Automatic segmentation of coronary vessels from digital subtracted angiograms: a knowledge-based approach

International Nuclear Information System (INIS)

Stansfield, S.A.

1986-01-01

This paper presents a rule-based expert system for identifying and isolating coronary vessels in digital angiograms. The system is written in OPS5 and LISP and uses low level processors written in C. The system embodies both stages of the vision hierarchy: The low level image processing stage works concurrently with edges (or lines) and regions to segment the input image. Its knowledge is that of segmentation, grouping, and shape analysis. The high level stage then uses its knowledge of cardiac anatomy and physiology to interpret the result and to eliminate those structures not desired in the output. (Auth.)

A higher-order tensor vessel tractography for segmentation of vascular structures.

Science.gov (United States)

Cetin, Suheyla; Unal, Gozde

2015-10-01

A new vascular structure segmentation method, which is based on a cylindrical flux-based higher order tensor (HOT), is presented. On a vessel structure, the HOT naturally models branching points, which create challenges for vessel segmentation algorithms. In a general linear HOT model embedded in 3D, one has to work with an even order tensor due to an enforced antipodal-symmetry on the unit sphere. However, in scenarios such as in a bifurcation, the antipodally-symmetric tensor embedded in 3D will not be useful. In order to overcome that limitation, we embed the tensor in 4D and obtain a structure that can model asymmetric junction scenarios. During construction of a higher order tensor (e.g. third or fourth order) in 4D, the orientation vectors lie on the unit 3-sphere, in contrast to the unit 2-sphere in 3D tensor modeling. This 4D tensor is exploited in a seed-based vessel segmentation algorithm, where the principal directions of the 4D HOT is obtained by decomposition, and used in a HOT tractography approach. We demonstrate quantitative validation of the proposed algorithm on both synthetic complex tubular structures as well as real cerebral vasculature in Magnetic Resonance Angiography (MRA) datasets and coronary arteries from Computed Tomography Angiography (CTA) volumes.

Automatic Vessel Segmentation on Retinal Images

Institute of Scientific and Technical Information of China (English)

Chun-Yuan Yu; Chia-Jen Chang; Yen-Ju Yao; Shyr-Shen Yu

2014-01-01

Several features of retinal vessels can be used to monitor the progression of diseases. Changes in vascular structures, for example, vessel caliber, branching angle, and tortuosity, are portents of many diseases such as diabetic retinopathy and arterial hyper-tension. This paper proposes an automatic retinal vessel segmentation method based on morphological closing and multi-scale line detection. First, an illumination correction is performed on the green band retinal image. Next, the morphological closing and subtraction processing are applied to obtain the crude retinal vessel image. Then, the multi-scale line detection is used to fine the vessel image. Finally, the binary vasculature is extracted by the Otsu algorithm. In this paper, for improving the drawbacks of multi-scale line detection, only the line detectors at 4 scales are used. The experimental results show that the accuracy is 0.939 for DRIVE (digital retinal images for vessel extraction) retinal database, which is much better than other methods.

Multimodal MEMPRAGE, FLAIR, and R2* Segmentation to Resolve Dura and Vessels from Cortical Gray Matter

Directory of Open Access Journals (Sweden)

Roberto Viviani

2017-05-01

Full Text Available While widely in use in automated segmentation approaches for the detection of group differences or of changes associated with continuous predictors in gray matter volume, T1-weighted images are known to represent dura and cortical vessels with signal intensities similar to those of gray matter. By considering multiple signal sources at once, multimodal segmentation approaches may be able to resolve these different tissue classes and address this potential confound. We explored here the simultaneous use of FLAIR and apparent transverse relaxation rates (a signal related to T2* relaxation maps and having similar contrast with T1-weighted images. Relative to T1-weighted images alone, multimodal segmentation had marked positive effects on 1. the separation of gray matter from dura, 2. the exclusion of vessels from the gray matter compartment, and 3. the contrast with extracerebral connective tissue. While obtainable together with the T1-weighted images without increasing scanning times, apparent transverse relaxation rates were less effective than added FLAIR images in providing the above mentioned advantages. FLAIR images also improved the detection of cortical matter in areas prone to susceptibility artifacts in standard MPRAGE T1-weighted images, while the addition of transverse relaxation maps exacerbated the effect of these artifacts on segmentation. Our results confirm that standard MPRAGE segmentation may overestimate gray matter volume by wrongly assigning vessels and dura to this compartment and show that multimodal approaches may greatly improve the specificity of cortical segmentation. Since multimodal segmentation is easily implemented, these benefits are immediately available to studies focusing on translational applications of structural imaging.

Supervised retinal vessel segmentation from color fundus images based on matched filtering and AdaBoost classifier.

Directory of Open Access Journals (Sweden)

Nogol Memari

Full Text Available The structure and appearance of the blood vessel network in retinal fundus images is an essential part of diagnosing various problems associated with the eyes, such as diabetes and hypertension. In this paper, an automatic retinal vessel segmentation method utilizing matched filter techniques coupled with an AdaBoost classifier is proposed. The fundus image is enhanced using morphological operations, the contrast is increased using contrast limited adaptive histogram equalization (CLAHE method and the inhomogeneity is corrected using Retinex approach. Then, the blood vessels are enhanced using a combination of B-COSFIRE and Frangi matched filters. From this preprocessed image, different statistical features are computed on a pixel-wise basis and used in an AdaBoost classifier to extract the blood vessel network inside the image. Finally, the segmented images are postprocessed to remove the misclassified pixels and regions. The proposed method was validated using publicly accessible Digital Retinal Images for Vessel Extraction (DRIVE, Structured Analysis of the Retina (STARE and Child Heart and Health Study in England (CHASE_DB1 datasets commonly used for determining the accuracy of retinal vessel segmentation methods. The accuracy of the proposed segmentation method was comparable to other state of the art methods while being very close to the manual segmentation provided by the second human observer with an average accuracy of 0.972, 0.951 and 0.948 in DRIVE, STARE and CHASE_DB1 datasets, respectively.

Multiscale Vessel-guided Airway Tree Segmentation

DEFF Research Database (Denmark)

Lo, Pechin Chien Pau; Sporring, Jon; de Bruijne, Marleen

2009-01-01

This paper presents a method for airway tree segmentation that uses a combination of a trained airway appearance model, vessel and airway orientation information, and region growing. The method uses a voxel classification based appearance model, which involves the use of a classifier that is trai...

Segmentation of vessels cluttered with cells using a physics based model.

Science.gov (United States)

Schmugge, Stephen J; Keller, Steve; Nguyen, Nhat; Souvenir, Richard; Huynh, Toan; Clemens, Mark; Shin, Min C

2008-01-01

Segmentation of vessels in biomedical images is important as it can provide insight into analysis of vascular morphology, topology and is required for kinetic analysis of flow velocity and vessel permeability. Intravital microscopy is a powerful tool as it enables in vivo imaging of both vasculature and circulating cells. However, the analysis of vasculature in those images is difficult due to the presence of cells and their image gradient. In this paper, we provide a novel method of segmenting vessels with a high level of cell related clutter. A set of virtual point pairs ("vessel probes") are moved reacting to forces including Vessel Vector Flow (VVF) and Vessel Boundary Vector Flow (VBVF) forces. Incorporating the cell detection, the VVF force attracts the probes toward the vessel, while the VBVF force attracts the virtual points of the probes to localize the vessel boundary without being distracted by the image features of the cells. The vessel probes are moved according to Newtonian Physics reacting to the net of forces applied on them. We demonstrate the results on a set of five real in vivo images of liver vasculature cluttered by white blood cells. When compared against the ground truth prepared by the technician, the Root Mean Squared Error (RMSE) of segmentation with VVF and VBVF was 55% lower than the method without VVF and VBVF.

An Automatic Cognitive Graph-Based Segmentation for Detection of Blood Vessels in Retinal Images

Directory of Open Access Journals (Sweden)

Rasha Al Shehhi

2016-01-01

Full Text Available This paper presents a hierarchical graph-based segmentation for blood vessel detection in digital retinal images. This segmentation employs some of perceptual Gestalt principles: similarity, closure, continuity, and proximity to merge segments into coherent connected vessel-like patterns. The integration of Gestalt principles is based on object-based features (e.g., color and black top-hat (BTH morphology and context and graph-analysis algorithms (e.g., Dijkstra path. The segmentation framework consists of two main steps: preprocessing and multiscale graph-based segmentation. Preprocessing is to enhance lighting condition, due to low illumination contrast, and to construct necessary features to enhance vessel structure due to sensitivity of vessel patterns to multiscale/multiorientation structure. Graph-based segmentation is to decrease computational processing required for region of interest into most semantic objects. The segmentation was evaluated on three publicly available datasets. Experimental results show that preprocessing stage achieves better results compared to state-of-the-art enhancement methods. The performance of the proposed graph-based segmentation is found to be consistent and comparable to other existing methods, with improved capability of detecting small/thin vessels.

Semiautomated segmentation of blood vessels using ellipse-overlap criteria: Method and comparison to manual editing

International Nuclear Information System (INIS)

Shiffman, Smadar; Rubin, Geoffrey D.; Schraedley-Desmond, Pamela; Napel, Sandy

2003-01-01

Two-dimensional intensity-based methods for the segmentation of blood vessels from computed-tomography-angiography data often result in spurious segments that originate from other objects whose intensity distributions overlap with those of the vessels. When segmented images include spurious segments, additional methods are required to select segments that belong to the target vessels. We describe a method that allows experts to select vessel segments from sequences of segmented images with little effort. Our method uses ellipse-overlap criteria to differentiate between segments that belong to different objects and are separated in plane but are connected in the through-plane direction. To validate our method, we used it to extract vessel regions from volumes that were segmented via analysis of isolabel-contour maps, and showed that the difference between the results of our method and manually-edited results was within inter-expert variability. Although the total editing duration for our method, which included user-interaction and computer processing, exceeded that of manual editing, the extent of user interaction required for our method was about a fifth of that required for manual editing

Comparative Study of Retinal Vessel Segmentation Based on Global Thresholding Techniques

Directory of Open Access Journals (Sweden)

Temitope Mapayi

2015-01-01

Full Text Available Due to noise from uneven contrast and illumination during acquisition process of retinal fundus images, the use of efficient preprocessing techniques is highly desirable to produce good retinal vessel segmentation results. This paper develops and compares the performance of different vessel segmentation techniques based on global thresholding using phase congruency and contrast limited adaptive histogram equalization (CLAHE for the preprocessing of the retinal images. The results obtained show that the combination of preprocessing technique, global thresholding, and postprocessing techniques must be carefully chosen to achieve a good segmentation performance.

Best practices for preparing vessel internals segmentation projects

International Nuclear Information System (INIS)

Boucau, Joseph; Segerud, Per; Sanchez, Moises

2016-01-01

Westinghouse has been involved in reactor internals segmentation activities in the U.S. and Europe for 30 years. Westinghouse completed in 2015 the segmentation of the reactor vessel and reactor vessel internals at the Jose Cabrera nuclear power plant in Spain and a similar project is on-going at Chooz A in France. For all reactor dismantling projects, it is essential that all activities are thoroughly planned and discussed up-front together with the customer. Detailed planning is crucial for achieving a successful project. One key activity in the preparation phase is the 'Segmentation and Packaging Plan' that documents the sequential steps required to segment, separate, and package each individual component, based on an activation analysis and component characterization study. Detailed procedures and specialized rigging equipment have to be developed to provide safeguards for preventing certain identified risks. The preparatory work can include some plant civil structure modifications for making the segmentation work easier and safer. Some original plant equipment is sometimes not suitable enough and need to be replaced. Before going to the site, testing and qualification are performed on full scale mock-ups in a specially designed pool for segmentation purposes. The mockup testing is an important step in order to verify the function of the equipment and minimize risk on site. This paper is describing the typical activities needed for preparing the reactor internals segmentation activities using under water mechanical cutting techniques. It provides experiences and lessons learned that Westinghouse has collected from its recent projects and that will be applied for the new awarded projects. (authors)

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

Science.gov (United States)

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

2017-11-01

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

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

Science.gov (United States)

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

2011-04-01

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

Hybrid Segmentation of Vessels and Automated Flow Measures in In-Vivo Ultrasound Imaging

DEFF Research Database (Denmark)

Moshavegh, Ramin; Martins, Bo; Hansen, Kristoffer Lindskov

2016-01-01

Vector Flow Imaging (VFI) has received an increasing attention in the scientific field of ultrasound, as it enables angle independent visualization of blood flow. VFI can be used in volume flow estimation, but a vessel segmentation is needed to make it fully automatic. A novel vessel segmentation...

Retinal Vessel Segmentation via Structure Tensor Coloring and Anisotropy Enhancement

Directory of Open Access Journals (Sweden)

Mehmet Nergiz

2017-11-01

Full Text Available Retinal vessel segmentation is one of the preliminary tasks for developing diagnosis software systems related to various retinal diseases. In this study, a fully automated vessel segmentation system is proposed. Firstly, the vessels are enhanced using a Frangi Filter. Afterwards, Structure Tensor is applied to the response of the Frangi Filter and a 4-D tensor field is obtained. After decomposing the Eigenvalues of the tensor field, the anisotropy between the principal Eigenvalues are enhanced exponentially. Furthermore, this 4-D tensor field is converted to the 3-D space which is composed of energy, anisotropy and orientation and then a Contrast Limited Adaptive Histogram Equalization algorithm is applied to the energy space. Later, the obtained energy space is multiplied by the enhanced mean surface curvature of itself and the modified 3-D space is converted back to the 4-D tensor field. Lastly, the vessel segmentation is performed by using Otsu algorithm and tensor coloring method which is inspired by the ellipsoid tensor visualization technique. Finally, some post-processing techniques are applied to the segmentation result. In this study, the proposed method achieved mean sensitivity of 0.8123, 0.8126, 0.7246 and mean specificity of 0.9342, 0.9442, 0.9453 as well as mean accuracy of 0.9183, 0.9442, 0.9236 for DRIVE, STARE and CHASE_DB1 datasets, respectively. The mean execution time of this study is 6.104, 6.4525 and 18.8370 s for the aforementioned three datasets respectively.

Vessel-guided airway segmentation based on voxel classification

DEFF Research Database (Denmark)

Lo, Pechin Chien Pau; Sporring, Jon; Ashraf, Haseem

2008-01-01

This paper presents a method for improving airway tree segmentation using vessel orientation information. We use the fact that an airway branch is always accompanied by an artery, with both structures having similar orientations. This work is based on a  voxel classification airway segmentation...... method proposed previously. The probability of a voxel belonging to the airway, from the voxel classification method, is augmented with an orientation similarity measure as a criterion for region growing. The orientation similarity measure of a voxel indicates how similar is the orientation...... of the surroundings of a voxel, estimated based on a tube model, is to that of a neighboring vessel. The proposed method is tested on 20 CT images from different subjects selected randomly from a lung cancer screening study. Length of the airway branches from the results of the proposed method are significantly...

Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks.

Science.gov (United States)

Joshi, Vinayak S; Reinhardt, Joseph M; Garvin, Mona K; Abramoff, Michael D

2014-01-01

The separation of the retinal vessel network into distinct arterial and venous vessel trees is of high interest. We propose an automated method for identification and separation of retinal vessel trees in a retinal color image by converting a vessel segmentation image into a vessel segment map and identifying the individual vessel trees by graph search. Orientation, width, and intensity of each vessel segment are utilized to find the optimal graph of vessel segments. The separated vessel trees are labeled as primary vessel or branches. We utilize the separated vessel trees for arterial-venous (AV) classification, based on the color properties of the vessels in each tree graph. We applied our approach to a dataset of 50 fundus images from 50 subjects. The proposed method resulted in an accuracy of 91.44% correctly classified vessel pixels as either artery or vein. The accuracy of correctly classified major vessel segments was 96.42%.

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

Science.gov (United States)

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

Feedback from Westinghouse experience on segmentation of reactor vessel internals - 59013

International Nuclear Information System (INIS)

Kreitman, Paul J.; Boucau, Joseph; Segerud, Per; Fallstroem, Stefan

2012-01-01

With more than 25 years of experience in the development of reactor vessel internals segmentation and packaging technology, Westinghouse has accumulated significant know-how in the reactor dismantling market. Building on tooling concepts and cutting methodologies developed decades ago for the successful removal of nuclear fuel from the damaged Three Mile Island Unit 2 reactor (TMI-2), Westinghouse has continuously improved its approach to internals segmentation and packaging by incorporating lessons learned and best practices into each successive project. Westinghouse has developed several concepts to dismantle reactor internals based on safe and reliable techniques, including plasma arc cutting (PAC), abrasive water-jet cutting (AWJC), metal disintegration machining (MDM), or mechanical cutting. Westinghouse has applied its technology to all types of reactors covering Pressurized Water Reactors (PWR's), Boiling Water Reactors (BWR's), Gas Cooled Reactors (GCR's) and sodium reactors. The primary challenges of a segmentation and packaging project are to separate the highly activated materials from the less-activated materials and package them into appropriate containers for disposal. Since space is almost always a limiting factor it is therefore important to plan and optimize the available room in the segmentation areas. The choice of the optimum cutting technology is important for a successful project implementation and depends on some specific constraints like disposal costs, project schedule, available areas or safety. Detailed 3-D modeling is the basis for tooling design and provides invaluable support in determining the optimum strategy for component cutting and disposal in waste containers, taking account of the radiological and packaging constraints. Westinghouse has also developed a variety of special handling tools, support fixtures, service bridges, water filtration systems, video-monitoring systems and customized rigging, all of which are required for a

Inner and outer coronary vessel wall segmentation from CCTA using an active contour model with machine learning-based 3D voxel context-aware image force

Science.gov (United States)

Sivalingam, Udhayaraj; Wels, Michael; Rempfler, Markus; Grosskopf, Stefan; Suehling, Michael; Menze, Bjoern H.

2016-03-01

In this paper, we present a fully automated approach to coronary vessel segmentation, which involves calcification or soft plaque delineation in addition to accurate lumen delineation, from 3D Cardiac Computed Tomography Angiography data. Adequately virtualizing the coronary lumen plays a crucial role for simulating blood ow by means of fluid dynamics while additionally identifying the outer vessel wall in the case of arteriosclerosis is a prerequisite for further plaque compartment analysis. Our method is a hybrid approach complementing Active Contour Model-based segmentation with an external image force that relies on a Random Forest Regression model generated off-line. The regression model provides a strong estimate of the distance to the true vessel surface for every surface candidate point taking into account 3D wavelet-encoded contextual image features, which are aligned with the current surface hypothesis. The associated external image force is integrated in the objective function of the active contour model, such that the overall segmentation approach benefits from the advantages associated with snakes and from the ones associated with machine learning-based regression alike. This yields an integrated approach achieving competitive results on a publicly available benchmark data collection (Rotterdam segmentation challenge).

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

Science.gov (United States)

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

2018-02-01

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

Facilitating coronary artery evaluation in MDCT using a 3D automatic vessel segmentation tool

International Nuclear Information System (INIS)

Fawad Khan, M.; Gurung, Jessen; Maataoui, Adel; Brehmer, Boris; Herzog, Christopher; Vogl, Thomas J.; Wesarg, Stefan; Dogan, Selami; Ackermann, Hanns; Assmus, Birgit

2006-01-01

The purpose of this study was to investigate a 3D coronary artery segmentation algorithm using 16-row MDCT data sets. Fifty patients underwent cardiac CT (Sensation 16, Siemens) and coronary angiography. Automatic and manual detection of coronary artery stenosis was performed. A 3D coronary artery segmentation algorithm (Fraunhofer Institute for Computer Graphics, Darmstadt) was used for automatic evaluation. All significant stenoses (>50%) in vessels >1.5 mm in diameter were protocoled. Each detection tool was used by one reader who was blinded to the results of the other detection method and the results of coronary angiography. Sensitivity and specificity were determined for automatic and manual detection as well as was the time for both CT-based evaluation methods. The overall sensitivity and specificity of the automatic and manual approach were 93.1 vs. 95.83% and 86.1 vs. 81.9%. The time required for automatic evaluation was significantly shorter than with the manual approach, i.e., 246.04±43.17 s for the automatic approach and 526.88±45.71 s for the manual approach (P<0.0001). In 94% of the coronary artery branches, automatic detection required less time than the manual approach. Automatic coronary vessel evaluation is feasible. It reduces the time required for cardiac CT evaluation with similar sensitivity and specificity as well as facilitates the evaluation of MDCT coronary angiography in a standardized fashion. (orig.)

Automatic segmentation of blood vessels from retinal fundus images ...

Indian Academy of Sciences (India)

The retinal blood vessels were segmented through color space conversion and color channel extraction, image pre-processing, Gabor filtering, image postprocessing, feature construction through application of principal component analysis, k-means clustering and first level classification using Naïve–Bayes classification ...

Detection and characterization of flaws in segments of light water reactor pressure vessels

International Nuclear Information System (INIS)

Cook, K.V.; Cunningham, R.A. Jr.; McClung, R.W.

1988-01-01

Studies have been conducted to determine flaw density in segments cut from light water reactor )LWR) pressure vessels as part of the Oak Ridge National Laboratory's Heavy-Section Steel Technology (H SST) Program. Segments from the Hope Creek Unit 2 vessel and the Pilgrim Unit 2 Vessel were purchased from salvage dealers. Hope Creek was a boiling water reactor (BWR) design and Pilgrim was a pressurized water reactor (PWR) design. Neither were ever placed in service. Objectives were to evaluate these LWR segments for flaws with ultrasonic and liquid penetrant techniques. Both objectives were successfully completed. One significant indication was detected in a Hope Creek seam weld by ultrasonic techniques and characterized by further analyses terminating with destructive correlation. This indication [with a through-wall dimension of ∼6 mm (∼0.24 in.)] was detected in only 3 m (10 ft) of weldment and offers extremely limited data when compared to the extent of welding even in a single pressure vessel. However, the detection and confirmation of the flaw in the arbitrarily selected sections implies the Marshall report estimates (and others) are nonconservative for such small flaws. No significant indications were detected in the Pilgrim material by ultrasonic techniques. Unfortunately, the Pilgrim segments contained relatively little weldment; thus, we limited our ultrasonic examinations to the cladding and subcladding regions. Fluorescent liquid penetrant inspection of the cladding surfaces for both LWR segments detected no significant indications [i.e., for a total of approximately 6.8 m 2 (72 ft 2 ) of cladding surface]. (author)

Optimization of reactor pressure vessel internals segmentation in Korea

Energy Technology Data Exchange (ETDEWEB)

Lee, Byung-Sik [Dankook Univ., Chungnam (Korea, Republic of). Dept. of Nuclear Engineering

2017-11-15

One of the most challenging tasks during plant decommissioning is the removal of highly radioactive internal components from the reactor pressure vessel (RPV). For RPV internals dismantling, it is essential that all activities are thoroughly planned and discussed in the early stage of the decommissioning project. One of the key activities in the detailed planning is to prepare the segmentation and packaging plan that describes the sequential steps required to segment, separate, and package each individual component of RPV, based on an activation analysis and component characterization study.

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

Science.gov (United States)

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).

Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting.

Science.gov (United States)

Gao, Shan; van 't Klooster, Ronald; Kitslaar, Pieter H; Coolen, Bram F; van den Berg, Alexandra M; Smits, Loek P; Shahzad, Rahil; Shamonin, Denis P; de Koning, Patrick J H; Nederveen, Aart J; van der Geest, Rob J

2017-10-01

The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid artery wall segmentation from dual-sequence MRI. The proposed method segments the lumen and outer wall surfaces including the bifurcation region by fitting a subdivision surface constructed hierarchical-tree model to the image data. In particular, a hybrid segmentation which combines deformable model fitting with boundary classification was applied to extract the lumen surface. The 3D model ensures the correct shape and topology of the carotid artery, while the boundary classification uses combined image information of 3D TOF-MRA and 3D BB-MRI to promote accurate delineation of the lumen boundaries. The proposed algorithm was validated on 25 subjects (48 arteries) including both healthy volunteers and atherosclerotic patients with 30% to 70% carotid stenosis. For both lumen and outer wall border detection, our result shows good agreement between manually and automatically determined contours, with contour-to-contour distance less than 1 pixel as well as Dice overlap greater than 0.87 at all different carotid artery sections. The presented 3D segmentation technique has demonstrated the capability of providing vessel wall delineation for 3D carotid MRI data with high accuracy and limited user interaction. This brings benefits to large-scale patient studies for assessing the effect of pharmacological treatment of atherosclerosis by reducing image analysis time and bias between human observers. © 2017 American Association of Physicists in Medicine.

Blood vessels segmentation of hatching eggs based on fully convolutional networks

Science.gov (United States)

Geng, Lei; Qiu, Ling; Wu, Jun; Xiao, Zhitao

2018-04-01

FCN, trained end-to-end, pixels-to-pixels, predict result of each pixel. It has been widely used for semantic segmentation. In order to realize the blood vessels segmentation of hatching eggs, a method based on FCN is proposed in this paper. The training datasets are composed of patches extracted from very few images to augment data. The network combines with lower layer and deconvolution to enables precise segmentation. The proposed method frees from the problem that training deep networks need large scale samples. Experimental results on hatching eggs demonstrate that this method can yield more accurate segmentation outputs than previous researches. It provides a convenient reference for fertility detection subsequently.

Automated image segmentation and registration of vessel wall MRI for quantitative assessment of carotid artery vessel wall dimensions and plaque composition

NARCIS (Netherlands)

Klooster, Ronald van 't

2014-01-01

The main goal of this thesis was to develop methods for automated segmentation, registration and classification of the carotid artery vessel wall and plaque components using multi-sequence MR vessel wall images to assess atherosclerosis. First, a general introduction into atherosclerosis and

Analysis of cerebral vessels dynamics using experimental data with missed segments

Science.gov (United States)

Pavlova, O. N.; Abdurashitov, A. S.; Ulanova, M. V.; Shihalov, G. M.; Semyachkina-Glushkovskaya, O. V.; Pavlov, A. N.

2018-04-01

Physiological signals often contain various bad segments that occur due to artifacts, failures of the recording equipment or varying experimental conditions. The related experimental data need to be preprocessed to avoid such parts of recordings. In the case of few bad segments, they can simply be removed from the signal and its analysis is further performed. However, when there are many extracted segments, the internal structure of the analyzed physiological process may be destroyed, and it is unclear whether such signal can be used in diagnostic-related studies. In this paper we address this problem for the case of cerebral vessels dynamics. We perform analysis of simulated data in order to reveal general features of quantifying scaling features of complex signals with distinct correlation properties and show that the effects of data loss are significantly different for experimental data with long-range correlations and anti-correlations. We conclude that the cerebral vessels dynamics is significantly less sensitive to missed data fragments as compared with signals with anti-correlated statistics.

Pulmonary vessel segmentation utilizing curved planar reformation and optimal path finding (CROP) in computed tomographic pulmonary angiography (CTPA) for CAD applications

Science.gov (United States)

Zhou, Chuan; Chan, Heang-Ping; Kuriakose, Jean W.; Chughtai, Aamer; Wei, Jun; Hadjiiski, Lubomir M.; Guo, Yanhui; Patel, Smita; Kazerooni, Ella A.

2012-03-01

Vessel segmentation is a fundamental step in an automated pulmonary embolism (PE) detection system. The purpose of this study is to improve the segmentation scheme for pulmonary vessels affected by PE and other lung diseases. We have developed a multiscale hierarchical vessel enhancement and segmentation (MHES) method for pulmonary vessel tree extraction based on the analysis of eigenvalues of Hessian matrices. However, it is difficult to segment the pulmonary vessels accurately under suboptimal conditions, such as vessels occluded by PEs, surrounded by lymphoid tissues or lung diseases, and crossing with other vessels. In this study, we developed a new vessel refinement method utilizing curved planar reformation (CPR) technique combined with optimal path finding method (MHES-CROP). The MHES segmented vessels straightened in the CPR volume was refined using adaptive gray level thresholding where the local threshold was obtained from least-square estimation of a spline curve fitted to the gray levels of the vessel along the straightened volume. An optimal path finding method based on Dijkstra's algorithm was finally used to trace the correct path for the vessel of interest. Two and eight CTPA scans were randomly selected as training and test data sets, respectively. Forty volumes of interest (VOIs) containing "representative" vessels were manually segmented by a radiologist experienced in CTPA interpretation and used as reference standard. The results show that, for the 32 test VOIs, the average percentage volume error relative to the reference standard was improved from 32.9+/-10.2% using the MHES method to 9.9+/-7.9% using the MHES-CROP method. The accuracy of vessel segmentation was improved significantly (pvolume between the automated segmentation and the reference standard was improved from 0.919 to 0.988. Quantitative comparison of the MHES method and the MHES-CROP method with the reference standard was also evaluated by the Bland-Altman plot. This preliminary

AN EFFICIENT TECHNIQUE FOR RETINAL VESSEL SEGMENTATION AND DENOISING USING MODIFIED ISODATA AND CLAHE

Directory of Open Access Journals (Sweden)

Khan Bahadar Khan

2016-11-01

Full Text Available Retinal damage caused due to complications of diabetes is known as Diabetic Retinopathy (DR. In this case, the vision is obscured due to the damage of retinal tinny blood vessels of the retina. These tinny blood vessels may cause leakage which affect the vision and can lead to complete blindness. Identification of these new retinal vessels and their structure is essential for analysis of DR. Automatic blood vessels segmentation plays a significant role to assist subsequent automatic methodologies that aid to such analysis. In literature most of the people have used computationally hungry a strong preprocessing steps followed by a simple thresholding and post processing, But in our proposed technique we utilize an arrangement of  light pre-processing which consists of Contrast Limited Adaptive Histogram Equalization (CLAHE for contrast enhancement, a difference image of green channel from its Gaussian blur filtered image to remove local noise or geometrical object, Modified Iterative Self Organizing Data Analysis Technique (MISODATA for segmentation of vessel and non-vessel pixels based on global and local thresholding, and a strong  post processing using region properties (area, eccentricity to eliminate the unwanted region/segment, non-vessel pixels and noise that never been used to reject misclassified foreground pixels. The strategy is tested on the publically accessible DRIVE (Digital Retinal Images for Vessel Extraction and STARE (STructured Analysis of the REtina databases. The performance of proposed technique is assessed comprehensively and the acquired accuracy, robustness, low complexity and high efficiency and very less computational time that make the method an efficient tool for automatic retinal image analysis. Proposed technique perform well as compared to the existing strategies on the online available databases in term of accuracy, sensitivity, specificity, false positive rate, true positive rate and area under receiver

Blood vessel-based liver segmentation through the portal phase of a CT dataset

Science.gov (United States)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Moriyama, Noriyuki; Utsunomiya, Toru; Shimada, Mitsuo

2013-02-01

Blood vessels are dispersed throughout the human body organs and carry unique information for each person. This information can be used to delineate organ boundaries. The proposed method relies on abdominal blood vessels (ABV) to segment the liver considering the potential presence of tumors through the portal phase of a CT dataset. ABV are extracted and classified into hepatic (HBV) and nonhepatic (non-HBV) with a small number of interactions. HBV and non-HBV are used to guide an automatic segmentation of the liver. HBV are used to individually segment the core region of the liver. This region and non-HBV are used to construct a boundary surface between the liver and other organs to separate them. The core region is classified based on extracted posterior distributions of its histogram into low intensity tumor (LIT) and non-LIT core regions. Non-LIT case includes normal part of liver, HBV, and high intensity tumors if exist. Each core region is extended based on its corresponding posterior distribution. Extension is completed when it reaches either a variation in intensity or the constructed boundary surface. The method was applied to 80 datasets (30 Medical Image Computing and Computer Assisted Intervention (MICCAI) and 50 non-MICCAI data) including 60 datasets with tumors. Our results for the MICCAI-test data were evaluated by sliver07 [1] with an overall score of 79.7, which ranks seventh best on the site (December 2013). This approach seems a promising method for extraction of liver volumetry of various shapes and sizes and low intensity hepatic tumors.

Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering.

Science.gov (United States)

Saffarzadeh, Vahid Mohammadi; Osareh, Alireza; Shadgar, Bita

2014-04-01

Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring some of the dark lesions, which have intensity structures different from the line-shaped vessels in the retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic curve and the segmentation accuracy. The proposed method achieves 0.9483 and 0.9387 localization accuracy against STARE and DRIVE respectively.

Retinal Vessel Segmentation Based on Primal-Dual Asynchronous Particle Swarm Optimisation (pdAPSO Algorithm

Directory of Open Access Journals (Sweden)

E. G. Dada

2017-04-01

Full Text Available Acute damage to the retina vessel has been identified to be main reason for blindness and impaired vision all over the world. A timely detection and control of these illnesses can greatly decrease the number of loss of sight cases. Developing a high performance unsupervised retinal vessel segmentation technique poses an uphill task. This paper presents study on the Primal-Dual Asynchronous Particle Swarm Optimisation (pdAPSO method for the segmentation of retinal vessels. A maximum average accuracy rate 0.9243 with an average specificity of sensitivity rate of 0.9834 and average sensitivity rate of 0.5721 were achieved on DRIVE database. The proposed method produces higher mean sensitivity and accuracy rates in the same range of very good specificity.

Novel algorithm by low complexity filter on retinal vessel segmentation

Science.gov (United States)

Rostampour, Samad

2011-10-01

This article shows a new method to detect blood vessels in the retina by digital images. Retinal vessel segmentation is important for detection of side effect of diabetic disease, because diabetes can form new capillaries which are very brittle. The research has been done in two phases: preprocessing and processing. Preprocessing phase consists to apply a new filter that produces a suitable output. It shows vessels in dark color on white background and make a good difference between vessels and background. The complexity is very low and extra images are eliminated. The second phase is processing and used the method is called Bayesian. It is a built-in in supervision classification method. This method uses of mean and variance of intensity of pixels for calculate of probability. Finally Pixels of image are divided into two classes: vessels and background. Used images are related to the DRIVE database. After performing this operation, the calculation gives 95 percent of efficiency average. The method also was performed from an external sample DRIVE database which has retinopathy, and perfect result was obtained

Hepatic vessel segmentation for 3D planning of liver surgery experimental evaluation of a new fully automatic algorithm.

Science.gov (United States)

Conversano, Francesco; Franchini, Roberto; Demitri, Christian; Massoptier, Laurent; Montagna, Francesco; Maffezzoli, Alfonso; Malvasi, Antonio; Casciaro, Sergio

2011-04-01

The aim of this study was to identify the optimal parameter configuration of a new algorithm for fully automatic segmentation of hepatic vessels, evaluating its accuracy in view of its use in a computer system for three-dimensional (3D) planning of liver surgery. A phantom reproduction of a human liver with vessels up to the fourth subsegment order, corresponding to a minimum diameter of 0.2 mm, was realized through stereolithography, exploiting a 3D model derived from a real human computed tomographic data set. Algorithm parameter configuration was experimentally optimized, and the maximum achievable segmentation accuracy was quantified for both single two-dimensional slices and 3D reconstruction of the vessel network, through an analytic comparison of the automatic segmentation performed on contrast-enhanced computed tomographic phantom images with actual model features. The optimal algorithm configuration resulted in a vessel detection sensitivity of 100% for vessels > 1 mm in diameter, 50% in the range 0.5 to 1 mm, and 14% in the range 0.2 to 0.5 mm. An average area overlap of 94.9% was obtained between automatically and manually segmented vessel sections, with an average difference of 0.06 mm(2). The average values of corresponding false-positive and false-negative ratios were 7.7% and 2.3%, respectively. A robust and accurate algorithm for automatic extraction of the hepatic vessel tree from contrast-enhanced computed tomographic volume images was proposed and experimentally assessed on a liver model, showing unprecedented sensitivity in vessel delineation. This automatic segmentation algorithm is promising for supporting liver surgery planning and for guiding intraoperative resections. Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2013-01-01

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

An objective method to optimize the MR sequence set for plaque classification in carotid vessel wall images using automated image segmentation.

Directory of Open Access Journals (Sweden)

Ronald van 't Klooster

Full Text Available A typical MR imaging protocol to study the status of atherosclerosis in the carotid artery consists of the application of multiple MR sequences. Since scanner time is limited, a balance has to be reached between the duration of the applied MR protocol and the quantity and quality of the resulting images which are needed to assess the disease. In this study an objective method to optimize the MR sequence set for classification of soft plaque in vessel wall images of the carotid artery using automated image segmentation was developed. The automated method employs statistical pattern recognition techniques and was developed based on an extensive set of MR contrast weightings and corresponding manual segmentations of the vessel wall and soft plaque components, which were validated by histological sections. Evaluation of the results from nine contrast weightings showed the tradeoff between scan duration and automated image segmentation performance. For our dataset the best segmentation performance was achieved by selecting five contrast weightings. Similar performance was achieved with a set of three contrast weightings, which resulted in a reduction of scan time by more than 60%. The presented approach can help others to optimize MR imaging protocols by investigating the tradeoff between scan duration and automated image segmentation performance possibly leading to shorter scanning times and better image interpretation. This approach can potentially also be applied to other research fields focusing on different diseases and anatomical regions.

