, an automated volumetry method for brain tumors in MRI was developed by use of a new three-dimensional (3-D) image segmentation technique. First, the central location of a tumor was identified by a radiologist, and then a volume of interest (VOI) was determined automatically. To substantially simplify tumor segmentation, we transformed the 3-D image of the tumor into a two-dimensional (2-D) image by use of a "spiral-scanning" technique, in which a radial line originating from the center of the tumor scanned the 3-D image spirally from the "north pole" to the "south pole". The voxels scanned by the radial line provided a transformed 2-D image. We employed dynamic programming to delineate an "optimal" outline of the tumor in the transformed 2-D image. We then transformed the optimal outline back into 3-D image space to determine the volume of the tumor. The volumetry method was trained and evaluated by use of 16 cases with 35 brain tumors. The agreement between tumor volumes provided by computer and a radiologist was employed as a performance metric. Our method provided relatively accurate results with a mean agreement value of 88%.

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.

Freesurfer-initialized large deformation diffeomorphic metric mapping with application to Parkinson's disease

NASA Astrophysics Data System (ADS)

Chen, Jingyun; Palmer, Samantha J.; Khan, Ali R.; Mckeown, Martin J.; Beg, Mirza Faial

2009-02-01

We apply a recently developed automated brain segmentation method, FS+LDDMM, to brain MRI scans from Parkinson's Disease (PD) subjects, and normal age-matched controls and compare the results to manual segmentation done by trained neuroscientists. The data set consisted of 14 PD subjects and 12 age-matched control subjects without neurologic disease and comparison was done on six subcortical brain structures (left and right caudate, putamen and thalamus). Comparison between automatic and manual segmentation was based on Dice Similarity Coefficient (Overlap Percentage), L1 Error, Symmetrized Hausdorff Distance and Symmetrized Mean Surface Distance. Results suggest that FS+LDDMM is well-suited for subcortical structure segmentation and further shape analysis in Parkinson's Disease. The asymmetry of the Dice Similarity Coefficient over shape change is also discussed based on the observation and measurement of FS+LDDMM segmentation results.

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

PubMed

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

2017-10-01

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

Neighborhood sampling: how many streets must an auditor walk?

PubMed

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

2010-03-12

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

Neighborhood sampling: how many streets must an auditor walk?

PubMed Central

2010-01-01

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

Line segment extraction for large scale unorganized point clouds

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection

PubMed Central

Ou, Yangming; Resnick, Susan M.; Gur, Ruben C.; Gur, Raquel E.; Satterthwaite, Theodore D.; Furth, Susan; Davatzikos, Christos

2016-01-01

Atlas-based automated anatomical labeling is a fundamental tool in medical image segmentation, as it defines regions of interest for subsequent analysis of structural and functional image data. The extensive investigation of multi-atlas warping and fusion techniques over the past 5 or more years has clearly demonstrated the advantages of consensus-based segmentation. However, the common approach is to use multiple atlases with a single registration method and parameter set, which is not necessarily optimal for every individual scan, anatomical region, and problem/data-type. Different registration criteria and parameter sets yield different solutions, each providing complementary information. Herein, we present a consensus labeling framework that generates a broad ensemble of labeled atlases in target image space via the use of several warping algorithms, regularization parameters, and atlases. The label fusion integrates two complementary sources of information: a local similarity ranking to select locally optimal atlases and a boundary modulation term to refine the segmentation consistently with the target image's intensity profile. The ensemble approach consistently outperforms segmentations using individual warping methods alone, achieving high accuracy on several benchmark datasets. The MUSE methodology has been used for processing thousands of scans from various datasets, producing robust and consistent results. MUSE is publicly available both as a downloadable software package, and as an application that can be run on the CBICA Image Processing Portal (https://ipp.cbica.upenn.edu), a web based platform for remote processing of medical images. PMID:26679328

3D variational brain tumor segmentation on a clustered feature set

NASA Astrophysics Data System (ADS)

Popuri, Karteek; Cobzas, Dana; Jagersand, Martin; Shah, Sirish L.; Murtha, Albert

2009-02-01

Tumor segmentation from MRI data is a particularly challenging and time consuming task. Tumors have a large diversity in shape and appearance with intensities overlapping the normal brain tissues. In addition, an expanding tumor can also deflect and deform nearby tissue. Our work addresses these last two difficult problems. We use the available MRI modalities (T1, T1c, T2) and their texture characteristics to construct a multi-dimensional feature set. Further, we extract clusters which provide a compact representation of the essential information in these features. The main idea in this paper is to incorporate these clustered features into the 3D variational segmentation framework. In contrast to the previous variational approaches, we propose a segmentation method that evolves the contour in a supervised fashion. The segmentation boundary is driven by the learned inside and outside region voxel probabilities in the cluster space. We incorporate prior knowledge about the normal brain tissue appearance, during the estimation of these region statistics. In particular, we use a Dirichlet prior that discourages the clusters in the ventricles to be in the tumor and hence better disambiguate the tumor from brain tissue. We show the performance of our method on real MRI scans. The experimental dataset includes MRI scans, from patients with difficult instances, with tumors that are inhomogeneous in appearance, small in size and in proximity to the major structures in the brain. Our method shows good results on these test cases.

Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts in simultaneous EEG-fMRI data.

PubMed

Kim, Hyun-Chul; Yoo, Seung-Schik; Lee, Jong-Hwan

2015-01-01

Electroencephalography (EEG) data simultaneously acquired with functional magnetic resonance imaging (fMRI) data are preprocessed to remove gradient artifacts (GAs) and ballistocardiographic artifacts (BCAs). Nonetheless, these data, especially in the gamma frequency range, can be contaminated by residual artifacts produced by mechanical vibrations in the MRI system, in particular the cryogenic pump that compresses and transports the helium that chills the magnet (the helium-pump). However, few options are available for the removal of helium-pump artifacts. In this study, we propose a recursive approach of EEG-segment-based principal component analysis (rsPCA) that enables the removal of these helium-pump artifacts. Using the rsPCA method, feature vectors representing helium-pump artifacts were successfully extracted as eigenvectors, and the reconstructed signals of the feature vectors were subsequently removed. A test using simultaneous EEG-fMRI data acquired from left-hand (LH) and right-hand (RH) clenching tasks performed by volunteers found that the proposed rsPCA method substantially reduced helium-pump artifacts in the EEG data and significantly enhanced task-related gamma band activity levels (p=0.0038 and 0.0363 for LH and RH tasks, respectively) in EEG data that have had GAs and BCAs removed. The spatial patterns of the fMRI data were estimated using a hemodynamic response function (HRF) modeled from the estimated gamma band activity in a general linear model (GLM) framework. Active voxel clusters were identified in the post-/pre-central gyri of motor area, only from the rsPCA method (uncorrected p<0.001 for both LH/RH tasks). In addition, the superior temporal pole areas were consistently observed (uncorrected p<0.001 for the LH task and uncorrected p<0.05 for the RH task) in the spatial patterns of the HRF model for gamma band activity when the task paradigm and movement were also included in the GLM. Copyright © 2014 Elsevier Inc. All rights reserved.

Theory and Performance of AIMS for Active Interrogation

NASA Astrophysics Data System (ADS)

Walters, William J.; Royston, Katherine E. K.; Haghighat, Alireza

2014-06-01

A hybrid Monte Carlo and deterministic methodology has been developed for application to active interrogation systems. The methodology consists of four steps: i) determination of neutron flux distribution due to neutron source transport and subcritical multiplication; ii) generation of gamma source distribution from (n, γ) interactions; iii) determination of gamma current at a detector window; iv) detection of gammas by the detector. This paper discusses the theory and results of the first three steps for the case of a cargo container with a sphere of HEU in third-density water. In the first step, a response-function formulation has been developed to calculate the subcritical multiplication and neutron flux distribution. Response coefficients are pre-calculated using the MCNP5 Monte Carlo code. The second step uses the calculated neutron flux distribution and Bugle-96 (n, γ) cross sections to find the resulting gamma source distribution. Finally, in the third step the gamma source distribution is coupled with a pre-calculated adjoint function to determine the gamma flux at a detector window. A code, AIMS (Active Interrogation for Monitoring Special-Nuclear-materials), has been written to output the gamma current for an source-detector assembly scanning across the cargo using the pre-calculated values and takes significantly less time than a reference MCNP5 calculation.

Neutron Resonance Spin Determination Using Multi-Segmented Detector DANCE

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

Baramsai, B.; Mitchell, G. E.; Chyzh, A.

2011-06-01

A sensitive method to determine the spin of neutron resonances is introduced based on the statistical pattern recognition technique. The new method was used to assign the spins of s-wave resonances in {sup 155}Gd. The experimental neutron capture data for these nuclei were measured with the DANCE (Detector for Advanced Neutron Capture Experiment) calorimeter at the Los Alamos Neutron Science Center. The highly segmented calorimeter provided detailed multiplicity distributions of the capture {gamma}-rays. Using this information, the spins of the neutron capture resonances were determined. With these new spin assignments, level spacings are determined separately for s-wave resonances with J{supmore » {pi}} = 1{sup -} and 2{sup -}.« less

Digital Data Acquisition System for experiments with segmented detectors at National Superconducting Cyclotron Laboratory

NASA Astrophysics Data System (ADS)

Starosta, K.; Vaman, C.; Miller, D.; Voss, P.; Bazin, D.; Glasmacher, T.; Crawford, H.; Mantica, P.; Tan, H.; Hennig, W.; Walby, M.; Fallu-Labruyere, A.; Harris, J.; Breus, D.; Grudberg, P.; Warburton, W. K.

2009-11-01

A 624-channel Digital Data Acquisition System capable of instrumenting the Segmented Germanium Array at National Superconducting Cyclotron Laboratory has been implemented using Pixie-16 Digital Gamma Finder modules by XIA LLC. The system opens an opportunity for determination of the first interaction position of a γ ray in a SeGA detector from implementation of γ-ray tracking. This will translate into a significantly improved determination of angle of emission, and in consequence much better Doppler corrections for experiments with fast beams. For stopped-beam experiments the system provides means for zero dead time measurements of rare decays, which occur on time scales of microseconds.

Drug Adverse Event Detection in Health Plan Data Using the Gamma Poisson Shrinker and Comparison to the Tree-based Scan Statistic

PubMed Central

Brown, Jeffrey S.; Petronis, Kenneth R.; Bate, Andrew; Zhang, Fang; Dashevsky, Inna; Kulldorff, Martin; Avery, Taliser R.; Davis, Robert L.; Chan, K. Arnold; Andrade, Susan E.; Boudreau, Denise; Gunter, Margaret J.; Herrinton, Lisa; Pawloski, Pamala A.; Raebel, Marsha A.; Roblin, Douglas; Smith, David; Reynolds, Robert

2013-01-01

Background: Drug adverse event (AE) signal detection using the Gamma Poisson Shrinker (GPS) is commonly applied in spontaneous reporting. AE signal detection using large observational health plan databases can expand medication safety surveillance. Methods: Using data from nine health plans, we conducted a pilot study to evaluate the implementation and findings of the GPS approach for two antifungal drugs, terbinafine and itraconazole, and two diabetes drugs, pioglitazone and rosiglitazone. We evaluated 1676 diagnosis codes grouped into 183 different clinical concepts and four levels of granularity. Several signaling thresholds were assessed. GPS results were compared to findings from a companion study using the identical analytic dataset but an alternative statistical method—the tree-based scan statistic (TreeScan). Results: We identified 71 statistical signals across two signaling thresholds and two methods, including closely-related signals of overlapping diagnosis definitions. Initial review found that most signals represented known adverse drug reactions or confounding. About 31% of signals met the highest signaling threshold. Conclusions: The GPS method was successfully applied to observational health plan data in a distributed data environment as a drug safety data mining method. There was substantial concordance between the GPS and TreeScan approaches. Key method implementation decisions relate to defining exposures and outcomes and informed choice of signaling thresholds. PMID:24300404

Low energy proton capture study of the 14N(p, gamma)15O reaction

NASA Astrophysics Data System (ADS)

Daigle, Stephen Michael

The 14N(p,gamma)15O reaction regulates the rate of energy production for stars slightly more massive than the sun throughout stable hydrogen burning on the main sequence. The 14N(p,gamma)15O reaction rate also determines the luminosity for all stars after leaving the main sequence when their cores have exhausted hydrogen fuel, and later when they become red giant stars. The significant role that this reaction plays in stellar evolution has far-reaching consequences, from neutrino production in our Sun, to age estimates of globular clusters in our Galaxy. The weak cross section and inherent coincidence summing in the 15O gamma-ray decay scheme make a precision measurement of the astrophysical S-factor especially challenging, particularly for the ground-state transition. The present study, performed in the Laboratory for Experimental Nuclear Astrophysics (LENA), was aimed at measuring the ground-state transition at low energy by utilizing a new 24-element, position-sensitive, NaI(Tl) detector array. Because the array is highly segmented, the 14N( p,gamma)15O S-factor was evaluated for transitions to the ground, 5.18, 6.18, and 6.79 MeV states without the need for coincidence summing corrections. Additionally, the position-sensitivity of the detector was exploited to measure the angular correlation of the two-photon cascades. Software cuts were made to the data in order to identify single and coincident gamma-ray events and a fraction fit analysis technique was used to extract the characteristic 15O peaks from the composite gamma-ray spectrum. The results from the current work demonstrated a new approach to measuring weak nuclear cross sections near astrophysically relevant energies that, with refinements, has broader applications in gamma-ray spectroscopy.

Sky and Elemental Planetary Mapping Via Gamma Ray Emissions

NASA Technical Reports Server (NTRS)

Roland, John M.

2011-01-01

Low-energy gamma ray emissions ((is) approximately 30keV to (is) approximately 30MeV) are significant to astrophysics because many interesting objects emit their primary energy in this regime. As such, there has been increasing demand for a complete map of the gamma ray sky, but many experiments to do so have encountered obstacles. Using an innovative method of applying the Radon Transform to data from BATSE (the Burst And Transient Source Experiment) on NASA's CGRO (Compton Gamma-Ray Observatory) mission, we have circumvented many of these issues and successfully localized many known sources to 0.5 - 1 deg accuracy. Our method, which is based on a simple 2-dimensional planar back-projection approximation of the inverse Radon transform (familiar from medical CAT-scan technology), can thus be used to image the entire sky and locate new gamma ray sources, specifically in energy bands between 200keV and 2MeV which have not been well surveyed to date. Samples of these results will be presented. This same technique can also be applied to elemental planetary surface mapping via gamma ray spectroscopy. Due to our method's simplicity and power, it could potentially improve a current map's resolution by a significant factor.

Accuracy of non-operative identification of the sentinel lymph node using combined gamma and ultrasound scanning.