Rotation invariant eigenvessels and auto-context for retinal vessel detection

Science.gov (United States)

Montuoro, Alessio; Simader, Christian; Langs, Georg; Schmidt-Erfurth, Ursula

2015-03-01

Retinal vessels are one of the few anatomical landmarks that are clearly visible in various imaging modalities of the eye. As they are also relatively invariant to disease progression, retinal vessel segmentation allows cross-modal and temporal registration enabling exact diagnosing for various eye diseases like diabetic retinopathy, hypertensive retinopathy or age-related macular degeneration (AMD). Due to the clinical significance of retinal vessels many different approaches for segmentation have been published in the literature. In contrast to other segmentation approaches our method is not specifically tailored to the task of retinal vessel segmentation. Instead we utilize a more general image classification approach and show that this can achieve comparable results. In the proposed method we utilize the concepts of eigenfaces and auto-context. Eigenfaces have been described quite extensively in the literature and their performance is well known. They are however quite sensitive to translation and rotation. The former was addressed by computing the eigenvessels in local image windows of different scales, the latter by estimating and correcting the local orientation. Auto-context aims to incorporate automatically generated context information into the training phase of classification approaches. It has been shown to improve the performance of spinal cord segmentation4 and 3D brain image segmentation. The proposed method achieves an area under the receiver operating characteristic (ROC) curve of Az = 0.941 on the DRIVE data set, being comparable to current state-of-the-art approaches.

Segmentation of retinal blood vessels for detection of diabetic retinopathy: A review

Directory of Open Access Journals (Sweden)

Rezty Amalia Aras

2016-05-01

Full Text Available Diabetic detinopathy (DR is effect of diabetes mellitus to the human vision that is the major cause of blindness. Early diagnosis of DR is an important requirement in diabetes treatment. Retinal fundus image is commonly used to observe the diabetic retinopathy symptoms. It can present retinal features such as blood vessel and also capture the pathologies which may lead to DR. Blood vessel is one of retinal features which can show the retina pathologies. It can be extracted from retinal image by image processing with following stages: pre-processing, segmentation, and post-processing. This paper contains a review of public retinal image dataset and several methods from various conducted researches. All discussed methods are applicable to each researcher cases. There is no further analysis to conclude the best method which can be used for general cases. However, we suggest morphological and multiscale method that gives the best accuracy in segmentation.

Blood Vessel Enhancement and Segmentation for Screening of Diabetic Retinopathy

Directory of Open Access Journals (Sweden)

Ibaa Jamal

2012-06-01

Full Text Available Diabetic retinopathy is an eye disease caused by the increase of insulin in blood and it is one of the main cuases of blindness in idusterlized countries. It is a progressive disease and needs an early detection and treatment. Vascular pattern of human retina helps the ophthalmologists in automated screening and diagnosis of diabetic retinopathy. In this article, we present a method for vascular pattern ehnacement and segmentation. We present an automated system which uses wavelets to enhance the vascular pattern and then it applies a piecewise threshold probing and adaptive thresholding for vessel localization and segmentation respectively. The method is evaluated and tested using publicly available retinal databases and we further compare our method with already proposed techniques.

Pelvi-ureteric junction obstruction related to crossing vessels: vascular anatomic variations and implication for surgical approaches.

Science.gov (United States)

Panthier, Frédéric; Lareyre, Fabien; Audouin, Marie; Raffort, Juliette

2018-03-01

Pelvi-ureteric junction obstruction corresponds to an impairment of urinary transport that can lead to renal dysfunction if not treated. Several mechanisms can cause the obstruction of the ureter including intrinsic factors or extrinsic factors such as the presence of crossing vessels. The treatment of the disease relies on surgical approaches, pyeloplasty being the standard reference. The technique consists in removing the pathologic ureteric segment and renal pelvis and transposing associated crossing vessels if present. The vascular anatomy of the pelvi-ureteric junction is complex and varies among individuals, and this can impact on the disease development and its surgical treatment. In this review, we summarize current knowledge on vascular anatomic variations in the pelvi-ureteric junction. Based on anatomic characteristics, we discuss implications for surgical approaches during pyeloplasty and vessel transposition.

Westinghouse experience in using mechanical cutting for reactor vessel internals segmentation

International Nuclear Information System (INIS)

Boucau, Joseph; Fallstroem, Stefan; Segerud, Per; Kreitman, Paul J.

2010-01-01

Some commercial nuclear power plants have been permanently shut down to date and decommissioned using dismantling methods. Other operating plants have decided to undergo an upgrade process that includes replacement of reactor internals. In both cases, there is a need to perform a segmentation of the reactor vessel internals with proven methods for long term waste disposal. Westinghouse has developed several concepts to dismantle reactor internals based on safe and reliable techniques. Mechanical cutting has been used by Westinghouse since 1999 for both PWRs and BWRs and its process has been continuously improved over the years. Detailed planning is essential to a successful project, and typically a 'Segmentation and Packaging Plan' is prepared to document the effort. The usual method is to start at the end of the process, by evaluating the waste disposal requirements imposed by the waste disposal agency, what type and size of containers are available for the different disposal options, and working backwards to select the best cutting tools and finally the cut geometry required. These plans are made utilizing advanced 3-D CAD software to model the process. Another area where the modelling has proven invaluable is in determining the logistics of component placement and movement in the reactor cavity, which is typically very congested when all the internals are out of the reactor vessel in various stages of segmentation. The main objective of the segmentation and packaging plan is to determine the strategy for separating the highly activated components from the less activated material, so that they can be disposed of in the most cost effective manner. Usually, highly activated components cannot be shipped off-site, so they must be packaged such that they can be dry stored with the spent fuel in an Independent Spent Fuel Storage Installation (ISFSI). Less activated components can be shipped to an off-site disposal site depending on space availability. Several of the

Automated identification of best-quality coronary artery segments from multiple-phase coronary CT angiography (cCTA) for vessel analysis

Science.gov (United States)

Zhou, Chuan; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Chughtai, Aamer; Wei, Jun; Kazerooni, Ella A.

2016-03-01

We are developing an automated method to identify the best quality segment among the corresponding segments in multiple-phase cCTA. The coronary artery trees are automatically extracted from different cCTA phases using our multi-scale vessel segmentation and tracking method. An automated registration method is then used to align the multiple-phase artery trees. The corresponding coronary artery segments are identified in the registered vessel trees and are straightened by curved planar reformation (CPR). Four features are extracted from each segment in each phase as quality indicators in the original CT volume and the straightened CPR volume. Each quality indicator is used as a voting classifier to vote the corresponding segments. A newly designed weighted voting ensemble (WVE) classifier is finally used to determine the best-quality coronary segment. An observer preference study is conducted with three readers to visually rate the quality of the vessels in 1 to 6 rankings. Six and 10 cCTA cases are used as training and test set in this preliminary study. For the 10 test cases, the agreement between automatically identified best-quality (AI-BQ) segments and radiologist's top 2 rankings is 79.7%, and between AI-BQ and the other two readers are 74.8% and 83.7%, respectively. The results demonstrated that the performance of our automated method was comparable to those of experienced readers for identification of the best-quality coronary segments.

An overview of reactor vessel internals segmentation for nuclear plant decommissioning

International Nuclear Information System (INIS)

Litka, T.J.

1994-01-01

Several nuclear plants have undergone reactor vessel (RV) internals segmentation as part of or in preparation for decommissioning the plant. In addition, several other nuclear facilities are planning for similar work efforts. The primary technology used for segmentation of RV internals, whether in-air or underwater is Plasma Arc Cutting (PAC). Metal Disintegration Machining (MDM) is also used for difficult to make cuts. PAC and MDM are deployed by various means including Long Handled Tools (LHTs), fixtures, tracks, and multi-axis manipulators. These enable remote cutting due to the radiation and/or underwater environment. A Boiling Water Reactor (BWR), a Pressurized Water Reactor (PWR), and a High Temperature Gas Reactor (HTGR) have had their internals removed and segmented using PAC and MDM. The cutting technology used for each component, location of cut, cut geometry and environment had to be determined well before the actual cutting operations. This allowed for the design, fabrication, and testing of the delivery systems. The technologies, selection process, and methodology for RV internals segmentation will be discussed in this paper

Phase contrast MR imaging measurements of blood flow in healthy human cerebral vessel segments

International Nuclear Information System (INIS)

MacDonald, Matthew Ethan; Frayne, Richard

2015-01-01

Phase contrast (PC) magnetic resonance imaging was used to obtain velocity measurements in 30 healthy subjects to provide an assessment of hemodynamic parameters in cerebral vessels. We expect a lower coefficient-of-variation (COV) of the volume flow rate (VFR) compared to peak velocity (v_p_e_a_k) measurements and the COV to increase in smaller caliber arteries compared to large arteries.PC velocity maps were processed to calculate v_p_e_a_k and VFR in 26 vessel segments. The mean, standard deviation and COV, of v_p_e_a_k and VFR in each segment were calculated. A bootstrap-style analysis was used to determine the minimum number of subjects required to accurately represent the population. Significance of v_p_e_a_k and VFR asymmetry was assessed in 10 vessel pairs.The bootstrap analysis suggested that averaging more than 20 subjects would give consistent results. When averaged over the subjects, v_p_e_a_k and VFR ranged from 5.2 ± 7.1 cm s"−"1, 0.41 ± 0.58 ml s"−"1 (in the anterior communicating artery; mean ± standard deviation) to 73 ± 23 cm s"−"1, 7.6 ± 1.7 ml s"−"1 (in the left internal carotid artery), respectively. A tendency for VFR to be higher in the left hemisphere was observed in 88.8% of artery pairs, while the VFR in the right transverse sinus was larger. The VFR COV was larger than v_p_e_a_k COV in 57.7% of segments, while smaller vessels had higher COV.Significance and potential impact: VFR COV was not generally higher than v_p_e_a_k COV. COV was higher in smaller vessels as expected. These summarized values provide a base against which v_p_e_a_k and VFR in various disease states can be compared. (paper)

Segmentation of retinal blood vessels using artificial neural networks for early detection of diabetic retinopathy

Science.gov (United States)

Mann, Kulwinder S.; Kaur, Sukhpreet

2017-06-01

There are various eye diseases in the patients suffering from the diabetes which includes Diabetic Retinopathy, Glaucoma, Hypertension etc. These all are the most common sight threatening eye diseases due to the changes in the blood vessel structure. The proposed method using supervised methods concluded that the segmentation of the retinal blood vessels can be performed accurately using neural networks training. It uses features which include Gray level features; Moment Invariant based features, Gabor filtering, Intensity feature, Vesselness feature for feature vector computation. Then the feature vector is calculated using only the prominent features.

Probabilistic atlas based labeling of the cerebral vessel tree

Science.gov (United States)

Van de Giessen, Martijn; Janssen, Jasper P.; Brouwer, Patrick A.; Reiber, Johan H. C.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

2015-03-01

Preoperative imaging of the cerebral vessel tree is essential for planning therapy on intracranial stenoses and aneurysms. Usually, a magnetic resonance angiography (MRA) or computed tomography angiography (CTA) is acquired from which the cerebral vessel tree is segmented. Accurate analysis is helped by the labeling of the cerebral vessels, but labeling is non-trivial due to anatomical topological variability and missing branches due to acquisition issues. In recent literature, labeling the cerebral vasculature around the Circle of Willis has mainly been approached as a graph-based problem. The most successful method, however, requires the definition of all possible permutations of missing vessels, which limits application to subsets of the tree and ignores spatial information about the vessel locations. This research aims to perform labeling using probabilistic atlases that model spatial vessel and label likelihoods. A cerebral vessel tree is aligned to a probabilistic atlas and subsequently each vessel is labeled by computing the maximum label likelihood per segment from label-specific atlases. The proposed method was validated on 25 segmented cerebral vessel trees. Labeling accuracies were close to 100% for large vessels, but dropped to 50-60% for small vessels that were only present in less than 50% of the set. With this work we showed that using solely spatial information of the vessel labels, vessel segments from stable vessels (>50% presence) were reliably classified. This spatial information will form the basis for a future labeling strategy with a very loose topological model.

Rigid 3D-3D registration of TOF MRA integrating vessel segmentation for quantification of recurrence volumes after coiling cerebral aneurysm

International Nuclear Information System (INIS)

Saering, Dennis; Forkert, Nils Daniel; Fiehler, Jens; Ries, Thorsten

2012-01-01

A fast and reproducible quantification of the recurrence volume of coiled aneurysms is required to enable a more timely evaluation of new coils. This paper presents two registration schemes for the semi-automatic quantification of aneurysm recurrence volumes based on baseline and follow-up 3D MRA TOF datasets. The quantification of shape changes requires a previous definition of corresponding structures in both datasets. For this, two different rigid registration methods have been developed and evaluated. Besides a state-of-the-art rigid registration method, a second approach integrating vessel segmentations is presented. After registration, the aneurysm recurrence volume can be calculated based on the difference image. The computed volumes were compared to manually extracted volumes. An evaluation based on 20 TOF MRA datasets (baseline and follow-up) of ten patients showed that both registration schemes are generally capable of providing sufficient registration results. Regarding the quantification of aneurysm recurrence volumes, the results suggest that the second segmentation-based registration method yields better results, while a reduction of the computation and interaction time is achieved at the same time. The proposed registration scheme incorporating vessel segmentation enables an improved quantification of recurrence volumes of coiled aneurysms with reduced computation and interaction time. (orig.)

A SURVEY OF RETINA BASED DISEASE IDENTIFICATION USING BLOOD VESSEL SEGMENTATION

Directory of Open Access Journals (Sweden)

P Kuppusamy

2016-11-01

Full Text Available The colour retinal photography is one of the most essential features to identify the confirmation of various eye diseases. The iris is primary attribute to authenticate the human. This research work presents the survey and comparison of various blood vessel related feature identification, segmentation, extraction and enhancement methods. Additionally, this study is observed the various databases performance for storing the images and testing in minimal time. This paper is also provides the better performance techniques based on the survey.

An approach to localize the retinal blood vessels using bit planes and centerline detection.

Science.gov (United States)

Fraz, M M; Barman, S A; Remagnino, P; Hoppe, A; Basit, A; Uyyanonvara, B; Rudnicka, A R; Owen, C G

2012-11-01

The change in morphology, diameter, branching pattern or tortuosity of retinal blood vessels is an important indicator of various clinical disorders of the eye and the body. This paper reports an automated method for segmentation of blood vessels in retinal images. A unique combination of techniques for vessel centerlines detection and morphological bit plane slicing is presented to extract the blood vessel tree from the retinal images. The centerlines are extracted by using the first order derivative of a Gaussian filter in four orientations and then evaluation of derivative signs and average derivative values is performed. Mathematical morphology has emerged as a proficient technique for quantifying the blood vessels in the retina. The shape and orientation map of blood vessels is obtained by applying a multidirectional morphological top-hat operator with a linear structuring element followed by bit plane slicing of the vessel enhanced grayscale image. The centerlines are combined with these maps to obtain the segmented vessel tree. The methodology is tested on three publicly available databases DRIVE, STARE and MESSIDOR. The results demonstrate that the performance of the proposed algorithm is comparable with state of the art techniques in terms of accuracy, sensitivity and specificity. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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

Science.gov (United States)

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

2007-07-01

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

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

International Nuclear Information System (INIS)

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

2007-01-01

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

An automated vessel segmentation of retinal images using multiscale vesselness

International Nuclear Information System (INIS)

Ben Abdallah, M.; Malek, J.; Tourki, R.; Krissian, K.

2011-01-01

The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. In this paper, we introduce an implementation of the anisotropic diffusion which allows reducing the noise and better preserving small structures like vessels in 2D images. A vessel detection filter, based on a multi-scale vesselness function, is then applied to enhance vascular structures.

Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies.

Science.gov (United States)

Sanz-Requena, Roberto; Moratal, David; García-Sánchez, Diego Ramón; Bodí, Vicente; Rieta, José Joaquín; Sanchis, Juan Manuel

2007-03-01

Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media-adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove noise from the images without blurring the edges. Segmentation of media-adventitia contour is achieved using active contours (snakes). In particular, we use the gradient vector flow (GVF) as external force for the snakes. The detection of lumen border is obtained taking into account gray-level information of the inner part of the previously detected contours. A knowledge-based approach is used to determine which level of gray corresponds statistically to the different regions of interest: intima, plaque and lumen. The catheter region is automatically discarded. An estimate of plaque type is also given. Finally, 3D reconstruction of all detected regions is made. The suitability of this methodology has been verified for the analysis and visualization of plaque length, stenosis severity, automatic detection of the most problematic regions, calculus of plaque volumes and a preliminary estimation of plaque type obtaining for automatic measures of lumen and vessel area an average error smaller than 1mm(2) (equivalent aproximately to 10% of the average measure), for calculus of plaque and lumen volume errors smaller than 0.5mm(3) (equivalent approximately to 20% of the average measure) and for plaque type estimates a mismatch of less than 8% in the analysed frames.

Automatic detection and segmentation of vascular structures in dermoscopy images using a novel vesselness measure based on pixel redness and tubularness

Science.gov (United States)

Kharazmi, Pegah; Lui, Harvey; Stoecker, William V.; Lee, Tim

2015-03-01

Vascular structures are one of the most important features in the diagnosis and assessment of skin disorders. The presence and clinical appearance of vascular structures in skin lesions is a discriminating factor among different skin diseases. In this paper, we address the problem of segmentation of vascular patterns in dermoscopy images. Our proposed method is composed of three parts. First, based on biological properties of human skin, we decompose the skin to melanin and hemoglobin component using independent component analysis of skin color images. The relative quantities and pure color densities of each component were then estimated. Subsequently, we obtain three reference vectors of the mean RGB values for normal skin, pigmented skin and blood vessels from the hemoglobin component by averaging over 100000 pixels of each group outlined by an expert. Based on the Euclidean distance thresholding, we generate a mask image that extracts the red regions of the skin. Finally, Frangi measure was applied to the extracted red areas to segment the tubular structures. Finally, Otsu's thresholding was applied to segment the vascular structures and get a binary vessel mask image. The algorithm was implemented on a set of 50 dermoscopy images. In order to evaluate the performance of our method, we have artificially extended some of the existing vessels in our dermoscopy data set and evaluated the performance of the algorithm to segment the newly added vessel pixels. A sensitivity of 95% and specificity of 87% were achieved.

A combined segmenting and non-segmenting approach to signal quality estimation for ambulatory photoplethysmography

International Nuclear Information System (INIS)

Wander, J D; Morris, D

2014-01-01

Continuous cardiac monitoring of healthy and unhealthy patients can help us understand the progression of heart disease and enable early treatment. Optical pulse sensing is an excellent candidate for continuous mobile monitoring of cardiovascular health indicators, but optical pulse signals are susceptible to corruption from a number of noise sources, including motion artifact. Therefore, before higher-level health indicators can be reliably computed, corrupted data must be separated from valid data. This is an especially difficult task in the presence of artifact caused by ambulation (e.g. walking or jogging), which shares significant spectral energy with the true pulsatile signal. In this manuscript, we present a machine-learning-based system for automated estimation of signal quality of optical pulse signals that performs well in the presence of periodic artifact. We hypothesized that signal processing methods that identified individual heart beats (segmenting approaches) would be more error-prone than methods that did not (non-segmenting approaches) when applied to data contaminated by periodic artifact. We further hypothesized that a fusion of segmenting and non-segmenting approaches would outperform either approach alone. Therefore, we developed a novel non-segmenting approach to signal quality estimation that we then utilized in combination with a traditional segmenting approach. Using this system we were able to robustly detect differences in signal quality as labeled by expert human raters (Pearson’s r = 0.9263). We then validated our original hypotheses by demonstrating that our non-segmenting approach outperformed the segmenting approach in the presence of contaminated signal, and that the combined system outperformed either individually. Lastly, as an example, we demonstrated the utility of our signal quality estimation system in evaluating the trustworthiness of heart rate measurements derived from optical pulse signals. (paper)

Particle filters, a quasi-Monte-Carlo-solution for segmentation of coronaries.

Science.gov (United States)

Florin, Charles; Paragios, Nikos; Williams, Jim

2005-01-01

In this paper we propose a Particle Filter-based approach for the segmentation of coronary arteries. To this end, successive planes of the vessel are modeled as unknown states of a sequential process. Such states consist of the orientation, position, shape model and appearance (in statistical terms) of the vessel that are recovered in an incremental fashion, using a sequential Bayesian filter (Particle Filter). In order to account for bifurcations and branchings, we consider a Monte Carlo sampling rule that propagates in parallel multiple hypotheses. Promising results on the segmentation of coronary arteries demonstrate the potential of the proposed approach.

Vacuum vessel for thermonuclear device

International Nuclear Information System (INIS)

Hagiwara, Koji; Imura, Yasuya.

1979-01-01

Purpose: To provide constituted method for easily performing baking of vacuum vessel, using short-circuiting segments. Constitution: At the time of baking, one turn circuit is formed by the vacuum vessel and short-circuiting segments, and current transformer converting the one turn circuit into a secondary circuit by the primary coil and iron core is formed, and the vacuum vessel is Joule heated by an induction current from the primary coil. After completion of baking, the short-circuiting segments are removed. (Kamimura, M.)

Soft computing approach to 3D lung nodule segmentation in CT.

Science.gov (United States)

Badura, P; Pietka, E

2014-10-01

This paper presents a novel, multilevel approach to the segmentation of various types of pulmonary nodules in computed tomography studies. It is based on two branches of computational intelligence: the fuzzy connectedness (FC) and the evolutionary computation. First, the image and auxiliary data are prepared for the 3D FC analysis during the first stage of an algorithm - the masks generation. Its main goal is to process some specific types of nodules connected to the pleura or vessels. It consists of some basic image processing operations as well as dedicated routines for the specific cases of nodules. The evolutionary computation is performed on the image and seed points in order to shorten the FC analysis and improve its accuracy. After the FC application, the remaining vessels are removed during the postprocessing stage. The method has been validated using the first dataset of studies acquired and described by the Lung Image Database Consortium (LIDC) and by its latest release - the LIDC-IDRI (Image Database Resource Initiative) database. Copyright © 2014 Elsevier Ltd. All rights reserved.

NCSX Vacuum Vessel Fabrication

International Nuclear Information System (INIS)

Viola ME; Brown T; Heitzenroeder P; Malinowski F; Reiersen W; Sutton L; Goranson P; Nelson B; Cole M; Manuel M; McCorkle D.

2005-01-01

The National Compact Stellarator Experiment (NCSX) is being constructed at the Princeton Plasma Physics Laboratory (PPPL) in conjunction with the Oak Ridge National Laboratory (ORNL). The goal of this experiment is to develop a device which has the steady state properties of a traditional stellarator along with the high performance characteristics of a tokamak. A key element of this device is its highly shaped Inconel 625 vacuum vessel. This paper describes the manufacturing of the vessel. The vessel is being fabricated by Major Tool and Machine, Inc. (MTM) in three identical 120 o vessel segments, corresponding to the three NCSX field periods, in order to accommodate assembly of the device. The port extensions are welded on, leak checked, cut off within 1-inch of the vessel surface at MTM and then reattached at PPPL, to accommodate assembly of the close-fitting modular coils that surround the vessel. The 120 o vessel segments are formed by welding two 60 o segments together. Each 60 o segment is fabricated by welding ten press-formed panels together over a collapsible welding fixture which is needed to precisely position the panels. The vessel is joined at assembly by welding via custom machined 8-inch (20.3 cm) wide spacer ''spool pieces''. The vessel must have a total leak rate less than 5 X 10 -6 t-l/s, magnetic permeability less than 1.02(micro), and its contours must be within 0.188-inch (4.76 mm). It is scheduled for completion in January 2006

Vessel discoloration detection in malarial retinopathy

Science.gov (United States)

Agurto, C.; Nemeth, S.; Barriga, S.; Soliz, P.; MacCormick, I.; Taylor, T.; Harding, S.; Lewallen, S.; Joshi, V.

2016-03-01

Cerebral malaria (CM) is a life-threatening clinical syndrome associated with malarial infection. It affects approximately 200 million people, mostly sub-Saharan African children under five years of age. Malarial retinopathy (MR) is a condition in which lesions such as whitening and vessel discoloration that are highly specific to CM appear in the retina. Other unrelated diseases can present with symptoms similar to CM, therefore the exact nature of the clinical symptoms must be ascertained in order to avoid misdiagnosis, which can lead to inappropriate treatment and, potentially, death. In this paper we outline the first system to detect the presence of discolored vessels associated with MR as a means to improve the CM diagnosis. We modified and improved our previous vessel segmentation algorithm by incorporating the `a' channel of the CIELab color space and noise reduction. We then divided the segmented vasculature into vessel segments and extracted features at the wall and in the centerline of the segment. Finally, we used a regression classifier to sort the segments into discolored and not-discolored vessel classes. By counting the abnormal vessel segments in each image, we were able to divide the analyzed images into two groups: normal and presence of vessel discoloration due to MR. We achieved an accuracy of 85% with sensitivity of 94% and specificity of 67%. In clinical practice, this algorithm would be combined with other MR retinal pathology detection algorithms. Therefore, a high specificity can be achieved. By choosing a different operating point in the ROC curve, our system achieved sensitivity of 67% with specificity of 100%.

Effect of a novel motion correction algorithm (SSF) on the image quality of coronary CTA with intermediate heart rates: Segment-based and vessel-based analyses

Energy Technology Data Exchange (ETDEWEB)

Li, Qianwen, E-mail: qianwen18@126.com; Li, Pengyu, E-mail: lipyu818@gmail.com; Su, Zhuangzhi, E-mail: suzhuangzhi@xwh.ccmu.edu.cn; Yao, Xinyu, E-mail: 314985151@qq.com; Wang, Yan, E-mail: wy19851121@126.com; Wang, Chen, E-mail: fskwangchen@gmail.com; Du, Xiangying, E-mail: duxying_xw@163.com; Li, Kuncheng, E-mail: kuncheng.li@gmail.com

2014-11-15

Highlights: • SSF provided better image quality than single-sector and bi-sector reconstruction among the intermediate heart rates (65–75 bpm). • Evidence for the application of prospective ECG-triggered coronary CTA with SSF onto an expanded heart rate range. • Information about the inconsistent effectiveness of SSF among the segments of coronary artery. - Abstract: Purpose: To evaluate the effect of SnapShot Freeze (SSF) reconstruction at an intermediate heart-rate (HR) range (65–75 bpm) and compare this method with single-sector reconstruction and bi-sector reconstruction on segmental and vessel bases in retrospective coronary computed tomography angiography (CCTA). Materials and methods: Retrospective electrocardiogram-gated CCTA was performed on 37 consecutive patients with HR between 65 and 75 bpm using a 64-row CT scanner. Retrospective single-sector reconstruction, bi-sector reconstruction, and SSF were performed for each patient. Multi-phase single-sector reconstruction was performed to select the optimal phase. SSF and bi-sector images were also reconstructed at the optimal phase. The images were interpreted in an intent-to-diagnose fashion by two experienced readers using a 5-point scale, with 3 points as diagnostically acceptable. Image quality among the three reconstruction groups were compared on per-patient, per-vessel, and per-segment bases. Results: The average HR of the enrolled patients was 69.4 ± 2.7 bpm. A total of 111 vessels and 481 coronary segments were assessed. SSF provided significantly higher interpretability of the coronary segments than bi-sector reconstructions. The qualified and excellent rates of SSF (97.9% and 82.3%) were significantly higher than those of single-sector (92.9% and 66.3%) and bi-sector (90.9% and 64.7%) reconstructions. The image quality score (IQS) using SSF was also significantly higher than those of single-sector and bi-sector reconstructions both on per-patient and per-vessel bases. On per-segment

A NEW APPROACH TO SEGMENT HANDWRITTEN DIGITS

NARCIS (Netherlands)

Oliveira, L.S.; Lethelier, E.; Bortolozzi, F.; Sabourin, R.

2004-01-01

This article presents a new segmentation approach applied to unconstrained handwritten digits. The novelty of the proposed algorithm is based on the combination of two types of structural features in order to provide the best segmentation path between connected entities. In this article, we first

Segmentation of arterial vessel wall motion to sub-pixel resolution using M-mode ultrasound.

Science.gov (United States)

Fancourt, Craig; Azer, Karim; Ramcharan, Sharmilee L; Bunzel, Michelle; Cambell, Barry R; Sachs, Jeffrey R; Walker, Matthew

2008-01-01

We describe a method for segmenting arterial vessel wall motion to sub-pixel resolution, using the returns from M-mode ultrasound. The technique involves measuring the spatial offset between all pairs of scans from their cross-correlation, converting the spatial offsets to relative wall motion through a global optimization, and finally translating from relative to absolute wall motion by interpolation over the M-mode image. The resulting detailed wall distension waveform has the potential to enhance existing vascular biomarkers, such as strain and compliance, as well as enable new ones.

Design of pressure vessels using shape optimization: An integrated approach

Energy Technology Data Exchange (ETDEWEB)

Carbonari, R.C., E-mail: ronny@usp.br [Department of Mechatronic Engineering, Escola Politecnica da Universidade de Sao Paulo, Av. Prof. Mello Moraes, 2231 Sao Paulo, SP 05508-900 (Brazil); Munoz-Rojas, P.A., E-mail: pablo@joinville.udesc.br [Department of Mechanical Engineering, Universidade do Estado de Santa Catarina, Bom Retiro, Joinville, SC 89223-100 (Brazil); Andrade, E.Q., E-mail: edmundoq@petrobras.com.br [CENPES, PDP/Metodos Cientificos, Petrobras (Brazil); Paulino, G.H., E-mail: paulino@uiuc.edu [Newmark Laboratory, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 North Mathews Av., Urbana, IL 61801 (United States); Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, 158 Mechanical Engineering Building, 1206 West Green Street, Urbana, IL 61801-2906 (United States); Nishimoto, K., E-mail: knishimo@usp.br [Department of Naval Architecture and Ocean Engineering, Escola Politecnica da Universidade de Sao Paulo, Av. Prof. Mello Moraes, 2231 Sao Paulo, SP 05508-900 (Brazil); Silva, E.C.N., E-mail: ecnsilva@usp.br [Department of Mechatronic Engineering, Escola Politecnica da Universidade de Sao Paulo, Av. Prof. Mello Moraes, 2231 Sao Paulo, SP 05508-900 (Brazil)

2011-05-15

Previous papers related to the optimization of pressure vessels have considered the optimization of the nozzle independently from the dished end. This approach generates problems such as thickness variation from nozzle to dished end (coupling cylindrical region) and, as a consequence, it reduces the optimality of the final result which may also be influenced by the boundary conditions. Thus, this work discusses shape optimization of axisymmetric pressure vessels considering an integrated approach in which the entire pressure vessel model is used in conjunction with a multi-objective function that aims to minimize the von-Mises mechanical stress from nozzle to head. Representative examples are examined and solutions obtained for the entire vessel considering temperature and pressure loading. It is noteworthy that different shapes from the usual ones are obtained. Even though such different shapes may not be profitable considering present manufacturing processes, they may be competitive for future manufacturing technologies, and contribute to a better understanding of the actual influence of shape in the behavior of pressure vessels. - Highlights: > Shape optimization of entire pressure vessel considering an integrated approach. > By increasing the number of spline knots, the convergence stability is improved. > The null angle condition gives lower stress values resulting in a better design. > The cylinder stresses are very sensitive to the cylinder length. > The shape optimization of the entire vessel must be considered for cylinder length.

Roi Detection and Vessel Segmentation in Retinal Image

Science.gov (United States)

Sabaz, F.; Atila, U.

2017-11-01

Diabetes disrupts work by affecting the structure of the eye and afterwards leads to loss of vision. Depending on the stage of disease that called diabetic retinopathy, there are sudden loss of vision and blurred vision problems. Automated detection of vessels in retinal images is a useful study to diagnose eye diseases, disease classification and other clinical trials. The shape and structure of the vessels give information about the severity of the disease and the stage of the disease. Automatic and fast detection of vessels allows for a quick diagnosis of the disease and the treatment process to start shortly. ROI detection and vessel extraction methods for retinal image are mentioned in this study. It is shown that the Frangi filter used in image processing can be successfully used in detection and extraction of vessels.

Evaluation of image quality on a per-patient, per-vessel, and per-segment basis by noninvasive coronary angiography with 64-section computed tomography. Dual-source versus single-source computed tomography

International Nuclear Information System (INIS)

Nakashima, Yoshiteru; Okada, Munemasa; Washida, Yasuo; Miura, Toshiro; Fujimura, Tatsuo; Nao, Tomoko; Matsunaga, Naofumi

2011-01-01

The purpose of this study was to evaluate the image quality (IQ) of dual-source CT (DSCT) versus single-source CT (SSCT). A total of 100 patients underwent 64-section CT coronary angiography (50 DSCT, 50 SSCT). Three observers evaluated the IQ of each coronary segment using a four-point scale (1, excellent; 2, good; 3, fair; 4, no assessment). The IQ of DSCT coronary angiography was compared with SSCT coronary angiography on a per-patient, per-vessel, and per-segment basis using the chi-squared test. The DSCT image quality score (IQS) was significantly lower on a per-patient basis and per-vessel basis for all vessels and on a per-segment basis for some segments (1, 2, 4PD, 4AV, 7, 9, 11, 12, 13) compared with SSCT. The DSCT IQS was significantly lower for certain segments (2, 4PD, 11, 13) with high heart rates (≥70 beats/min). The DSCT IQS was significantly lower for certain segments (1, 2, 3, 4PD, 4AV, 7, 8, 9, 10, 12, 13) with low heart rates (<70 beats/min). DSCT showed a significantly better IQ than SSCT, especially in patients with low heart rates. (author)

Leisure market segmentation : an integrated preferences/constraints-based approach

NARCIS (Netherlands)

Stemerding, M.P.; Oppewal, H.; Beckers, T.A.M.; Timmermans, H.J.P.

1996-01-01

Traditional segmentation schemes are often based on a grouping of consumers with similar preference functions. The research steps, ultimately leading to such segmentation schemes, are typically independent. In the present article, a new integrated approach to segmentation is introduced, which

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

Energy Technology Data Exchange (ETDEWEB)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich [Departments of Electrical and Computer Engineering and Internal Medicine, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, A-8010 Graz (Austria); Department of Electrical and Computer Engineering, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Radiology, Medical University Graz, Auenbruggerplatz 34, A-8010 Graz (Austria)

2012-03-15

Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

International Nuclear Information System (INIS)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

2012-01-01

Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods.

Science.gov (United States)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

2012-03-01

Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and∕or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of user interaction

Enhancement of optic cup detection through an improved vessel kink detection framework

Science.gov (United States)

Wong, Damon W. K.; Liu, Jiang; Tan, Ngan Meng; Zhang, Zhuo; Lu, Shijian; Lim, Joo Hwee; Li, Huiqi; Wong, Tien Yin

2010-03-01

Glaucoma is a leading cause of blindness. The presence and extent of progression of glaucoma can be determined if the optic cup can be accurately segmented from retinal images. In this paper, we present a framework which improves the detection of the optic cup. First, a region of interest is obtained from the retinal fundus image, and a pallor-based preliminary cup contour estimate is determined. Patches are then extracted from the ROI along this contour. To improve the usability of the patches, adaptive methods are introduced to ensure the patches are within the optic disc and to minimize redundant information. The patches are then analyzed for vessels by an edge transform which generates pixel segments of likely vessel candidates. Wavelet, color and gradient information are used as input features for a SVM model to classify the candidates as vessel or non-vessel. Subsequently, a rigourous non-parametric method is adopted in which a bi-stage multi-resolution approach is used to probe and localize the location of kinks along the vessels. Finally, contenxtual information is used to fuse pallor and kink information to obtain an enhanced optic cup segmentation. Using a batch of 21 images obtained from the Singapore Eye Research Institute, the new method results in a 12.64% reduction in the average overlap error against a pallor only cup, indicating viable improvements in the segmentation and supporting the use of kinks for optic cup detection.

ROI DETECTION AND VESSEL SEGMENTATION IN RETINAL IMAGE

Directory of Open Access Journals (Sweden)

F. Sabaz

2017-11-01

Full Text Available Diabetes disrupts work by affecting the structure of the eye and afterwards leads to loss of vision. Depending on the stage of disease that called diabetic retinopathy, there are sudden loss of vision and blurred vision problems. Automated detection of vessels in retinal images is a useful study to diagnose eye diseases, disease classification and other clinical trials. The shape and structure of the vessels give information about the severity of the disease and the stage of the disease. Automatic and fast detection of vessels allows for a quick diagnosis of the disease and the treatment process to start shortly. ROI detection and vessel extraction methods for retinal image are mentioned in this study. It is shown that the Frangi filter used in image processing can be successfully used in detection and extraction of vessels.

Pressure vessel for nuclear reactors

International Nuclear Information System (INIS)

1975-01-01

The invention applies to a pressure vessel for nuclear reactors whose shell, made of cast metal segments, has a steel liner. This liner must be constructed to withstand all operational stresses and to be easily repairable. The invention solves this problem by installing the liner at a certain distance from the inner wall of the pressure vessel shell and by filling this clearance with supporting concrete. Both the concrete and the steel liner must have a lower prestress than the pressure vessel shell. In order to avoid damage to the liner when prestressing the pressure vessel shell, special connecting elements are provided which consist of welded-on fastening elements projecting into recesses in the cast metal segments of the pressure vessel. Their design is described in detail. (TK) [de

A hybrid segmentation approach for geographic atrophy in fundus auto-fluorescence images for diagnosis of age-related macular degeneration.

Science.gov (United States)

Lee, Noah; Laine, Andrew F; Smith, R Theodore

2007-01-01

Fundus auto-fluorescence (FAF) images with hypo-fluorescence indicate geographic atrophy (GA) of the retinal pigment epithelium (RPE) in age-related macular degeneration (AMD). Manual quantification of GA is time consuming and prone to inter- and intra-observer variability. Automatic quantification is important for determining disease progression and facilitating clinical diagnosis of AMD. In this paper we describe a hybrid segmentation method for GA quantification by identifying hypo-fluorescent GA regions from other interfering retinal vessel structures. First, we employ background illumination correction exploiting a non-linear adaptive smoothing operator. Then, we use the level set framework to perform segmentation of hypo-fluorescent areas. Finally, we present an energy function combining morphological scale-space analysis with a geometric model-based approach to perform segmentation refinement of false positive hypo- fluorescent areas due to interfering retinal structures. The clinically apparent areas of hypo-fluorescence were drawn by an expert grader and compared on a pixel by pixel basis to our segmentation results. The mean sensitivity and specificity of the ROC analysis were 0.89 and 0.98%.