PubMed

Whelehan, P; Vinnicombe, S J; Brown, D C; McLean, D; Evans, A

2014-08-01

To assess how accurately the sentinel lymph node (SLN) can be identified percutaneously, using gamma probe and ultrasound technology. Women with breast cancer, scheduled for wide local excision or mastectomy with SLN biopsy (SLNB), were included. Peri-areolar intradermal injection of technetium-99 nanocolloid was performed on the morning of surgery and 1-2 ml of blue dye was injected in the peri-areolar region once the patient was anaesthetized. Prior to surgery, a gamma probe was used over the skin to identify any hot spot that could represent a SLN. Ultrasound, guided by the hot spot, was then used to visualize potential SLNs and guide the insertion of a localizing wire. The accuracy in localizing the SLN by preoperative gamma-probe guided ultrasonography was assessed by comparison to SLNB. A SLN was correctly identified and marked using gamma-probe guided ultrasonography in 44 of 59 cases (75%; 95% CI: 63-86%). This study supports the case for investigating percutaneous gamma probe and ultrasound guided interventions in the axilla in women with breast cancer, as a potential alternative to surgical SLNB. Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Growth plate closure: Apex view on bone scan

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

Giles, P.H.; Trochei, M.; Yeates, K.

1984-01-01

Angular deformities of the extremities in children following premature closure of the growth plate are well known. The deformities depend on the position of an osseus bridge which forms between the epiphysis and metaphysis. Several surgical procedures including resection of the osseus bridge have been described, however, delineation of the site of fusion is difficult to define. The commonest site of growth plate arrest is the distal femoral or proximal tibial growth plate. A new technique using the bone scan has been developed which accurately defines the area and position of these osseus bridges. Two hours after injection of technetiummore » 99m methylene diphosphonate apex views of the affected distal femoral growth plate were performed. The knee was flexed into its smallest angle. Using a pinhole collimator the gamma camera was angled to face the affected growth plate end on. The image was collected onto computer and analysed by: (I) regions of interest over segments of the growth plate to calculate the relative area of total growth plate affected: (II) generating histograms: (III) thresholding or performing isocontours to accentuate abnormal areas. The growth plate is normally uniformly increased when compared to the normal shaft of the bone. Fusion across the plate appears as an area of diminished uptake. The apex view gives a unique functional map of the growth plate such that abnormal areas are displayed, and the site, size and position of osseus fusion obtained. The technique has the potential for determining the metabolic activity of the growth plate before and after surgery. Serial studies will allow assessment of regneration of the plate and reformation of new osseus bridges.« less

Phenotypic consequences of deletion of the {gamma}{sub 3}, {alpha}{sub 5}, or {beta}{sub 3} subunit of the type A {gamma}-aminobutyric acid receptor in mice

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

Culia, C.T.; Stubbs, L.J.; Montgomery, C.S.

1994-03-29

Three genes (Gabrg3, Gabra5, and Gabrb3) encoding the {gamma}{sub 3}, {alpha}{sub 5}, and {beta}{sub 3} subunits of the type A {gamma}-aminobutyric acid receptor, respectively, are known to map near the pink-eyed dilution (p) locus in mouse chromosome 7. This region shares homology with a segment of human chromosome 15 that is implicated in Angelman syndrome, an inherited neurobehavioral disorder. By mapping Gabrg3-Gabra5-Gabrb3-telomere. Like Gabrb3, neither the Gabra5 nor Gabrg3 gene is functionally imprinted in adult mouse brain. Mice deleted for all three subunits die at birth with a cleft palate, although there are rare survivors ({approximately} 5%) that do notmore » have a cleft palate but do exhibit a neurological abnormality characterized by tremor, jerky gait, and runtiness. The authors have previously suggested that deficiency of the {beta}{sub 3} subunit may be responsible for the clefting defect. Most notably, however, in this report they describe mice carrying two overlapping, complementing p deletions that fail to express the {gamma}{sub 3} transcript, as well as mice from another line that express neither the {gamma}{sub 3} nor {alpha}{sub 5} transcripts. Surprisingly, mice from both of these lines are phenotypically normal and do not exhibit any of the neurological symptoms characteristic of the rare survivors that are deleted for all three ({gamma}{sub 3}, {alpha}{sub 5}, and {beta}{sub 3}) subunits. These mice therefore provide a whole-organism type A {gamma}-aminobutyric-acid receptor background that is devoid of any receptor subtypes that normally contain the {gamma}{sub 3} and/or {alpha}{sub 5} subunits. The absence of an overt neurological phenotype in mice lacking the {gamma}{sub 3} and/or {alpha}{sub 5} subunits also suggests that mutations in these genes are unlikely to provide useful animal models for Angelman syndrome in humans.« less

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

PubMed

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

1995-08-25

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

Object segmentation and recovery via neural oscillators implementing the similarity and prior knowledge gestalt rules.

PubMed

Ursino, Mauro; Magosso, Elisa; La Cara, Giuseppe-Emiliano; Cuppini, Cristiano

2006-09-01

Object recognition requires the solution of the binding and segmentation problems, i.e., grouping different features to achieve a coherent representation. Synchronization of neural activity in the gamma-band, associated with gestalt perception, has often been proposed as a putative mechanism to solve these problems, not only as to low-level processing, but also in higher cortical functions. In the present work, a network of Wilson-Cowan oscillators is used to segment simultaneous objects, and recover an object from partial or corrupted information, by implementing two gestalt rules: similarity and prior knowledge. The network consists of H different areas, each devoted to representation of a particular feature of the object, according to a topological organization. The similarity law is realized via lateral intra-area connections, arranged as a "Mexican-hat". Prior knowledge is realized via inter-area connections, which link properties belonging to a previously memorized object. A global inhibitor allows segmentation of several objects avoiding interference. Simulation results, performed using three simultaneous input objects, show that the network is able to detect an object even in difficult conditions (i.e., when some features are absent or shifted with respect to the original one). Moreover, the trade-off between sensitivity (capacity to detect true positives) and specificity (capacity to reject false positives) can be controlled acting on the extension of lateral synapses (i.e., on the level of accepted similarity). Finally, the network can also deal with correlated objects, i.e., objects which have some common features. Simulations performed using a different number of objects (2, 3, 4 or 5) suggest that the network is able to segment and recall up to four objects, but the oscillation frequency must increase, the lower the number of objects simultaneously present. The model, although quite simpler compared with neurophysiology, may represent a theoretical framework for the analysis of the relationships between object representation, memory, learning, and gamma-band activity. In particular, it extends previous studies on autoassociative memory since it exploits not only oscillatory dynamics, but also a topological organization of features.

HCP to FCT + precipitate transformations in lamellar gamma-titanium aluminide alloys

NASA Astrophysics Data System (ADS)

Karadge, Mallikarjun Baburao

Fully lamellar gamma-TiAl [alpha2(HCP) + gamma(FCT)] based alloys are potential structural materials for aerospace engine applications. Lamellar structure stabilization and additional strengthening mechanisms are major issues in the ongoing development of titanium aluminides due to the microstructural instability resulting from decomposition of the strengthening alpha 2 phase. This work addresses characterization of multi-component TiAl systems to identify the mechanism of lamellar structure refinement and assess the effects of light element additions (C and Si) on creep deformation behavior. Transmission electron microscopy studies directly confirmed for the first time that, fine lamellar structure is formed by the nucleation and growth of a large number of basal stacking faults on the 1/6<112¯0> dislocations cross slipping repeatedly into and out of basal planes. This lamellar structure can be tailored by modifying jog heights through chemistry and thermal processing. alpha 2 → gamma transformation during heating (investigated by differential scanning calorimetry and X-ray diffraction) is a two step process involving the formation of a novel disordered FCC gamma' TiAl [with a(gamma') = c(gamma)] as an intermediate phase followed by ordering. Addition of carbon and silicon induced Ti2AlC H-type carbide precipitation inside the alpha2 lath and Ti 5(Al,Si)3 zeta-type silicide precipitation at the alpha 2/gamma interface. The H-carbides preserve alpha2/gamma type interfaces, while zeta-silicide precipitates restrict ledge growth and interfacial sliding enabling strong resistance to creep deformation.

The effects of segmentation algorithms on the measurement of 18F-FDG PET texture parameters in non-small cell lung cancer.

PubMed

Bashir, Usman; Azad, Gurdip; Siddique, Muhammad Musib; Dhillon, Saana; Patel, Nikheel; Bassett, Paul; Landau, David; Goh, Vicky; Cook, Gary

2017-12-01

Measures of tumour heterogeneity derived from 18-fluoro-2-deoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) scans are increasingly reported as potential biomarkers of non-small cell lung cancer (NSCLC) for classification and prognostication. Several segmentation algorithms have been used to delineate tumours, but their effects on the reproducibility and predictive and prognostic capability of derived parameters have not been evaluated. The purpose of our study was to retrospectively compare various segmentation algorithms in terms of inter-observer reproducibility and prognostic capability of texture parameters derived from non-small cell lung cancer (NSCLC) 18 F-FDG PET/CT images. Fifty three NSCLC patients (mean age 65.8 years; 31 males) underwent pre-chemoradiotherapy 18 F-FDG PET/CT scans. Three readers segmented tumours using freehand (FH), 40% of maximum intensity threshold (40P), and fuzzy locally adaptive Bayesian (FLAB) algorithms. Intraclass correlation coefficient (ICC) was used to measure the inter-observer variability of the texture features derived by the three segmentation algorithms. Univariate cox regression was used on 12 commonly reported texture features to predict overall survival (OS) for each segmentation algorithm. Model quality was compared across segmentation algorithms using Akaike information criterion (AIC). 40P was the most reproducible algorithm (median ICC 0.9; interquartile range [IQR] 0.85-0.92) compared with FLAB (median ICC 0.83; IQR 0.77-0.86) and FH (median ICC 0.77; IQR 0.7-0.85). On univariate cox regression analysis, 40P found 2 out of 12 variables, i.e. first-order entropy and grey-level co-occurence matrix (GLCM) entropy, to be significantly associated with OS; FH and FLAB found 1, i.e., first-order entropy. For each tested variable, survival models for all three segmentation algorithms were of similar quality, exhibiting comparable AIC values with overlapping 95% CIs. Compared with both FLAB and FH, segmentation with 40P yields superior inter-observer reproducibility of texture features. Survival models generated by all three segmentation algorithms are of at least equivalent utility. Our findings suggest that a segmentation algorithm using a 40% of maximum threshold is acceptable for texture analysis of 18 F-FDG PET in NSCLC.

Techniques on semiautomatic segmentation using the Adobe Photoshop

NASA Astrophysics Data System (ADS)

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

2005-04-01

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

Automatic detection of cone photoreceptors in split detector adaptive optics scanning light ophthalmoscope images.

PubMed

Cunefare, David; Cooper, Robert F; Higgins, Brian; Katz, David F; Dubra, Alfredo; Carroll, Joseph; Farsiu, Sina

2016-05-01

Quantitative analysis of the cone photoreceptor mosaic in the living retina is potentially useful for early diagnosis and prognosis of many ocular diseases. Non-confocal split detector based adaptive optics scanning light ophthalmoscope (AOSLO) imaging reveals the cone photoreceptor inner segment mosaics often not visualized on confocal AOSLO imaging. Despite recent advances in automated cone segmentation algorithms for confocal AOSLO imagery, quantitative analysis of split detector AOSLO images is currently a time-consuming manual process. In this paper, we present the fully automatic adaptive filtering and local detection (AFLD) method for detecting cones in split detector AOSLO images. We validated our algorithm on 80 images from 10 subjects, showing an overall mean Dice's coefficient of 0.95 (standard deviation 0.03), when comparing our AFLD algorithm to an expert grader. This is comparable to the inter-observer Dice's coefficient of 0.94 (standard deviation 0.04). To the best of our knowledge, this is the first validated, fully-automated segmentation method which has been applied to split detector AOSLO images.

Dual-energy imaging method to improve the image quality and the accuracy of dose calculation for cone-beam computed tomography.

PubMed

Men, Kuo; Dai, Jianrong; Chen, Xinyuan; Li, Minghui; Zhang, Ke; Huang, Peng

2017-04-01

To improve the image quality and accuracy of dose calculation for cone-beam computed tomography (CT) images through implementation of a dual-energy cone-beam computed tomography method (DE-CBCT), and evaluate the improvement quantitatively. Two sets of CBCT projections were acquired using the X-ray volumetric imaging (XVI) system on a Synergy (Elekta, Stockholm, Sweden) system with 120kV (high) and 70kV (low) X-rays, respectively. Then, the electron density relative to water (relative electron density (RED)) of each voxel was calculated using a projection-based dual-energy decomposition method. As a comparison, single-energy cone-beam computed tomography (SE-CBCT) was used to calculate RED with the Hounsfield unit-RED calibration curve generated by a CIRS phantom scan with identical imaging parameters. The imaging dose was measured with a dosimetry phantom. The image quality was evaluated quantitatively using a Catphan 503 phantom with the evaluation indices of the reproducibility of the RED values, high-contrast resolution (MTF 50% ), uniformity, and signal-to-noise ratio (SNR). Dose calculation of two simulated volumetric-modulated arc therapy plans using an Eclipse treatment-planning system (Varian Medical Systems, Palo Alto, CA, USA) was performed on an Alderson Rando Head and Neck (H&N) phantom and a Pelvis phantom. Fan-beam planning CT images for the H&N and Pelvis phantom were set as the reference. A global three-dimensional gamma analysis was used to compare dose distributions with the reference. The average gamma values for targets and OAR were analyzed with paired t-tests between DE-CBCT and SE-CBCT. In two scans (H&N scan and body scan), the imaging dose of DE-CBCT increased by 1.0% and decreased by 1.3%. It had a better reproducibility of the RED values (mean bias: 0.03 and 0.07) compared with SE-CBCT (mean bias: 0.13 and 0.16). It also improved the image uniformity (57.5% and 30.1%) and SNR (9.7% and 2.3%), but did not affect the MTF 50% . Gamma analyses of the 3D dose distribution with criteria of 1%/1mm showed a pass rate of 99.0-100% and 85.3-97.6% for DE-CBCT and 73.5-99.1% and 80.4-92.7% for SE-CBCT. The average gamma values were reduced significantly by DE-CBCT (p< 0.05). Gamma index maps showed that matching of the dose distribution between CBCT-based and reference was improved by DE-CBCT. DE-CBCT can achieve both better image quality and higher accuracy of dose calculation, and could be applied to adaptive radiotherapy. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Simultaneous skull-stripping and lateral ventricle segmentation via fast multi-atlas likelihood fusion

NASA Astrophysics Data System (ADS)

Tang, Xiaoying; Kutten, Kwame; Ceritoglu, Can; Mori, Susumu; Miller, Michael I.