Application of morphological bit planes in retinal blood vessel extraction.

Science.gov (United States)

Fraz, M M; Basit, A; Barman, S A

2013-04-01

The appearance of the retinal blood vessels is an important diagnostic indicator of various clinical disorders of the eye and the body. Retinal blood vessels have been shown to provide evidence in terms of change in diameter, branching angles, or tortuosity, as a result of ophthalmic disease. This paper reports the development for an automated method for segmentation of blood vessels in retinal images. A unique combination of methods for retinal blood vessel skeleton detection and multidirectional morphological bit plane slicing is presented to extract the blood vessels from the color retinal images. The skeleton of main vessels is extracted by the application of directional differential operators and then evaluation of combination of derivative signs and average derivative values. Mathematical morphology has been materialized as a proficient technique for quantifying the retinal vasculature in ocular fundus images. A multidirectional top-hat operator with rotating structuring elements is used to emphasize the vessels in a particular direction, and information is extracted using bit plane slicing. An iterative region growing method is applied to integrate the main skeleton and the images resulting from bit plane slicing of vessel direction-dependent morphological filters. The approach is tested on two publicly available databases DRIVE and STARE. Average accuracy achieved by the proposed method is 0.9423 for both the databases with significant values of sensitivity and specificity also; the algorithm outperforms the second human observer in terms of precision of segmented vessel tree.

U.S. and French approaches to reactor pressure vessel integrity

International Nuclear Information System (INIS)

Griesbach, T.J.; Buchalet, C.; Server, W.L.

1990-01-01

The effects of radiation embrittlement on the reactor pressure vessel must be considered for continued safe operation of nuclear power plants. The consequences of radiation embrittlement require detailed assessments of the margins of safety against brittle fracture of the vessel. The American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code and U.S. Regulations often use conservative approaches for these assessments which can eventually lead to severe operational hardships for some plants. Taking a look at alternative integrity approaches, such as those demonstrated in France, could ultimately result in improved ASME Code and Regulatory limits. The French studies have shown the significance of performing proper in- service inspections to reliably show that no defects larger than a predetermined size (or class) exist in the inspected region of a vessel. The predetermined size is based upon previous studies on the types of manufacturing defects which can potentially exist in French vessels. Enhanced linear elastic and elastic-plastic fracture mechanics methodologies can be applied to evaluate such defects to assure that brittle fracture will not occur

Innovative visualization and segmentation approaches for telemedicine

Science.gov (United States)

Nguyen, D.; Roehrig, Hans; Borders, Marisa H.; Fitzpatrick, Kimberly A.; Roveda, Janet

2014-09-01

In health care applications, we obtain, manage, store and communicate using high quality, large volume of image data through integrated devices. In this paper we propose several promising methods that can assist physicians in image data process and communication. We design a new semi-automated segmentation approach for radiological images, such as CT and MRI to clearly identify the areas of interest. This approach combines the advantages from both the region-based method and boundary-based methods. It has three key steps compose: coarse segmentation by using fuzzy affinity and homogeneity operator, image division and reclassification using the Voronoi Diagram, and refining boundary lines using the level set model.

Hyperspectral image segmentation using a cooperative nonparametric approach

Science.gov (United States)

Taher, Akar; Chehdi, Kacem; Cariou, Claude

2013-10-01

In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.

Implicit vessel surface reconstruction for visualization and CFD simulation

International Nuclear Information System (INIS)

Schumann, Christian; Peitgen, Heinz-Otto; Neugebauer, Mathias; Bade, Ragnar; Preim, Bernhard

2008-01-01

Accurate and high-quality reconstructions of vascular structures are essential for vascular disease diagnosis and blood flow simulations.These applications necessitate a trade-off between accuracy and smoothness. An additional requirement for the volume grid generation for Computational Fluid Dynamics (CFD) simulations is a high triangle quality. We propose a method that produces an accurate reconstruction of the vessel surface with satisfactory surface quality. A point cloud representing the vascular boundary is generated based on a segmentation result. Thin vessels are subsampled to enable an accurate reconstruction. A signed distance field is generated using Multi-level Partition of Unity Implicits and subsequently polygonized using a surface tracking approach. To guarantee a high triangle quality, the surface is remeshed. Compared to other methods, our approach represents a good trade-off between accuracy and smoothness. For the tested data, the average surface deviation to the segmentation results is 0.19 voxel diagonals and the maximum equi-angle skewness values are below 0.75. The generated surfaces are considerably more accurate than those obtained using model-based approaches. Compared to other model-free approaches, the proposed method produces smoother results and thus better supports the perception and interpretation of the vascular topology. Moreover, the triangle quality of the generated surfaces is suitable for CFD simulations. (orig.)

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

Science.gov (United States)

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

2012-07-01

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

Automated Urban Travel Interpretation: A Bottom-up Approach for Trajectory Segmentation

Directory of Open Access Journals (Sweden)

Rahul Deb Das

2016-11-01

Full Text Available Understanding travel behavior is critical for an effective urban planning as well as for enabling various context-aware service provisions to support mobility as a service (MaaS. Both applications rely on the sensor traces generated by travellers’ smartphones. These traces can be used to interpret travel modes, both for generating automated travel diaries as well as for real-time travel mode detection. Current approaches segment a trajectory by certain criteria, e.g., drop in speed. However, these criteria are heuristic, and, thus, existing approaches are subjective and involve significant vagueness and uncertainty in activity transitions in space and time. Also, segmentation approaches are not suited for real time interpretation of open-ended segments, and cannot cope with the frequent gaps in the location traces. In order to address all these challenges a novel, state based bottom-up approach is proposed. This approach assumes a fixed atomic segment of a homogeneous state, instead of an event-based segment, and a progressive iteration until a new state is found. The research investigates how an atomic state-based approach can be developed in such a way that can work in real time, near-real time and offline mode and in different environmental conditions with their varying quality of sensor traces. The results show the proposed bottom-up model outperforms the existing event-based segmentation models in terms of adaptivity, flexibility, accuracy and richness in information delivery pertinent to automated travel behavior interpretation.

Automated Urban Travel Interpretation: A Bottom-up Approach for Trajectory Segmentation.

Science.gov (United States)

Das, Rahul Deb; Winter, Stephan

2016-11-23

Understanding travel behavior is critical for an effective urban planning as well as for enabling various context-aware service provisions to support mobility as a service (MaaS). Both applications rely on the sensor traces generated by travellers' smartphones. These traces can be used to interpret travel modes, both for generating automated travel diaries as well as for real-time travel mode detection. Current approaches segment a trajectory by certain criteria, e.g., drop in speed. However, these criteria are heuristic, and, thus, existing approaches are subjective and involve significant vagueness and uncertainty in activity transitions in space and time. Also, segmentation approaches are not suited for real time interpretation of open-ended segments, and cannot cope with the frequent gaps in the location traces. In order to address all these challenges a novel, state based bottom-up approach is proposed. This approach assumes a fixed atomic segment of a homogeneous state, instead of an event-based segment, and a progressive iteration until a new state is found. The research investigates how an atomic state-based approach can be developed in such a way that can work in real time, near-real time and offline mode and in different environmental conditions with their varying quality of sensor traces. The results show the proposed bottom-up model outperforms the existing event-based segmentation models in terms of adaptivity, flexibility, accuracy and richness in information delivery pertinent to automated travel behavior interpretation.

Blood vessel classification into arteries and veins in retinal images

Science.gov (United States)

Kondermann, Claudia; Kondermann, Daniel; Yan, Michelle

2007-03-01

The prevalence of diabetes is expected to increase dramatically in coming years; already today it accounts for a major proportion of the health care budget in many countries. Diabetic Retinopathy (DR), a micro vascular complication very often seen in diabetes patients, is the most common cause of visual loss in working age population of developed countries today. Since the possibility of slowing or even stopping the progress of this disease depends on the early detection of DR, an automatic analysis of fundus images would be of great help to the ophthalmologist due to the small size of the symptoms and the large number of patients. An important symptom for DR are abnormally wide veins leading to an unusually low ratio of the average diameter of arteries to veins (AVR). There are also other diseases like high blood pressure or diseases of the pancreas with one symptom being an abnormal AVR value. To determine it, a classification of vessels as arteries or veins is indispensable. As to our knowledge despite the importance there have only been two approaches to vessel classification yet. Therefore we propose an improved method. We compare two feature extraction methods and two classification methods based on support vector machines and neural networks. Given a hand-segmentation of vessels our approach achieves 95.32% correctly classified vessel pixels. This value decreases by 10% on average, if the result of a segmentation algorithm is used as basis for the classification.

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

Science.gov (United States)

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

2016-03-01

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

Segmentation strategies for the irradiated and tritium contaminated PPPL TFTR

International Nuclear Information System (INIS)

Walton, G.R.; Spampinato, P.T.

1995-01-01

The Tokamak Fusion Test Reactor (TFTR) at Princeton Plasma Physics Laboratory is scheduled to complete its final experiments in the Fall of 1995. As a result, the TFTR will be activated and tritium contaminated. After the experiments are complete, the TFTR will undergo Shutdown and Removal (S and R). The space vacated by the TFTR will be used for a new test reactor, the Tokamak Physics Experiment (TPX). Remote methods may be required to remove components and to segment the Vacuum Vessel. The TFTR has been studied to determine alternatives for the segmentation of the Vacuum Vessel from the inside (In-Vessel). The methodology to determine suitable strategies to segment the Vacuum Vessel from In-Vessel included several areas of concentration. These areas were segmentation locations, cutting/removal technologies, pros and cons, and cutting/removal technology delivery systems. The segmentation locations for easiest implementation and minimal steps in cutting and removal have been identified. Each of these will also achieve the baseline for packaging and shipment. The methods for cutting and removal of components were determined. In addition, the delivery systems were conceptualized

Segmentation strategies for the irradiated and tritium contaminated PPPL TFTR

Energy Technology Data Exchange (ETDEWEB)

Walton, G.R. [Princeton Univ., NJ (United States). Plasma Physics Lab.; Litka, T.J. [Advanced Consulting Group, Inc., Chicago, IL (United States); Spampinato, P.T. [RHD Consultants, Inc., Princeton, NJ (United States)

1995-02-09

The Tokamak Fusion Test Reactor (TFTR) at Princeton Plasma Physics Laboratory is scheduled to complete its final experiments in the Fall of 1995. As a result, the TFTR will be activated and tritium contaminated. After the experiments are complete, the TFTR will undergo Shutdown and Removal (S and R). The space vacated by the TFTR will be used for a new test reactor, the Tokamak Physics Experiment (TPX). Remote methods may be required to remove components and to segment the Vacuum Vessel. The TFTR has been studied to determine alternatives for the segmentation of the Vacuum Vessel from the inside (In-Vessel). The methodology to determine suitable strategies to segment the Vacuum Vessel from In-Vessel included several areas of concentration. These areas were segmentation locations, cutting/removal technologies, pros and cons, and cutting/removal technology delivery systems. The segmentation locations for easiest implementation and minimal steps in cutting and removal have been identified. Each of these will also achieve the baseline for packaging and shipment. The methods for cutting and removal of components were determined. In addition, the delivery systems were conceptualized.

Muscle-splitting approach to superior and inferior gluteal vessels: versatile source of recipient vessels for free-tissue transfer to sacral, gluteal, and ischial regions.

Science.gov (United States)

Park, S

2000-07-01

The superior gluteal vessel has been reported as a recipient in free-tissue transfer for the coverage of complex soft-tissue defects in the lumbosacral region, where a suitable recipient vessel is difficult to find. The characteristics of proximity, vessel caliber, and constancy make the superior gluteal vessel preferable to previously reported recipient vessels. However, there are technical difficulties in microsurgery (e.g., short pedicle length and deep location) and muscle injury (transection of the muscle) associated with use of the superior gluteal vessel. The purpose of this article is to present a modification of an approach to the gluteal vessel to alleviate technical difficulties and minimize muscle injury. From August of 1997 to January of 1999, six patients received microvascular transfer of the latissimus dorsi muscle or myocutaneous flap to the sacral (4) and ischial (2) regions. The causes of defects were tumor (1), trauma (1), and pressure sores (4). A muscle-splitting approach was used on the superior gluteal vessel and was later applied to the inferior gluteal vessel. The gluteus maximus muscle was split as needed in the direction of its fibers, and the perforators were dissected down to the superior or inferior gluteal artery and vein deep into the muscle. The follow-up period ranged from 6 to 22 months, and all of the flaps survived with complete recovery of the lesion. The major drawbacks of using the superior and inferior gluteal vessels can be overcome with the muscle-splitting approach, which provides increased accessibility and additional length to the vascular pedicle while causing minimal injury to the muscle itself. It also proves to be an easy, safe, and reliable method of dissection. When free-tissue transfer to sacral, gluteal, and ischial regions is indicated, the muscle-splitting approach to the superior and inferior gluteal vessels is a recommended option in the selection of a recipient vessel.

A Nordic approach to impact assessment of accidents with nuclear-propelled vessels

International Nuclear Information System (INIS)

Reistad, O.; Hustveit, S.; Palsson, S.E.; Hoe, S.; Lahtinen, J.

2012-11-01

The MareNuc project has identified the parameters in a graded approach to impact assessment for marine nuclear reactors. The graded approach is founded on the following elements: 1) More detailed understanding of previous accidents in nuclear-propelled vessels (initiating events, accident developments, release fractions), including release mechanisms (radionuclide retention in vessel construction); 2) Bench-marking of release scenarios using modelling tools applied in the Nordic countries, in addition to demonstration of generally accessible and free software developed by the IAEA; 3) Other systematic approaches to safety assessments of vessel port calls, and to the design and maintenance of emergency preparedness systems; More specifically, increased emphasis compared to earlier analysis after the Kursk accident is given to the engineered vessel barriers. Relevant standards from impact assessments for commercial nuclear power plants have been identified, such as from the NUREG series. The Nordic approaches to safety evaluation, impact assessments and emergency preparedness organisation was also reported as part of the project. The Canadian approach for international port calls was carefully reported and assessed as part of the project, and commended for its broad and comprehensive approach to reactor and vessel design for the nationalities involved, to the design and maintenance of emergency preparedness systems, and the well-structured and broad cooperation between civilian and military institutions. This approach goes beyond the current approach in the Nordic countries, also in the case of Norway, which experience regular port calls from allied nuclear navies. The overall result is a broader understanding in the Nordic countries for the importance of the various parameters for impact assessment of releases from marine reactors, and to the design and maintenance of an emergency preparedness organisation without detailed knowledge of the installation in question

A Nordic approach to impact assessment of accidents with nuclear-propelled vessels

Energy Technology Data Exchange (ETDEWEB)

Reistad, O. [Institute for Energy Technology, Kjeller (Norway); Hustveit, S. [Norwegian Radiation Protection Authority, Oesteraes (Norway); Palsson, S.E. [Icelandic Radiation Safety Authority, Reykjavik (Iceland); Hoe, S. [Danish Emergency Management Agency, Birkeroed (Denmark); Lahtinen, J. [STUK, Helsinki (Finland)

2012-11-15

The MareNuc project has identified the parameters in a graded approach to impact assessment for marine nuclear reactors. The graded approach is founded on the following elements: 1) More detailed understanding of previous accidents in nuclear-propelled vessels (initiating events, accident developments, release fractions), including release mechanisms (radionuclide retention in vessel construction); 2) Bench-marking of release scenarios using modelling tools applied in the Nordic countries, in addition to demonstration of generally accessible and free software developed by the IAEA; 3) Other systematic approaches to safety assessments of vessel port calls, and to the design and maintenance of emergency preparedness systems; More specifically, increased emphasis compared to earlier analysis after the Kursk accident is given to the engineered vessel barriers. Relevant standards from impact assessments for commercial nuclear power plants have been identified, such as from the NUREG series. The Nordic approaches to safety evaluation, impact assessments and emergency preparedness organisation was also reported as part of the project. The Canadian approach for international port calls was carefully reported and assessed as part of the project, and commended for its broad and comprehensive approach to reactor and vessel design for the nationalities involved, to the design and maintenance of emergency preparedness systems, and the well-structured and broad cooperation between civilian and military institutions. This approach goes beyond the current approach in the Nordic countries, also in the case of Norway, which experience regular port calls from allied nuclear navies. The overall result is a broader understanding in the Nordic countries for the importance of the various parameters for impact assessment of releases from marine reactors, and to the design and maintenance of an emergency preparedness organisation without detailed knowledge of the installation in question

Latest feedback from a major reactor vessel dismantling project

International Nuclear Information System (INIS)

Boucau, J.; Segerud, P.; Sanchez, M.; Garcia, R.

2015-01-01

Westinghouse performed two large segmentation projects in 2010-2013 and then 2013-2015 at the Jose Cabrera nuclear power plant in Spain. The power plant is located in Almonacid de Zorita, 43 miles east of Madrid, Spain and was in operation between 1968 and 2006. This paper will describe the sequential steps required to prepare, segment, separate, and package the individual component segments using under water mechanical techniques. The paper will also include experiences and lessons learned that Westinghouse has collected from the activities performed during the reactor vessel and vessel internals segmentation projects. (authors)

Identifying target groups for environmentally sustainable transport: assessment of different segmentation approaches

DEFF Research Database (Denmark)

Haustein, Sonja; Hunecke, Marcel

2013-01-01

Recently, the use of attitude-based market segmentation to promote environmentally sustainable transport has significantly increased. The segmentation of the population into meaningful groups sharing similar attitudes and preferences provides valuable information about how green measures should...... and behavioural segmentations are compared regarding marketing criteria. Although none of the different approaches can claim absolute superiority, attitudinal approaches show advantages in providing startingpoints for interventions to reduce car use....

Lay-out and construction of a pressure vessel built-up of cast steel segments for a pebble-bed high temperature reactor with a thermal power of 3000 MW

International Nuclear Information System (INIS)

Voigt, J.

1978-03-01

The prestressed cast vessel is an alternative to the prestressed concrete vessel for big high temperature reactors. In this report different cast steel vessel concepts for an HTR for generation of current with 3000 MW(th) are compared concerning their realization and economy. The most favourable variant serves as a base for the lay-out of the single vessel components as cast steel segments, bracing, cooling and outer sealing. Hereby the actual available possibilities of production and transport are considered. For the concept worked out possibilities of inspection and repair are suggested. A comparison of costs with adequate proposititons of the industry for a prestressed concrete and a cast iron pressure vessel investigates the economical competition. (orig.) [de

Social discourses of healthy eating. A market segmentation approach.

Science.gov (United States)

Chrysochou, Polymeros; Askegaard, Søren; Grunert, Klaus G; Kristensen, Dorthe Brogård

2010-10-01

This paper proposes a framework of discourses regarding consumers' healthy eating as a useful conceptual scheme for market segmentation purposes. The objectives are: (a) to identify the appropriate number of health-related segments based on the underlying discursive subject positions of the framework, (b) to validate and further describe the segments based on their socio-demographic characteristics and attitudes towards healthy eating, and (c) to explore differences across segments in types of associations with food and health, as well as perceptions of food healthfulness.316 Danish consumers participated in a survey that included measures of the underlying subject positions of the proposed framework, followed by a word association task that aimed to explore types of associations with food and health, and perceptions of food healthfulness. A latent class clustering approach revealed three consumer segments: the Common, the Idealists and the Pragmatists. Based on the addressed objectives, differences across the segments are described and implications of findings are discussed.

Retina image–based optic disc segmentation

Directory of Open Access Journals (Sweden)

Ching-Lin Wang

2016-05-01

Full Text Available The change of optic disc can be used to diagnose many eye diseases, such as glaucoma, diabetic retinopathy and macular degeneration. Moreover, retinal blood vessel pattern is unique for human beings even for identical twins. It is a highly stable pattern in biometric identification. Since optic disc is the beginning of the optic nerve and main blood vessels in retina, it can be used as a reference point of identification. Therefore, optic disc segmentation is an important technique for developing a human identity recognition system and eye disease diagnostic system. This article hence presents an optic disc segmentation method to extract the optic disc from a retina image. The experimental results show that the optic disc segmentation method can give impressive results in segmenting the optic disc from a retina image.

Detection of hypertensive retinopathy using vessel measurements and textural features.

Science.gov (United States)

Agurto, Carla; Joshi, Vinayak; Nemeth, Sheila; Soliz, Peter; Barriga, Simon

2014-01-01

Features that indicate hypertensive retinopathy have been well described in the medical literature. This paper presents a new system to automatically classify subjects with hypertensive retinopathy (HR) using digital color fundus images. Our method consists of the following steps: 1) normalization and enhancement of the image; 2) determination of regions of interest based on automatic location of the optic disc; 3) segmentation of the retinal vasculature and measurement of vessel width and tortuosity; 4) extraction of color features; 5) classification of vessel segments as arteries or veins; 6) calculation of artery-vein ratios using the six widest (major) vessels for each category; 7) calculation of mean red intensity and saturation values for all arteries; 8) calculation of amplitude-modulation frequency-modulation (AM-FM) features for entire image; and 9) classification of features into HR and non-HR using linear regression. This approach was tested on 74 digital color fundus photographs taken with TOPCON and CANON retinal cameras using leave-one out cross validation. An area under the ROC curve (AUC) of 0.84 was achieved with sensitivity and specificity of 90% and 67%, respectively.

A spectral k-means approach to bright-field cell image segmentation.

Science.gov (United States)

Bradbury, Laura; Wan, Justin W L

2010-01-01

Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical artifacts such as halo exist in bright-field images. In this paper, we present a robust segmentation method which combines the spectral and k-means clustering techniques to locate cells in bright-field images. This approach models an image as a matrix graph and segment different regions of the image by computing the appropriate eigenvectors of the matrix graph and using the k-means algorithm. We illustrate the effectiveness of the method by segmentation results of C2C12 (muscle) cells in bright-field images.

A Nash-game approach to joint image restoration and segmentation

OpenAIRE

Kallel , Moez; Aboulaich , Rajae; Habbal , Abderrahmane; Moakher , Maher

2014-01-01

International audience; We propose a game theory approach to simultaneously restore and segment noisy images. We define two players: one is restoration, with the image intensity as strategy, and the other is segmentation with contours as strategy. Cost functions are the classical relevant ones for restoration and segmentation, respectively. The two players play a static game with complete information, and we consider as solution to the game the so-called Nash Equilibrium. For the computation ...

Advanced Approach of Reactor Pressure Vessel In-service Inspection

International Nuclear Information System (INIS)

Matokovic, A.; Picek, E.; Pajnic, M.

2006-01-01

The most important task of every utility operating a nuclear power plant is the continuously keeping of the desired safety and reliability level. This is achieved by the performance of numerous inspections of the components, equipment and system of the nuclear power plant in operation and in particular during the scheduled maintenance periods at re-fueling time. Periodic non-destructive in-service inspections provide most relevant criteria of the integrity of primary circuit pressure components. The task is to reliably detect defects and realistically size and characterize them. One of most important and the most extensive examination is a reactor pressure vessel in-service inspection. That inspection demand high standards of technology and quality and continual innovation in the field of non-destructive testing (NDT) advanced technology as well as regarding reactor pressure vessel tool and control systems. A remote underwater contact ultrasonic technique is employed for the examination of the defined sections (reactor welds), whence eddy current method is applied for clad surface examinations. Visual inspection is used for examination of the vessel inner surface. The movement of probes and data positioning are assured by using new reactor pressure vessel tool concept that is fully integrated with NDT systems. The successful performance is attributed thorough pre-outage planning, training and successful performance demonstration qualification of chosen NDT techniques on the specimens with artificial and/or real defects. Furthermore, use of advanced approach of inspection through implementation the state of the art examination equipment significantly reduced the inspection time, radiation exposure to examination personnel, shortening nuclear power plant outage and cutting the total inspection costs. The advanced approach as presented in this paper offer more flexibility of application (non-destructive tests, local grinding action as well as taking of boat samples

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

Science.gov (United States)

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

2014-03-01

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

Cannulation and continuous cross-sectional area measurement of small blood vessels

NARCIS (Netherlands)

VanBavel, E.; Mooij, T.; Giezeman, M. J.; Spaan, J. A.

1990-01-01

Techniques have been developed for the study of isolated small arteries. To pressurize and perfuse segments of these vessels, a cannula with a low resistance to flow was developed. This cannula consisted of two concentric micropipettes. The end of a vessel segment was sucked into the inner pipette

Under Water Thermal Cutting of the Moderator Vessel and Thermal Shield

International Nuclear Information System (INIS)

Loeb, A.; Sokcic-Kostic, M.; Eisenmann, B.; Prechtl, E.

2007-01-01

This paper presents the segmentation of the in 8 meter depth of water and for cutting through super alloyed moderator vessel and of the thermal shield of the MZFR stainless steel up to 130 mm wall thickness. Depending on the research reactor by means of under water plasma and contact arc metal cutting. The moderator vessel and the thermal shield are the most essential parts of the MZFR reactor vessel internals. These components have been segmented in 2005 by means of remotely controlled under water cutting utilizing a special manipulator system, a plasma torch and CAMC (Contact Arc Metal Cutting) as cutting tools. The engineered equipment used is a highly advanced design developed in a two years R and D program. It was qualified to cut through steel walls of more than 100 mm thickness in 8 meters water depth. Both the moderator vessel and the thermal shield had to be cut into such size that the segments could afterwards be packed into shielded waste containers each with a volume of roughly 1 m 3 . Segmentation of the moderator vessel and of the thermal shield was performed within 15 months. (author)

TOURISM SEGMENTATION BASED ON TOURISTS PREFERENCES: A MULTIVARIATE APPROACH

Directory of Open Access Journals (Sweden)

Sérgio Dominique Ferreira

2010-11-01

Full Text Available Over the last decades, tourism became one of the most important sectors of the international economy. Specifically in Portugal and Brazil, its contribution to Gross Domestic Product (GDP and job creation is quite relevant. In this sense, to follow a strong marketing approach on the management of tourism resources of a country comes to be paramount. Such an approach should be based on innovations which help unveil the preferences of tourists with accuracy, turning it into a competitive advantage. In this context, the main objective of the present study is to illustrate the importance and benefits associated with the use of multivariate methodologies for market segmentation. Another objective of this work is to illustrate on the importance of a post hoc segmentation. In this work, the authors applied a Cluster Analysis, with a hierarchical method followed by an  optimization method. The main results of this study allow the identification of five clusters that are distinguished by assigning special importance to certain tourism attributes at the moment of choosing a specific destination. Thus, the authors present the advantages of post hoc segmentation based on tourists’ preferences, in opposition to an a priori segmentation based on socio-demographic characteristics.

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

Science.gov (United States)

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

2012-03-01

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

THE ROLE OF ECG IN LOCALIZING THE CULPRIT VESSEL OCCLUSION IN ACUTE ST SEGMENT ELEVATION MYOCARDICAL INFARCTION WITH ANGIOGRAPHIC CORRELATION

Directory of Open Access Journals (Sweden)

Markandeya Rao

2015-12-01

Full Text Available BACKGROUND & OBJECTIVES The Electrocardiogram remains a crucial tool in the identification and management of acute myocardial infarction. A detailed analysis of patterns of ST-segment elevation may influence decisions regarding the perfusion therapy. This study was undertaken to identify the culprit vessel from ECG in patients with acute ST elevation myocardial infarction and correlate with coronary angiogram. MATERIALS & METHODS This is a prospective study, conducted on 126 patients in Osmania General Hospital, Hyderabad. Patients with ST segment elevation from ECG was evaluated to identify culprit vessel and later correlated with coronary angiogram. RESULTS Amongst 126 patients in this study, 70 patients had anterior wall and 56 patients had inferior wall myocardial infarction. ST> 1mm in V4R, ST  V3/ST  LIII Lead II was the most sensitive and ratio of STV3/STLIII >1.2 was the most specific criteria. ST in inferior leads > 1mm had maximum sensitivity in localizing occlusion in proximal D1 occlusion proximal to S1 as well. Absence of ST i in inferior leads is the most sensitive criteria in occlusion distal to S1 as well as in distal D1 in AWMI. CONCLUSION The admission ECG in patients with ST elevation AMI is valuable not only for determining early reperfusion treatment, but also provides important information to guide clinical decision-making.

The Proposal to “Snapshot” Raim Method for Gnss Vessel Receivers Working in Poor Space Segment Geometry

Directory of Open Access Journals (Sweden)

Nowak Aleksander

2015-12-01

Full Text Available Nowadays, we can observe an increase in research on the use of small unmanned autonomous vessel (SUAV to patrol and guiding critical areas including harbours. The proposal to “snapshot” RAIM (Receiver Autonomous Integrity Monitoring method for GNSS receivers mounted on SUAV operating in poor space segment geometry is presented in the paper. Existing “snapshot” RAIM methods and algorithms which are used in practical applications have been developed for airborne receivers, thus two main assumptions have been made. The first one is that the geometry of visible satellites is strong. It means that the exclusion of any satellite from the positioning solution don’t cause significant deterioration of Dilution of Precision (DOP coefficients. The second one is that only one outlier could appear in pseudorange measurements. In case of SUAV operating in harbour these two assumptions cannot be accepted. Because of their small dimensions, GNSS antenna is only a few decimetres above sea level and regular ships, buildings and harbour facilities block and reflect satellite signals. Thus, different approach to “snapshot” RAIM is necessary. The proposal to method based on analyses of allowable maximal separation of positioning sub-solutions with using some information from EGNOS messages is described in the paper. Theoretical assumptions and results of numerical experiments are presented.

A Quantitative Comparison of Semantic Web Page Segmentation Approaches

NARCIS (Netherlands)

Kreuzer, Robert; Hage, J.; Feelders, A.J.

2015-01-01

We compare three known semantic web page segmentation algorithms, each serving as an example of a particular approach to the problem, and one self-developed algorithm, WebTerrain, that combines two of the approaches. We compare the performance of the four algorithms for a large benchmark of modern

NONINVASIVE METHODS ASSESSMENT BLOOD FLOW IN ANTERIOR SEGMENT AND CLINICAL APPLICATION PERSPECTIVE

Directory of Open Access Journals (Sweden)

T. N. Kiseleva

2017-01-01

Full Text Available The literature review contains information on the anatomical and physiological features of the vessels of the conjunctiva, iris, ciliary body. There are data on the development and application of new non-invasive methods for the study of hemodynamics in the microvessels of anterior eye segment. To study the blood flow of the anterior segment of the eye, biomycroscopy, photography and videobiomicroscopy, television biomicroscopy of vessels, darkfield visualization, application fluorescence angiography, photoacoustic angiography, orthogonal polarization spectroscopy, laser Doppler flowmetry and OCT-angiography were used in recent years. These methods allow to determine the qualitative and quantitative characteristics of conjunctiva, iris, ciliary body microcirculation. They are highly informative for assess of various drugs effect on the vascular eye system. Investigation of hemodynamics in the eye microvessels is necessary for a fundamental approach to the study of the pathophysiology of systemic circulatory pathologies (with arterial hypertension, diabetes, etc. and changes in regional blood flow in organ of vision disease. Monitoring of anterior segment microcirculation in clinical practice makes possible to monitor the effectiveness of drug and surgical treatment.

Superpixel-based segmentation of glottal area from videolaryngoscopy images

Science.gov (United States)

Turkmen, H. Irem; Albayrak, Abdulkadir; Karsligil, M. Elif; Kocak, Ismail

2017-11-01

Segmentation of the glottal area with high accuracy is one of the major challenges for the development of systems for computer-aided diagnosis of vocal-fold disorders. We propose a hybrid model combining conventional methods with a superpixel-based segmentation approach. We first employed a superpixel algorithm to reveal the glottal area by eliminating the local variances of pixels caused by bleedings, blood vessels, and light reflections from mucosa. Then, the glottal area was detected by exploiting a seeded region-growing algorithm in a fully automatic manner. The experiments were conducted on videolaryngoscopy images obtained from both patients having pathologic vocal folds as well as healthy subjects. Finally, the proposed hybrid approach was compared with conventional region-growing and active-contour model-based glottal area segmentation algorithms. The performance of the proposed method was evaluated in terms of segmentation accuracy and elapsed time. The F-measure, true negative rate, and dice coefficients of the hybrid method were calculated as 82%, 93%, and 82%, respectively, which are superior to the state-of-art glottal-area segmentation methods. The proposed hybrid model achieved high success rates and robustness, making it suitable for developing a computer-aided diagnosis system that can be used in clinical routines.

AUTOMOTIVE MARKET- FROM A GENERAL TO A MARKET SEGMENTATION APPROACH

Directory of Open Access Journals (Sweden)

Liviana Andreea Niminet

2013-12-01

Full Text Available Automotive market and its corresponding industry are undoubtedly of outmost importance and therefore proper market segmentation is crucial for market players, potential competitors and customers as well. Time has proved that market economic analysis often shown flaws in determining the relevant market, by using solely or mainly the geographic aspect and disregarding the importance of segments on the automotive market. For these reasons we propose a new approach of the automotive market proving the importance of proper market segmentation and defining the strategic groups within the automotive market.

Blood Vessel Extraction in Color Retinal Fundus Images with Enhancement Filtering and Unsupervised Classification

Directory of Open Access Journals (Sweden)

Zafer Yavuz

2017-01-01

Full Text Available Retinal blood vessels have a significant role in the diagnosis and treatment of various retinal diseases such as diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. For this reason, retinal vasculature extraction is important in order to help specialists for the diagnosis and treatment of systematic diseases. In this paper, a novel approach is developed to extract retinal blood vessel network. Our method comprises four stages: (1 preprocessing stage in order to prepare dataset for segmentation; (2 an enhancement procedure including Gabor, Frangi, and Gauss filters obtained separately before a top-hat transform; (3 a hard and soft clustering stage which includes K-means and Fuzzy C-means (FCM in order to get binary vessel map; and (4 a postprocessing step which removes falsely segmented isolated regions. The method is tested on color retinal images obtained from STARE and DRIVE databases which are available online. As a result, Gabor filter followed by K-means clustering method achieves 95.94% and 95.71% of accuracy for STARE and DRIVE databases, respectively, which are acceptable for diagnosis systems.

New algorithm for detecting smaller retinal blood vessels in fundus images

Science.gov (United States)

LeAnder, Robert; Bidari, Praveen I.; Mohammed, Tauseef A.; Das, Moumita; Umbaugh, Scott E.

2010-03-01

About 4.1 million Americans suffer from diabetic retinopathy. To help automatically diagnose various stages of the disease, a new blood-vessel-segmentation algorithm based on spatial high-pass filtering was developed to automatically segment blood vessels, including the smaller ones, with low noise. Methods: Image database: Forty, 584 x 565-pixel images were collected from the DRIVE image database. Preprocessing: Green-band extraction was used to obtain better contrast, which facilitated better visualization of retinal blood vessels. A spatial highpass filter of mask-size 11 was applied. A histogram stretch was performed to enhance contrast. A median filter was applied to mitigate noise. At this point, the gray-scale image was converted to a binary image using a binary thresholding operation. Then, a NOT operation was performed by gray-level value inversion between 0 and 255. Postprocessing: The resulting image was AND-ed with its corresponding ring mask to remove the outer-ring (lens-edge) artifact. At this point, the above algorithm steps had extracted most of the major and minor vessels, with some intersections and bifurcations missing. Vessel segments were reintegrated using the Hough transform. Results: After applying the Hough transform, both the average peak SNR and the RMS error improved by 10%. Pratt's Figure of Merit (PFM) was decreased by 6%. Those averages were better than [1] by 10-30%. Conclusions: The new algorithm successfully preserved the details of smaller blood vessels and should prove successful as a segmentation step for automatically identifying diseases that affect retinal blood vessels.

Tissues segmentation based on multi spectral medical images

Science.gov (United States)

Li, Ya; Wang, Ying

2017-11-01

Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

Multimodal segmentation of optic disc and cup from stereo fundus and SD-OCT images

Science.gov (United States)

Miri, Mohammad Saleh; Lee, Kyungmoo; Niemeijer, Meindert; Abràmoff, Michael D.; Kwon, Young H.; Garvin, Mona K.

2013-03-01

Glaucoma is one of the major causes of blindness worldwide. One important structural parameter for the diagnosis and management of glaucoma is the cup-to-disc ratio (CDR), which tends to become larger as glaucoma progresses. While approaches exist for segmenting the optic disc and cup within fundus photographs, and more recently, within spectral-domain optical coherence tomography (SD-OCT) volumes, no approaches have been reported for the simultaneous segmentation of these structures within both modalities combined. In this work, a multimodal pixel-classification approach for the segmentation of the optic disc and cup within fundus photographs and SD-OCT volumes is presented. In particular, after segmentation of other important structures (such as the retinal layers and retinal blood vessels) and fundus-to-SD-OCT image registration, features are extracted from both modalities and a k-nearest-neighbor classification approach is used to classify each pixel as cup, rim, or background. The approach is evaluated on 70 multimodal image pairs from 35 subjects in a leave-10%-out fashion (by subject). A significant improvement in classification accuracy is obtained using the multimodal approach over that obtained from the corresponding unimodal approach (97.8% versus 95.2%; p < 0:05; paired t-test).