2015-03-01

In this paper, we propose and validate a fully automated pipeline for simultaneous skull-stripping and lateral ventricle segmentation using T1-weighted images. The pipeline is built upon a segmentation algorithm entitled fast multi-atlas likelihood-fusion (MALF) which utilizes multiple T1 atlases that have been pre-segmented into six whole-brain labels - the gray matter, the white matter, the cerebrospinal fluid, the lateral ventricles, the skull, and the background of the entire image. This algorithm, MALF, was designed for estimating brain anatomical structures in the framework of coordinate changes via large diffeomorphisms. In the proposed pipeline, we use a variant of MALF to estimate those six whole-brain labels in the test T1-weighted image. The three tissue labels (gray matter, white matter, and cerebrospinal fluid) and the lateral ventricles are then grouped together to form a binary brain mask to which we apply morphological smoothing so as to create the final mask for brain extraction. For computational purposes, all input images to MALF are down-sampled by a factor of two. In addition, small deformations are used for the changes of coordinates. This substantially reduces the computational complexity, hence we use the term "fast MALF". The skull-stripping performance is qualitatively evaluated on a total of 486 brain scans from a longitudinal study on Alzheimer dementia. Quantitative error analysis is carried out on 36 scans for evaluating the accuracy of the pipeline in segmenting the lateral ventricle. The volumes of the automated lateral ventricle segmentations, obtained from the proposed pipeline, are compared across three different clinical groups. The ventricle volumes from our pipeline are found to be sensitive to the diagnosis.

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

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.

Reproducibility of Brain Morphometry from Short-Term Repeat Clinical MRI Examinations: A Retrospective Study

PubMed Central

Liu, Hon-Man; Chen, Shan-Kai; Chen, Ya-Fang; Lee, Chung-Wei; Yeh, Lee-Ren

2016-01-01

Purpose To assess the inter session reproducibility of automatic segmented MRI-derived measures by FreeSurfer in a group of subjects with normal-appearing MR images. Materials and Methods After retrospectively reviewing a brain MRI database from our institute consisting of 14,758 adults, those subjects who had repeat scans and had no history of neurodegenerative disorders were selected for morphometry analysis using FreeSurfer. A total of 34 subjects were grouped by MRI scanner model. After automatic segmentation using FreeSurfer, label-wise comparison (involving area, thickness, and volume) was performed on all segmented results. An intraclass correlation coefficient was used to estimate the agreement between sessions. Wilcoxon signed rank test was used to assess the population mean rank differences across sessions. Mean-difference analysis was used to evaluate the difference intervals across scanners. Absolute percent difference was used to estimate the reproducibility errors across the MRI models. Kruskal-Wallis test was used to determine the across-scanner effect. Results The agreement in segmentation results for area, volume, and thickness measurements of all segmented anatomical labels was generally higher in Signa Excite and Verio models when compared with Sonata and TrioTim models. There were significant rank differences found across sessions in some labels of different measures. Smaller difference intervals in global volume measurements were noted on images acquired by Signa Excite and Verio models. For some brain regions, significant MRI model effects were observed on certain segmentation results. Conclusions Short-term scan-rescan reliability of automatic brain MRI morphometry is feasible in the clinical setting. However, since repeatability of software performance is contingent on the reproducibility of the scanner performance, the scanner performance must be calibrated before conducting such studies or before using such software for retrospective reviewing. PMID:26812647

Use of landsat ETM+ SLC-off segment-based gap-filled imagery for crop type mapping

USGS Publications Warehouse

Maxwell, S.K.; Craig, M.E.

2008-01-01

Failure of the Scan Line Corrector (SLC) on the Landsat ETM+ sensor has had a major impact on many applications that rely on continuous medium resolution imagery to meet their objectives. The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) program uses Landsat imagery as the primary source of data to produce crop-specific maps for 20 states in the USA. A new method has been developed to fill the image gaps resulting from the SLC failure to support the needs of Landsat users who require coincident spectral data, such as for crop type mapping and monitoring. We tested the new gap-filled method for a CDL crop type mapping project in eastern Nebraska. Scan line gaps were simulated on two Landsat 5 images (spring and late summer 2003) and then gap-filled using landscape boundary models, or segment models, that were derived from 1992 and 2002 Landsat images (used in the gap-fill process). Various date combinations of original and gap-filled images were used to derive crop maps using a supervised classification process. Overall kappa values were slightly higher for crop maps derived from SLC-off gap-filled images compared to crop maps derived from the original imagery (0.3–1.3% higher). Although the age of the segment model used to derive the SLC-off gap-filled product did not negatively impact the overall agreement, differences in individual cover type agreement did increase (−0.8%–1.6% using the 2002 segment model to −5.0–5.1% using the 1992 segment model). Classification agreement also decreased for most of the classes as the size of the segment used in the gap-fill process increased.

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

Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans

NASA Astrophysics Data System (ADS)

Lassen, B. C.; Jacobs, C.; Kuhnigk, J.-M.; van Ginneken, B.; van Rikxoort, E. M.

2015-02-01

The malignancy of lung nodules is most often detected by analyzing changes of the nodule diameter in follow-up scans. A recent study showed that comparing the volume or the mass of a nodule over time is much more significant than comparing the diameter. Since the survival rate is higher when the disease is still in an early stage it is important to detect the growth rate as soon as possible. However manual segmentation of a volume is time-consuming. Whereas there are several well evaluated methods for the segmentation of solid nodules, less work is done on subsolid nodules which actually show a higher malignancy rate than solid nodules. In this work we present a fast, semi-automatic method for segmentation of subsolid nodules. As minimal user interaction the method expects a user-drawn stroke on the largest diameter of the nodule. First, a threshold-based region growing is performed based on intensity analysis of the nodule region and surrounding parenchyma. In the next step the chest wall is removed by a combination of a connected component analyses and convex hull calculation. Finally, attached vessels are detached by morphological operations. The method was evaluated on all nodules of the publicly available LIDC/IDRI database that were manually segmented and rated as non-solid or part-solid by four radiologists (Dataset 1) and three radiologists (Dataset 2). For these 59 nodules the Jaccard index for the agreement of the proposed method with the manual reference segmentations was 0.52/0.50 (Dataset 1/Dataset 2) compared to an inter-observer agreement of the manual segmentations of 0.54/0.58 (Dataset 1/Dataset 2). Furthermore, the inter-observer agreement using the proposed method (i.e. different input strokes) was analyzed and gave a Jaccard index of 0.74/0.74 (Dataset 1/Dataset 2). The presented method provides satisfactory segmentation results with minimal observer effort in minimal time and can reduce the inter-observer variability for segmentation of subsolid nodules in clinical routine.

Metabolically active tumour volume segmentation from dynamic [(18)F]FLT PET studies in non-small cell lung cancer.

PubMed

Hoyng, Lieke L; Frings, Virginie; Hoekstra, Otto S; Kenny, Laura M; Aboagye, Eric O; Boellaard, Ronald

2015-01-01

Positron emission tomography (PET) with (18)F-3'-deoxy-3'-fluorothymidine ([(18)F]FLT) can be used to assess tumour proliferation. A kinetic-filtering (KF) classification algorithm has been suggested for segmentation of tumours in dynamic [(18)F]FLT PET data. The aim of the present study was to evaluate KF segmentation and its test-retest performance in [(18)F]FLT PET in non-small cell lung cancer (NSCLC) patients. Nine NSCLC patients underwent two 60-min dynamic [(18)F]FLT PET scans within 7 days prior to treatment. Dynamic scans were reconstructed with filtered back projection (FBP) as well as with ordered subsets expectation maximisation (OSEM). Twenty-eight lesions were identified by an experienced physician. Segmentation was performed using KF applied to the dynamic data set and a source-to-background corrected 50% threshold (A50%) was applied to the sum image of the last three frames (45- to 60-min p.i.). Furthermore, several adaptations of KF were tested. Both for KF and A50% test-retest (TRT) variability of metabolically active tumour volume and standard uptake value (SUV) were evaluated. KF performed better on OSEM- than on FBP-reconstructed PET images. The original KF implementation segmented 15 out of 28 lesions, whereas A50% segmented each lesion. Adapted KF versions, however, were able to segment 26 out of 28 lesions. In the best performing adapted versions, metabolically active tumour volume and SUV TRT variability was similar to those of A50%. KF misclassified certain tumour areas as vertebrae or liver tissue, which was shown to be related to heterogeneous [(18)F]FLT uptake areas within the tumour. For [(18)F]FLT PET studies in NSCLC patients, KF and A50% show comparable tumour volume segmentation performance. The KF method needs, however, a site-specific optimisation. The A50% is therefore a good alternative for tumour segmentation in NSCLC [(18)F]FLT PET studies in multicentre studies. Yet, it was observed that KF has the potential to subsegment lesions in high and low proliferative areas.

A semi-automatic technique to quantify complex tuberculous lung lesions on 18F-fluorodeoxyglucose positron emission tomography/computerised tomography images.

PubMed

Malherbe, Stephanus T; Dupont, Patrick; Kant, Ilse; Ahlers, Petri; Kriel, Magdalena; Loxton, André G; Chen, Ray Y; Via, Laura E; Thienemann, Friedrich; Wilkinson, Robert J; Barry, Clifton E; Griffith-Richards, Stephanie; Ellman, Annare; Ronacher, Katharina; Winter, Jill; Walzl, Gerhard; Warwick, James M

2018-06-25

There is a growing interest in the use of 18 F-FDG PET-CT to monitor tuberculosis (TB) treatment response. However, TB causes complex and widespread pathology, which is challenging to segment and quantify in a reproducible manner. To address this, we developed a technique to standardise uptake (Z-score), segment and quantify tuberculous lung lesions on PET and CT concurrently, in order to track changes over time. We used open source tools and created a MATLAB script. The technique was optimised on a training set of five pulmonary tuberculosis (PTB) cases after standard TB therapy and 15 control patients with lesion-free lungs. We compared the proposed method to a fixed threshold (SUV > 1) and manual segmentation by two readers and piloted the technique successfully on scans of five control patients and five PTB cases (four cured and one failed treatment case), at diagnosis and after 1 and 6 months of treatment. There was a better correlation between the Z-score-based segmentation and manual segmentation than SUV > 1 and manual segmentation in terms of overall spatial overlap (measured in Dice similarity coefficient) and specificity (1 minus false positive volume fraction). However, SUV > 1 segmentation appeared more sensitive. Both the Z-score and SUV > 1 showed very low variability when measuring change over time. In addition, total glycolytic activity, calculated using segmentation by Z-score and lesion-to-background ratio, correlated well with traditional total glycolytic activity calculations. The technique quantified various PET and CT parameters, including the total glycolytic activity index, metabolic lesion volume, lesion volumes at different CT densities and combined PET and CT parameters. The quantified metrics showed a marked decrease in the cured cases, with changes already apparent at month one, but remained largely unchanged in the failed treatment case. Our technique is promising to segment and quantify the lung scans of pulmonary tuberculosis patients in a semi-automatic manner, appropriate for measuring treatment response. Further validation is required in larger cohorts.

Automated measurements of metabolic tumor volume and metabolic parameters in lung PET/CT imaging

NASA Astrophysics Data System (ADS)

Orologas, F.; Saitis, P.; Kallergi, M.

2017-11-01

Patients with lung tumors or inflammatory lung disease could greatly benefit in terms of treatment and follow-up by PET/CT quantitative imaging, namely measurements of metabolic tumor volume (MTV), standardized uptake values (SUVs) and total lesion glycolysis (TLG). The purpose of this study was the development of an unsupervised or partially supervised algorithm using standard image processing tools for measuring MTV, SUV, and TLG from lung PET/CT scans. Automated metabolic lesion volume and metabolic parameter measurements were achieved through a 5 step algorithm: (i) The segmentation of the lung areas on the CT slices, (ii) the registration of the CT segmented lung regions on the PET images to define the anatomical boundaries of the lungs on the functional data, (iii) the segmentation of the regions of interest (ROIs) on the PET images based on adaptive thresholding and clinical criteria, (iv) the estimation of the number of pixels and pixel intensities in the PET slices of the segmented ROIs, (v) the estimation of MTV, SUVs, and TLG from the previous step and DICOM header data. Whole body PET/CT scans of patients with sarcoidosis were used for training and testing the algorithm. Lung area segmentation on the CT slices was better achieved with semi-supervised techniques that reduced false positive detections significantly. Lung segmentation results agreed with the lung volumes published in the literature while the agreement between experts and algorithm in the segmentation of the lesions was around 88%. Segmentation results depended on the image resolution selected for processing. The clinical parameters, SUV (either mean or max or peak) and TLG estimated by the segmented ROIs and DICOM header data provided a way to correlate imaging data to clinical and demographic data. In conclusion, automated MTV, SUV, and TLG measurements offer powerful analysis tools in PET/CT imaging of the lungs. Custom-made algorithms are often a better approach than the manufacturer’s general analysis software at much lower cost. Relatively simple processing techniques could lead to customized, unsupervised or partially supervised methods that can successfully perform the desirable analysis and adapt to the specific disease requirements.

Effect of target color and scanning geometry on terrestrial LiDAR point-cloud noise and plane fitting

NASA Astrophysics Data System (ADS)

Bolkas, Dimitrios; Martinez, Aaron

2018-01-01

Point-cloud coordinate information derived from terrestrial Light Detection And Ranging (LiDAR) is important for several applications in surveying and civil engineering. Plane fitting and segmentation of target-surfaces is an important step in several applications such as in the monitoring of structures. Reliable parametric modeling and segmentation relies on the underlying quality of the point-cloud. Therefore, understanding how point-cloud errors affect fitting of planes and segmentation is important. Point-cloud intensity, which accompanies the point-cloud data, often goes hand-in-hand with point-cloud noise. This study uses industrial particle boards painted with eight different colors (black, white, grey, red, green, blue, brown, and yellow) and two different sheens (flat and semi-gloss) to explore how noise and plane residuals vary with scanning geometry (i.e., distance and incidence angle) and target-color. Results show that darker colors, such as black and brown, can produce point clouds that are several times noisier than bright targets, such as white. In addition, semi-gloss targets manage to reduce noise in dark targets by about 2-3 times. The study of plane residuals with scanning geometry reveals that, in many of the cases tested, residuals decrease with increasing incidence angles, which can assist in understanding the distribution of plane residuals in a dataset. Finally, a scheme is developed to derive survey guidelines based on the data collected in this experiment. Three examples demonstrate that users should consider instrument specification, required precision of plane residuals, required point-spacing, target-color, and target-sheen, when selecting scanning locations. Outcomes of this study can aid users to select appropriate instrumentation and improve planning of terrestrial LiDAR data-acquisition.

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

PubMed

Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

2018-01-01

The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

Investigation of the accuracy of breast tissue segmentation methods for the purpose of developing breast deformation models for use in adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Juneja, P.; Harris, E. J.; Evans, P. M.

2014-03-01

Realistic modelling of breast deformation requires the breast tissue to be segmented into fibroglandular and fatty tissue and assigned suitable material properties. There are a number of breast tissue segmentation methods proposed and used in the literature. The purpose of this study was to validate and compare the accuracy of various segmentation methods and to investigate the effect of the tissue distribution on the segmentation accuracy. Computed tomography (CT) data for 24 patients, both in supine and prone positions were segmented into fibroglandular and fatty tissue. The segmentation methods explored were: physical density thresholding; interactive thresholding; fuzzy c-means clustering (FCM) with three classes (FCM3) and four classes (FCM4); and k-means clustering. Validation was done in two-stages: firstly, a new approach, supine-prone validation based on the assumption that the breast composition should appear the same in the supine and prone scans was used. Secondly, outlines from three experts were used for validation. This study found that FCM3 gave the most accurate segmentation of breast tissue from CT data and that the segmentation accuracy is adversely affected by the sparseness of the fibroglandular tissue distribution.