Automatic segmentation of coronary angiograms based on fuzzy inferring and probabilistic tracking

Directory of Open Access Journals (Sweden)

Shoujun Zhou

2010-08-01

Full Text Available Abstract Background Segmentation of the coronary angiogram is important in computer-assisted artery motion analysis or reconstruction of 3D vascular structures from a single-plan or biplane angiographic system. Developing fully automated and accurate vessel segmentation algorithms is highly challenging, especially when extracting vascular structures with large variations in image intensities and noise, as well as with variable cross-sections or vascular lesions. Methods This paper presents a novel tracking method for automatic segmentation of the coronary artery tree in X-ray angiographic images, based on probabilistic vessel tracking and fuzzy structure pattern inferring. The method is composed of two main steps: preprocessing and tracking. In preprocessing, multiscale Gabor filtering and Hessian matrix analysis were used to enhance and extract vessel features from the original angiographic image, leading to a vessel feature map as well as a vessel direction map. In tracking, a seed point was first automatically detected by analyzing the vessel feature map. Subsequently, two operators [e.g., a probabilistic tracking operator (PTO and a vessel structure pattern detector (SPD] worked together based on the detected seed point to extract vessel segments or branches one at a time. The local structure pattern was inferred by a multi-feature based fuzzy inferring function employed in the SPD. The identified structure pattern, such as crossing or bifurcation, was used to control the tracking process, for example, to keep tracking the current segment or start tracking a new one, depending on the detected pattern. Results By appropriate integration of these advanced preprocessing and tracking steps, our tracking algorithm is able to extract both vessel axis lines and edge points, as well as measure the arterial diameters in various complicated cases. For example, it can walk across gaps along the longitudinal vessel direction, manage varying vessel

Automatic detection of blood vessels in retinal images for diabetic retinopathy diagnosis.

Science.gov (United States)

Raja, D Siva Sundhara; Vasuki, S

2015-01-01

Diabetic retinopathy (DR) is a leading cause of vision loss in diabetic patients. DR is mainly caused due to the damage of retinal blood vessels in the diabetic patients. It is essential to detect and segment the retinal blood vessels for DR detection and diagnosis, which prevents earlier vision loss in diabetic patients. The computer aided automatic detection and segmentation of blood vessels through the elimination of optic disc (OD) region in retina are proposed in this paper. The OD region is segmented using anisotropic diffusion filter and subsequentially the retinal blood vessels are detected using mathematical binary morphological operations. The proposed methodology is tested on two different publicly available datasets and achieved 93.99% sensitivity, 98.37% specificity, 98.08% accuracy in DRIVE dataset and 93.6% sensitivity, 98.96% specificity, and 95.94% accuracy in STARE dataset, respectively.

New approach for validating the segmentation of 3D data applied to individual fibre extraction

DEFF Research Database (Denmark)

Emerson, Monica Jane; Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

2017-01-01

We present two approaches for validating the segmentation of 3D data. The first approach consists on comparing the amount of estimated material to a value provided by the manufacturer. The second approach consists on comparing the segmented results to those obtained from imaging modalities...

A Review of Algorithms for Retinal Vessel Segmentation

Directory of Open Access Journals (Sweden)

Monserrate Intriago Pazmiño

2014-10-01

Full Text Available This paper presents a review of algorithms for extracting blood vessels network from retinal images. Since retina is a complex and delicate ocular structure, a huge effort in computer vision is devoted to study blood vessels network for helping the diagnosis of pathologies like diabetic retinopathy, hypertension retinopathy, retinopathy of prematurity or glaucoma. To carry out this process many works for normal and abnormal images have been proposed recently. These methods include combinations of algorithms like Gaussian and Gabor filters, histogram equalization, clustering, binarization, motion contrast, matched filters, combined corner/edge detectors, multi-scale line operators, neural networks, ants, genetic algorithms, morphological operators. To apply these algorithms pre-processing tasks are needed. Most of these algorithms have been tested on publicly retinal databases. We have include a table summarizing algorithms and results of their assessment.

Markerless tracking in nuclear power plants. A line segment-based approach

International Nuclear Information System (INIS)

Ishii, Hirotake; Kimura, Taro; Tokumaru, Hiroki; Shimoda, Hiroshi; Koda, Yuya

2017-01-01

To develop augmented reality-based support systems, a tracking method that measures the camera's position and orientation in real time is indispensable. A relocalization is one step that is used to (re)start the tracking. A line-segment-based relocalization method that uses a RGB-D camera and coarse-to-fine approach was developed and evaluated for this study. In the preparation stage, the target environment is scanned with a RGB-D camera. Line segments are recognized. Then three-dimensional positions of the line segments are calculated, and statistics of the line segments are calculated and stored in a database. In the relocalization stage, a few images that closely resemble the current RGB-D camera image are chosen from the database by comparing the statistics of the line segments. Then the most similar image is chosen using Normalized Cross-Correlation. This coarse-to-fine approach reduces the computational load to find the most similar image. The method was evaluated in the water purification room of the Fugen nuclear power plant. Results showed that the success rate of the relocalization is 93.6% and processing time is 45.7 ms per frame on average, which is promising for practical use. (author)

Three-dimensional renal CT angiography for guiding segmental renal artery clamping during laparoscopic partial nephrectomy

International Nuclear Information System (INIS)

Xu, Yi; Shao, Pengfei; Zhu, Xiaomei; Lv, Qiang; Liu, Wangyan; Xu, Hai; Zhu, Yinsu; Yang, Guangyu; Tang, Lijun; Yin, Changjun

2013-01-01

Aim: To evaluate the effectiveness of three-dimensional (3D) renal computed tomography angiography (CTA) in guiding segmental renal artery clamping during laparoscopic partial nephrectomy (LPN). Materials and methods: Forty-three patients with renal tumours undergoing renal CTA before LPN were retrospectively enrolled in this study. 3D arteriogram reconstructed images were created to identify the renal tumour-supplying arteries. The number and location of these targeted vessels were annotated on 3D images preoperatively and compared with the clamped vessels during LPN. The consistency between target vessels annotated at CTA and clamped arteries at LPN was compared both using a patient-based analysis and vessel-based analysis. The χ 2 test was applied to analyse the influence of tumour size, location, and growth pattern on the number of clamped segmental renal branches. Results: On patient-based analysis, the number of targeted vessels was consistent with the clamped vessels during LPN in 33 of 43 patients. On vessel-based analysis, 56 of 65 target vessels annotated at CTA were clamped during LPN. More segmental renal branches (p = 0.04) were clamped in patients with tumours of larger size. Tumour location and growth pattern had no association with the number of clamped segmental branches during LPN. Conclusion: High-quality CTA images and 3D reconstruction images can detect detailed information of tumour-supplying arteries to renal tumours. 3D renal CTA is an effective way to guide segmental renal artery clamping during LPN

Deformable 4DCT lung registration with vessel bifurcations

International Nuclear Information System (INIS)

Hilsmann, A.; Vik, T.; Kaus, M.; Franks, K.; Bissonette, J.P.; Purdie, T.; Beziak, A.; Aach, T.

2007-01-01

In radiotherapy planning of lung cancer, breathing motion causes uncertainty in the determination of the target volume. Image registration makes it possible to get information about the deformation of the lung and the tumor movement in the respiratory cycle from a few images. A dedicated, automatic, landmark-based technique was developed that finds corresponding vessel bifurcations. Hereby, we developed criteria to characterize pronounced bifurcations for which correspondence finding was more stable and accurate. The bifurcations were extracted from automatically segmented vessel trees in maximum inhale and maximum exhale CT thorax data sets. To find corresponding bifurcations in both data sets we used the shape context approach of Belongie et al. Finally, a volumetric lung deformation was obtained using thin-plate spline interpolation and affine registration. The method is evaluated on 10 4D-CT data sets of patients with lung cancer. (orig.)

Commissioning result of the KSTAR in-vessel cryo-pump

Energy Technology Data Exchange (ETDEWEB)

Chang, Y. B.; Lee, H. J.; Park, Y.M. [National Fusion Research Institute, Daejeon (Korea, Republic of); and others

2013-12-15

KSTAR in-vessel cryo-pump has been installed in the vacuum vessel top and bottom side with up-down symmetry for the better plasma density control in the D-shape H-mode. The cryogenic helium lines of the in-vessel cryo-pump are located at the vertical positions from the vacuum vessel torus center 2,000 mm. The inductive electrical potential has been optimized to reduce risk of electrical breakdown during plasma disruption. In-vessel cryo-pump consists of three parts of coaxial circular shape components; cryo-panel, thermal shield and particle shield. The cryo-panel is cooled down to below 4.5 K. The cryo-panel and thermal shields were made by Inconel 625 tube for higher mechanical strength. The thermal shields and their cooling tubes were annealed in air environment to improve the thermal radiation emissivity on the surface. Surface of cryo-panel was electro-polished to minimize the thermal radiation heat load. The in-vessel cryo-pump was pre-assembled on a test bed in 180 degree segment base. The leak test was carried out after the thermal shock between room temperature to LN2 one before installing them into vacuum vessel. Two segments were welded together in the vacuum vessel and final leak test was performed after the thermal shock. Commissioning of the in-vessel cryo-pump was carried out using a temporary liquid helium supply system.

Computer-aided detection of pulmonary embolism: Influence on radiologists' detection performance with respect to vessel segments

International Nuclear Information System (INIS)

Das, Marco; Muehlenbruch, Georg; Helm, Anita; Guenther, Rolf W.; Wildberger, Joachim E.; Bakai, Annemarie; Salganicoff, Marcos; Liang, Jianming; Wolf, Matthias; Stanzel, Sven

2008-01-01

The purpose was to assess the sensitivity of a CAD software prototype for the detection of pulmonary embolism in MDCT chest examinations with regard to vessel level and to assess the influence on radiologists' detection performance. Forty-three patients with suspected PE were included in this retrospective study. MDCT chest examinations with a standard PE protocol were acquired at a 16-slice MDCT. All patient data were read by three radiologists (R1, R2, R3), and all thrombi were marked. A CAD prototype software was applied to all datasets, and each finding of the software was analyzed with regard to vessel level. The standard of reference was assessed in a consensus read. Sensitivity for the radiologists and CAD software was assessed. Thirty-three patients were positive for PE, with a total of 215 thrombi. The mean overall sensitivity for the CAD software alone was 83% (specificity, 80%). Radiologist sensitivity was 77% = R3, 82% = R2, and R1 = 87%. With the aid of the CAD software, sensitivities increased to 98% (R1), 93% (R2), and 92% (R3) (p<0.0001). CAD performance at the lobar level was 87%, at the segmental 90% and at the subsegmental 77%. With the use of CAD for PE, the detection performance of radiologists can be improved. (orig.)

Radioactivity concentration measuring device for radiation waste containing vessel

International Nuclear Information System (INIS)

Goto, Tetsuo.

1994-01-01

The device of the present invention can precisely and accurately measure a radioactive concentration of radioactive wastes irrespective of the radioactivity concentration distribution. Namely, a Ge detector having a collimator and a plurality of radiation detectors are placed at the outside of the radioactive waste containing vessel in such a way that it can rotate and move vertically relative to the vessel. The plurality of radiation detectors detect radiation coefficient signals at an assumed segment unit of a predetermined length in vertical direction and for every predetermined angle unit in the rotational direction. A weight measuring device determines the weight of the vessel. A computer calculates an average density of radioactivity for the region filled with radioactivity based on the determined net weight and radiation coefficient signals assuming that the volume of the radioactivity is constant. In addition, the computer calculates the amount of radioactivity in the assumed segment by conducting γ -ray absorption compensation calculation for the material in the vessel. Each of the amount of radioactivity is integrated to determine the amount of radioactivity in the vessel. (I.S.)

Two separate thoroscopic segmentectomies with vessel sealing system.

Science.gov (United States)

Watanabe, Atsushi; Miyajima, Masahiro; Kawaharada, Nobuyoshi; Higami, Tetsuya

2012-04-01

Total thoracoscopic segmentectomy is an appealing concept in terms of providing a parenchyma-sparing treatment. We describe our technique of two seperate total thoracoscopic segmentectomies by using a vessel sealing system (VSS). A 76-year old female with four gradually enlarging ground glass lesions on the right segment 2 (10 and 3 mm) and segment 6 (8 and 3 mm) was admitted to our institute for surgical diagnosis and treatment. Preoperative three-dimensional computed tomography showed that the A2 is composed of descending A2 and ascending A2, branch of V6 coursed to V2 and B1a originated from B2 and B1b from B3. Two separate segmentectomies were subsequently scheduled. Pulmonary vessel division was performed with VSS after proximal ligation. Intersegmental division by VSS and electrocautery was performed with the use of inflation-deflation demarcation line and the pulmonary veins along the intersegmental plane (V2a and V2c for segment 2 and V6b and V6c for segment 6) as guides to confirm the intersegmental plane after pulmonary artery and bronchial divisions. The intraoperative frozen-section examinations revealed adenocarcinoma in situ. Two separate segmentectomies were successfully completed, with a total operative time of 240 min and blood loss of 30 ml. VSS is a very useful and safe device for intersegmental division and pulmonary vessel division.

Retinal vascular segmentation using superpixel-based line operator and its application to vascular topology estimation.

Science.gov (United States)

Na, Tong; Xie, Jianyang; Zhao, Yitian; Zhao, Yifan; Liu, Yue; Wang, Yongtian; Liu, Jiang

2018-05-09

Automatic methods of analyzing of retinal vascular networks, such as retinal blood vessel detection, vascular network topology estimation, and arteries/veins classification are of great assistance to the ophthalmologist in terms of diagnosis and treatment of a wide spectrum of diseases. We propose a new framework for precisely segmenting retinal vasculatures, constructing retinal vascular network topology, and separating the arteries and veins. A nonlocal total variation inspired Retinex model is employed to remove the image intensity inhomogeneities and relatively poor contrast. For better generalizability and segmentation performance, a superpixel-based line operator is proposed as to distinguish between lines and the edges, thus allowing more tolerance in the position of the respective contours. The concept of dominant sets clustering is adopted to estimate retinal vessel topology and classify the vessel network into arteries and veins. The proposed segmentation method yields competitive results on three public data sets (STARE, DRIVE, and IOSTAR), and it has superior performance when compared with unsupervised segmentation methods, with accuracy of 0.954, 0.957, and 0.964, respectively. The topology estimation approach has been applied to five public databases (DRIVE,STARE, INSPIRE, IOSTAR, and VICAVR) and achieved high accuracy of 0.830, 0.910, 0.915, 0.928, and 0.889, respectively. The accuracies of arteries/veins classification based on the estimated vascular topology on three public databases (INSPIRE, DRIVE and VICAVR) are 0.90.9, 0.910, and 0.907, respectively. The experimental results show that the proposed framework has effectively addressed crossover problem, a bottleneck issue in segmentation and vascular topology reconstruction. The vascular topology information significantly improves the accuracy on arteries/veins classification. © 2018 American Association of Physicists in Medicine.

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

Science.gov (United States)

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

2017-02-01

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

Pressure vessels fabricated with high-strength wire and electroformed nickel

Science.gov (United States)

Roth, B.

1966-01-01

Metal pressure vessels of various shapes having high strength-to-weight ratios are fabricated by using known techniques of filament winding and electroforming. This eliminates nonuniform wall thickness and unequal wall strength which resulted from welding formed vessel segments together.

A segmentation approach for a delineation of terrestrial ecoregions

Science.gov (United States)

Nowosad, J.; Stepinski, T.

2017-12-01

Terrestrial ecoregions are the result of regionalization of land into homogeneous units of similar ecological and physiographic features. Terrestrial Ecoregions of the World (TEW) is a commonly used global ecoregionalization based on expert knowledge and in situ observations. Ecological Land Units (ELUs) is a global classification of 250 meters-sized cells into 4000 types on the basis of the categorical values of four environmental variables. ELUs are automatically calculated and reproducible but they are not a regionalization which makes them impractical for GIS-based spatial analysis and for comparison with TEW. We have regionalized terrestrial ecosystems on the basis of patterns of the same variables (land cover, soils, landform, and bioclimate) previously used in ELUs. Considering patterns of categorical variables makes segmentation and thus regionalization possible. Original raster datasets of the four variables are first transformed into regular grids of square-sized blocks of their cells called eco-sites. Eco-sites are elementary land units containing local patterns of physiographic characteristics and thus assumed to contain a single ecosystem. Next, eco-sites are locally aggregated using a procedure analogous to image segmentation. The procedure optimizes pattern homogeneity of all four environmental variables within each segment. The result is a regionalization of the landmass into land units characterized by uniform pattern of land cover, soils, landforms, climate, and, by inference, by uniform ecosystem. Because several disjoined segments may have very similar characteristics, we cluster the segments to obtain a smaller set of segment types which we identify with ecoregions. Our approach is automatic, reproducible, updatable, and customizable. It yields the first automatic delineation of ecoregions on the global scale. In the resulting vector database each ecoregion/segment is described by numerous attributes which make it a valuable GIS resource for

Comparison of different deep learning approaches for parotid gland segmentation from CT images

Science.gov (United States)

Hänsch, Annika; Schwier, Michael; Gass, Tobias; Morgas, Tomasz; Haas, Benjamin; Klein, Jan; Hahn, Horst K.

2018-02-01

The segmentation of target structures and organs at risk is a crucial and very time-consuming step in radiotherapy planning. Good automatic methods can significantly reduce the time clinicians have to spend on this task. Due to its variability in shape and often low contrast to surrounding structures, segmentation of the parotid gland is especially challenging. Motivated by the recent success of deep learning, we study different deep learning approaches for parotid gland segmentation. Particularly, we compare 2D, 2D ensemble and 3D U-Net approaches and find that the 2D U-Net ensemble yields the best results with a mean Dice score of 0.817 on our test data. The ensemble approach reduces false positives without the need for an automatic region of interest detection. We also apply our trained 2D U-Net ensemble to segment the test data of the 2015 MICCAI head and neck auto-segmentation challenge. With a mean Dice score of 0.861, our classifier exceeds the highest mean score in the challenge. This shows that the method generalizes well onto data from independent sites. Since appropriate reference annotations are essential for training but often difficult and expensive to obtain, it is important to know how many samples are needed to properly train a neural network. We evaluate the classifier performance after training with differently sized training sets (50-450) and find that 250 cases (without using extensive data augmentation) are sufficient to obtain good results with the 2D ensemble. Adding more samples does not significantly improve the Dice score of the segmentations.

Quantification of common carotid artery and descending aorta vessel wall thickness from MR vessel wall imaging using a fully automated processing pipeline.

Science.gov (United States)

Gao, Shan; van 't Klooster, Ronald; Brandts, Anne; Roes, Stijntje D; Alizadeh Dehnavi, Reza; de Roos, Albert; Westenberg, Jos J M; van der Geest, Rob J

2017-01-01

To develop and evaluate a method that can fully automatically identify the vessel wall boundaries and quantify the wall thickness for both common carotid artery (CCA) and descending aorta (DAO) from axial magnetic resonance (MR) images. 3T MRI data acquired with T 1 -weighted gradient-echo black-blood imaging sequence from carotid (39 subjects) and aorta (39 subjects) were used to develop and test the algorithm. The vessel wall segmentation was achieved by respectively fitting a 3D cylindrical B-spline surface to the boundaries of lumen and outer wall. The tube-fitting was based on the edge detection performed on the signal intensity (SI) profile along the surface normal. To achieve a fully automated process, Hough Transform (HT) was developed to estimate the lumen centerline and radii for the target vessel. Using the outputs of HT, a tube model for lumen segmentation was initialized and deformed to fit the image data. Finally, lumen segmentation was dilated to initiate the adaptation procedure of outer wall tube. The algorithm was validated by determining: 1) its performance against manual tracing; 2) its interscan reproducibility in quantifying vessel wall thickness (VWT); 3) its capability of detecting VWT difference in hypertensive patients compared with healthy controls. Statistical analysis including Bland-Altman analysis, t-test, and sample size calculation were performed for the purpose of algorithm evaluation. The mean distance between the manual and automatically detected lumen/outer wall contours was 0.00 ± 0.23/0.09 ± 0.21 mm for CCA and 0.12 ± 0.24/0.14 ± 0.35 mm for DAO. No significant difference was observed between the interscan VWT assessment using automated segmentation for both CCA (P = 0.19) and DAO (P = 0.94). Both manual and automated segmentation detected significantly higher carotid (P = 0.016 and P = 0.005) and aortic (P < 0.001 and P = 0.021) wall thickness in the hypertensive patients. A reliable and reproducible pipeline for fully

A modified Seeded Region Growing algorithm for vessel segmentation in breast MRI images for investigating the nature of potential lesions

Science.gov (United States)

Glotsos, D.; Vassiou, K.; Kostopoulos, S.; Lavdas, El; Kalatzis, I.; Asvestas, P.; Arvanitis, D. L.; Fezoulidis, I. V.; Cavouras, D.

2014-03-01

The role of Magnetic Resonance Imaging (MRI) as an alternative protocol for screening of breast cancer has been intensively investigated during the past decade. Preliminary research results have indicated that gadolinium-agent administrative MRI scans may reveal the nature of breast lesions by analyzing the contrast-agent's uptake time. In this study, we attempt to deduce the same conclusion, however, from a different perspective by investigating, using image processing, the vascular network of the breast at two different time intervals following the administration of gadolinium. Twenty cases obtained from a 3.0-T MRI system (SIGNA HDx; GE Healthcare) were included in the study. A new modification of the Seeded Region Growing (SRG) algorithm was used to segment vessels from surrounding background. Delineated vessels were investigated by means of their topology, morphology and texture. Results have shown that it is possible to estimate the nature of the lesions with approximately 94.4% accuracy, thus, it may be claimed that the breast vascular network does encodes useful, patterned, information, which can be used for characterizing breast lesions.

Healthy Lung Vessel Morphology Derived From Thoracic Computed Tomography

Directory of Open Access Journals (Sweden)

Michael Pienn

2018-04-01

Full Text Available Knowledge of the lung vessel morphology in healthy subjects is necessary to improve our understanding about the functional network of the lung and to recognize pathologic deviations beyond the normal inter-subject variation. Established values of normal lung morphology have been derived from necropsy material of only very few subjects. In order to determine morphologic readouts from a large number of healthy subjects, computed tomography pulmonary angiography (CTPA datasets, negative for pulmonary embolism, and other thoracic pathologies, were analyzed using a fully-automatic, in-house developed artery/vein separation algorithm. The number, volume, and tortuosity of the vessels in a diameter range between 2 and 10 mm were determined. Visual inspection of all datasets was used to exclude subjects with poor image quality or inadequate artery/vein separation from the analysis. Validation of the algorithm was performed manually by a radiologist on randomly selected subjects. In 123 subjects (men/women: 55/68, aged 59 ± 17 years, the median overlap between visual inspection and fully-automatic segmentation was 94.6% (69.2–99.9%. The median number of vessel segments in the ranges of 8–10, 6–8, 4–6, and 2–4 mm diameter was 9, 34, 134, and 797, respectively. Number of vessel segments divided by the subject's lung volume was 206 vessels/L with arteries and veins contributing almost equally. In women this vessel density was about 15% higher than in men. Median arterial and venous volumes were 1.52 and 1.54% of the lung volume, respectively. Tortuosity was best described with the sum-of-angles metric and was 142.1 rad/m (138.3–144.5 rad/m. In conclusion, our fully-automatic artery/vein separation algorithm provided reliable measures of pulmonary arteries and veins with respect to age and gender. There was a large variation between subjects in all readouts. No relevant dependence on age, gender, or vessel type was observed. These data may

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

Science.gov (United States)

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.

Robust nuclei segmentation in cyto-histopathological images using statistical level set approach with topology preserving constraint

Science.gov (United States)

Taheri, Shaghayegh; Fevens, Thomas; Bui, Tien D.

2017-02-01

Computerized assessments for diagnosis or malignancy grading of cyto-histopathological specimens have drawn increased attention in the field of digital pathology. Automatic segmentation of cell nuclei is a fundamental step in such automated systems. Despite considerable research, nuclei segmentation is still a challenging task due noise, nonuniform illumination, and most importantly, in 2D projection images, overlapping and touching nuclei. In most published approaches, nuclei refinement is a post-processing step after segmentation, which usually refers to the task of detaching the aggregated nuclei or merging the over-segmented nuclei. In this work, we present a novel segmentation technique which effectively addresses the problem of individually segmenting touching or overlapping cell nuclei during the segmentation process. The proposed framework is a region-based segmentation method, which consists of three major modules: i) the image is passed through a color deconvolution step to extract the desired stains; ii) then the generalized fast radial symmetry transform is applied to the image followed by non-maxima suppression to specify the initial seed points for nuclei, and their corresponding GFRS ellipses which are interpreted as the initial nuclei borders for segmentation; iii) finally, these nuclei border initial curves are evolved through the use of a statistical level-set approach along with topology preserving criteria for segmentation and separation of nuclei at the same time. The proposed method is evaluated using Hematoxylin and Eosin, and fluorescent stained images, performing qualitative and quantitative analysis, showing that the method outperforms thresholding and watershed segmentation approaches.

Automated retinal vessel type classification in color fundus images

Science.gov (United States)

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

2013-02-01

Automated retinal vessel type classification is an essential first step toward machine-based quantitative measurement of various vessel topological parameters and identifying vessel abnormalities and alternations in cardiovascular disease risk analysis. This paper presents a new and accurate automatic artery and vein classification method developed for arteriolar-to-venular width ratio (AVR) and artery and vein tortuosity measurements in regions of interest (ROI) of 1.5 and 2.5 optic disc diameters from the disc center, respectively. This method includes illumination normalization, automatic optic disc detection and retinal vessel segmentation, feature extraction, and a partial least squares (PLS) classification. Normalized multi-color information, color variation, and multi-scale morphological features are extracted on each vessel segment. We trained the algorithm on a set of 51 color fundus images using manually marked arteries and veins. We tested the proposed method in a previously unseen test data set consisting of 42 images. We obtained an area under the ROC curve (AUC) of 93.7% in the ROI of AVR measurement and 91.5% of AUC in the ROI of tortuosity measurement. The proposed AV classification method has the potential to assist automatic cardiovascular disease early detection and risk analysis.

Characterization of a sequential pipeline approach to automatic tissue segmentation from brain MR Images

International Nuclear Information System (INIS)

Hou, Zujun; Huang, Su

2008-01-01

Quantitative analysis of gray matter and white matter in brain magnetic resonance imaging (MRI) is valuable for neuroradiology and clinical practice. Submission of large collections of MRI scans to pipeline processing is increasingly important. We characterized this process and suggest several improvements. To investigate tissue segmentation from brain MR images through a sequential approach, a pipeline that consecutively executes denoising, skull/scalp removal, intensity inhomogeneity correction and intensity-based classification was developed. The denoising phase employs a 3D-extension of the Bayes-Shrink method. The inhomogeneity is corrected by an improvement of the Dawant et al.'s method with automatic generation of reference points. The N3 method has also been evaluated. Subsequently the brain tissue is segmented into cerebrospinal fluid, gray matter and white matter by a generalized Otsu thresholding technique. Intensive comparisons with other sequential or iterative methods have been carried out using simulated and real images. The sequential approach with judicious selection on the algorithm selection in each stage is not only advantageous in speed, but also can attain at least as accurate segmentation as iterative methods under a variety of noise or inhomogeneity levels. A sequential approach to tissue segmentation, which consecutively executes the wavelet shrinkage denoising, scalp/skull removal, inhomogeneity correction and intensity-based classification was developed to automatically segment the brain tissue into CSF, GM and WM from brain MR images. This approach is advantageous in several common applications, compared with other pipeline methods. (orig.)

Flaw density examinations of a clad boiling water reactor pressure vessel segment

International Nuclear Information System (INIS)

Cook, K.V.; McClung, R.W.

1986-01-01

Flaw density is the greatest uncertainty involved in probabilistic analyses of reactor pressure vessel failure. As part of the Heavy-Section Steel Technology (HSST) Program, studies have been conducted to determine flaw density in a section of reactor pressure vessel cut from the Hope Creek Unit 2 vessel [nominally 0.7 by 3 m (2 by 10 ft)]. This section (removed from the scrapped vessel that was never in service) was evaluated nondestructively to determine the as-fabricated status. We had four primary objectives: (1) evaluate longitudinal and girth welds for flaws with manual ultrasonics, (2) evaluate the zone under the nominal 6.3-mm (0.25-in.) clad for cracking (again with manual ultrasonics), (3) evaluate the cladding for cracks with a high-sensitivity fluorescent penetrant method, and (4) determine the source of indications detected

Computer aided solution for segmenting the neuron line in hippocampal microscope images

Science.gov (United States)

Albaidhani, Tahseen; Jassim, Sabah; Al-Assam, Hisham

2017-05-01

The brain Hippocampus component is known to be responsible for memory and spatial navigation. Its functionality depends on the status of different blood vessels within the Hippocampus and is severely impaired by Alzheimer's disease as a result blockage of increasing number of blood vessels by accumulation of amyloid-beta (Aβ) protein. Accurate counting of blood vessels within the Hippocampus of mice brain, from microscopic images, is an active research area for the understanding of Alzheimer's disease. Here, we report our work on automatic detection of the Region of Interest, i.e. the region in which blood vessels are located. This area typically falls between the hippocampus edge and the line of neurons within the Hippocampus. This paper proposes a new method to detect and exclude the neuron line to improve the accuracy of blood vessel counting because some neurons on it might lead to false positive cases as they look like blood vessels. Our proposed solution is based on using trainable segmentation approach with morphological operations, taking into account variation in colour, intensity values, and image texture. Experiments on a sufficient number of microscopy images of mouse brain demonstrate the effectiveness of the developed solution in preparation for blood vessels counting.

Automated detection of kinks from blood vessels for optic cup segmentation in retinal images

Science.gov (United States)

Wong, D. W. K.; Liu, J.; Lim, J. H.; Li, H.; Wong, T. Y.

2009-02-01

The accurate localization of the optic cup in retinal images is important to assess the cup to disc ratio (CDR) for glaucoma screening and management. Glaucoma is physiologically assessed by the increased excavation of the optic cup within the optic nerve head, also known as the optic disc. The CDR is thus an important indicator of risk and severity of glaucoma. In this paper, we propose a method of determining the cup boundary using non-stereographic retinal images by the automatic detection of a morphological feature within the optic disc known as kinks. Kinks are defined as the bendings of small vessels as they traverse from the disc to the cup, providing physiological validation for the cup boundary. To detect kinks, localized patches are first generated from a preliminary cup boundary obtained via level set. Features obtained using edge detection and wavelet transform are combined using a statistical approach rule to identify likely vessel edges. The kinks are then obtained automatically by analyzing the detected vessel edges for angular changes, and these kinks are subsequently used to obtain the cup boundary. A set of retinal images from the Singapore Eye Research Institute was obtained to assess the performance of the method, with each image being clinically graded for the CDR. From experiments, when kinks were used, the error on the CDR was reduced to less than 0.1 CDR units relative to the clinical CDR, which is within the intra-observer variability of 0.2 CDR units.

Manufacture of EAST VS In-Vessel Coil

International Nuclear Information System (INIS)

Long, Feng; Wu, Yu; Du, Shijun; Jin, Huan; Yu, Min; Han, Qiyang; Wan, Jiansheng; Liu, Bin; Qiao, Jingchun; Liu, Xiaochuan; Li, Chang; Cai, Denggang; Tong, Yunhua

2013-01-01

Highlights: • ITER like Stainless Steel Mineral Insulation Conductor (SSMIC) used for EAST Tokamak VS In-Vessel Coil manufacture first time. • Research on SSMIC fabrication was introduced in detail. • Two sets totally four single-turn VS coils were manufactured and installed in place symmetrically above and below the mid-plane in the vacuum vessel of EAST. • The manufacture and inspection of the EAST VS coil especially the joint for the SSMIC connection was described in detail. • The insulation resistances of all the VS coils have no significant reduction after endurance test. -- Abstract: In the ongoing latest update round of EAST (Experimental Advanced Superconducting Tokamak), two sets of two single-turn Vertical Stabilization (VS) coils were manufactured and installed symmetrically above and below the mid-plane in the vacuum vessel of EAST. The Stainless Steel Mineral Insulated Conductor (SSMIC) developed for ITER In-Vessel Coils (IVCs) in Institute of Plasma Physics, Chinese Academy of Science (ASIPP) was used for the EAST VS coils manufacture. Each turn poloidal field VS coil includes three internal joints in the vacuum vessel. The middle joint connects two pieces of conductor which together form an R2.3 m arc segment inside the vacuum vessel. The other two joints connect the arc segment with the two feeders near the port along the toroidal direction to bear lower electromagnetic loads during operation. Main processes and tests include material performances checking, conductor fabrication, joint connection and testing, coil forming, insulation performances measurement were described herein

Cerebrovascular plaque segmentation using object class uncertainty snake in MR images

Science.gov (United States)

Das, Bipul; Saha, Punam K.; Wolf, Ronald; Song, Hee Kwon; Wright, Alexander C.; Wehrli, Felix W.

2005-04-01

Atherosclerotic cerebrovascular disease leads to formation of lipid-laden plaques that can form emboli when ruptured causing blockage to cerebral vessels. The clinical manifestation of this event sequence is stroke; a leading cause of disability and death. In vivo MR imaging provides detailed image of vascular architecture for the carotid artery making it suitable for analysis of morphological features. Assessing the status of carotid arteries that supplies blood to the brain is of primary interest to such investigations. Reproducible quantification of carotid artery dimensions in MR images is essential for plaque analysis. Manual segmentation being the only method presently makes it time consuming and sensitive to inter and intra observer variability. This paper presents a deformable model for lumen and vessel wall segmentation of carotid artery from MR images. The major challenges of carotid artery segmentation are (a) low signal-to-noise ratio, (b) background intensity inhomogeneity and (c) indistinct inner and/or outer vessel wall. We propose a new, effective object-class uncertainty based deformable model with additional features tailored toward this specific application. Object-class uncertainty optimally utilizes MR intensity characteristics of various anatomic entities that enable the snake to avert leakage through fuzzy boundaries. To strengthen the deformable model for this application, some other properties are attributed to it in the form of (1) fully arc-based deformation using a Gaussian model to maximally exploit vessel wall smoothness, (2) construction of a forbidden region for outer-wall segmentation to reduce interferences by prominent lumen features and (3) arc-based landmark for efficient user interaction. The algorithm has been tested upon T1- and PD- weighted images. Measures of lumen area and vessel wall area are computed from segmented data of 10 patient MR images and their accuracy and reproducibility are examined. These results correspond

A Hybrid Approach for Improving Image Segmentation: Application to Phenotyping of Wheat Leaves.

Directory of Open Access Journals (Sweden)

Joshua Chopin

Full Text Available In this article we propose a novel tool that takes an initial segmented image and returns a more accurate segmentation that accurately captures sharp features such as leaf tips, twists and axils. Our algorithm utilizes basic a-priori information about the shape of plant leaves and local image orientations to fit active contour models to important plant features that have been missed during the initial segmentation. We compare the performance of our approach with three state-of-the-art segmentation techniques, using three error metrics. The results show that leaf tips are detected with roughly one half of the original error, segmentation accuracy is almost always improved and more than half of the leaf breakages are corrected.

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

Science.gov (United States)

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

1981-01-01

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

Remote handling assessment of attachment concepts for DEMO blanket segments

Energy Technology Data Exchange (ETDEWEB)

Iglesias, Daniel, E-mail: daniel.iglesias@ccfe.ac.uk [CCFE, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Bastow, Roger; Cooper, Dave; Crowe, Robert; Middleton-Gear, Dave [CCFE, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Sibois, Romain [VTT, Technical Research Centre of Finland, Industrial Systems, ROViR, Tampere (Finland); Carloni, Dario [Institute of Neutron Physics and Reactor Technology, Karlsruhe Institute of Technology (KIT) (Germany); Vizvary, Zsolt; Crofts, Oliver [CCFE, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Harman, Jon [EFDA Close Support Unit Garching, Boltzmannstaße 2, D-85748 Garching bei München (Germany); Loving, Antony [CCFE, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom)

2015-10-15

Highlights: • Challenges are identified for the remote handling of blanket segments’ attachments. • Two attachment design approaches are assessed for remote handling (RH) feasibility. • An alternative is proposed, which potentially simplifies and speeds-up RH operations. • Up to three different assemblies are proposed for the remote handling of the attachments. • Proposed integrated design of upper port is compatible with the attachment systems. - Abstract: The replacement strategy of the massive Multi-Module Blanket Segments (MMS) is a key driver in the design of several DEMO systems. These include the blankets themselves, the vacuum vessel (VV) and its ports and the Remote Maintenance System (RMS). Common challenges to any blanket attachment system have been identified, such as the need for applying a preload to the MMS manifold, the effects of the decay heat and several uncertainties related to permanent deformations when removing the blanket segments after service. The WP12 kinematics of the MMS in-vessel transportation was adapted to the requirements of each of the supports during 2013 and 2014 design activities. The RM equipment envisaged for handling attachments and earth connections may be composed of up to three different assemblies. An In-Vessel Mover at the divertor level handles the lower support and earth bonding, and could stabilize the MMS during transportation. A Shield Plug crane with a 6 DoF manipulator operates the upper attachment and earth straps. And a Vertical Maintenance Crane is responsible for the in-vessel MMS transportation and can handle the removable upper support pins. A final proposal is presented which can potentially reduce the number of required systems, at the same time that speeds-up the RMS global operations.