Segmentation of deformable organs from medical images using particle swarm optimization and nonlinear shape priors

NASA Astrophysics Data System (ADS)

Afifi, Ahmed; Nakaguchi, Toshiya; Tsumura, Norimichi

2010-03-01

In many medical applications, the automatic segmentation of deformable organs from medical images is indispensable and its accuracy is of a special interest. However, the automatic segmentation of these organs is a challenging task according to its complex shape. Moreover, the medical images usually have noise, clutter, or occlusion and considering the image information only often leads to meager image segmentation. In this paper, we propose a fully automated technique for the segmentation of deformable organs from medical images. In this technique, the segmentation is performed by fitting a nonlinear shape model with pre-segmented images. The kernel principle component analysis (KPCA) is utilized to capture the complex organs deformation and to construct the nonlinear shape model. The presegmentation is carried out by labeling each pixel according to its high level texture features extracted using the overcomplete wavelet packet decomposition. Furthermore, to guarantee an accurate fitting between the nonlinear model and the pre-segmented images, the particle swarm optimization (PSO) algorithm is employed to adapt the model parameters for the novel images. In this paper, we demonstrate the competence of proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans of different patients.

Probabilistic brain tissue segmentation in neonatal magnetic resonance imaging.

PubMed

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

2008-02-01

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

Nuclear myocardial perfusion imaging using thallium-201 with a novel multifocal collimator SPECT/CT: IQ-SPECT versus conventional protocols in normal subjects.

PubMed

Matsuo, Shinro; Nakajima, Kenichi; Onoguchi, Masahisa; Wakabayash, Hiroshi; Okuda, Koichi; Kinuya, Seigo

2015-06-01

A novel multifocal collimator, IQ-SPECT (Siemens) consists of SMARTZOOM, cardio-centric and 3D iterative SPECT reconstruction and makes it possible to perform MPI scans in a short time. The aims are to delineate the normal uptake in thallium-201 ((201)Tl) SPECT in each acquisition method and to compare the distribution between new and conventional protocol, especially in patients with normal imaging. Forty patients (eight women, mean age of 75 years) who underwent myocardial perfusion imaging were included in the study. All patients underwent one-day protocol perfusion scan after an adenosine-stress test and at rest after administering (201)Tl and showed normal results. Acquisition was performed on a Symbia T6 equipped with a conventional dual-headed gamma camera system (Siemens ECAM) and with a multifocal SMARTZOOM collimator. Imaging was performed with a conventional system followed by IQ-SPECT/computed tomography (CT). Reconstruction was performed with or without X-ray CT-derived attenuation correction (AC). Two nuclear physicians blinded to clinical information interpreted all myocardial perfusion images. A semi-quantitative myocardial perfusion was analyzed by a 17-segment model with a 5-point visual scoring. The uptake of each segment was measured and left ventricular functions were analyzed by QPS software. IQ-SPECT provided good or excellent image quality. The quality of IQ-SPECT images without AC was similar to those of conventional LEHR study. Mid-inferior defect score (0.3 ± 0.5) in the conventional LEHR study was increased significantly in IQ-SPECT with AC (0 ± 0). IQ-SPECT with AC improved the mid-inferior decreased perfusion shown in conventional images. The apical tracer count in IQ-SPECT with AC was decreased compared to that in LEHR (0.1 ± 0.3 vs. 0.5 ± 0.7, p < 0.05). The left ventricular ejection fraction from IQ-SPECT was significantly higher than that from the LEHR collimator (p = 0.0009). The images of IQ-SPECT acquired in a short time are equivalent to that of conventional LEHR. The results indicated that the IQ-SPECT system with AC is capable of correcting inferior artifacts with high image quality.

On Interpreting Stereo Disparity

DTIC Science & Technology

1989-04-01

denominators shall now be examined in some detail. The term _," (R) can h, expanded (with the aid of double angle formulas) as -x[&(x,y) .(cos 20, sin 20...histogram computations: Expand eight- connectivity regions about a central pixel until the desired number of inputs have been scanned. In this example, it...takes two iterations of the algorithm to locate the second line segment. For this figure, line segments are depicted with black; expanding serach

Testing and Performance Validation of a Sensitive Gamma Ray Camera Designed for Radiation Detection and Decommissioning Measurements in Nuclear Facilities-13044

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

Mason, John A.; Looman, Marc R.; Poundall, Adam J.

2013-07-01

This paper describes the measurements, testing and performance validation of a sensitive gamma ray camera designed for radiation detection and quantification in the environment and decommissioning and hold-up measurements in nuclear facilities. The instrument, which is known as RadSearch, combines a sensitive and highly collimated LaBr{sub 3} scintillation detector with an optical (video) camera with controllable zoom and focus and a laser range finder in one detector head. The LaBr{sub 3} detector has a typical energy resolution of between 2.5% and 3% at the 662 keV energy of Cs-137 compared to that of NaI detectors with a resolution of typicallymore » 7% to 8% at the same energy. At this energy the tungsten shielding of the detector provides a shielding ratio of greater than 900:1 in the forward direction and 100:1 on the sides and from the rear. The detector head is mounted on a pan/tile mechanism with a range of motion of ±180 degrees (pan) and ±90 degrees (tilt) equivalent to 4 π steradians. The detector head with pan/tilt is normally mounted on a tripod or wheeled cart. It can also be mounted on vehicles or a mobile robot for access to high dose-rate areas and areas with high levels of contamination. Ethernet connects RadSearch to a ruggedized notebook computer from which it is operated and controlled. Power can be supplied either as 24-volts DC from a battery or as 50 volts DC supplied by a small mains (110 or 230 VAC) power supply unit that is co-located with the controlling notebook computer. In this latter case both power and Ethernet are supplied through a single cable that can be up to 80 metres in length. If a local battery supplies power, the unit can be controlled through wireless Ethernet. Both manual operation and automatic scanning of surfaces and objects is available through the software interface on the notebook computer. For each scan element making up a part of an overall scanned area, the unit measures a gamma ray spectrum. Multiple radionuclides may be selected by the operator and will be identified if present. In scanning operation the unit scans a designated region and superimposes over a video image the distribution of measured radioactivity. For the total scanned area or object RadSearch determines the total activity of operator selected radionuclides present and the gamma dose-rate measured at the detector head. Results of hold-up measurements made in a nuclear facility are presented, as are test measurements of point sources distributed arbitrarily on surfaces. These latter results are compared with the results of benchmarked MCNP Monte Carlo calculations. The use of the device for hold-up and decommissioning measurements is validated. (authors)« less

Design and performance tests of the calorimetric tract of a Compton Camera for small-animals imaging

NASA Astrophysics Data System (ADS)

Rossi, P.; Baldazzi, G.; Battistella, A.; Bello, M.; Bollini, D.; Bonvicini, V.; Fontana, C. L.; Gennaro, G.; Moschini, G.; Navarria, F.; Rashevsky, A.; Uzunov, N.; Zampa, G.; Zampa, N.; Vacchi, A.