A study of reactor vessel integrity assessment

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Hoon [Korea Institute of Nuclear Safety, Taejon (Korea, Republic of); Kim, Jong Kyung; Shin, Chang Ho; Seo, Bo Kyun [Hanyang Univ., Seoul (Korea, Republic of)

1999-02-15

The fast neutron fluence at the Reactor Pressure Vessel(RPV) of KNGR designed for 60 years lifetime was calculated by full-scope Monte Carlo simulation for reactor vessel integrity assessment. KNGR core geometry was modeled on a three-dimensional representation of the one-sixteenth of the reactor in-vessel component. Each fuel assemblies were modeled explicitly, and each fuel pins were axially divided into 5 segments. The maximum flux of 4.3 x 10{sup 10} neutrons/cm{sup 2}. sec at the RPV was obtained by tallying neutrons crossing the beltline of inner surface of the RPV.

Automatic localization of bifurcations and vessel crossings in digital fundus photographs using location regression

Science.gov (United States)

Niemeijer, Meindert; Dumitrescu, Alina V.; van Ginneken, Bram; Abrámoff, Michael D.

2011-03-01

Parameters extracted from the vasculature on the retina are correlated with various conditions such as diabetic retinopathy and cardiovascular diseases such as stroke. Segmentation of the vasculature on the retina has been a topic that has received much attention in the literature over the past decade. Analysis of the segmentation result, however, has only received limited attention with most works describing methods to accurately measure the width of the vessels. Analyzing the connectedness of the vascular network is an important step towards the characterization of the complete vascular tree. The retinal vascular tree, from an image interpretation point of view, originates at the optic disc and spreads out over the retina. The tree bifurcates and the vessels also cross each other. The points where this happens form the key to determining the connectedness of the complete tree. We present a supervised method to detect the bifurcations and crossing points of the vasculature of the retina. The method uses features extracted from the vasculature as well as the image in a location regression approach to find those locations of the segmented vascular tree where the bifurcation or crossing occurs (from here, POI, points of interest). We evaluate the method on the publicly available DRIVE database in which an ophthalmologist has marked the POI.

Reactor vessel dismantling at the high flux materials testing reactor Petten

International Nuclear Information System (INIS)

Tas, A.; Teunissen, G.

1986-01-01

The project of replacing the reactor vessel of the high flux materials testing reactor (HFR) originated in 1974 when results of several research programs confirmed severe neutron embrittlement of aluminium alloys suggesting a limited life of the existing facility. This report describes the dismantling philosophy and organisation, the design of special underwater equipment, the dismantling of the reactor vessel and thermal column, and the conditioning and shielding activities resulting in a working area for the installation of the new vessel with no access limitations due to radiation. Finally an overview of the segmentation, waste disposal and radiation exposure is given. The total dismantling, segmentation and conditioning activities resulted in a total collective radiation dose of 300 mSv. (orig.) [de

Classification of semiurban landscapes from very high-resolution satellite images using a regionalized multiscale segmentation approach

Science.gov (United States)

Kavzoglu, Taskin; Erdemir, Merve Yildiz; Tonbul, Hasan

2017-07-01

In object-based image analysis, obtaining representative image objects is an important prerequisite for a successful image classification. The major threat is the issue of scale selection due to the complex spatial structure of landscapes portrayed as an image. This study proposes a two-stage approach to conduct regionalized multiscale segmentation. In the first stage, an initial high-level segmentation is applied through a "broadscale," and a set of image objects characterizing natural borders of the landscape features are extracted. Contiguous objects are then merged to create regions by considering their normalized difference vegetation index resemblance. In the second stage, optimal scale values are estimated for the extracted regions, and multiresolution segmentation is applied with these settings. Two satellite images with different spatial and spectral resolutions were utilized to test the effectiveness of the proposed approach and its transferability to different geographical sites. Results were compared to those of image-based single-scale segmentation and it was found that the proposed approach outperformed the single-scale segmentations. Using the proposed methodology, significant improvement in terms of segmentation quality and classification accuracy (up to 5%) was achieved. In addition, the highest classification accuracies were produced using fine-scale values.

Automatic coronary artery segmentation based on multi-domains remapping and quantile regression in angiographies.

Science.gov (United States)

Li, Zhixun; Zhang, Yingtao; Gong, Huiling; Li, Weimin; Tang, Xianglong

2016-12-01

Coronary artery disease has become the most dangerous diseases to human life. And coronary artery segmentation is the basis of computer aided diagnosis and analysis. Existing segmentation methods are difficult to handle the complex vascular texture due to the projective nature in conventional coronary angiography. Due to large amount of data and complex vascular shapes, any manual annotation has become increasingly unrealistic. A fully automatic segmentation method is necessary in clinic practice. In this work, we study a method based on reliable boundaries via multi-domains remapping and robust discrepancy correction via distance balance and quantile regression for automatic coronary artery segmentation of angiography images. The proposed method can not only segment overlapping vascular structures robustly, but also achieve good performance in low contrast regions. The effectiveness of our approach is demonstrated on a variety of coronary blood vessels compared with the existing methods. The overall segmentation performances si, fnvf, fvpf and tpvf were 95.135%, 3.733%, 6.113%, 96.268%, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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.

Low QRS Voltage on Presenting Electrocardiogram Predicts Multi-vessel Disease in Anterior ST-segment Elevation Myocardial Infarction.

Science.gov (United States)

Kobayashi, Akihiro; Misumida, Naoki; Aoi, Shunsuke; Kanei, Yumiko

Low QRS voltage was reported to predict adverse outcomes in acute myocardial infarction in the pre-thrombolytic era. However, the association between low voltage and angiographic findings has not been fully addressed. We performed a retrospective analysis of patients with anterior ST-segment elevation myocardial infarction (STEMI). Low QRS voltage was defined as either peak to peak QRS complex voltage voltage. Patients with low voltage had a higher rate of multi-vessel disease (MVD) (76% vs. 52%, p=0.01). Patients with low voltage were more likely to undergo coronary artery bypass grafting (CABG) during admission (11% vs. 2%, p=0.028). Low voltage was an independent predictor for MVD (OR 2.50; 95% CI 1.12 to 6.03; p=0.032). Low QRS voltage was associated with MVD and in-hospital CABG in anterior STEMI. Copyright © 2017 Elsevier Inc. All rights reserved.

Automatic evaluation of vessel diameter variation from 2D X-ray angiography.

Science.gov (United States)

M'hiri, Faten; Duong, Luc; Desrosiers, Christian; Dahdah, Nagib; Miró, Joaquim; Cheriet, Mohamed

2017-11-01

Early detection of blood vessel pathologies can be made through the evaluation of functional and structural abnormalities in the arteries, including the arterial distensibility measure. We propose a feasibility study on computing arterial distensibility automatically from monoplane 2D X-ray sequences for both small arteries (such as coronary arteries) and larger arteries (such as the aorta). To compute the distensibility measure, three steps were developed: First, the segment of an artery is extracted using our graph-based segmentation method. Then, the same segment is tracked in the moving sequence using our spatio-temporal segmentation method: the Temporal Vessel Walker. Finally, the diameter of the artery is measured automatically at each frame of the sequence based on the segmentation results. The method was evaluated using one simulated sequence and 4 patients' angiograms depicting the coronary arteries and three depicting the ascending aorta. Results of the simulated sequence achieved a Dice index of 98%, with a mean squared error in diameter measurement of [Formula: see text] mm. Results obtained from patients' X-ray sequences are consistent with manual assessment of the diameter by experts. The proposed method measures changes in diameter of a specific segment of a blood vessel during the cardiac sequence, automatically based on monoplane 2D X-ray sequence. Such information might become a key to help physicians in the detection of variations of arterial stiffness associated with early stages of various vasculopathies.

Definition of AVM nidus for radiosurgery using segmentation tools

International Nuclear Information System (INIS)

Baker, E.H.; Mehta, M.P.; Sorenson, J.A.

1995-01-01

Purpose/Objective: The complex 3-D anatomy of an AVM nidus is very difficult to appreciate and reconstruct using conventional angiography. MR angiography (MRA) is increasingly being utilized to assist in better defining the nidus. There is, however, considerable operator-dependent bias in determining the true extent of the nidus, with any imaging technique. The generic problem of dividing an image into meaningful regions is known as image segmentation. We have developed several image segmentation tools for our 3-D treatment planning software and have applied these tools to attempt to improve nidus localization. Materials and Methods: Five AVM patients from our archives who had both MRI and MRA images prior to radiosurgery were evaluated. These patients were studied with a spin-echo sequence with density-weighted anatomical images of the entire brain and a time-of-flight (TOF) sequence with vascular images of the AVM. The density-weighted images have good contrast among stationary tissues such as grey matter and white matter, but all vessels are black 'flow voids'. On the TOF images, vessels have a signal that is roughly proportional to the velocity of the flow within them; fast-moving blood is very bright, while slow-moving blood is similar to stationary tissues. By applying segmentation techniques to registered image sets, we were able to use information in density-weighted images to distinguish vessels from non-vessels, and information in TOF images to distinguish fast-flowing blood in the feeder vessels from slower-flowing blood in the nidus. Results: Since this work is in progress, image acquisition parameters varied, and some TOF images had poor signal-to-noise. In spite of this, we were able to segment the AVM nidus in all cases and display it in a readily-distinguishable manner. The nidus velocity appeared to be moderate in three cases, mixed in one, and slow in another. In the latter case, the slow velocity produced some overlap with draining veins. In all

Inferior vena cava segmentation with parameter propagation and graph cut.

Science.gov (United States)

Yan, Zixu; Chen, Feng; Wu, Fa; Kong, Dexing

2017-09-01

The inferior vena cava (IVC) is one of the vital veins inside the human body. Accurate segmentation of the IVC from contrast-enhanced CT images is of great importance. This extraction not only helps the physician understand its quantitative features such as blood flow and volume, but also it is helpful during the hepatic preoperative planning. However, manual delineation of the IVC is time-consuming and poorly reproducible. In this paper, we propose a novel method to segment the IVC with minimal user interaction. The proposed method performs the segmentation block by block between user-specified beginning and end masks. At each stage, the proposed method builds the segmentation model based on information from image regional appearances, image boundaries, and a prior shape. The intensity range and the prior shape for this segmentation model are estimated based on the segmentation result from the last block, or from user- specified beginning mask if at first stage. Then, the proposed method minimizes the energy function and generates the segmentation result for current block using graph cut. Finally, a backward tracking step from the end of the IVC is performed if necessary. We have tested our method on 20 clinical datasets and compared our method to three other vessel extraction approaches. The evaluation was performed using three quantitative metrics: the Dice coefficient (Dice), the mean symmetric distance (MSD), and the Hausdorff distance (MaxD). The proposed method has achieved a Dice of [Formula: see text], an MSD of [Formula: see text] mm, and a MaxD of [Formula: see text] mm, respectively, in our experiments. The proposed approach can achieve a sound performance with a relatively low computational cost and a minimal user interaction. The proposed algorithm has high potential to be applied for the clinical applications in the future.

Automated segmentation of geographic atrophy using deep convolutional neural networks

Science.gov (United States)

Hu, Zhihong; Wang, Ziyuan; Sadda, SriniVas R.

2018-02-01

Geographic atrophy (GA) is an end-stage manifestation of the advanced age-related macular degeneration (AMD), the leading cause of blindness and visual impairment in developed nations. Techniques to rapidly and precisely detect and quantify GA would appear to be of critical importance in advancing the understanding of its pathogenesis. In this study, we develop an automated supervised classification system using deep convolutional neural networks (CNNs) for segmenting GA in fundus autofluorescene (FAF) images. More specifically, to enhance the contrast of GA relative to the background, we apply the contrast limited adaptive histogram equalization. Blood vessels may cause GA segmentation errors due to similar intensity level to GA. A tensor-voting technique is performed to identify the blood vessels and a vessel inpainting technique is applied to suppress the GA segmentation errors due to the blood vessels. To handle the large variation of GA lesion sizes, three deep CNNs with three varying sized input image patches are applied. Fifty randomly chosen FAF images are obtained from fifty subjects with GA. The algorithm-defined GA regions are compared with manual delineation by a certified grader. A two-fold cross-validation is applied to evaluate the algorithm performance. The mean segmentation accuracy, true positive rate (i.e. sensitivity), true negative rate (i.e. specificity), positive predictive value, false discovery rate, and overlap ratio, between the algorithm- and manually-defined GA regions are 0.97 +/- 0.02, 0.89 +/- 0.08, 0.98 +/- 0.02, 0.87 +/- 0.12, 0.13 +/- 0.12, and 0.79 +/- 0.12 respectively, demonstrating a high level of agreement.

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

Science.gov (United States)

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

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

Energy Technology Data Exchange (ETDEWEB)

Beichel, Reinhard R., E-mail: reinhard-beichel@uiowa.edu [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Internal Medicine, University of Iowa, Iowa City, Iowa 52242 (United States); Van Tol, Markus; Ulrich, Ethan J.; Bauer, Christian [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa 52242 (United States); Chang, Tangel; Plichta, Kristin A. [Department of Radiation Oncology, University of Iowa, Iowa City, Iowa 52242 (United States); Smith, Brian J. [Department of Biostatistics, University of Iowa, Iowa City, Iowa 52242 (United States); Sunderland, John J.; Graham, Michael M. [Department of Radiology, University of Iowa, Iowa City, Iowa 52242 (United States); Sonka, Milan [Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Radiation Oncology, The University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Buatti, John M. [Department of Radiation Oncology, University of Iowa, Iowa City, Iowa 52242 (United States); Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States)

2016-06-15

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

Design features of the KSTAR in-vessel control coils

Energy Technology Data Exchange (ETDEWEB)

Kim, H.K. [National Fusion Research Institute (NFRI), 52 Yeoeun-dong, Yusung-ku, Daejeon, 305-333 (Korea, Republic of)], E-mail: hkkim@nfri.re.kr; Yang, H.L.; Kim, G.H.; Kim, Jin-Yong; Jhang, Hogun; Bak, J.S.; Lee, G.S. [National Fusion Research Institute (NFRI), 52 Yeoeun-dong, Yusung-ku, Daejeon, 305-333 (Korea, Republic of)

2009-06-15

In-vessel control coils (IVCCs) are to be used for the fast plasma position control, field error correction (FEC), and resistive wall mode (RWM) stabilization for the Korea Superconducting Tokamak Advanced Research (KSTAR) device. The IVCC system comprises 16 segments to be unified into a single set to achieve following remarkable engineering advantages; (1) enhancement of the coil system reliability with no welding or brazing works inside the vacuum vessel, (2) simplification in fabrication and installation owing to coils being fabricated outside the vacuum vessel and installed after device assembly, and (3) easy repair and maintenance of the coil system. Each segment is designed in 8 turns coil of 32 mm x 15 mm rectangular oxygen free high conductive copper with a 7 mm diameter internal coolant hole. The conductors are enclosed in 2 mm thick Inconel 625 rectangular welded vacuum jacket with epoxy/glass insulation. Structural analyses were implemented to evaluate structural safety against electromagnetic loads acting on the IVCC for the various operation scenarios using finite element analysis. This paper describes the design features and structural analysis results of the KSTAR in-vessel control coils.

An argument for the use of multiple segment stents in curved arteries.

Science.gov (United States)

Kasiri, Saeid; Kelly, Daniel J

2011-08-01

Stenting of curved arteries is generally perceived to be more challenging than straight vessels. Conceptually implanting multiple shorter stents rather than a single longer stent into such a curved artery represents a promising concept, but little is known about the impact of such an approach. The objective of this study is to evaluate the effectiveness of using a multiple segment stent rather than a single long stent to dilate a curved artery using the finite element method. A double segment stent (DSS) and a single segment stent (SSS) were modeled. The stents were compared when expanded into a model of a curved artery. The model predicts that the DSS provides higher flexibility, more conformity, and lower recoil in comparison to the SSS. The volume of arterial tissue experiencing high levels of stress due to stent implantation is also reduced for the DSS. It is suggested that a multiple segment stenting system is a potential solution to the problem of higher rates of in-stent restenosis in curved arteries and mechanically challenging environments.

Spectral-spatial classification of hyperspectral data with mutual information based segmented stacked autoencoder approach

Science.gov (United States)

Paul, Subir; Nagesh Kumar, D.

2018-04-01

Hyperspectral (HS) data comprises of continuous spectral responses of hundreds of narrow spectral bands with very fine spectral resolution or bandwidth, which offer feature identification and classification with high accuracy. In the present study, Mutual Information (MI) based Segmented Stacked Autoencoder (S-SAE) approach for spectral-spatial classification of the HS data is proposed to reduce the complexity and computational time compared to Stacked Autoencoder (SAE) based feature extraction. A non-parametric dependency measure (MI) based spectral segmentation is proposed instead of linear and parametric dependency measure to take care of both linear and nonlinear inter-band dependency for spectral segmentation of the HS bands. Then morphological profiles are created corresponding to segmented spectral features to assimilate the spatial information in the spectral-spatial classification approach. Two non-parametric classifiers, Support Vector Machine (SVM) with Gaussian kernel and Random Forest (RF) are used for classification of the three most popularly used HS datasets. Results of the numerical experiments carried out in this study have shown that SVM with a Gaussian kernel is providing better results for the Pavia University and Botswana datasets whereas RF is performing better for Indian Pines dataset. The experiments performed with the proposed methodology provide encouraging results compared to numerous existing approaches.

AN ADAPTIVE APPROACH FOR SEGMENTATION OF 3D LASER POINT CLOUD

Directory of Open Access Journals (Sweden)

Z. Lari

2012-09-01

Full Text Available Automatic processing and object extraction from 3D laser point cloud is one of the major research topics in the field of photogrammetry. Segmentation is an essential step in the processing of laser point cloud, and the quality of extracted objects from laser data is highly dependent on the validity of the segmentation results. This paper presents a new approach for reliable and efficient segmentation of planar patches from a 3D laser point cloud. In this method, the neighbourhood of each point is firstly established using an adaptive cylinder while considering the local point density and surface trend. This neighbourhood definition has a major effect on the computational accuracy of the segmentation attributes. In order to efficiently cluster planar surfaces and prevent introducing ambiguities, the coordinates of the origin's projection on each point's best fitted plane are used as the clustering attributes. Then, an octree space partitioning method is utilized to detect and extract peaks from the attribute space. Each detected peak represents a specific cluster of points which are located on a distinct planar surface in the object space. Experimental results show the potential and feasibility of applying this method for segmentation of both airborne and terrestrial laser data.

Filling Landsat ETM+ SLC-off gaps using a segmentation model approach

Science.gov (United States)

Maxwell, Susan

2004-01-01

The purpose of this article is to present a methodology for filling Landsat Scan Line Corrector (SLC)-off gaps with same-scene spectral data guided by a segmentation model. Failure of the SLC on the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument resulted in a loss of approximately 25 percent of the spectral data. The missing data span across most of the image with scan gaps varying in size from two pixels near the center of the image to 14 pixels along the east and west edges. Even with the scan gaps, the radiometric and geometric qualities of the remaining portions of the image still meet design specifications and therefore contain useful information (see http:// landsat7.usgs.gov for additional information). The U.S. Geological Survey EROS Data Center (EDC) is evaluating several techniques to fill the gaps in SLC-off data to enhance the usability of the imagery (Howard and Lacasse 2004) (PE&RS, August 2004). The method presented here uses a segmentation model approach that allows for same-scene spectral data to be used to fill the gaps. The segment model is generated from a complete satellite image with no missing spectral data (e.g., Landsat 5, Landsat 7 SLCon, SPOT). The model is overlaid on the Landsat SLC-off image, and the missing data within the gaps are then estimated using SLC-off spectral data that intersect the segment boundary. A major advantage of this approach is that the gaps are filled using spectral data derived from the same SLC-off satellite image.

A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images

Directory of Open Access Journals (Sweden)

Yaozhong Luo

2017-01-01

Full Text Available Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality. In this paper, we propose a new segmentation scheme to combine both region- and edge-based information into the robust graph-based (RGB segmentation method. The only interaction required is to select two diagonal points to determine a region of interest (ROI on the original image. The ROI image is smoothed by a bilateral filter and then contrast-enhanced by histogram equalization. Then, the enhanced image is filtered by pyramid mean shift to improve homogeneity. With the optimization of particle swarm optimization (PSO algorithm, the RGB segmentation method is performed to segment the filtered image. The segmentation results of our method have been compared with the corresponding results obtained by three existing approaches, and four metrics have been used to measure the segmentation performance. The experimental results show that the method achieves the best overall performance and gets the lowest ARE (10.77%, the second highest TPVF (85.34%, and the second lowest FPVF (4.48%.

A variational approach to liver segmentation using statistics from multiple sources

Science.gov (United States)

Zheng, Shenhai; Fang, Bin; Li, Laquan; Gao, Mingqi; Wang, Yi

2018-01-01

Medical image segmentation plays an important role in digital medical research, and therapy planning and delivery. However, the presence of noise and low contrast renders automatic liver segmentation an extremely challenging task. In this study, we focus on a variational approach to liver segmentation in computed tomography scan volumes in a semiautomatic and slice-by-slice manner. In this method, one slice is selected and its connected component liver region is determined manually to initialize the subsequent automatic segmentation process. From this guiding slice, we execute the proposed method downward to the last one and upward to the first one, respectively. A segmentation energy function is proposed by combining the statistical shape prior, global Gaussian intensity analysis, and enforced local statistical feature under the level set framework. During segmentation, the shape of the liver shape is estimated by minimization of this function. The improved Chan-Vese model is used to refine the shape to capture the long and narrow regions of the liver. The proposed method was verified on two independent public databases, the 3D-IRCADb and the SLIVER07. Among all the tested methods, our method yielded the best volumetric overlap error (VOE) of 6.5 +/- 2.8 % , the best root mean square symmetric surface distance (RMSD) of 2.1 +/- 0.8 mm, the best maximum symmetric surface distance (MSD) of 18.9 +/- 8.3 mm in 3D-IRCADb dataset, and the best average symmetric surface distance (ASD) of 0.8 +/- 0.5 mm, the best RMSD of 1.5 +/- 1.1 mm in SLIVER07 dataset, respectively. The results of the quantitative comparison show that the proposed liver segmentation method achieves competitive segmentation performance with state-of-the-art techniques.

Computerized analysis of coronary artery disease: Performance evaluation of segmentation and tracking of coronary arteries in CT angiograms

Energy Technology Data Exchange (ETDEWEB)

Zhou, Chuan, E-mail: chuan@umich.edu; Chan, Heang-Ping; Chughtai, Aamer; Kuriakose, Jean; Agarwal, Prachi; Kazerooni, Ella A.; Hadjiiski, Lubomir M.; Patel, Smita; Wei, Jun [Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109 (United States)

2014-08-15

Purpose: The authors are developing a computer-aided detection system to assist radiologists in analysis of coronary artery disease in coronary CT angiograms (cCTA). This study evaluated the accuracy of the authors’ coronary artery segmentation and tracking method which are the essential steps to define the search space for the detection of atherosclerotic plaques. Methods: The heart region in cCTA is segmented and the vascular structures are enhanced using the authors’ multiscale coronary artery response (MSCAR) method that performed 3D multiscale filtering and analysis of the eigenvalues of Hessian matrices. Starting from seed points at the origins of the left and right coronary arteries, a 3D rolling balloon region growing (RBG) method that adapts to the local vessel size segmented and tracked each of the coronary arteries and identifies the branches along the tracked vessels. The branches are queued and subsequently tracked until the queue is exhausted. With Institutional Review Board approval, 62 cCTA were collected retrospectively from the authors’ patient files. Three experienced cardiothoracic radiologists manually tracked and marked center points of the coronary arteries as reference standard following the 17-segment model that includes clinically significant coronary arteries. Two radiologists visually examined the computer-segmented vessels and marked the mistakenly tracked veins and noisy structures as false positives (FPs). For the 62 cases, the radiologists marked a total of 10191 center points on 865 visible coronary artery segments. Results: The computer-segmented vessels overlapped with 83.6% (8520/10191) of the center points. Relative to the 865 radiologist-marked segments, the sensitivity reached 91.9% (795/865) if a true positive is defined as a computer-segmented vessel that overlapped with at least 10% of the reference center points marked on the segment. When the overlap threshold is increased to 50% and 100%, the sensitivities were 86

Performance Analysis of Segmentation of Hyperspectral Images Based on Color Image Segmentation

Directory of Open Access Journals (Sweden)

Praveen Agarwal

2017-06-01

Full Text Available Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without texture. The final segmentation is simply achieved by a spatially color segmentation using feature vector with the set of color values contained around the pixel to be classified with some mathematical equations. The spatial constraint allows taking into account the inherent spatial relationships of any image and its color. This approach provides effective PSNR for the segmented image. These results have the better performance as the segmented images are compared with Watershed & Region Growing Algorithm and provide effective segmentation for the Spectral Images & Medical Images.

Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing

2011-01-01

We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.

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

Science.gov (United States)

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

2016-04-01

Atlas-based segmentation is a powerful method for automatic structural segmentation of several sub-structures in many organs. However, such an approach has been very scarcely used in the context of muscle segmentation, and so far no study has assessed such a method for the automatic delineation of individual muscles of the quadriceps femoris (QF). In the present study, we have evaluated a fully automated multi-atlas method and a semi-automated single-atlas method for the segmentation and volume quantification of the four muscles of the QF and for the QF as a whole. The study was conducted in 32 young healthy males, using high-resolution magnetic resonance images (MRI) of the thigh. The multi-atlas-based segmentation method was conducted in 25 subjects. Different non-linear registration approaches based on free-form deformable (FFD) and symmetric diffeomorphic normalization algorithms (SyN) were assessed. Optimal parameters of two fusion methods, i.e., STAPLE and STEPS, were determined on the basis of the highest Dice similarity index (DSI) considering manual segmentation (MSeg) as the ground truth. Validation and reproducibility of this pipeline were determined using another MRI dataset recorded in seven healthy male subjects on the basis of additional metrics such as the muscle volume similarity values, intraclass coefficient, and coefficient of variation. Both non-linear registration methods (FFD and SyN) were also evaluated as part of a single-atlas strategy in order to assess longitudinal muscle volume measurements. The multi- and the single-atlas approaches were compared for the segmentation and the volume quantification of the four muscles of the QF and for the QF as a whole. Considering each muscle of the QF, the DSI of the multi-atlas-based approach was high 0.87 ± 0.11 and the best results were obtained with the combination of two deformation fields resulting from the SyN registration method and the STEPS fusion algorithm. The optimal variables for FFD

Active Segmentation.

Science.gov (United States)

Mishra, Ajay; Aloimonos, Yiannis

2009-01-01

The human visual system observes and understands a scene/image by making a series of fixations. Every fixation point lies inside a particular region of arbitrary shape and size in the scene which can either be an object or just a part of it. We define as a basic segmentation problem the task of segmenting that region containing the fixation point. Segmenting the region containing the fixation is equivalent to finding the enclosing contour- a connected set of boundary edge fragments in the edge map of the scene - around the fixation. This enclosing contour should be a depth boundary.We present here a novel algorithm that finds this bounding contour and achieves the segmentation of one object, given the fixation. The proposed segmentation framework combines monocular cues (color/intensity/texture) with stereo and/or motion, in a cue independent manner. The semantic robots of the immediate future will be able to use this algorithm to automatically find objects in any environment. The capability of automatically segmenting objects in their visual field can bring the visual processing to the next level. Our approach is different from current approaches. While existing work attempts to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Experiments with real imagery collected by our active robot and from the known databases 1 demonstrate the promise of the approach.

A method for smoothing segmented lung boundary in chest CT images

Science.gov (United States)

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.

Pancreas and cyst segmentation

Science.gov (United States)

Dmitriev, Konstantin; Gutenko, Ievgeniia; Nadeem, Saad; Kaufman, Arie

2016-03-01

Accurate segmentation of abdominal organs from medical images is an essential part of surgical planning and computer-aided disease diagnosis. Many existing algorithms are specialized for the segmentation of healthy organs. Cystic pancreas segmentation is especially challenging due to its low contrast boundaries, variability in shape, location and the stage of the pancreatic cancer. We present a semi-automatic segmentation algorithm for pancreata with cysts. In contrast to existing automatic segmentation approaches for healthy pancreas segmentation which are amenable to atlas/statistical shape approaches, a pancreas with cysts can have even higher variability with respect to the shape of the pancreas due to the size and shape of the cyst(s). Hence, fine results are better attained with semi-automatic steerable approaches. We use a novel combination of random walker and region growing approaches to delineate the boundaries of the pancreas and cysts with respective best Dice coefficients of 85.1% and 86.7%, and respective best volumetric overlap errors of 26.0% and 23.5%. Results show that the proposed algorithm for pancreas and pancreatic cyst segmentation is accurate and stable.

Validation of a model of left ventricular segmentation for interpretation of SPET myocardial perfusion images

Energy Technology Data Exchange (ETDEWEB)

Aepfelbacher, F.C.; Johnson, R.B.; Schwartz, J.G.; Danias, P.G. [Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States); Chen, L.; Parker, R.A. [Biometrics Center, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States); Parker, A.J. [Nuclear Medicine Division, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States)

2001-11-01

Several models of left ventricular segmentation have been developed that assume a standard coronary artery distribution, and are currently used for interpretation of single-photon emission tomography (SPET) myocardial perfusion imaging. This approach has the potential for incorrect assignment of myocardial segments to vascular territories, possibly over- or underestimating the number of vessels with significant coronary artery disease (CAD). We therefore sought to validate a 17-segment model of myocardial perfusion by comparing the predefined coronary territory assignment with the actual angiographically derived coronary distribution. We examined 135 patients who underwent both coronary angiography and stress SPET imaging within 30 days. Individualized coronary distribution was determined by review of the coronary angiograms and used to identify the coronary artery supplying each of the 17 myocardial segments of the model. The actual coronary distribution was used to assess the accuracy of the assumed coronary distribution of the model. The sensitivities and specificities of stress SPET for detection of CAD in individual coronary arteries and the classification regarding perceived number of diseased coronary arteries were also compared between the two coronary distributions (actual and assumed). The assumed coronary distribution corresponded to the actual coronary anatomy in all but one segment (3). The majority of patients (80%) had 14 or more concordant segments. Sensitivities and specificities of stress SPET for detection of CAD in the coronary territories were similar, with the exception of the RCA territory, for which specificity for detection of CAD was better for the angiographically derived coronary artery distribution than for the model. There was 95% agreement between assumed and angiographically derived coronary distributions in classification to single- versus multi-vessel CAD. Reassignment of a single segment (segment 3) from the LCX to the LAD

Validation of a model of left ventricular segmentation for interpretation of SPET myocardial perfusion images

International Nuclear Information System (INIS)

Aepfelbacher, F.C.; Johnson, R.B.; Schwartz, J.G.; Danias, P.G.; Chen, L.; Parker, R.A.; Parker, A.J.

2001-01-01

Several models of left ventricular segmentation have been developed that assume a standard coronary artery distribution, and are currently used for interpretation of single-photon emission tomography (SPET) myocardial perfusion imaging. This approach has the potential for incorrect assignment of myocardial segments to vascular territories, possibly over- or underestimating the number of vessels with significant coronary artery disease (CAD). We therefore sought to validate a 17-segment model of myocardial perfusion by comparing the predefined coronary territory assignment with the actual angiographically derived coronary distribution. We examined 135 patients who underwent both coronary angiography and stress SPET imaging within 30 days. Individualized coronary distribution was determined by review of the coronary angiograms and used to identify the coronary artery supplying each of the 17 myocardial segments of the model. The actual coronary distribution was used to assess the accuracy of the assumed coronary distribution of the model. The sensitivities and specificities of stress SPET for detection of CAD in individual coronary arteries and the classification regarding perceived number of diseased coronary arteries were also compared between the two coronary distributions (actual and assumed). The assumed coronary distribution corresponded to the actual coronary anatomy in all but one segment (3). The majority of patients (80%) had 14 or more concordant segments. Sensitivities and specificities of stress SPET for detection of CAD in the coronary territories were similar, with the exception of the RCA territory, for which specificity for detection of CAD was better for the angiographically derived coronary artery distribution than for the model. There was 95% agreement between assumed and angiographically derived coronary distributions in classification to single- versus multi-vessel CAD. Reassignment of a single segment (segment 3) from the LCX to the LAD

Evaluation of multimodal segmentation based on 3D T1-, T2- and FLAIR-weighted images - the difficulty of choosing.

Science.gov (United States)

Lindig, Tobias; Kotikalapudi, Raviteja; Schweikardt, Daniel; Martin, Pascal; Bender, Friedemann; Klose, Uwe; Ernemann, Ulrike; Focke, Niels K; Bender, Benjamin

2018-04-15

Voxel-based morphometry is still mainly based on T1-weighted MRI scans. Misclassification of vessels and dura mater as gray matter has been previously reported. Goal of the present work was to evaluate the effect of multimodal segmentation methods available in SPM12, and their influence on identification of age related atrophy and lesion detection in epilepsy patients. 3D T1-, T2- and FLAIR-images of 77 healthy adults (mean age 35.8 years, 19-66 years, 45 females), 7 patients with malformation of cortical development (MCD) (mean age 28.1 years,19-40 years, 3 females), and 5 patients with left hippocampal sclerosis (LHS) (mean age 49.0 years, 25-67 years, 3 females) from a 3T scanner were evaluated. Segmentation based on T1-only, T1+T2, T1+FLAIR, T2+FLAIR, and T1+T2+FLAIR were compared in the healthy subjects. Clinical VBM results based on the different segmentation approaches for MCD and for LHS were compared. T1-only segmentation overestimated total intracranial volume by about 80ml compared to the other segmentation methods. This was due to misclassification of dura mater and vessels as GM and CSF. Significant differences were found for several anatomical regions: the occipital lobe, the basal ganglia/thalamus, the pre- and postcentral gyrus, the cerebellum, and the brainstem. None of the segmentation methods yielded completely satisfying results for the basal ganglia/thalamus and the brainstem. The best correlation with age could be found for the multimodal T1+T2+FLAIR segmentation. Highest T-scores for identification of LHS were found for T1+T2 segmentation, while highest T-scores for MCD were dependent on lesion and anatomical location. Multimodal segmentation is superior to T1-only segmentation and reduces the misclassification of dura mater and vessels as GM and CSF. Depending on the anatomical region and the pathology of interest (atrophy, lesion detection, etc.), different combinations of T1, T2 and FLAIR yield optimal results. Copyright © 2017 Elsevier

Optimization Approach for Multi-scale Segmentation of Remotely Sensed Imagery under k-means Clustering Guidance

Directory of Open Access Journals (Sweden)

WANG Huixian

2015-05-01

Full Text Available In order to adapt different scale land cover segmentation, an optimized approach under the guidance of k-means clustering for multi-scale segmentation is proposed. At first, small scale segmentation and k-means clustering are used to process the original images; then the result of k-means clustering is used to guide objects merging procedure, in which Otsu threshold method is used to automatically select the impact factor of k-means clustering; finally we obtain the segmentation results which are applicable to different scale objects. FNEA method is taken for an example and segmentation experiments are done using a simulated image and a real remote sensing image from GeoEye-1 satellite, qualitative and quantitative evaluation demonstrates that the proposed method can obtain high quality segmentation results.

Endovascular Treatment of a Splenic Aneurysm Associated With Segmental Arterial Mediolysis

Directory of Open Access Journals (Sweden)

A. Khan

Full Text Available : Introduction: Segmental arterial mediolysis is a rare disorder characterised by disintegration of the medial layer of an arterial wall usually affecting the intra-abdominal splanchnic vessels. Report: A case of 50 year old man who presented with sudden-onset left sided flank pain is reported. A computed tomography mesenteric angiogram showed haemorrhage and a stable left upper quadrant haematoma arising from 8 × 8 mm splenic artery aneurysm. Discussion: The patient underwent a successful endovascular coiling procedure to exclude the aneurysm and for complete resolution of his symptoms. Keywords: Segmental arterial mediolysis, Splanchnic vessels, Splenic artery aneurysm

THE ALGORITHM OF DETERMINATION OF EYE FUNDUS VESSELS BLOOD FLOW CHARACTERISTICS ON VIDEOSEQUENCE

Directory of Open Access Journals (Sweden)

O. V. Nedzvedz

2018-01-01

Full Text Available The method of determination of the dynamic characteristics like the vessel diameter change, the linear and volume blood velocities in the vessels of the eye fundus is considered. Such characteristics allow to determine blood flow changes in the microvasculature affecting the blood flow in the brain, kidneys and coronary vessels. Developed algorithm includes four stages: the video sequence stabilization, the vessels segmentation with the help of a neural network, the determination of the instantaneous velocity in the vessels based on the optical flow and the analysis of the results.

Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

NARCIS (Netherlands)

Weijers, G.; Starke, A.; Haudum, A.; Thijssen, J.M.; Rehage, J.; Korte, C.L. de

2010-01-01

The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty

Emergency disconnect means for the manipulator arm of a nuclear reactor vessel inspection apparatus

International Nuclear Information System (INIS)

Jacobs, F.; Morris, D.W.

1980-01-01

An emergency disconnect means is disclosed for uncoupling a portion of the linkage means which connects the several segments of an articulating manipulator arm employed in a nuclear reactor vessel inspection device. One of the motor housings included in the manipulator arm's segmented drive train is pivotably coupled between two segments thereof. In the event of power failure or the necessity of manual retraction of the manipulator arm from within the vessel, a lever is manually operated and moved from its normally locked position wherein the motor housing is positionally fixed to a release position wherein the motor housing and the remainder of the manipulator arm segments connected forwardly thereof are pivotally released to shorten the normal arm reach and alter the normal orientation of the manipulator arm to expedite removal without danger of collision. (auth)

The irradiation embrittlement of two pressure vessel steels -Contribution of local approach

Energy Technology Data Exchange (ETDEWEB)

Soulat, P; Marini, B [CEA Centre d` Etudes Nucleaires de Saclay, 91 - Gif-sur-Yvette (France). Service de Recherches Metallurgiques Appliquees; Miannay, D; Horowitz, H [CEA Centre d` Etudes de Fontenay-aux-Roses, 92 (France). Inst. de Protection et de Surete Nucleaire; Schill, R [CEA Centre d` Etudes de Saclay, 91 - Gif-sur-Yvette (France). Dept. de Mecanique et de Technologie

1994-12-31

Within the IAEA Coordinated Research Programme on ``Optimizing the Reactor Pressure Vessel Surveillance Programmes and their Analyses``, the French participation has been focused on the contribution of the local approach to the determination of the sensitivity to radiation embrittlement of two different pressure vessel steels: a low sensitive French forging steel (FFA) and a high sensitive ``monitor`` Japanese plate steel (JRQ) were irradiated to a fluence of 3.10{sup 19} n/cm{sup 2} at 290 C. The irradiation embrittlement of the two steels measured by the shift of Charpy V transition curves is in good agreement with the estimated shifts given by theoretical prediction. The fracture toughness properties were examined at low temperature with brittle fracture, and at service temperature (290 C), with ductile tearing. The values of K{sub 1C} or K{sub JC} for the brittle fracture and J{sub 1C} for the ductile fracture are compared to predictions established using the local approach of cleavage fracture (Weibull analysis) and the critical rate of void growth respectively. 8 refs., 14 figs., 10 tabs.

A combined approach for the enhancement and segmentation of mammograms using modified fuzzy C-means method in wavelet domain.

Science.gov (United States)

Srivastava, Subodh; Sharma, Neeraj; Singh, S K; Srivastava, R

2014-07-01

In this paper, a combined approach for enhancement and segmentation of mammograms is proposed. In preprocessing stage, a contrast limited adaptive histogram equalization (CLAHE) method is applied to obtain the better contrast mammograms. After this, the proposed combined methods are applied. In the first step of the proposed approach, a two dimensional (2D) discrete wavelet transform (DWT) is applied to all the input images. In the second step, a proposed nonlinear complex diffusion based unsharp masking and crispening method is applied on the approximation coefficients of the wavelet transformed images to further highlight the abnormalities such as micro-calcifications, tumours, etc., to reduce the false positives (FPs). Thirdly, a modified fuzzy c-means (FCM) segmentation method is applied on the output of the second step. In the modified FCM method, the mutual information is proposed as a similarity measure in place of conventional Euclidian distance based dissimilarity measure for FCM segmentation. Finally, the inverse 2D-DWT is applied. The efficacy of the proposed unsharp masking and crispening method for image enhancement is evaluated in terms of signal-to-noise ratio (SNR) and that of the proposed segmentation method is evaluated in terms of random index (RI), global consistency error (GCE), and variation of information (VoI). The performance of the proposed segmentation approach is compared with the other commonly used segmentation approaches such as Otsu's thresholding, texture based, k-means, and FCM clustering as well as thresholding. From the obtained results, it is observed that the proposed segmentation approach performs better and takes lesser processing time in comparison to the standard FCM and other segmentation methods in consideration.

Segmentation of Lung Structures in CT

DEFF Research Database (Denmark)

Lo, Pechin Chien Pau

This thesis proposes and evaluates new algorithms for segmenting various lung structures in computed tomography (CT) images, namely the lungs, airway trees and vessel trees. The main objective of these algorithms is to facilitate a better platform for studying Chronic Obstructive Pulmonary Disease......, 200 randomly selected CT scans were manually evaluated by medical experts, and only negligible or minor errors were found in nine scans. The proposed algorithm has been used to study how changes in smoking behavior affect CT based emphysema quantification. The algorithms for segmenting the airway...

A fourth order PDE based fuzzy c- means approach for segmentation of microscopic biopsy images in presence of Poisson noise for cancer detection.

Science.gov (United States)

Kumar, Rajesh; Srivastava, Subodh; Srivastava, Rajeev

2017-07-01

For cancer detection from microscopic biopsy images, image segmentation step used for segmentation of cells and nuclei play an important role. Accuracy of segmentation approach dominate the final results. Also the microscopic biopsy images have intrinsic Poisson noise and if it is present in the image the segmentation results may not be accurate. The objective is to propose an efficient fuzzy c-means based segmentation approach which can also handle the noise present in the image during the segmentation process itself i.e. noise removal and segmentation is combined in one step. To address the above issues, in this paper a fourth order partial differential equation (FPDE) based nonlinear filter adapted to Poisson noise with fuzzy c-means segmentation method is proposed. This approach is capable of effectively handling the segmentation problem of blocky artifacts while achieving good tradeoff between Poisson noise removals and edge preservation of the microscopic biopsy images during segmentation process for cancer detection from cells. The proposed approach is tested on breast cancer microscopic biopsy data set with region of interest (ROI) segmented ground truth images. The microscopic biopsy data set contains 31 benign and 27 malignant images of size 896 × 768. The region of interest selected ground truth of all 58 images are also available for this data set. Finally, the result obtained from proposed approach is compared with the results of popular segmentation algorithms; fuzzy c-means, color k-means, texture based segmentation, and total variation fuzzy c-means approaches. The experimental results shows that proposed approach is providing better results in terms of various performance measures such as Jaccard coefficient, dice index, Tanimoto coefficient, area under curve, accuracy, true positive rate, true negative rate, false positive rate, false negative rate, random index, global consistency error, and variance of information as compared to other

Novel Therapy for Bone Regeneration in Large Segmental Defects

Science.gov (United States)

2017-12-01

can maintain bone length and allow successfully regeneration in segmental defects. r 2006 Elsevier Ltd. All rights reserved. Keywords: Bone...pre- formed endothelial networks, as the MSCs can act as pericytes to the newly formed blood vessels. Pirraco et al. [159] also cultured ECs and...AWARD NUMBER: W81XWH-13-1-0407 TITLE: Novel Therapy for Bone Regeneration in Large Segmental Defects PRINCIPAL INVESTIGATOR: Melissa Kacena

Civacuve analysis software for mis machine examination of pressurized water reactor vessels

International Nuclear Information System (INIS)

Dubois, Ph.; Gagnor, A.

2001-01-01

The product software CIVACUVE is used by INTERCONTROLE for the analysis of UT examinations, for detection, performed by the In-Service Inspection Machine (MIS) of the vessels of nuclear power plants. This software is based on an adaptation of an algorithm of SEGMENTATION (CEA CEREM), which is applied prior to any analysis. It is equipped with tools adapted to industrial use. It allows to: - perform image analysis thanks to advanced graphic tools (Zooms, True Bscan, 'contour' selection...), - backup of all data in a database (complete and transparent backup of all informations used and obtained during the different analysis operations), - connect PC to the Database (export of Reports and even of segmented points), - issue Examination Reports, Operating Condition Sheets, Sizing curves... - and last, perform a graphic and numerical comparison between different inspections of the same vessel. Used in Belgium and France on different kind of reactor vessels, CIVACUVE has allowed to show that the principle of SEGMENTATION can be adapted to detection exams. The use of CIVACUVE generates a important time gain as well as the betterment of quality in analysis. Wide data opening toward PC's allows a real flexibility with regard to client's requirements and preoccupations

A Rough Set Approach for Customer Segmentation

Directory of Open Access Journals (Sweden)

Prabha Dhandayudam

2014-04-01

Full Text Available Customer segmentation is a process that divides a business's total customers into groups according to their diversity of purchasing behavior and characteristics. The data mining clustering technique can be used to accomplish this customer segmentation. This technique clusters the customers in such a way that the customers in one group behave similarly when compared to the customers in other groups. The customer related data are categorical in nature. However, the clustering algorithms for categorical data are few and are unable to handle uncertainty. Rough set theory (RST is a mathematical approach that handles uncertainty and is capable of discovering knowledge from a database. This paper proposes a new clustering technique called MADO (Minimum Average Dissimilarity between Objects for categorical data based on elements of RST. The proposed algorithm is compared with other RST based clustering algorithms, such as MMR (Min-Min Roughness, MMeR (Min Mean Roughness, SDR (Standard Deviation Roughness, SSDR (Standard deviation of Standard Deviation Roughness, and MADE (Maximal Attributes DEpendency. The results show that for the real customer data considered, the MADO algorithm achieves clusters with higher cohesion, lower coupling, and less computational complexity when compared to the above mentioned algorithms. The proposed algorithm has also been tested on a synthetic data set to prove that it is also suitable for high dimensional data.

Application of a stereoscopic digital subtraction angiography approach to blood flow analysis

International Nuclear Information System (INIS)

Fencil, L.E.; Doi, K.; Hoffmann, K.R.

1986-01-01

The authors are developing a stereoscopic digital subtraction angiographic (DSA) approach for accurate measurement of the size, magnification factor, orientation, and blood flow of a selected vessel segment. We employ a Siemens Digitron 2 and a Stereolix x-ray tube with a 25-mm tube shift. Absolute vessel sizes in each stereoscopic image are determined using the magnification factor and an iterative deconvolution technique employing the LSF of the DSA system. From data on vessel diameter and three-dimensional orientation, the effective attenuation coefficient of the diluted contrast medium can be determined, thus allowing accurate blood flow analysis in high-frame-rate DSA images. The accuracy and precision of the approach will be studied using both static and dynamic phantoms

Feasibility of Using the Marginal Blood Vessels as Reference Landmarks for CT Colonography

Science.gov (United States)

Wei, Zhuoshi; Yao, Jianhua; Wang, Shijun; Liu, Jiamin; Dwyer, Andrew J.; Pickhardt, Perry J.; Nowinski, Wieslaw L.; Summers, Ronald M.

2015-01-01

OBJECTIVE The purpose of this study was to show the spatial relationship of the colonic marginal blood vessels and the teniae coli on CT colonography (CTC) and the use of the marginal blood vessels for supine-prone registration of polyps and for determination of proper connectivity of collapsed colonic segments. MATERIALS AND METHODS We manually labeled the marginal blood vessels on 15 CTC examinations. Colon segmentation, centerline extraction, teniae detection, and teniae identification were automatically performed. For assessment of their spatial relationships, the distances from the marginal blood vessels to the three teniae coli and to the colon were measured. Student t tests (paired, two-tailed) were performed to evaluate the differences among these distances. To evaluate the reliability of the marginal vessels as reference points for polyp correlation, we analyzed 20 polyps from 20 additional patients who underwent supine and prone CTC. The average difference of the circumferential polyp position on the supine and prone scans was computed. Student t tests (paired, two-tailed) were performed to evaluate the supine-prone differences of the distance. We performed a study on 10 CTC studies from 10 patients with collapsed colonic segments by manually tracing the marginal blood vessels near the collapsed regions to resolve the ambiguity of the colon path. RESULTS The average distances (± SD) from the marginal blood vessels to the tenia mesocolica, tenia omentalis, and tenia libera were 20.1 ± 3.1 mm (95% CI, 18.5–21.6 mm), 39.5 ± 4.8 mm (37.1–42.0 mm), and 36.9 ± 4.2 mm (34.8–39.1 mm), respectively. Pairwise comparison showed that these distances to the tenia libera and tenia omentalis were significantly different from the distance to the tenia mesocolica (p marginal blood vessels to the colon wall was 15.3 ± 2.0 mm (14.2–16.3 mm). For polyp localization, the average difference of the circumferential polyp position on the supine and prone scans was 9

A Multidimensional Environmental Value Orientation Approach to Forest Recreation Area Tourism Market Segmentation

Directory of Open Access Journals (Sweden)

Cheng-Ping Wang

2016-04-01

Full Text Available This paper uses multidimensional environmental value orientations as the segmentation bases for analyzing a natural destination tourism market of the National Forest Recreation Areas in Taiwan. Cluster analyses identify two segments, Acceptance and Conditionality, within 1870 usable observations. Independent sample t test and crosstab analyses are applied to examine these segments’ forest value orientations, sociodemographic features, and service demands. The Acceptance group tends to be potential ecotourists, while still recognizing the commercial value of the natural resources. The Conditionality group may not possess a strong sense of ecotourism, given that its favored services can affect the environment. Overall, this article confirms the use of multidimensional environmental value orientation approaches can generate a comprehensive natural tourist segment comparison that benefits practical management decision making.

VIPAR, a quantitative approach to 3D histopathology applied to lymphatic malformations.

Science.gov (United States)

Hägerling, René; Drees, Dominik; Scherzinger, Aaron; Dierkes, Cathrin; Martin-Almedina, Silvia; Butz, Stefan; Gordon, Kristiana; Schäfers, Michael; Hinrichs, Klaus; Ostergaard, Pia; Vestweber, Dietmar; Goerge, Tobias; Mansour, Sahar; Jiang, Xiaoyi; Mortimer, Peter S; Kiefer, Friedemann

2017-08-17

Lack of investigatory and diagnostic tools has been a major contributing factor to the failure to mechanistically understand lymphedema and other lymphatic disorders in order to develop effective drug and surgical therapies. One difficulty has been understanding the true changes in lymph vessel pathology from standard 2D tissue sections. VIPAR (volume information-based histopathological analysis by 3D reconstruction and data extraction), a light-sheet microscopy-based approach for the analysis of tissue biopsies, is based on digital reconstruction and visualization of microscopic image stacks. VIPAR allows semiautomated segmentation of the vasculature and subsequent nonbiased extraction of characteristic vessel shape and connectivity parameters. We applied VIPAR to analyze biopsies from healthy lymphedematous and lymphangiomatous skin. Digital 3D reconstruction provided a directly visually interpretable, comprehensive representation of the lymphatic and blood vessels in the analyzed tissue volumes. The most conspicuous features were disrupted lymphatic vessels in lymphedematous skin and a hyperplasia (4.36-fold lymphatic vessel volume increase) in the lymphangiomatous skin. Both abnormalities were detected by the connectivity analysis based on extracted vessel shape and structure data. The quantitative evaluation of extracted data revealed a significant reduction of lymphatic segment length (51.3% and 54.2%) and straightness (89.2% and 83.7%) for lymphedematous and lymphangiomatous skin, respectively. Blood vessel length was significantly increased in the lymphangiomatous sample (239.3%). VIPAR is a volume-based tissue reconstruction data extraction and analysis approach that successfully distinguished healthy from lymphedematous and lymphangiomatous skin. Its application is not limited to the vascular systems or skin. Max Planck Society, DFG (SFB 656), and Cells-in-Motion Cluster of Excellence EXC 1003.

Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography

Science.gov (United States)

Yong, Yan Ling; Tan, Li Kuo; McLaughlin, Robert A.; Chee, Kok Han; Liew, Yih Miin

2017-12-01

Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.

Marketing ambulatory care to women: a segmentation approach.

Science.gov (United States)

Harrell, G D; Fors, M F

1985-01-01

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

International Cooperation for the Dismantling of Chooz A Reactor Pressure Vessel

International Nuclear Information System (INIS)

Grenouillet, J.J.; Posivak, E.

2009-01-01

Chooz A is the first PWR that is being decommissioned in France. The main issue that is conditioning the success of the project is the Reactor Pressure Vessel (RPV) and Reactor Vessel Internals (RVI) segmentation. Whereas Chooz A is the first and unique RPV and RVI being dismantled in France, there are many similar experiences available in the world. Thus the project team was eager to cooperate with other teams facing or being faced with the same issue. A cooperation programme was established in two separate ways: - Benefiting from experience feedback from completed RPV and RVI dismantling projects, - Looking for synergy with future RPV dismantling projects for activities such as segmentation tools design, qualification and manufacturing for example. This paper describes the implementation of this programme and how the outcome of the cooperation was used for the implementation of Chooz-A RPV and RVI segmentation project. It shows also the limits of such a cooperation. (authors)

Evidence of Flicker-Induced Functional Hyperaemia in the Smallest Vessels of the Human Retinal Blood Supply.

Directory of Open Access Journals (Sweden)

Angelina Duan

Full Text Available Regional changes in blood flow are initiated within neural tissue to help fuel local differences in neural activity. Classically, this response was thought to arise only in larger arterioles and venules. However, recently, it has been proposed that a the smallest vessels of the circulation make a comparable contribution, and b the response should be localised intermittently along such vessels, due to the known distribution of contractile mural cells. To assess these hypotheses in human neural tissue in vivo, we imaged the retinal microvasculature (diameters 3-28 μm non-invasively, using adaptive optics, before and after delivery of focal (360 μm patches of flickering visible light. Our results demonstrated a definite average response in 35% of all vessel segments analysed. In these responding vessels, the magnitude of proportional dilation (mean ± SEM for pre-capillary arterioles 13 ± 5%, capillaries 31 ± 8%, and post-capillary venules 10 ± 3% is generally far greater than the magnitudes we and others have measured in the larger retinal vessels, supporting proposition a above. The dilations observed in venules were unexpected based on previous animal work, and may be attributed either to differences in stimulus or species. Response heterogeneity across the network was high; responses were also heterogeneous along individual vessels (45% of vessel segments showed demonstrable locality in their response. These observations support proposition b above. We also observed a definite average constriction across 7% of vessel segments (mean ± SEM constriction for capillaries -16 ± 3.2%, and post-capillary venules -18 ± 12%, which paints a picture of dynamic redistribution of flow throughout the smallest vessel networks in the retina in response to local, stimulus-driven metabolic demand.

Roentgenoendovascular dilatation and recanalization of vessels of lower extremities

International Nuclear Information System (INIS)

Rabkin, I.Kh.; Matevosov, A.L.; Gotman, L.N.

1987-01-01

Advantages and disadvantages of using roentgenoendovascular dilatation (RED) of vessels of lower extremities are presented. RED is recommended in treating patients with short segmented stenoses of common and external illiac arteries and also with the similar damages of surficial femoral arteries. Dilatation is a success when there is permeability in at least one of the three central crus arteries. Success of delayed results of vessel dilatation is to a certain degree in inverse proportion to time and length of occlusion

A Variational Approach to Simultaneous Image Segmentation and Bias Correction.

Science.gov (United States)

Zhang, Kaihua; Liu, Qingshan; Song, Huihui; Li, Xuelong

2015-08-01

This paper presents a novel variational approach for simultaneous estimation of bias field and segmentation of images with intensity inhomogeneity. We model intensity of inhomogeneous objects to be Gaussian distributed with different means and variances, and then introduce a sliding window to map the original image intensity onto another domain, where the intensity distribution of each object is still Gaussian but can be better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying the bias field with a piecewise constant signal within the sliding window. A maximum likelihood energy functional is then defined on each local region, which combines the bias field, the membership function of the object region, and the constant approximating the true signal from its corresponding object. The energy functional is then extended to the whole image domain by the Bayesian learning approach. An efficient iterative algorithm is proposed for energy minimization, via which the image segmentation and bias field correction are simultaneously achieved. Furthermore, the smoothness of the obtained optimal bias field is ensured by the normalized convolutions without extra cost. Experiments on real images demonstrated the superiority of the proposed algorithm to other state-of-the-art representative methods.

Design of the ITER vacuum vessel

International Nuclear Information System (INIS)

Ioki, K.; Johnson, G.; Shimizu, K.; Williamson, D.

1995-01-01

The ITER vacuum vessel is a major safety barrier and must support electromagnetic loads during plasma disruptions and vertical displacement events (VDE) and withstand plausible accidents without losing confinement.The vacuum vessel has a double wall structure to provide structural and electrical continuity in the toroidal direction. The inner and outer shells and poloidal stiffening ribs between them are joined by welding, which gives the vessel the required mechanical strength. The space between the shells will be filled with steel balls and plate inserts to provide additional nuclear shielding. Water flowing in this space is required to remove nuclear heat deposition, which is 0.2-2.5% of the total fusion power. The minor and major radii of the tokamak are 3.9 m and 13 m respectively, and the overall height is 15 m. The total thickness of the vessel wall structure is 0.4-0.7 m.The inboard and outboard blanket segments are supported from the vacuum vessel. The support structure is required to withstand a large total vertical force of 200-300 MN due to VDE and to allow for differential thermal expansion.The first candidate for the vacuum vessel material is Inconel 625, due to its higher electric resistivity and higher yield strength, even at high temperatures. Type 316 stainless steel is also considered a vacuum vessel material candidate, owing to its large database and because it is supported by more conventional fabrication technology. (orig.)

Wireless Positioning Based on a Segment-Wise Linear Approach for Modeling the Target Trajectory

DEFF Research Database (Denmark)

Figueiras, Joao; Pedersen, Troels; Schwefel, Hans-Peter

2008-01-01

Positioning solutions in infrastructure-based wireless networks generally operate by exploiting the channel information of the links between the Wireless Devices and fixed networking Access Points. The major challenge of such solutions is the modeling of both the noise properties of the channel...... measurements and the user mobility patterns. One class of typical human being movement patterns is the segment-wise linear approach, which is studied in this paper. Current tracking solutions, such as the Constant Velocity model, hardly handle such segment-wise linear patterns. In this paper we propose...... a segment-wise linear model, called the Drifting Points model. The model results in an increased performance when compared with traditional solutions....

A two-stage rule-constrained seedless region growing approach for mandibular body segmentation in MRI.

Science.gov (United States)

Ji, Dong Xu; Foong, Kelvin Weng Chiong; Ong, Sim Heng

2013-09-01

Extraction of the mandible from 3D volumetric images is frequently required for surgical planning and evaluation. Image segmentation from MRI is more complex than CT due to lower bony signal-to-noise. An automated method to extract the human mandible body shape from magnetic resonance (MR) images of the head was developed and tested. Anonymous MR images data sets of the head from 12 subjects were subjected to a two-stage rule-constrained region growing approach to derive the shape of the body of the human mandible. An initial thresholding technique was applied followed by a 3D seedless region growing algorithm to detect a large portion of the trabecular bone (TB) regions of the mandible. This stage is followed with a rule-constrained 2D segmentation of each MR axial slice to merge the remaining portions of the TB regions with lower intensity levels. The two-stage approach was replicated to detect the cortical bone (CB) regions of the mandibular body. The TB and CB regions detected from the preceding steps were merged and subjected to a series of morphological processes for completion of the mandibular body region definition. Comparisons of the accuracy of segmentation between the two-stage approach, conventional region growing method, 3D level set method, and manual segmentation were made with Jaccard index, Dice index, and mean surface distance (MSD). The mean accuracy of the proposed method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of CRG is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of the 3D level set method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The proposed method shows improvement in accuracy over CRG and 3D level set. Accurate segmentation of the body of the human mandible from MR images is achieved with the

Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

Energy Technology Data Exchange (ETDEWEB)

Ross, James C., E-mail: jross@bwh.harvard.edu [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States); Kindlmann, Gordon L. [Computer Science Department and Computation Institute, University of Chicago, Chicago, Illinois 60637 (United States); Okajima, Yuka; Hatabu, Hiroto [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Díaz, Alejandro A. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 and Department of Pulmonary Diseases, Pontificia Universidad Católica de Chile, Santiago (Chile); Silverman, Edwin K. [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 and Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Washko, George R. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Dy, Jennifer [ECE Department, Northeastern University, Boston, Massachusetts 02115 (United States); Estépar, Raúl San José [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States)

2013-12-15

Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The

Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

International Nuclear Information System (INIS)

Ross, James C.; Kindlmann, Gordon L.; Okajima, Yuka; Hatabu, Hiroto; Díaz, Alejandro A.; Silverman, Edwin K.; Washko, George R.; Dy, Jennifer; Estépar, Raúl San José

2013-01-01

Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The proposed

Automated detection and classification of major retinal vessels for determination of diameter ratio of arteries and veins

Science.gov (United States)

Muramatsu, Chisako; Hatanaka, Yuji; Iwase, Tatsuhiko; Hara, Takeshi; Fujita, Hiroshi

2010-03-01

Abnormalities of retinal vasculatures can indicate health conditions in the body, such as the high blood pressure and diabetes. Providing automatically determined width ratio of arteries and veins (A/V ratio) on retinal fundus images may help physicians in the diagnosis of hypertensive retinopathy, which may cause blindness. The purpose of this study was to detect major retinal vessels and classify them into arteries and veins for the determination of A/V ratio. Images used in this study were obtained from DRIVE database, which consists of 20 cases each for training and testing vessel detection algorithms. Starting with the reference standard of vasculature segmentation provided in the database, major arteries and veins each in the upper and lower temporal regions were manually selected for establishing the gold standard. We applied the black top-hat transformation and double-ring filter to detect retinal blood vessels. From the extracted vessels, large vessels extending from the optic disc to temporal regions were selected as target vessels for calculation of A/V ratio. Image features were extracted from the vessel segments from quarter-disc to one disc diameter from the edge of optic discs. The target segments in the training cases were classified into arteries and veins by using the linear discriminant analysis, and the selected parameters were applied to those in the test cases. Out of 40 pairs, 30 pairs (75%) of arteries and veins in the 20 test cases were correctly classified. The result can be used for the automated calculation of A/V ratio.

Integrating social marketing into sustainable resource management at Padre Island National Seashore: an attitude-based segmentation approach.

Science.gov (United States)

Lai, Po-Hsin; Sorice, Michael G; Nepal, Sanjay K; Cheng, Chia-Kuen

2009-06-01

High demand for outdoor recreation and increasing diversity in outdoor recreation participants have imposed a great challenge on the National Park Service (NPS), which is tasked with the mission to provide open access for quality outdoor recreation and maintain the ecological integrity of the park system. In addition to management practices of education and restrictions, building a sense of natural resource stewardship among visitors may also facilitate the NPS ability to react to this challenge. The purpose of our study is to suggest a segmentation approach that is built on the social marketing framework and aimed at influencing visitor behaviors to support conservation. Attitude toward natural resource management, an indicator of natural resource stewardship, is used as the basis for segmenting park visitors. This segmentation approach is examined based on a survey of 987 visitors to the Padre Island National Seashore (PAIS) in Texas in 2003. Results of the K-means cluster analysis identify three visitor segments: Conservation-Oriented, Development-Oriented, and Status Quo visitors. This segmentation solution is verified using respondents' socio-demographic backgrounds, use patterns, experience preferences, and attitudes toward a proposed regulation. Suggestions are provided to better target the three visitor segments and facilitate a sense of natural resource stewardship among them.

Fast retinal vessel detection and measurement using wavelets and edge location refinement.

Directory of Open Access Journals (Sweden)

Peter Bankhead

Full Text Available The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available.

Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore

Directory of Open Access Journals (Sweden)

Lian Leng Low

2017-11-01

Full Text Available Abstract Background Segmenting the population into groups that are relatively homogeneous in healthcare characteristics or needs is crucial to facilitate integrated care and resource planning. We aimed to evaluate the feasibility of segmenting the population into discrete, non-overlapping groups using a practical expert and literature driven approach. We hypothesized that this approach is feasible utilizing the electronic health record (EHR in SingHealth. Methods In addition to well-defined segments of “Mostly healthy”, “Serious acute illness but curable” and “End of life” segments that are also present in the Ministry of Health Singapore framework, patients with chronic diseases were segmented into “Stable chronic disease”, “Complex chronic diseases without frequent hospital admissions”, and “Complex chronic diseases with frequent hospital admissions”. Using the electronic health record (EHR, we applied this framework to all adult patients who had a healthcare encounter in the Singapore Health Services Regional Health System in 2012. ICD-9, 10 and polyclinic codes were used to define chronic diseases with a comprehensive look-back period of 5 years. Outcomes (hospital admissions, emergency attendances, specialist outpatient clinic attendances and mortality were analyzed for years 2012 to 2015. Results Eight hundred twenty five thousand eight hundred seventy four patients were included in this study with the majority being healthy without chronic diseases. The most common chronic disease was hypertension. Patients with “complex chronic disease” with frequent hospital admissions segment represented 0.6% of the eligible population, but accounted for the highest hospital admissions (4.33 ± 2.12 admissions; p < 0.001 and emergency attendances (ED (3.21 ± 3.16 ED visits; p < 0.001 per patient, and a high mortality rate (16%. Patients with metastatic disease accounted for the highest specialist outpatient

Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.

Science.gov (United States)

Valverde, Sergi; Cabezas, Mariano; Roura, Eloy; González-Villà, Sandra; Pareto, Deborah; Vilanova, Joan C; Ramió-Torrentà, Lluís; Rovira, Àlex; Oliver, Arnau; Lladó, Xavier

2017-07-15

In this paper, we present a novel automated method for White Matter (WM) lesion segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a cascade of two 3D patch-wise convolutional neural networks (CNN). The first network is trained to be more sensitive revealing possible candidate lesion voxels while the second network is trained to reduce the number of misclassified voxels coming from the first network. This cascaded CNN architecture tends to learn well from a small (n≤35) set of labeled data of the same MRI contrast, which can be very interesting in practice, given the difficulty to obtain manual label annotations and the large amount of available unlabeled Magnetic Resonance Imaging (MRI) data. We evaluate the accuracy of the proposed method on the public MS lesion segmentation challenge MICCAI2008 dataset, comparing it with respect to other state-of-the-art MS lesion segmentation tools. Furthermore, the proposed method is also evaluated on two private MS clinical datasets, where the performance of our method is also compared with different recent public available state-of-the-art MS lesion segmentation methods. At the time of writing this paper, our method is the best ranked approach on the MICCAI2008 challenge, outperforming the rest of 60 participant methods when using all the available input modalities (T1-w, T2-w and FLAIR), while still in the top-rank (3rd position) when using only T1-w and FLAIR modalities. On clinical MS data, our approach exhibits a significant increase in the accuracy segmenting of WM lesions when compared with the rest of evaluated methods, highly correlating (r≥0.97) also with the expected lesion volume. Copyright © 2017 Elsevier Inc. All rights reserved.

Coronary arteries segmentation based on the 3D discrete wavelet transform and 3D neutrosophic transform.

Science.gov (United States)

Chen, Shuo-Tsung; Wang, Tzung-Dau; Lee, Wen-Jeng; Huang, Tsai-Wei; Hung, Pei-Kai; Wei, Cheng-Yu; Chen, Chung-Ming; Kung, Woon-Man

2015-01-01

Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

Processing of MRI images weighted in TOF for blood vessels analysis: 3-D reconstruction

Energy Technology Data Exchange (ETDEWEB)

Hernandez D, J.; Cordova F, T. [Universidad de Guanajuato, Campus Leon, Departamento de Ingenieria Fisica, Loma del Bosque No. 103, Lomas del Campestre, 37150 Leon, Guanajuato (Mexico); Cruz A, I., E-mail: hernandezdj.gto@gmail.com [CONACYT, Centro de Investigacion en Matematicas, A. C., Jalisco s/n, Col. Valenciana, 36000 Guanajuato, Gto. (Mexico)

2015-10-15

This paper presents a novel presents an approach based on differences of intensities for the identification of vascular structures in medical images from MRI studies of type time of flight method (TOF). The plating method hypothesis gave high intensities belonging to the vascular system image type TOF can be segmented by thresholding of the histogram. The enhanced vascular structures is performed using the filter Vesselness, upon completion of a decision based on fuzzy thresholding minimizes error in the selection of vascular structures. It will give a brief introduction to the vascular system problems and how the images have helped diagnosis, is summarized the physical history of the different imaging modalities and the evolution of digital images with computers. Segmentation and 3-D reconstruction became image type time of flight; these images are typically used in medical diagnosis of cerebrovascular diseases. The proposed method has less error in segmentation and reconstruction of volumes related to the vascular system, clear images and less noise compared with edge detection methods. (Author)

Processing of MRI images weighted in TOF for blood vessels analysis: 3-D reconstruction

International Nuclear Information System (INIS)

Hernandez D, J.; Cordova F, T.; Cruz A, I.

2015-10-01

This paper presents a novel presents an approach based on differences of intensities for the identification of vascular structures in medical images from MRI studies of type time of flight method (TOF). The plating method hypothesis gave high intensities belonging to the vascular system image type TOF can be segmented by thresholding of the histogram. The enhanced vascular structures is performed using the filter Vesselness, upon completion of a decision based on fuzzy thresholding minimizes error in the selection of vascular structures. It will give a brief introduction to the vascular system problems and how the images have helped diagnosis, is summarized the physical history of the different imaging modalities and the evolution of digital images with computers. Segmentation and 3-D reconstruction became image type time of flight; these images are typically used in medical diagnosis of cerebrovascular diseases. The proposed method has less error in segmentation and reconstruction of volumes related to the vascular system, clear images and less noise compared with edge detection methods. (Author)

Parallel segmented outlet flow high performance liquid chromatography with multiplexed detection

International Nuclear Information System (INIS)

Camenzuli, Michelle; Terry, Jessica M.; Shalliker, R. Andrew; Conlan, Xavier A.; Barnett, Neil W.; Francis, Paul S.

2013-01-01

Graphical abstract: -- Highlights: •Multiplexed detection for liquid chromatography. •‘Parallel segmented outlet flow’ distributes inner and outer portions of the analyte zone. •Three detectors were used simultaneously for the determination of opiate alkaloids. -- Abstract: We describe a new approach to multiplex detection for HPLC, exploiting parallel segmented outlet flow – a new column technology that provides pressure-regulated control of eluate flow through multiple outlet channels, which minimises the additional dead volume associated with conventional post-column flow splitting. Using three detectors: one UV-absorbance and two chemiluminescence systems (tris(2,2′-bipyridine)ruthenium(III) and permanganate), we examine the relative responses for six opium poppy (Papaver somniferum) alkaloids under conventional and multiplexed conditions, where approximately 30% of the eluate was distributed to each detector and the remaining solution directed to a collection vessel. The parallel segmented outlet flow mode of operation offers advantages in terms of solvent consumption, waste generation, total analysis time and solute band volume when applying multiple detectors to HPLC, but the manner in which each detection system is influenced by changes in solute concentration and solution flow rates must be carefully considered

Parallel segmented outlet flow high performance liquid chromatography with multiplexed detection

Energy Technology Data Exchange (ETDEWEB)

Camenzuli, Michelle [Australian Centre for Research on Separation Science (ACROSS), School of Science and Health, University of Western Sydney (Parramatta), Sydney, NSW (Australia); Terry, Jessica M. [Centre for Chemistry and Biotechnology, School of Life and Environmental Sciences, Deakin University, Geelong, Victoria 3216 (Australia); Shalliker, R. Andrew, E-mail: r.shalliker@uws.edu.au [Australian Centre for Research on Separation Science (ACROSS), School of Science and Health, University of Western Sydney (Parramatta), Sydney, NSW (Australia); Conlan, Xavier A.; Barnett, Neil W. [Centre for Chemistry and Biotechnology, School of Life and Environmental Sciences, Deakin University, Geelong, Victoria 3216 (Australia); Francis, Paul S., E-mail: paul.francis@deakin.edu.au [Centre for Chemistry and Biotechnology, School of Life and Environmental Sciences, Deakin University, Geelong, Victoria 3216 (Australia)

2013-11-25

Graphical abstract: -- Highlights: •Multiplexed detection for liquid chromatography. •‘Parallel segmented outlet flow’ distributes inner and outer portions of the analyte zone. •Three detectors were used simultaneously for the determination of opiate alkaloids. -- Abstract: We describe a new approach to multiplex detection for HPLC, exploiting parallel segmented outlet flow – a new column technology that provides pressure-regulated control of eluate flow through multiple outlet channels, which minimises the additional dead volume associated with conventional post-column flow splitting. Using three detectors: one UV-absorbance and two chemiluminescence systems (tris(2,2′-bipyridine)ruthenium(III) and permanganate), we examine the relative responses for six opium poppy (Papaver somniferum) alkaloids under conventional and multiplexed conditions, where approximately 30% of the eluate was distributed to each detector and the remaining solution directed to a collection vessel. The parallel segmented outlet flow mode of operation offers advantages in terms of solvent consumption, waste generation, total analysis time and solute band volume when applying multiple detectors to HPLC, but the manner in which each detection system is influenced by changes in solute concentration and solution flow rates must be carefully considered.

A benefit segmentation approach for innovation-oriented university-business collaboration

DEFF Research Database (Denmark)

Kesting, Tobias; Gerstlberger, Wolfgang; Baaken, Thomas

2018-01-01

to deal with this situation by academic engagement, hereby providing external research support for businesses. Relying on the market segmentation approach, promoting beneficial exchange relations between academia and businesses enables the integration of both perspectives and may contribute to solving......Increasing competition in the light of globalisation imposes challenges on both academia and businesses. Universities have to compete for additional financial means, while companies, particular in high technology business environments, are facing a stronger pressure to innovate. Universities seek...

Clinical significance of exercise induced ST segment depression after successful percutaneous transluminal coronary angioplasty

International Nuclear Information System (INIS)

Aoki, Toshikazu; Konishi, Tokuji; Futagami, Yasuo

1989-01-01

To evaluate the clinical significance of ST segment depression during repeated Treadmill exercise after successful PTCA, Thallium-201 SPECT was performed. The Thallium-201 SPECT was performed before, one week after and 3-6 months after PTCA. All thirty-five patients had one vessel disease and positive Thallium-201 exercise test. During follow-up period for 3-6 months, 11 of 35 patients had persistent ST segment depression. Restenosis of dilated coronary lesion was demonstrated in 6 of 11 patients. In another 3 of 35 patients, exercise induced ST segment depression was disappered during follow-up Treadmill exercise. In 14 patients with persistent or transient ST segment depression after PTCA, Thallium-201 SPECT demonstrated transient ischemia in 5 of 6 patients with restenosis. In other 8 patients without restenosis, SPECT images did not demonstrate myocardial ischemia and coronary arteriographic findings could not verify side branch stenosis or intimal dissection which might cause myocardial ischemia. The etiology of ST segment depression after successful PTCA in one vessel disease is not produced by exercise induced myocardial ischemia but still unknown mechanisms may be present. (author)

Gadolinium Enhanced MR Coronary Vessel Wall Imaging at 3.0 Tesla

Directory of Open Access Journals (Sweden)

Sebastian Kelle

2010-01-01

Full Text Available Purpose. We evaluated the influence of the time between low-dose gadolinium (Gd contrast administration and coronary vessel wall enhancement (LGE detected by 3T magnetic resonance imaging (MRI in healthy subjects and patients with coronary artery disease (CAD. Materials and Methods. Four healthy subjects (4 men, mean age 29  ±  3 years and eleven CAD patients (6 women, mean age 61±10 years were studied on a commercial 3.0 Tesla (T whole-body MR imaging system (Achieva 3.0 T; Philips, Best, The Netherlands. T1-weighted inversion-recovery coronary magnetic resonance imaging (MRI was repeated up to 75 minutes after administration of low-dose Gadolinium (Gd (0.1 mmol/kg Gd-DTPA. Results. LGE was seen in none of the healthy subjects, however in all of the CAD patients. In CAD patients, fifty-six of 62 (90.3% segments showed LGE of the coronary artery vessel wall at time-interval 1 after contrast. At time-interval 2, 34 of 42 (81.0% and at time-interval 3, 29 of 39 evaluable segments (74.4% were enhanced. Conclusion. In this work, we demonstrate LGE of the coronary artery vessel wall using 3.0 T MRI after a single, low-dose Gd contrast injection in CAD patients but not in healthy subjects. In the majority of the evaluated coronary segments in CAD patients, LGE of the coronary vessel wall was already detectable 30–45 minutes after administration of the contrast agent.

Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography.

Science.gov (United States)

Yong, Yan Ling; Tan, Li Kuo; McLaughlin, Robert A; Chee, Kok Han; Liew, Yih Miin

2017-12-01

Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Xylem vulnerability to cavitation can be accurately characterised in species with long vessels using a centrifuge method.

Science.gov (United States)

Tobin, M F; Pratt, R B; Jacobsen, A L; De Guzman, M E

2013-05-01

Vulnerability to cavitation curves describe the decrease in xylem hydraulic conductivity as xylem pressure declines. Several techniques for constructing vulnerability curves use centrifugal force to induce negative xylem pressure in stem or root segments. Centrifuge vulnerability curves constructed for long-vesselled species have been hypothesised to overestimate xylem vulnerability to cavitation due to increased vulnerability of vessels cut open at stem ends that extend to the middle or entirely through segments. We tested two key predictions of this hypothesis: (i) centrifugation induces greater embolism than dehydration in long-vesselled species, and (ii) the proportion of open vessels changes centrifuge vulnerability curves. Centrifuge and dehydration vulnerability curves were compared for a long- and short-vesselled species. The effect of open vessels was tested in four species by comparing centrifuge vulnerability curves for stems of two lengths. Centrifuge and dehydration vulnerability curves agreed well for the long- and short-vesselled species. Centrifuge vulnerability curves constructed using two stem lengths were similar. Also, the distribution of embolism along the length of centrifuged stems matched the theoretical pressure profile induced by centrifugation. We conclude that vulnerability to cavitation can be accurately characterised with vulnerability curves constructed using a centrifuge technique, even in long-vesselled species. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.

Examining the Approaches of Customer Segmentation in a Cosmetic Company: A Case Study on L'oreal Malaysia SDN BHD

OpenAIRE

Ong, Poh Choo

2010-01-01

Purpose – The purpose of this study is to examine the market segmentation approaches available and identify which segmentation approaches best suit for L’Oreal Malaysia. Design/methodology/approach – Questionnaires were distributed to 80 L’Oreal cosmetic users in Malaysia and 55 completed questionnaires were analyzed. Besides, two interviews being conducted at L’Oreal Malaysia office and the result were analyzed too. Findings – The results were as follows. First, analysis of L’Oreal cos...

Segmentation methods for breast vasculature in dual-energy contrast-enhanced digital breast tomosynthesis

Science.gov (United States)

Lau, Kristen C.; Lee, Hyo Min; Singh, Tanushriya; Maidment, Andrew D. A.

2015-03-01

Dual-energy contrast-enhanced digital breast tomosynthesis (DE CE-DBT) uses an iodinated contrast agent to image the three-dimensional breast vasculature. The University of Pennsylvania has an ongoing DE CE-DBT clinical study in patients with known breast cancers. The breast is compressed continuously and imaged at four time points (1 pre-contrast; 3 post-contrast). DE images are obtained by a weighted logarithmic subtraction of the high-energy (HE) and low-energy (LE) image pairs. Temporal subtraction of the post-contrast DE images from the pre-contrast DE image is performed to analyze iodine uptake. Our previous work investigated image registration methods to correct for patient motion, enhancing the evaluation of vascular kinetics. In this project we investigate a segmentation algorithm which identifies blood vessels in the breast from our temporal DE subtraction images. Anisotropic diffusion filtering, Gabor filtering, and morphological filtering are used for the enhancement of vessel features. Vessel labeling methods are then used to distinguish vessel and background features successfully. Statistical and clinical evaluations of segmentation accuracy in DE-CBT images are ongoing.

A robust technique based on VLM and Frangi filter for retinal vessel extraction and denoising.

Directory of Open Access Journals (Sweden)

Khan Bahadar Khan

Full Text Available The exploration of retinal vessel structure is colossally important on account of numerous diseases including stroke, Diabetic Retinopathy (DR and coronary heart diseases, which can damage the retinal vessel structure. The retinal vascular network is very hard to be extracted due to its spreading and diminishing geometry and contrast variation in an image. The proposed technique consists of unique parallel processes for denoising and extraction of blood vessels in retinal images. In the preprocessing section, an adaptive histogram equalization enhances dissimilarity between the vessels and the background and morphological top-hat filters are employed to eliminate macula and optic disc, etc. To remove local noise, the difference of images is computed from the top-hat filtered image and the high-boost filtered image. Frangi filter is applied at multi scale for the enhancement of vessels possessing diverse widths. Segmentation is performed by using improved Otsu thresholding on the high-boost filtered image and Frangi's enhanced image, separately. In the postprocessing steps, a Vessel Location Map (VLM is extracted by using raster to vector transformation. Postprocessing steps are employed in a novel way to reject misclassified vessel pixels. The final segmented image is obtained by using pixel-by-pixel AND operation between VLM and Frangi output image. The method has been rigorously analyzed on the STARE, DRIVE and HRF datasets.

Multislice CT coronary angiography: evaluation of an automatic vessel detection tool

International Nuclear Information System (INIS)

Dewey, M.; Schnapauff, D.; Lembcke, A.; Hamm, B.; Rogalla, P.; Laule, M.; Borges, A.C.; Rutsch, W.

2004-01-01

Purpose: To investigate the potential of a new detection tool for multisliceCT (MSCT) coronary angiography with automatic display of curved multiplanar reformations and orthogonal cross-sections. Materials and Methods: Thirty-five patients were consecutively enrolled in a prospective intention-to-diagnose study and examined using a MSCT scanner with 16 x 0.5 mm detector collimation and 400 ms gantry rotation time (Aquilion, Toshiba). A multisegment algorithm using up to four segments was applied for ECG-gated reconstruction. Automatic and manual detection of coronary arteries was conducted using the coronary artery CT protocol of a workstation (Vitrea 2, Version 3.3, Vital Images) to detect significant stenoses (≥50%) in all segments of ≥1.5 mm in diameter. Each detection tool was used by one reader who was blinded to the results of the other detection method and the results of conventional coronary angiography. Results: The overall sensitivity, specificity, nondiagnostic rate, and accuracy of the automatic and manual approach were 90 vs. 94%, 89 vs. 84%, 6 vs. 6%, and 89 vs. 88%, respectively (p=n.s.). The vessel length detected with the automatic and manual approach were highly correlated for the left main/left anterior descending (143±30 vs. 146±24 mm, r=0.923, p [de

Comparison of anterior segment optical coherence tomography angiography and fluorescein angiography for iris vasculature analysis.

Science.gov (United States)

Zett, Claudio; Stina, Deborah M Rosa; Kato, Renata Tiemi; Novais, Eduardo Amorim; Allemann, Norma

2018-04-01

The aim of this study is to perform imaging of irises of different colors using spectral domain anterior segment optical coherence tomography angiography (AS-OCTA) and iris fluorescein angiography (IFA) and compare their effectiveness in examining iris vasculature. This is a cross-sectional observational clinical study. Patients with no vascular iris alterations and different pigmentation levels were recruited. Participants were imaged using OCTA adapted with an anterior segment lens and IFA with a confocal scanning laser ophthalmoscope (cSLO) adapted with an anterior segment lens. AS-OCTA and IFA images were then compared. Two blinded readers classified iris pigmentation and compared the percentage of visible vessels between OCTA and IFA images. Twenty eyes of 10 patients with different degrees of iris pigmentation were imaged using AS-OCTA and IFA. Significantly more visible iris vessels were observed using OCTA than using FA (W = 5.22; p Iris pigmentation was negatively correlated to the percentage of visible vessels in both imaging methods (OCTA, rho = - 0.73, p iris vasculature. In both AS-OCTA and IFA, iris pigmentation caused vasculature imaging blockage, but AS-OCTA provided more detailed iris vasculature images than IFA. Additional studies including different iris pathologies are needed to determine the most optimal scanning parameters in OCTA of the anterior segment.

NEW APPROACHES TO CUSTOMER BASE SEGMENTATION FOR SMALL AND MEDIUM-SIZED ENTERPRISES

Directory of Open Access Journals (Sweden)

Meleancă Raluca-Cristina

2012-12-01

Full Text Available The primary purpose of this paper is to explore current praxis and theory related to customer segmentation and to offer an approach which is best suited for small and medium sized enterprises. The proposed solution is the result of an exploratory research aiming to recognize the main variables which influence the practice of segmenting the customer base and to study the most applied alternatives available for all types of enterprises. The research has been performed by studying a large set of secondary data, scientific literature and case studies regarding smaller companies from the European Union. The result of the research consists in an original approach to customer base segmentation, which combines aspects belonging to different well spread practices and applies them to the specific needs of a small or medium company, which typically has limited marketing resources in general and targeted marketing resources in particular. The significance of the proposed customer base segmentation approach lies in the fact that, even though smaller enterprises are in most economies the greatest in number compared to large companies, most of the literature on targeting practices has focused primarily on big companies dealing with a very large clientele, while the case of the smaller companies has been to some extent unfairly neglected. Targeted marketing is becoming more and more important for all types of companies nowadays, as a result of technology advances which make targeted communication easier and less expensive than in the past and also due to the fact that broad-based media have decreased their impact over the years. For a very large proportion of smaller companies, directing their marketing budgets towards targeted campaigns is a clever initiative, as broad based approaches are in many cases less effective and much more expensive. Targeted marketing stratagems are generally related to high tech domains such as artificial intelligence, data mining

Pressure vessels supported in the soil submitted to axissymetrical loads

International Nuclear Information System (INIS)

Gouvea, J.P. de; Bevilacqua, L.

1982-01-01

A pressure vessel, spherical segment or vertical cylinder, is supported in the soil and submitted to axissymetrical loads. The soil is considered as a semi-infinite elastic solid and the support as a lattice. The method of rigidity is used. (E.G.) [pt

Standard and biological treatment in large vessel vasculitis: guidelines and current approaches.

Science.gov (United States)

Muratore, Francesco; Pipitone, Nicolò; Salvarani, Carlo

2017-04-01

Giant cell arteritis and Takayasu arteritis are the two major forms of idiopathic large vessel vasculitis. High doses of glucocorticoids are effective in inducing remission in both conditions, but relapses and recurrences are common, requiring prolonged glucocorticoid treatment with the risk of the related adverse events. Areas covered: In this article, we will review the standard and biological treatment strategies in large vessel vasculitis, and we will focus on the current approaches to these diseases. Expert commentary: The results of treatment trials with conventional immunosuppressive agents such as methotrexate, azathioprine, mycophenolate mofetil, and cyclophosphamide have overall been disappointing. TNF-α blockers are ineffective in giant cell arteritis, while observational evidence and a phase 2 randomized trial support the use of tocilizumab in relapsing giant cell arteritis. Observational evidence strongly supports the use of anti-TNF-α agents and tocilizumab in Takayasu patients with relapsing disease. However biological agents are not curative, and relapses remain common.

Smart markers for watershed-based cell segmentation.

Directory of Open Access Journals (Sweden)

Can Fahrettin Koyuncu

Full Text Available Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

Smart markers for watershed-based cell segmentation.

Science.gov (United States)

Koyuncu, Can Fahrettin; Arslan, Salim; Durmaz, Irem; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2012-01-01

Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

MORPHOMETRIC STUDY OF THE AREOLAR SPACE BETWEEN THE GREAT VESSELS AND THE LUMBAR SPINE

Directory of Open Access Journals (Sweden)

Luis Marchi

2015-12-01

Full Text Available Objective : This work aims to study the areolar space anterior to the lumbar spine, and also the positioning of the large vessels focusing a lateral approach. Methods :This is a morphometric study of 108 cases based on T2 weighted-MRI images in the supine position. The following measurements were performed: lumbar and segmental lordosis; anteroposterior disc diameter; space between the disc/vertebral body and the vessels; bifurcation between the abdominal aorta and the common iliac veins confluence in relation to the lumbar level. Results :The areolar space with respect to the iliac veins, and with the vena cava increased cranially (p<0.001, starting from average 0.6mm at L4-L5 and reaching 8.4mm at L2, while the abdominal aorta showed no increase or decrease pattern across the different levels (p=0.135 ranging from 1.8 to 4.6mm. The diameter of the discs increased distally (p<0.01 as well as the lordosis (p<0.001. The disc diameter was 11% larger when compared to the adjacent vertebral bodies (p<0.001 and that resulted in a smaller distance of the vessels in the disc level than in the level of the adjacent vertebral bodies (p<0.001. The aortic bifurcation was generally ahead of L4 (52% and less frequently at L3-L4 (28% and L4-L5 (18%. The confluence of the veins was usually at the L4-L5 level (38% and at L5 (37%, and less frequently at L4 (26%. Conclusions : There is an identifiable plane between the great vessels and the lumbar spine which is particularly narrow in its distal portion. It is theoretically feasible to reach this plan, handle the anterior complex disc/ALL and protect the great vessels by lateral approach, however, it is challenging.

Morphometry of A1 segment of the anterior cerebral artery and its clinical importance.

Science.gov (United States)

Krishnamurthy, A; Nayak, S R; Bagoji, I B; D'Costa, S; Pai, M M; Jiji, P J; Kumar, C G; Rai, R

2010-01-01

Anterior cerebral artery, one of the terminal branches of the internal carotid artery is an important vessel taking part in the formation of circle of Willis. It supplies a large part of the medial surface of the cerebral hemisphere containing the areas of motor and somatosensory cortices of the lower limb. Aim of this study was the morphometry of A1 segment of the anterior cerebral artery. 93 formalin fixed brain specimen of either sex and of Indian origin were studied. The mean length, mean external diameter and the anomalies present in A1 segment of the vessel were studied in detail and photographed. The mean length of A1 segment of the vessel was 14.49+/-0.28 mm and 14.22+/-0.22 mm on right and left side respectively. The mean external diameter of the vessel on right and left side was 2.12+/-0.07 mm and 2.32+/-0.06 mm respectively. Narrowing, aneurysm formation, buttonhole formation and median anterior cerebral artery were the anomalies seen with an occurrence of 15.05%, 5.37%, 3.22% and 12.9%, respectively. The above anomalies did not have any sex or side predilection. Knowledge of morphometry of the vessel will be of use to neurosurgeons while performing the shunt operation, in assessing the feasibility of such operations and in the choice of patients. From this study we infer that the morphometry of anterior cerebral artery varies in different population and that the neurosurgeons operating should have a thorough knowledge of the possible variations.

Risks in surgery-first orthognathic approach: complications of segmental osteotomies of the jaws. A systematic review.

Science.gov (United States)

Pelo, S; Saponaro, G; Patini, R; Staderini, E; Giordano, A; Gasparini, G; Garagiola, U; Azzuni, C; Cordaro, M; Foresta, E; Moro, A

2017-01-01

To date, no systematic review has been undertaken to identify the complications of segmental osteotomies. The aim of the present systematic review was to analyze the type and incidence of complications of segmental osteotomies, as well as the time of subjective and/or clinical onset of the intra- and post-operative problems. A search was conducted in two electronic databases (MEDLINE - Pubmed database and Scopus) for articles published in English between 1 January 2000 and 30 August 2015; only human studies were selected. Case report studies were excluded. Two independent researchers selected the studies and extracted the data. Two studies were selected, four additional publications were recovered from the bibliography search of the selected articles, and one additional article was added through a manual search. The results of this systematic review demonstrate a relatively low rate of complications in segmental osteotomies, suggesting this surgical approach is safe and reliable in routine orthognathic surgery. Due to the small number of studies included in this systematic review, the rate of complication related to surgery first approach may be slightly higher than those associated with traditional orthognathic surgery, since the rate of complications of segmental osteotomies must be added to the complication rate of basal osteotomies. A surgery-first approach could be considered riskier than a traditional one, but further studies that include a greater number of subjects should be conducted to confirm these findings.

Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

Directory of Open Access Journals (Sweden)

Shuo-Tsung Chen

2015-01-01

Full Text Available Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Results. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Conclusion. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

Classifying and profiling Social Networking Site users: a latent segmentation approach.

Science.gov (United States)

Alarcón-del-Amo, María-del-Carmen; Lorenzo-Romero, Carlota; Gómez-Borja, Miguel-Ángel

2011-09-01

Social Networking Sites (SNSs) have showed an exponential growth in the last years. The first step for an efficient use of SNSs stems from an understanding of the individuals' behaviors within these sites. In this research, we have obtained a typology of SNS users through a latent segmentation approach, based on the frequency by which users perform different activities within the SNSs, sociodemographic variables, experience in SNSs, and dimensions related to their interaction patterns. Four different segments have been obtained. The "introvert" and "novel" users are the more occasional. They utilize SNSs mainly to communicate with friends, although "introverts" are more passive users. The "versatile" user performs different activities, although occasionally. Finally, the "expert-communicator" performs a greater variety of activities with a higher frequency. They tend to perform some marketing-related activities such as commenting on ads or gathering information about products and brands as well as commenting ads. The companies can take advantage of these segmentation schemes in different ways: first, by tracking and monitoring information interchange between users regarding their products and brands. Second, they should match the SNS users' profiles with their market targets to use SNSs as marketing tools. Finally, for most business, the expert users could be interesting opinion leaders and potential brand influencers.

A Segmental Approach with SWT Technique for Denoising the EOG Signal

Directory of Open Access Journals (Sweden)

Naga Rajesh

2015-01-01

Full Text Available The Electrooculogram (EOG signal is often contaminated with artifacts and power-line while recording. It is very much essential to denoise the EOG signal for quality diagnosis. The present study deals with denoising of noisy EOG signals using Stationary Wavelet Transformation (SWT technique by two different approaches, namely, increasing segments of the EOG signal and different equal segments of the EOG signal. For performing the segmental denoising analysis, an EOG signal is simulated and added with controlled noise powers of 5 dB, 10 dB, 15 dB, 20 dB, and 25 dB so as to obtain five different noisy EOG signals. The results obtained after denoising them are extremely encouraging. Root Mean Square Error (RMSE values between reference EOG signal and EOG signals with noise powers of 5 dB, 10 dB, and 15 dB are very less when compared with 20 dB and 25 dB noise powers. The findings suggest that the SWT technique can be used to denoise the noisy EOG signal with optimum noise powers ranging from 5 dB to 15 dB. This technique might be useful in quality diagnosis of various neurological or eye disorders.

A Semi-automated Approach to Improve the Efficiency of Medical Imaging Segmentation for Haptic Rendering.

Science.gov (United States)

Banerjee, Pat; Hu, Mengqi; Kannan, Rahul; Krishnaswamy, Srinivasan

2017-08-01

The Sensimmer platform represents our ongoing research on simultaneous haptics and graphics rendering of 3D models. For simulation of medical and surgical procedures using Sensimmer, 3D models must be obtained from medical imaging data, such as magnetic resonance imaging (MRI) or computed tomography (CT). Image segmentation techniques are used to determine the anatomies of interest from the images. 3D models are obtained from segmentation and their triangle reduction is required for graphics and haptics rendering. This paper focuses on creating 3D models by automating the segmentation of CT images based on the pixel contrast for integrating the interface between Sensimmer and medical imaging devices, using the volumetric approach, Hough transform method, and manual centering method. Hence, automating the process has reduced the segmentation time by 56.35% while maintaining the same accuracy of the output at ±2 voxels.

A Variational Level Set Approach Based on Local Entropy for Image Segmentation and Bias Field Correction.

Science.gov (United States)

Tang, Jian; Jiang, Xiaoliang

2017-01-01

Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.

Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

OpenAIRE

Shuo-Tsung Chen; Tzung-Dau Wang; Wen-Jeng Lee; Tsai-Wei Huang; Pei-Kai Hung; Cheng-Yu Wei; Chung-Ming Chen; Woon-Man Kung

2015-01-01

Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband c...

Vessel network detection using contour evolution and color components

Energy Technology Data Exchange (ETDEWEB)

Ushizima, Daniela; Medeiros, Fatima; Cuadros, Jorge; Martins, Charles

2011-06-22

Automated retinal screening relies on vasculature segmentation before the identification of other anatomical structures of the retina. Vasculature extraction can also be input to image quality ranking, neovascularization detection and image registration, among other applications. There is an extensive literature related to this problem, often excluding the inherent heterogeneity of ophthalmic clinical images. The contribution of this paper relies on an algorithm using front propagation to segment the vessel network. The algorithm includes a penalty in the wait queue on the fast marching heap to minimize leakage of the evolving interface. The method requires no manual labeling, a minimum number of parameters and it is capable of segmenting color ocular fundus images in real scenarios, where multi-ethnicity and brightness variations are parts of the problem.

Local approach of cleavage fracture applied to a vessel with subclad flaw. A benchmark on computational simulation

International Nuclear Information System (INIS)

Moinereau, D.; Brochard, J.; Guichard, D.; Bhandari, S.; Sherry, A.; France, C.

1996-10-01

A benchmark on the computational simulation of a cladded vessel with a 6.2 mm sub-clad flaw submitted to a thermal transient has been conducted. Two-dimensional elastic and elastic-plastic finite element computations of the vessel have been performed by the different partners with respective finite element codes ASTER (EDF), CASTEM 2000 (CEA), SYSTUS (Framatome) and ABAQUS (AEA Technology). Main results have been compared: temperature field in the vessel, crack opening, opening stress at crack tips, stress intensity factor in cladding and base metal, Weibull stress σ w and probability of failure in base metal, void growth rate R/R 0 in cladding. This comparison shows an excellent agreement on main results, in particular on results obtained with local approach. (K.A.)

Utilization of self-expanding stents in the treatment of intracranial atherosclerotic disease in the distal small cerebral vessels

International Nuclear Information System (INIS)

Turk, Aquilla S.; Niemann, David B.; Aagaard-Kienitz, Beverly; Ahmed, Azam; Brooks, Nathaniel; Levine, Ross L.

2007-01-01

Previously, endovascular treatment of stenosis related to intracranial atherosclerosis (ICAD) involving arteries measuring less than 2 mm in diameter was limited. To our knowledge, there are no reports in the literature addressing stent placement for treatment of stenosis in arteries of this size. Four patients aged 33 to 80 years (mean 57.5 years) with medically refractory ICAD underwent angioplasty and stenting of small (<2 mm) distal intracerebral arteries. Vessel location and length of follow-up were anterior cerebral artery (ACA) A1 segment (5 months), ACA A2 segment (18 months), middle cerebral artery M1 segment (18 months), and posterior cerebral artery P1 segment (8 months) with vessel calibers ranging from 1.2 to 1.8 mm. Clinical and imaging follow-up ranged from 5 to 18 months. All procedures were successfully performed without complications. Follow-up out to 18 months demonstrated one vessel that went on to occlusion while the other stented vessel segments remained patent. One patient died 8 months after stenting, but the death was not related to neurological disease. The remaining patients experienced resolution of the presenting symptomatology and remained asymptomatic throughout follow-up. In this small series, stenoses of distal (<2 mm) cerebral arteries were amenable to treatment using new self-expanding stents. We safely and successfully treated four arteries smaller than 2 mm in diameter with newer self-expanding stents. All patients remained clinically asymptomatic. One stent occluded at 5 months and the others remained patent during follow-up. Longer term clinical follow-up is required to determine the durability and viability of this therapy. (orig.)

Resection of Segments 4, 5 and 8 for a Cystic Liver Tumor Using the Double Liver Hanging Maneuver

Directory of Open Access Journals (Sweden)

Atsushi Nanashima

2008-03-01

Full Text Available To achieve complete anatomic central hepatectomy for a large tumor compressing surrounding vessels, transection by an anterior approach is preferred but a skillful technique is necessary. We propose the modified technique of Belghiti’s liver hanging maneuver (LHM. The case was a 77-year-old female with a 6-cm liver cystic tumor in the central liver compressing hilar vessels and the right hepatic vein. At the hepatic hilum, the spaces between Glisson’s pedicle and hepatic parenchyma were dissected, which were (1 the space between the right anterior and posterior Glisson pedicles and (2 the space adjacent to the umbilical Glisson pedicle. Two tubes were repositioned in each space and ‘double LHM’ was possible at the two resected planes of segments 4, 5 and 8. Cut planes were easily and adequately obtained and the compressed vessels were secured. Double LHM is a useful surgical technique for hepatectomy for a large tumor located in the central liver.

Segmentation of the Infant Food Market

OpenAIRE

Hrůzová, Daniela

2015-01-01

The theoretical part covers general market segmentation, namely the marketing importance of differences among consumers, the essence of market segmentation, its main conditions and the process of segmentation, which consists of four consecutive phases - defining the market, determining important criteria, uncovering segments and developing segment profiles. The segmentation criteria, segmentation approaches, methods and techniques for the process of market segmentation are also described in t...

Polynomial fuzzy model-based approach for underactuated surface vessels

DEFF Research Database (Denmark)

Khooban, Mohammad Hassan; Vafamand, Navid; Dragicevic, Tomislav

2018-01-01

The main goal of this study is to introduce a new polynomial fuzzy model-based structure for a class of marine systems with non-linear and polynomial dynamics. The suggested technique relies on a polynomial Takagi–Sugeno (T–S) fuzzy modelling, a polynomial dynamic parallel distributed compensation...... surface vessel (USV). Additionally, in order to overcome the USV control challenges, including the USV un-modelled dynamics, complex nonlinear dynamics, external disturbances and parameter uncertainties, the polynomial fuzzy model representation is adopted. Moreover, the USV-based control structure...... and a sum-of-squares (SOS) decomposition. The new proposed approach is a generalisation of the standard T–S fuzzy models and linear matrix inequality which indicated its effectiveness in decreasing the tracking time and increasing the efficiency of the robust tracking control problem for an underactuated...

Giant-cell arteritis. Concordance study between aortic CT angiography and FDG-PET/CT in detection of large-vessel involvement

International Nuclear Information System (INIS)

Boysson, Hubert de; Dumont, Anael; Boutemy, Jonathan; Maigne, Gwenola; Martin Silva, Nicolas; Sultan, Audrey; Bienvenu, Boris; Aouba, Achille; Liozon, Eric; Ly, Kim Heang; Lambert, Marc; Aide, Nicolas; Manrique, Alain

2017-01-01

The purpose of our study was to assess the concordance of aortic CT angiography (CTA) and FDG-PET/CT in the detection of large-vessel involvement at diagnosis in patients with giant-cell arteritis (GCA). We created a multicenter cohort of patients with GCA diagnosed between 2010 and 2015, and who underwent both FDG-PET/CT and aortic CTA before or in the first ten days following treatment introduction. Eight vascular segments were studied on each procedure. We calculated concordance between both imaging techniques in a per-patient and a per-segment analysis, using Cohen's kappa concordance index. We included 28 patients (21/7 women/men, median age 67 [56-82]). Nineteen patients had large-vessel involvement on PET/CT and 18 of these patients also presented positive findings on CTA. In a per-segment analysis, a median of 5 [1-7] and 3 [1-6] vascular territories were involved on positive PET/CT and CTA, respectively (p = 0.03). In qualitative analysis, i.e., positivity of the procedure suggesting a large-vessel involvement, the concordance rate between both procedures was 0.85 [0.64-1]. In quantitative analysis, i.e., per-segment analysis in both procedures, the global concordance rate was 0.64 [0.54-0.75]. Using FDG-PET/CT as a reference, CTA showed excellent sensitivity (95%) and specificity (100%) in a per-patient analysis. In a per-segment analysis, sensitivity and specificity were 61% and 97.9%, respectively. CTA and FDG-PET/CT were both able to detect large-vessel involvement in GCA with comparable results in a per-patient analysis. However, PET/CT showed higher performance in a per-segment analysis, especially in the detection of inflammation of the aorta's branches. (orig.)

Giant-cell arteritis. Concordance study between aortic CT angiography and FDG-PET/CT in detection of large-vessel involvement

Energy Technology Data Exchange (ETDEWEB)

Boysson, Hubert de; Dumont, Anael; Boutemy, Jonathan; Maigne, Gwenola; Martin Silva, Nicolas; Sultan, Audrey; Bienvenu, Boris; Aouba, Achille [Caen University Hospital, Department of Internal Medicine, Caen (France); Liozon, Eric; Ly, Kim Heang [Limoges University Hospital, Department of Internal Medicine, Limoges (France); Lambert, Marc [Lille University Hospital, Department of Internal Medicine, Lille (France); Aide, Nicolas [Caen University Hospital, Department of Nuclear Medicine, Caen (France); INSERM U1086 ' ' ANTICIPE' ' , Francois Baclesse Cancer Centre, Caen (France); Manrique, Alain [Caen University Hospital, Department of Nuclear Medicine, Caen (France); Normandy University, Caen (France)

2017-12-15

The purpose of our study was to assess the concordance of aortic CT angiography (CTA) and FDG-PET/CT in the detection of large-vessel involvement at diagnosis in patients with giant-cell arteritis (GCA). We created a multicenter cohort of patients with GCA diagnosed between 2010 and 2015, and who underwent both FDG-PET/CT and aortic CTA before or in the first ten days following treatment introduction. Eight vascular segments were studied on each procedure. We calculated concordance between both imaging techniques in a per-patient and a per-segment analysis, using Cohen's kappa concordance index. We included 28 patients (21/7 women/men, median age 67 [56-82]). Nineteen patients had large-vessel involvement on PET/CT and 18 of these patients also presented positive findings on CTA. In a per-segment analysis, a median of 5 [1-7] and 3 [1-6] vascular territories were involved on positive PET/CT and CTA, respectively (p = 0.03). In qualitative analysis, i.e., positivity of the procedure suggesting a large-vessel involvement, the concordance rate between both procedures was 0.85 [0.64-1]. In quantitative analysis, i.e., per-segment analysis in both procedures, the global concordance rate was 0.64 [0.54-0.75]. Using FDG-PET/CT as a reference, CTA showed excellent sensitivity (95%) and specificity (100%) in a per-patient analysis. In a per-segment analysis, sensitivity and specificity were 61% and 97.9%, respectively. CTA and FDG-PET/CT were both able to detect large-vessel involvement in GCA with comparable results in a per-patient analysis. However, PET/CT showed higher performance in a per-segment analysis, especially in the detection of inflammation of the aorta's branches. (orig.)

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

Science.gov (United States)

Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

Fully automatic algorithm for the analysis of vessels in the angiographic image of the eye fundus

Directory of Open Access Journals (Sweden)

Koprowski Robert

2012-06-01

Full Text Available Abstract Background The available scientific literature contains descriptions of manual, semi-automated and automated methods for analysing angiographic images. The presented algorithms segment vessels calculating their tortuosity or number in a given area. We describe a statistical analysis of the inclination of the vessels in the fundus as related to their distance from the center of the optic disc. Methods The paper presents an automated method for analysing vessels which are found in angiographic images of the eye using a Matlab implemented algorithm. It performs filtration and convolution operations with suggested masks. The result is an image containing information on the location of vessels and their inclination angle in relation to the center of the optic disc. This is a new approach to the analysis of vessels whose usefulness has been confirmed in the diagnosis of hypertension. Results The proposed algorithm analyzed and processed the images of the eye fundus using a classifier in the form of decision trees. It enabled the proper classification of healthy patients and those with hypertension. The result is a very good separation of healthy subjects from the hypertensive ones: sensitivity - 83%, specificity - 100%, accuracy - 96%. This confirms a practical usefulness of the proposed method. Conclusions This paper presents an algorithm for the automatic analysis of morphological parameters of the fundus vessels. Such an analysis is performed during fluorescein angiography of the eye. The presented algorithm automatically calculates the global statistical features connected with both tortuosity of vessels and their total area or their number.

A decision-theoretic approach for segmental classification

OpenAIRE

Yau, Christopher; Holmes, Christopher C.

2013-01-01

This paper is concerned with statistical methods for the segmental classification of linear sequence data where the task is to segment and classify the data according to an underlying hidden discrete state sequence. Such analysis is commonplace in the empirical sciences including genomics, finance and speech processing. In particular, we are interested in answering the following question: given data $y$ and a statistical model $\\pi(x,y)$ of the hidden states $x$, what should we report as the ...

Remote Sensing Image Fusion at the Segment Level Using a Spatially-Weighted Approach: Applications for Land Cover Spectral Analysis and Mapping

Directory of Open Access Journals (Sweden)

Brian Johnson

2015-01-01

Full Text Available Segment-level image fusion involves segmenting a higher spatial resolution (HSR image to derive boundaries of land cover objects, and then extracting additional descriptors of image segments (polygons from a lower spatial resolution (LSR image. In past research, an unweighted segment-level fusion (USF approach, which extracts information from a resampled LSR image, resulted in more accurate land cover classification than the use of HSR imagery alone. However, simply fusing the LSR image with segment polygons may lead to significant errors due to the high level of noise in pixels along the segment boundaries (i.e., pixels containing multiple land cover types. To mitigate this, a spatially-weighted segment-level fusion (SWSF method was proposed for extracting descriptors (mean spectral values of segments from LSR images. SWSF reduces the weights of LSR pixels located on or near segment boundaries to reduce errors in the fusion process. Compared to the USF approach, SWSF extracted more accurate spectral properties of land cover objects when the ratio of the LSR image resolution to the HSR image resolution was greater than 2:1, and SWSF was also shown to increase classification accuracy. SWSF can be used to fuse any type of imagery at the segment level since it is insensitive to spectral differences between the LSR and HSR images (e.g., different spectral ranges of the images or different image acquisition dates.

Deformable meshes for medical image segmentation accurate automatic segmentation of anatomical structures

CERN Document Server

Kainmueller, Dagmar

2014-01-01

? Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author's core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatom

Segmenting hospitals for improved management strategy.

Science.gov (United States)

Malhotra, N K

1989-09-01

The author presents a conceptual framework for the a priori and clustering-based approaches to segmentation and evaluates them in the context of segmenting institutional health care markets. An empirical study is reported in which the hospital market is segmented on three state-of-being variables. The segmentation approach also takes into account important organizational decision-making variables. The sophisticated Thurstone Case V procedure is employed. Several marketing implications for hospitals, other health care organizations, hospital suppliers, and donor publics are identified.

Long term integrity of reactor pressure vessel and primary containment vessel after the severe accidents in Fukushima Daiichi Nuclear Power Station. Leaching property of spent oxide fuel segment and corrosion property of a carbon steel under artificial seawater immersion

International Nuclear Information System (INIS)

2014-06-01

Primary containment vessel (PCV), reactor pressure vessel and pedestal in Fukushima Daiichi Nuclear power station units 1 through 3 have been exposed to severe thermal, chemical and mechanical conditions due to core meltdown events and seawater injections for emergent core cooling. These components will be immersed in diluted seawater with dissolved fission products under irradiation until the end of debris removal. Fresh water injected into the cores contacts with debris to cool, dissolves or erodes their constituents, mixed with retained water, and becomes 'accumulated water' with radioactive nuclides. We have focused the leaching of fission products into the accumulated water under lower temperature (323 K). FUGEN spent oxide fuel segments were immersed to determine the leaching factor of fission product and actinide elements. Since PCV made from carbon steel is one of the most important boundaries to prevent from fission products release, corrosion behavior has been paid attention to evaluate their integrity. Carbon steel specimens were immersion- and electrochemical-tested in diluted seawater with simulants of the accumulated water at 323 K in order to evaluate the effect of fission products in particular cesium and radiation. (author)

An Approach to a Comprehensive Test Framework for Analysis and Evaluation of Text Line Segmentation Algorithms

Directory of Open Access Journals (Sweden)

Zoran N. Milivojevic

2011-09-01

Full Text Available The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.

Value and limitations of segmental analysis of stress thallium myocardial imaging for localization of coronary artery disease

International Nuclear Information System (INIS)

Rigo, P.; Bailey, I.K.; Griffith, L.S.C.; Pitt, B.; Borow, R.D.; Wagner, H.N.; Becker, L.C.