2011-02-01

The bio-distribution and targeting capability of pharmaceuticals may be assessed in small animals by imaging gamma-rays emitted from radio-isotope markers. Detectors that exploit the Compton concept allow higher gamma-ray efficiency compared to conventional Anger cameras employing collimators, and feature sub-millimeter spatial resolution and compact geometry. We are developing a Compton Camera that has to address several requirements: the high rates typical of the Compton concept; detection of gamma-rays of different energies that may range from 140 keV ( 99 mTc) to 511 keV ( β+ emitters); presence of gamma and beta radiation with energies up to 2 MeV in case of 188Re. The camera consists of a thin position-sensitive Tracker that scatters the gamma ray, and a second position-sensitive detection system to totally absorb the energy of the scattered photons (Calorimeter). In this paper we present the design and discuss the realization of the calorimetric tract, including the choice of scintillator crystal, pixel size, and detector geometry. Simulations of the gamma-ray trajectories from source to detectors have helped to assess the accuracy of the system and decide on camera design. Crystals of different materials, such as LaBr 3 GSO and YAP, and of different size, in continuous or segmented geometry, have been optically coupled to a multi-anode Hamamatsu H8500 detector, allowing measurements of spatial resolution and efficiency.

Essays in Space Science

NASA Technical Reports Server (NTRS)

Ramaty, Reuven (Editor); Cline, Thomas L. (Editor); Ormes, Jonathan F. (Editor)

1987-01-01

The papers presented cover a broad segment of space research and are an acknowledgement of the personal involvement of Frank McDonald in many of these efforts. The totality of the papers were chosen so as to sample the scientific areas influenced by him in a significant manner. Three broad areas are covered: particles and fields of the solar system; cosmic ray astrophysics; and gamma ray, X-ray, and infrared astronomics.

Gamma index evaluation of IMRT technique using gafchromic film EBT3 for homogeneous and inhomogeneous material

NASA Astrophysics Data System (ADS)

Nisauf, T. A.; Wibowo, W. E.; Pawiro, S. A.

2017-07-01

This study was done to evaluate the gamma index for registering between the planar of dose planning and the measurement of EBT film. The treatment plan was simulated for 5 patients using Fan Beam Computerized Tomography (FBCT) modality, Philips Pinnacle planning system, 6 MV photon energy, 50 segments IMRT technique, and calculation grid resolution (CGR) of 0.2 cm. Gamma Index (GI) evaluation was done with criteria of dose difference (DD) of 2 %, dose to agreement (DTA) of 2 mm and dose difference (DD) of 5 % DTA of 3 mm, SAD 100 cm, depth of 5 cm and 10 cm of the phantom. The result shows that GI for homogeneous material is greater than for inhomogeneous material with discrepancy to previous work is about 1.98 % for homogeneous material (depth 5 cm) and 2.05 % (depth 10 cm) while it was found of 2.98 % for inhomogeneous material (equivalent depth 5 cm) and 4.59 % (equivalent depth 10 cm).

Synchronization Dynamics in Response to Plaid Stimuli in Monkey V1

PubMed Central

Lima, Bruss; Singer, Wolf; Chen, Nan-Hui

2010-01-01

Gamma synchronization has generally been associated with grouping processes in the visual system. Here, we examine in monkey V1 whether gamma oscillations play a functional role in segmenting surfaces of plaid stimuli. Local field potentials (LFPs) and spiking activity were recorded simultaneously from multiple sites in the opercular and calcarine regions while the monkeys were presented with sequences of single and superimposed components of plaid stimuli. In accord with the previous studies, responses to the single components (gratings) exhibited strong and sustained gamma-band oscillations (30–65 Hz). The superposition of the second component, however, led to profound changes in the temporal structure of the responses, characterized by a drastic reduction of gamma oscillations in the spiking activity and systematic shifts to higher frequencies in the LFP (∼10% increase). Comparisons between cerebral hemispheres and across monkeys revealed robust subject-specific spectral signatures. A possible interpretation of our results may be that single gratings induce strong cooperative interactions among populations of cells that share similar response properties, whereas plaids lead to competition. Overall, our results suggest that the functional architecture of the cortex is a major determinant of the neuronal synchronization dynamics in V1. PMID:19812238

Automatic segmentation of cortical vessels in pre- and post-tumor resection laser range scan images

NASA Astrophysics Data System (ADS)

Ding, Siyi; Miga, Michael I.; Thompson, Reid C.; Garg, Ishita; Dawant, Benoit M.

2009-02-01

Measurement of intra-operative cortical brain movement is necessary to drive mechanical models developed to predict sub-cortical shift. At our institution, this is done with a tracked laser range scanner. This device acquires both 3D range data and 2D photographic images. 3D cortical brain movement can be estimated if 2D photographic images acquired over time can be registered. Previously, we have developed a method, which permits this registration using vessels visible in the images. But, vessel segmentation required the localization of starting and ending points for each vessel segment. Here, we propose a method, which automates the segmentation process further. This method involves several steps: (1) correction of lighting artifacts, (2) vessel enhancement, and (3) vessels' centerline extraction. Result obtained on 5 images obtained in the operating room suggests that our method is robust and is able to segment vessels reliably.

Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Charpiat, Guillaume; Brucker, Ludovic; Menze, Bjoern H.

2014-01-01

We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

Atlas-based liver segmentation and hepatic fat-fraction assessment for clinical trials.

PubMed

Yan, Zhennan; Zhang, Shaoting; Tan, Chaowei; Qin, Hongxing; Belaroussi, Boubakeur; Yu, Hui Jing; Miller, Colin; Metaxas, Dimitris N

2015-04-01

Automated assessment of hepatic fat-fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of hepatic fat-fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver anatomy as well as the diverse sources the images were acquired from. In this paper, we propose an automated and robust framework for liver segmentation and assessment. It uses single statistical atlas registration to initialize a robust deformable model to obtain fine segmentation. Fat-fraction map is computed by using chemical shift based method in the delineated region of liver. This proposed method is validated on 14 abdominal magnetic resonance (MR) volumetric scans. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance comparing with two other atlas-based methods. Experimental results demonstrate the promises of our assessment framework. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sloped terrain segmentation for autonomous drive using sparse 3D point cloud.

PubMed

Cho, Seoungjae; Kim, Jonghyun; Ikram, Warda; Cho, Kyungeun; Jeong, Young-Sik; Um, Kyhyun; Sim, Sungdae

2014-01-01

A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D) point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels) and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame.

Progress in manufacturing the first 8.4 m off-axis segment for the Giant Magellan Telescope

NASA Astrophysics Data System (ADS)

Martin, H. M.; Burge, J. H.; Cuerden, B.; Davison, W. B.; Kingsley, J. S.; Kittrell, W. C.; Lutz, R. D.; Miller, S. M.; Zhao, C.; Zobrist, T.

2008-07-01

The first of the 8.4 m off-axis segments for the primary mirror of the Giant Magellan Telescope is being manufactured at the Steward Observatory Mirror Lab. In addition to the manufacture of the segment, this project includes the development of a complete facility to make and measure all seven segments. We have installed a new 28 m test tower and designed a set of measurements to guide the fabrication and qualify the finished segments. The first test, a laser-tracker measurement of the ground surface, is operational. The principal optical test is a full-aperture interferometric test with a null corrector that includes a 3.75 m spherical mirror, a smaller sphere, and a computer-generated hologram. We have also designed a scanning pentaprism test to validate the measurement of low-order aberrations. The first segment has been cast and generated, and is in the process of loose-abrasive grinding.

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-4 scientific results

NASA Technical Reports Server (NTRS)

Matteson, J.

1979-01-01

Observations of galactic sources, extragalactic sources and gamma bursts with the A-4 instrument at energy 1 energies of between 0.1 to 10 MeV are discussed. Aximuthal scans are presented. The Crab Nebula and its spectrum and the spectrum of Cygnus Z-1 are described.