1980-01-01

This study was done to determine the value of thallium-201 myocardial scintigraphic imaging (MSI) for identifying disease in the individual coronary arteries. Segmental analysis of rest and stress MSI was performed in 133 patients with ateriographically proved coronary artery disease (CAD). Certain scintigraphic segments were highly specific (97 to 100%) for the three major coronary arteries: anterior wall and septum for the left anterior descending (LAD) coronary artery; the inferior wall for the right coronary artery (RCA); and the proximal lateral wall for the circumflex (LCX) artery. Perfusion defects located in the anterolateral wall in the anterior view were highly specific for proximal disease in the LAD involving the major diagonal branches, but this was not true for septal defects. The apical segments were not specific for any of the three major vessels. Although MSI was abnormal in 89% of these patients with CAD, it was less sensitive for identifying individual vessel disease: 63% for LAD, 50% for RCA, and 21% for LCX disease (narrowings > = 50%). Sensitivity increased with the severity of stenosis, but even for 100% occlusions was only 87% for LAD, 58% for RCA and 38% for LCX. Sensitivity diminished as the number of vessels involved increased: with single-vessel disease, 80% of LAD, 54% of RAC and 33% of LCX lesions were detected, but in patients with triple-vessel disease, only 50% of LAD, 50% of RCA and 16% of LCX lesions were identified. Thus, although segmented analysis of MSI can identify disease in the individual coronary arteries with high specificity, only moderate sensitivity is achieved, reflecting the tendency of MSI to identify only the most severely ischemic area among several that may be present in a heart. Perfusion scintigrams display relative distributions rather than absolute values for myocardial blood flow

Short time effects of radiotherapy on lymphatic vessels and restorative lymphatic pathways: experimental approaches ina mouse model.

Science.gov (United States)

Pastouret, F; Lievens, P; Leduc, O; Bourgeois, P; Tournel, K; Lamote, J; Zirak, C; Leduc, A

2014-06-01

Radiotherapy (RT) is an important component in the therapeutic approach to oncologic conditions. This study presents the investigative results on the impact of RT on lymphatic vessels and on the regenerative response of the lymphatic system in a mouse model. We first irradiated 3 groups of ten mice using brachytherapy in a single treatment of 20 Gy. We then performed morphological examination of the irradiated lymphatic vessels using an in vivo microscopic transillumination technique at 2, 4, and 6 weeks. Next we evaluated lymphatic flow using lymphoscintigraphy and in vivo microscopy at 6 to 11 weeks in: 10 additional mice following irradiation as above (IR), in 10 mice following incision of a lymphatic vessel (I), and in a non-treated control group of 10 mice (N). Intact lymphatic vessels were observed in all mice at 2, 4, and 8 weeks following the single dose of radiotherapy in the first group of mice and normal lymphatic flow was fully restored in the irradiated (IR) and incised (I) mice indicating that the reparative substitution lymphatic pathways are functioning normally. We found that following irradiation with one dose of 20 Gy, lymphatic vessels were not visibly damaged and also that lymphatic flow was consistently restored and substitutive lymphatic pathways formed.

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

Energy Technology Data Exchange (ETDEWEB)

Zhou, Chuan, E-mail: chuan@umich.edu; Chan, Heang-Ping; Hadjiyski, Lubomir M.; Chughtai, Aamer; Wei, Jun; Kazerooni, Ella A. [Department of Radiology, The University of Michigan, Ann Arbor, Michigan 48109-0904 (United States)

2016-10-15

Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment

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

International Nuclear Information System (INIS)

Zhou, Chuan; Chan, Heang-Ping; Hadjiyski, Lubomir M.; Chughtai, Aamer; Wei, Jun; Kazerooni, Ella A.

2016-01-01

Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment

Cutting Technology for Decommissioning of the Reactor Pressure Vessels in Nuclear Power Plants

International Nuclear Information System (INIS)

Jeong, Kwan Seong; Kim, Geun Ho; Moon, Jei Kwon; Choi, Byung Seon

2012-01-01

Lots of nuclear power plants have been decommissioned during the last 2 decades. An essential part of this work is the dismantling of the Reactor Pressure Vessel and its Internals. For this purpose a wide variety of different cutting technologies have been developed, adapted and applied. A detailed introduction to Plasma Arc cutting, Contact Arc Metal cutting and Abrasive Water Suspension Jet cutting is given, as it turned out that these cutting technologies are particularly suitable for these type of segmentation work. A comparison of these technologies including gaseous emissions, cutting power, manipulator requirements as well as selected design approaches are given. Process limits as well as actual limits of application are presented

Scorpion image segmentation system

Science.gov (United States)

Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Bello Salau, H.; Salami, M. J. E.

2013-12-01

Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.

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

Science.gov (United States)

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

2018-04-01

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

Form Follows Function. A new approach to determining vessel function

Directory of Open Access Journals (Sweden)

Vincent van der Veen

2018-05-01

Full Text Available In this article I present a theoretical model for assigning functions to categories of Roman ceramics. This model was designed to make broad statements about assemblages that are too large to analyse in detail. It is therefore based on the 'ideal use' of a vessel - i.e. the function the potter had in mind when he chose the clay, temper, forming techniques and so on - rather than 'non-ideal' or actual use. Characteristics considered are, among others, shape, size, weight, surface treatment and wall thickness. Seven distinct functions have been identified, taking the inherent multi-functionality of certain vessels into account. In many cases an individual vessel type will be suitable for more than one function. In a case study the commonly made functional distinction between smooth-tempered one-handled flagons (kruiken as tableware and two-handled flagons (kruikamforen as storage vessels is challenged. Furthermore, differences in their deposition within both grave and settlement assemblages are explored.

Enhancement of nerve structure segmentation by a correntropy-based pre-image approach

Directory of Open Access Journals (Sweden)

J. Gil-González

2017-05-01

Full Text Available Peripheral Nerve Blocking (PNB is a commonly used technique for performing regional anesthesia and managing pain. PNB comprises the administration of anesthetics in the proximity of a nerve. In this sense, the success of PNB procedures depends on an accurate location of the target nerve. Recently, ultrasound images (UI have been widely used to locate nerve structures for PNB, since they enable a noninvasive visualization of the target nerve and the anatomical structures around it. However, UI are affected by speckle noise, which makes it difficult to accurately locate a given nerve. Thus, it is necessary to perform a filtering step to attenuate the speckle noise without eliminating relevant anatomical details that are required for high-level tasks, such as segmentation of nerve structures. In this paper, we propose an UI improvement strategy with the use of a pre-image-based filter. In particular, we map the input images by a nonlinear function (kernel. Specifically, we employ a correntropybased mapping as kernel functional to code higher-order statistics of the input data under both nonlinear and non-Gaussian conditions. We validate our approach against an UI dataset focused on nerve segmentation for PNB. Likewise, our Correntropy-based Pre-Image Filtering (CPIF is applied as a pre-processing stage to segment nerve structures in a UI. The segmentation performance is measured in terms of the Dice coefficient. According to the results, we observe that CPIF finds a suitable approximation for UI by highlighting discriminative nerve patterns.

Distribution of Different Sized Ocular Surface Vessels in Diabetics and Normal Individuals.

Science.gov (United States)

Banaee, Touka; Pourreza, Hamidreza; Doosti, Hassan; Abrishami, Mojtaba; Ehsaei, Asieh; Basiry, Mohsen; Pourreza, Reza

2017-01-01

To compare the distribution of different sized vessels using digital photographs of the ocular surface of diabetic and normal individuals. In this cross-sectional study, red-free conjunctival photographs of diabetic and normal individuals, aged 30-60 years, were taken under defined conditions and analyzed using a Radon transform-based algorithm for vascular segmentation. The image areas occupied by vessels (AOV) of different diameters were calculated. The main outcome measure was the distribution curve of mean AOV of different sized vessels. Secondary outcome measures included total AOV and standard deviation (SD) of AOV of different sized vessels. Two hundred and sixty-eight diabetic patients and 297 normal (control) individuals were included, differing in age (45.50 ± 5.19 vs. 40.38 ± 6.19 years, P distribution curves of mean AOV differed between patients and controls (smaller AOV for larger vessels in patients; P distribution curve of vessels compared to controls. Presence of diabetes mellitus is associated with contraction of larger vessels in the conjunctiva. Smaller vessels dilate with diabetic retinopathy. These findings may be useful in the photographic screening of diabetes mellitus and retinopathy.

Evaluation of WWER-1000 vessel materials fracture toughness

International Nuclear Information System (INIS)

Grinik, Eh.U.; Revka, V.N.; Chirko, L.I.; Chajkovskij, Yu.V.

2007-01-01

The lifetime of WWER-1000-type reactor vessels is finally conditioned by the fracture toughness (crack growth resistance) of RPV materials. Up to now in line with the regulations the fracture toughness is characterized by the critical temperature of brittleness determined by the results of the Charpy specimen impact testing. Such approach is typical for all countries operating the water pressure reactors. However, regulatory approach is known from the western specialists not always to characterize adequately the crack growth resistance of the vessel materials and in some cases to underestimate their characteristics in the reference state that leads to unreasonably high conservatism. Excessive conservatism may lead to the invalid restrictions in the operating modes and the service life of the reactor vessel. Therefore there appeared the necessity to apply another approaches based on the state-of-the-art experimental methods of the fracture mechanics and allowing evaluating the fracture toughness parameters sufficiently. The paper presents the results of the comparison of the regulatory approach and the Master curve approach from the point of view of the adequate determination of the vessel material crack growth resistance parameters. Analysis of the experimental data of the surveillance specimens illustrated the potential possibility of applying the new statistical method for the WWER-1000- type reactor vessel lifetime extension

Quantification of Tumor Vessels in Glioblastoma Patients Using Time-of-Flight Angiography at 7 Tesla: A Feasibility Study

Science.gov (United States)

Radbruch, Alexander; Eidel, Oliver; Wiestler, Benedikt; Paech, Daniel; Burth, Sina; Kickingereder, Philipp; Nowosielski, Martha; Bäumer, Philipp; Wick, Wolfgang; Schlemmer, Heinz-Peter; Bendszus, Martin; Ladd, Mark; Nagel, Armin Michael; Heiland, Sabine

2014-01-01

Purpose To analyze if tumor vessels can be visualized, segmented and quantified in glioblastoma patients with time of flight (ToF) angiography at 7 Tesla and multiscale vessel enhancement filtering. Materials and Methods Twelve patients with newly diagnosed glioblastoma were examined with ToF angiography (TR = 15 ms, TE = 4.8 ms, flip angle = 15°, FOV = 160×210 mm2, voxel size: 0.31×0.31×0.40 mm3) on a whole-body 7 T MR system. A volume of interest (VOI) was placed within the border of the contrast enhancing part on T1-weighted images of the glioblastoma and a reference VOI was placed in the non-affected contralateral white matter. Automated segmentation and quantification of vessels within the two VOIs was achieved using multiscale vessel enhancement filtering in ImageJ. Results Tumor vessels were clearly visible in all patients. When comparing tumor and the reference VOI, total vessel surface (45.3±13.9 mm2 vs. 29.0±21.0 mm2 (pTesla MRI enables characterization and quantification of the internal vascular morphology of glioblastoma and may be used for the evaluation of therapy response within future studies. PMID:25415327

MULTISPECTRAL PANSHARPENING APPROACH USING PULSE-COUPLED NEURAL NETWORK SEGMENTATION

Directory of Open Access Journals (Sweden)

X. J. Li

2018-04-01

Full Text Available The paper proposes a novel pansharpening method based on the pulse-coupled neural network segmentation. In the new method, uniform injection gains of each region are estimated through PCNN segmentation rather than through a simple square window. Since PCNN segmentation agrees with the human visual system, the proposed method shows better spectral consistency. Our experiments, which have been carried out for both suburban and urban datasets, demonstrate that the proposed method outperforms other methods in multispectral pansharpening.

Segmenting articular cartilage automatically using a voxel classification approach

DEFF Research Database (Denmark)

Folkesson, Jenny; Dam, Erik B; Olsen, Ole F

2007-01-01

We present a fully automatic method for articular cartilage segmentation from magnetic resonance imaging (MRI) which we use as the foundation of a quantitative cartilage assessment. We evaluate our method by comparisons to manual segmentations by a radiologist and by examining the interscan...... reproducibility of the volume and area estimates. Training and evaluation of the method is performed on a data set consisting of 139 scans of knees with a status ranging from healthy to severely osteoarthritic. This is, to our knowledge, the only fully automatic cartilage segmentation method that has good...... agreement with manual segmentations, an interscan reproducibility as good as that of a human expert, and enables the separation between healthy and osteoarthritic populations. While high-field scanners offer high-quality imaging from which the articular cartilage have been evaluated extensively using manual...

Novel Computerized Method for Measurement of Retinal Vessel Diameters

Directory of Open Access Journals (Sweden)

Hichem Guedri

2017-03-01

Full Text Available Several clinical studies reveal the relationship between alterations in the topologies of the human retinal blood vessel, the outcrop and the disease evolution, such as diabetic retinopathy, hypertensive retinopathy, and macular degeneration. Indeed, the detection of these vascular changes always has gaps. In addition, the manual steps are slow, which may be subjected to a bias of the perceiver. However, we can overcome these troubles using computer algorithms that are quicker and more accurate. This paper presents and investigates a novel method for measuring the blood vessel diameter in the retinal image. The proposed method is based on a thresholding segmentation and thinning step, followed by the characteristic point determination step by the Douglas-Peucker algorithm. Thereafter, it uses the active contours to detect vessel contour. Finally, Heron’s Formula is applied to assure the calculation of vessel diameter. The obtained results for six sample images showed that the proposed method generated less errors compared to other techniques, which confirms the high performance of the proposed method.

Vessel head penetrations: French approach for maintenance in the PLIM program

International Nuclear Information System (INIS)

Champigny, F.

2002-01-01

Full text: In 1991, in the Bugey nuclear power plant, for the first time a leak occurred at the level of a vessel head penetration made with base nickel alloy (Inconel 600). This leak was caused by a primary stress corrosion cracking coming from inside the penetration tube. The crack was trough wall extent and primary fluid went out from the top of the vessel head. Immediately, Electricite de France launched important research programs and expertise in order to understand the root causes and propose solutions to this problem. The root causes confirmed PWSCC, and in the same time solutions for repair were studied and an inspection program was established to check the base metal of other vessel head penetrations. After several tests, repair solutions were abandoned because of their high costs (financial and dosimetry). EDF decided to replace all the vessel heads with Inconel 600 penetrations. Non destructive developments leaded to use eddy currents for detection and characterization but also televisual techniques to confirm. In a second step, in order to inspect without removing the inside thermal sleeve, eddy current and ultrasonic sword probes were achieved and used to inspect all vessel heads penetrations. Up to now, 75% of the vessel head have been replaced on the 900 MW and 1300 MW fleets but to replace wisely the last vessel heads EDF continues to perform NDE of the penetrations on the basis of safety criteria. This paper describes the different steps of the applied policy in France, NDE methods, criteria and the results obtained. (author)

Market segmentation in behavioral perspective.

OpenAIRE

Wells, V.K.; Chang, S.W.; Oliveira-Castro, J.M.; Pallister, J.

2010-01-01

A segmentation approach is presented using both traditional demographic segmentation bases (age, social class/occupation, and working status) and a segmentation by benefits sought. The benefits sought in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (BPM). Using data from 1,847 consumers and from a total of 76,682 individual purchases, brand choice and price and reinforcement responsiveness were assessed for each segment a...

Contour tracing for segmentation of mammographic masses

International Nuclear Information System (INIS)

Elter, Matthias; Held, Christian; Wittenberg, Thomas

2010-01-01

CADx systems have the potential to support radiologists in the difficult task of discriminating benign and malignant mammographic lesions. The segmentation of mammographic masses from the background tissue is an important module of CADx systems designed for the characterization of mass lesions. In this work, a novel approach to this task is presented. The segmentation is performed by automatically tracing the mass' contour in-between manually provided landmark points defined on the mass' margin. The performance of the proposed approach is compared to the performance of implementations of three state-of-the-art approaches based on region growing and dynamic programming. For an unbiased comparison of the different segmentation approaches, optimal parameters are selected for each approach by means of tenfold cross-validation and a genetic algorithm. Furthermore, segmentation performance is evaluated on a dataset of ROI and ground-truth pairs. The proposed method outperforms the three state-of-the-art methods. The benchmark dataset will be made available with publication of this paper and will be the first publicly available benchmark dataset for mass segmentation.

Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

Science.gov (United States)

Weijers, Gert; Starke, Alexander; Haudum, Alois; Thijssen, Johan M; Rehage, Jürgen; De Korte, Chris L

2010-07-01

The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty liver disease, to test this hypothesis. Five transcutaneous and five intraoperative US liver images were acquired in each animal and a liverbiopsy was taken. In liver tissue samples, triacylglycerol (TAG) was measured by biochemical analysis and hepatic diseases other than hepatic lipidosis were excluded by histopathologic examination. Ultrasonic tissue characterization (UTC) parameters--Mean echo level, standard deviation (SD) of echo level, signal-to-noise ratio (SNR), residual attenuation coefficient (ResAtt) and axial and lateral speckle size--were derived using a computer-aided US (CAUS) protocol and software package. First, the liver tissue was interactively segmented by two observers. With increasing fat content, fewer hepatic vessels were visible in the ultrasound images and, therefore, a smaller proportion of the liver needed to be excluded from these images. Automatic-segmentation algorithms were implemented and it was investigated whether better results could be achieved than with the subjective and time-consuming interactive-segmentation procedure. The automatic-segmentation algorithms were based on both fixed and adaptive thresholding techniques in combination with a 'speckle'-shaped moving-window exclusion technique. All data were analyzed with and without postprocessing as contained in CAUS and with different automated-segmentation techniques. This enabled us to study the effect of the applied postprocessing steps on single and multiple linear regressions ofthe various UTC parameters with TAG. Improved correlations for all US parameters were found by using automatic-segmentation techniques. Stepwise multiple linear-regression formulas where derived and used

Automatic segmentation of colon glands using object-graphs.

Science.gov (United States)

Gunduz-Demir, Cigdem; Kandemir, Melih; Tosun, Akif Burak; Sokmensuer, Cenk

2010-02-01

Gland segmentation is an important step to automate the analysis of biopsies that contain glandular structures. However, this remains a challenging problem as the variation in staining, fixation, and sectioning procedures lead to a considerable amount of artifacts and variances in tissue sections, which may result in huge variances in gland appearances. In this work, we report a new approach for gland segmentation. This approach decomposes the tissue image into a set of primitive objects and segments glands making use of the organizational properties of these objects, which are quantified with the definition of object-graphs. As opposed to the previous literature, the proposed approach employs the object-based information for the gland segmentation problem, instead of using the pixel-based information alone. Working with the images of colon tissues, our experiments demonstrate that the proposed object-graph approach yields high segmentation accuracies for the training and test sets and significantly improves the segmentation performance of its pixel-based counterparts. The experiments also show that the object-based structure of the proposed approach provides more tolerance to artifacts and variances in tissues.

Classifier Directed Data Hybridization for Geographic Sample Supervised Segment Generation

Directory of Open Access Journals (Sweden)

Christoff Fourie

2014-11-01

Full Text Available Quality segment generation is a well-known challenge and research objective within Geographic Object-based Image Analysis (GEOBIA. Although methodological avenues within GEOBIA are diverse, segmentation commonly plays a central role in most approaches, influencing and being influenced by surrounding processes. A general approach using supervised quality measures, specifically user provided reference segments, suggest casting the parameters of a given segmentation algorithm as a multidimensional search problem. In such a sample supervised segment generation approach, spatial metrics observing the user provided reference segments may drive the search process. The search is commonly performed by metaheuristics. A novel sample supervised segment generation approach is presented in this work, where the spectral content of provided reference segments is queried. A one-class classification process using spectral information from inside the provided reference segments is used to generate a probability image, which in turn is employed to direct a hybridization of the original input imagery. Segmentation is performed on such a hybrid image. These processes are adjustable, interdependent and form a part of the search problem. Results are presented detailing the performances of four method variants compared to the generic sample supervised segment generation approach, under various conditions in terms of resultant segment quality, required computing time and search process characteristics. Multiple metrics, metaheuristics and segmentation algorithms are tested with this approach. Using the spectral data contained within user provided reference segments to tailor the output generally improves the results in the investigated problem contexts, but at the expense of additional required computing time.

Fold distributions at clover, crystal and segment levels for segmented clover detectors

International Nuclear Information System (INIS)

Kshetri, R; Bhattacharya, P

2014-01-01

Fold distributions at clover, crystal and segment levels have been extracted for an array of segmented clover detectors for various gamma energies. A simple analysis of the results based on a model independant approach has been presented. For the first time, the clover fold distribution of an array and associated array addback factor have been extracted. We have calculated the percentages of the number of crystals and segments that fire for a full energy peak event

Probabilistic Segmentation of Folk Music Recordings

Directory of Open Access Journals (Sweden)

Ciril Bohak

2016-01-01

Full Text Available The paper presents a novel method for automatic segmentation of folk music field recordings. The method is based on a distance measure that uses dynamic time warping to cope with tempo variations and a dynamic programming approach to handle pitch drifting for finding similarities and estimating the length of repeating segment. A probabilistic framework based on HMM is used to find segment boundaries, searching for optimal match between the expected segment length, between-segment similarities, and likely locations of segment beginnings. Evaluation of several current state-of-the-art approaches for segmentation of commercial music is presented and their weaknesses when dealing with folk music are exposed, such as intolerance to pitch drift and variable tempo. The proposed method is evaluated and its performance analyzed on a collection of 206 folk songs of different ensemble types: solo, two- and three-voiced, choir, instrumental, and instrumental with singing. It outperforms current commercial music segmentation methods for noninstrumental music and is on a par with the best for instrumental recordings. The method is also comparable to a more specialized method for segmentation of solo singing folk music recordings.

Materials requirements for the ITER vacuum vessel and in-vessel components - approaching the construction phase

International Nuclear Information System (INIS)

Barabash, V.; Ioki, K.; Pick, M.; Girard, J.P.; Merola, M.

2007-01-01

Full text of publication follows: The ITER activities are fully devoted toward its construction. In accordance with the ITER integrated project schedule, the procurement specifications for the manufacturing of the Vacuum Vessel should be prepared by March 2008 and the procurement specifications for the in-vessel components (first wall/blanket, divertor) by 2009. To update the design, considering design and technology evolution, the ITER Design Review has been launched. Among the various topics being discussed are the important issues related to selection of materials, material procurement, and assessment of performance during operation. The main requirements related to materials for the vacuum vessel and the in-vessel components are summarized in the paper. The specific licensing requirements are to be followed for structural materials of pressure and nuclear pressure equipment components for construction of ITER. In addition, the procurements in ITER will be done mostly 'in-kind' and it is assumed that materials for these components will be produced by different Parties. However, in accordance with the regulatory requirements and quality requirements for operation, common specifications and the general rules to fulfill these requirements are to be adopted. For some ITER components (e.g. first wall, divertor high heat flux components), the ultimate qualification of the joining technologies (Be/Cu, SS/Cu, CFC/Cu, W/Cu) is under final evaluation. Successful accomplishment of the qualification program will allow to proceed with procurements of the components for ITER. The criteria for acceptance of these components and materials after manufacturing are described and the main results will be reported. Additional materials issues, which come from the on-going manufacturing R and D program, will be also described. Finally, further materials activity during the construction phase, needs for final qualification and acceptance of materials are discussed. (authors)

Initiation and arrest - two approaches to pressure vessel safety

International Nuclear Information System (INIS)

Brumovsky, M.; Filip, R.; Stepanek, S.

1976-01-01

The safety analysis is described of the reactor pressure vessel related to brittle fracture based on the fracture mechanics theory using two different approximations, i.e., the Crack Arrest Temperature (CAT) or Nil Ductility Temperature (NDT), and fracture toughness. The variation of CAT with stress was determined for different steel specimens of 120 to 200 mm in thickness. A diagram is shown of CAT variation with stress allowing the determination of crack arrest temperature for all types of commonly used steels independently of the NDT initial value. The diagram also shows that the difference between fracture transition elastic (FTE) and NDT depends on the type of material and determines the value of the ΔTsub(sigma) factor typical of the safety coefficient. The so-called fracture toughness reference value Ksub(IR) is recommended for the computation of pressure vessel criticality. Also shown is a defect analysis diagram which may be used for the calculation of pressure vessel safety prior to and during operation and which may also be used in making the decision on what crack sizes are critical, what cracks may be arrested and what cracks are likely to expand. The diagram is also important for the fact that it is material-independent and may be employed for the estimates of pre-operational and operational inspections and for pressure vessel life prediction. It is generally applicable to materials of greater thickness in the region where the validity of linear elastic fracture mechanics is guaranteed. (J.P.)

Color Segmentation Approach of Infrared Thermography Camera Image for Automatic Fault Diagnosis

International Nuclear Information System (INIS)

Djoko Hari Nugroho; Ari Satmoko; Budhi Cynthia Dewi

2007-01-01

Predictive maintenance based on fault diagnosis becomes very important in current days to assure the availability and reliability of a system. The main purpose of this research is to configure a computer software for automatic fault diagnosis based on image model acquired from infrared thermography camera using color segmentation approach. This technique detects hot spots in equipment of the plants. Image acquired from camera is first converted to RGB (Red, Green, Blue) image model and then converted to CMYK (Cyan, Magenta, Yellow, Key for Black) image model. Assume that the yellow color in the image represented the hot spot in the equipment, the CMYK image model is then diagnosed using color segmentation model to estimate the fault. The software is configured utilizing Borland Delphi 7.0 computer programming language. The performance is then tested for 10 input infrared thermography images. The experimental result shows that the software capable to detect the faulty automatically with performance value of 80 % from 10 sheets of image input. (author)

Measuring tourist satisfaction: a factor-cluster segmentation approach

OpenAIRE

Andriotis, Konstantinos; Agiomirgianakis, George; Mihiotis, Athanasios

2008-01-01

Tourist satisfaction has been considered as a tool for increasing destination competitiveness. In an attempt to gain a better understanding of tourists’ satisfaction in an island mass destination this study has taken Crete as a case with the aim to identify the underlying dimensions of tourists’ satisfaction, to investigate whether tourists could be grouped into distinct segments and to examine the significant difference between the segments and sociodemographic and travel arrangement charact...

Subintimal angioplasty for the treatment of long segment occlusion of superficial femoral artery: the midterm results

International Nuclear Information System (INIS)

Lou Wensheng; Gu Jianping; He Xu; Chen Liang; Chen Guoping; Su Haobo; Song Jinhua; Wang Tao; Xu Ke

2011-01-01

Objective: To discuss the clinical value of subintimal angioplasty in treating long segment occlusion of superficial femoral artery and to observe its midterm results. Methods: Subintimal angioplasty was performed in 45 patients with long segment occlusion of superficial femoral artery, whose clinical presentation was intermittent claudication or critical limb ischemia. The primary patency, limb salvage and factors influencing long-term patency were observed, and the clinical data were analyzed. Results: Of the total 45 cases, the subintimal angioplasty was successfully accomplished in 43. The success rate of antegrade approach technique via the superficial femoral artery was 80% (n=36), the occlusion was recanalized by using retrograde approach technique via ipsilateral popliteal artery in 7 case. The total technical success rate was 95.6%. The primary patency in 43 successful cases at 6, 12, 24 and 36 months was 85.7%, 69.0% 57.3% and 50.9%, respectively. No statistically significant difference in primary patency existed between the group of intermittent claudication and the group of critical limb ischemia (P>0.05). Statistically significant prediction factors for primary patency included the number of the run off vessels below the knee and the length of the occlusion (P<0.05). Conclusion: Subintimal angioplasty is an effective procedure for the treatment of long segment occlusions of superficial femoral artery with satisfactory mid-term results. (authors)

Pyramidal approach to license plate segmentation

Science.gov (United States)

Postolache, Alexandru; Trecat, Jacques C.

1996-07-01

Car identification is a goal in traffic control, transport planning, travel time measurement, managing parking lot traffic and so on. Most car identification algorithms contain a standalone plate segmentation process followed by a plate contents reading. A pyramidal algorithm for license plate segmentation, looking for textured regions, has been developed on a PC based system running Unix. It can be used directly in applications not requiring real time. When input images are relatively small, real-time performance is in fact accomplished by the algorithm. When using large images, porting the algorithm to special digital signal processors can easily lead to preserving real-time performance. Experimental results, for stationary and moving cars in outdoor scenes, showed high accuracy and high scores in detecting the plate. The algorithm also deals with cases where many character strings are present in the image, and not only the one corresponding to the plate. This is done by the means of a constrained texture regions classification.

Quantification and visualization of carotid segmentation accuracy and precision using a 2D standardized carotid map

International Nuclear Information System (INIS)

Chiu, Bernard; Ukwatta, Eranga; Shavakh, Shadi; Fenster, Aaron

2013-01-01

This paper describes a framework for vascular image segmentation evaluation. Since the size of vessel wall and plaque burden is defined by the lumen and wall boundaries in vascular segmentation, these two boundaries should be considered as a pair in statistical evaluation of a segmentation algorithm. This work proposed statistical metrics to evaluate the difference of local vessel wall thickness (VWT) produced by manual and algorithm-based semi-automatic segmentation methods (ΔT) with the local segmentation standard deviation of the wall and lumen boundaries considered. ΔT was further approximately decomposed into the local wall and lumen boundary differences (ΔW and ΔL respectively) in order to provide information regarding which of the wall and lumen segmentation errors contribute more to the VWT difference. In this study, the lumen and wall boundaries in 3D carotid ultrasound images acquired for 21 subjects were each segmented five times manually and by a level-set segmentation algorithm. The (absolute) difference measures (i.e., ΔT, ΔW, ΔL and their absolute values) and the pooled local standard deviation of manually and algorithmically segmented wall and lumen boundaries were computed for each subject and represented in a 2D standardized map. The local accuracy and variability of the segmentation algorithm at each point can be quantified by the average of these metrics for the whole group of subjects and visualized on the 2D standardized map. Based on the results shown on the 2D standardized map, a variety of strategies, such as adding anchor points and adjusting weights of different forces in the algorithm, can be introduced to improve the accuracy and variability of the algorithm. (paper)

A Nonparametric Shape Prior Constrained Active Contour Model for Segmentation of Coronaries in CTA Images

Directory of Open Access Journals (Sweden)

Yin Wang

2014-01-01

Full Text Available We present a nonparametric shape constrained algorithm for segmentation of coronary arteries in computed tomography images within the framework of active contours. An adaptive scale selection scheme, based on the global histogram information of the image data, is employed to determine the appropriate window size for each point on the active contour, which improves the performance of the active contour model in the low contrast local image regions. The possible leakage, which cannot be identified by using intensity features alone, is reduced through the application of the proposed shape constraint, where the shape of circular sampled intensity profile is used to evaluate the likelihood of current segmentation being considered vascular structures. Experiments on both synthetic and clinical datasets have demonstrated the efficiency and robustness of the proposed method. The results on clinical datasets have shown that the proposed approach is capable of extracting more detailed coronary vessels with subvoxel accuracy.

Testing program for burning plasma experiment vacuum vessel bolted joint

International Nuclear Information System (INIS)

Hsueh, P.K.; Khan, M.Z.; Swanson, J.; Feng, T.; Dinkevich, S.; Warren, J.

1992-01-01

As presently designed, the Burning Plasma Experiment vacuum vessel will be segmentally fabricated and assembled by bolted joints in the field. Due to geometry constraints, most of the bolted joints have significant eccentricity which causes the joint behavior to be sensitive to joint clamping forces. Experience indicates that as a result of this eccentricity, the joint will tend to open at the side closest to the applied load with the extent of the opening being dependent on the initial preload. In this paper analytical models coupled with a confirmatory testing program are developed to investigate and predict the non-linear behavior of the vacuum vessel bolted joint

Region of interest-based versus whole-lung segmentation-based approach for MR lung perfusion quantification in 2-year-old children after congenital diaphragmatic hernia repair

International Nuclear Information System (INIS)

Weis, M.; Sommer, V.; Hagelstein, C.; Schoenberg, S.O.; Neff, K.W.; Zoellner, F.G.; Zahn, K.; Schaible, T.

2016-01-01

With a region of interest (ROI)-based approach 2-year-old children after congenital diaphragmatic hernia (CDH) show reduced MR lung perfusion values on the ipsilateral side compared to the contralateral. This study evaluates whether results can be reproduced by segmentation of whole-lung and whether there are differences between the ROI-based and whole-lung measurements. Using dynamic contrast-enhanced (DCE) MRI, pulmonary blood flow (PBF), pulmonary blood volume (PBV) and mean transit time (MTT) were quantified in 30 children after CDH repair. Quantification results of an ROI-based (six cylindrical ROIs generated of five adjacent slices per lung-side) and a whole-lung segmentation approach were compared. In both approaches PBF and PBV were significantly reduced on the ipsilateral side (p always <0.0001). In ipsilateral lungs, PBF of the ROI-based and the whole-lung segmentation-based approach was equal (p=0.50). In contralateral lungs, the ROI-based approach significantly overestimated PBF in comparison to the whole-lung segmentation approach by approximately 9.5 % (p=0.0013). MR lung perfusion in 2-year-old children after CDH is significantly reduced ipsilaterally. In the contralateral lung, the ROI-based approach significantly overestimates perfusion, which can be explained by exclusion of the most ventral parts of the lung. Therefore whole-lung segmentation should be preferred. (orig.)

Region of interest-based versus whole-lung segmentation-based approach for MR lung perfusion quantification in 2-year-old children after congenital diaphragmatic hernia repair

Energy Technology Data Exchange (ETDEWEB)

Weis, M.; Sommer, V.; Hagelstein, C.; Schoenberg, S.O.; Neff, K.W. [Heidelberg University, Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany); Zoellner, F.G. [Heidelberg University, Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Mannheim (Germany); Zahn, K. [University of Heidelberg, Department of Paediatric Surgery, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany); Schaible, T. [Heidelberg University, Department of Paediatrics, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany)

2016-12-15

With a region of interest (ROI)-based approach 2-year-old children after congenital diaphragmatic hernia (CDH) show reduced MR lung perfusion values on the ipsilateral side compared to the contralateral. This study evaluates whether results can be reproduced by segmentation of whole-lung and whether there are differences between the ROI-based and whole-lung measurements. Using dynamic contrast-enhanced (DCE) MRI, pulmonary blood flow (PBF), pulmonary blood volume (PBV) and mean transit time (MTT) were quantified in 30 children after CDH repair. Quantification results of an ROI-based (six cylindrical ROIs generated of five adjacent slices per lung-side) and a whole-lung segmentation approach were compared. In both approaches PBF and PBV were significantly reduced on the ipsilateral side (p always <0.0001). In ipsilateral lungs, PBF of the ROI-based and the whole-lung segmentation-based approach was equal (p=0.50). In contralateral lungs, the ROI-based approach significantly overestimated PBF in comparison to the whole-lung segmentation approach by approximately 9.5 % (p=0.0013). MR lung perfusion in 2-year-old children after CDH is significantly reduced ipsilaterally. In the contralateral lung, the ROI-based approach significantly overestimates perfusion, which can be explained by exclusion of the most ventral parts of the lung. Therefore whole-lung segmentation should be preferred. (orig.)

Small vessel vasculitis History, classification, etiology, histopathology, clinic, diagnosis and treatment

International Nuclear Information System (INIS)

Iglesias Gamarra, Antonio; Matteson, Eric L; Restrepo, Jose Felix

2007-01-01

Small-vessel vasculitis is a convenient descriptor for a wide range of diseases characterized by vascular inflammation of the venules, capillaries, and/or arterioles with pleomorphic clinical manifestations. The classical clinical phenotype is leucocytoclastic vasculitis with palpable purpura, but manifestations vary widely depending upon the organs involved. Histopathologic examination in leucocytoclastic vasculitis reveals angiocentric segmental inflammation, fibrinoid necrosis, and a neutrophilic infiltrate around the blood vessel walls with erythrocyte extravasation. The etiology of small-vessel vasculitis is unknown in many cases, but in others, drugs, post viral syndromes, malignancy, primary vasculitis such as microscopic polyarteritis, and connective tissue disorders are associated, The diagnosis of small- vessel vasculitis relies on a thorough history and physical examination, as well as relevant antibody testing including antinuclear antibody and anti neutrophil cytoplasmic antibody, hepatitis B and C serologies, assessment of complement, immunoglobulins, blood count, serum creatinine liver function tests, urinalysis, radiographic imaging and biopsy. The treatment is based primarily on corticosteroid and immunosuppressive agents

Improvement of retinal blood vessel detection using morphological component analysis.

Science.gov (United States)

Imani, Elaheh; Javidi, Malihe; Pourreza, Hamid-Reza

2015-03-01

Detection and quantitative measurement of variations in the retinal blood vessels can help diagnose several diseases including diabetic retinopathy. Intrinsic characteristics of abnormal retinal images make blood vessel detection difficult. The major problem with traditional vessel segmentation algorithms is producing false positive vessels in the presence of diabetic retinopathy lesions. To overcome this problem, a novel scheme for extracting retinal blood vessels based on morphological component analysis (MCA) algorithm is presented in this paper. MCA was developed based on sparse representation of signals. This algorithm assumes that each signal is a linear combination of several morphologically distinct components. In the proposed method, the MCA algorithm with appropriate transforms is adopted to separate vessels and lesions from each other. Afterwards, the Morlet Wavelet Transform is applied to enhance the retinal vessels. The final vessel map is obtained by adaptive thresholding. The performance of the proposed method is measured on the publicly available DRIVE and STARE datasets and compared with several state-of-the-art methods. An accuracy of 0.9523 and 0.9590 has been respectively achieved on the DRIVE and STARE datasets, which are not only greater than most methods, but are also superior to the second human observer's performance. The results show that the proposed method can achieve improved detection in abnormal retinal images and decrease false positive vessels in pathological regions compared to other methods. Also, the robustness of the method in the presence of noise is shown via experimental result. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Ultrasound assessment of the posterior circumflex humeral artery in elite volleyball players: Aneurysm prevalence, anatomy, branching pattern and vessel characteristics

OpenAIRE

van de Pol, Daan; Maas, Mario; Terpstra, Aart; Pannekoek-Hekman, Marja; Alaeikhanehshir, Sena; Kuijer, P. Paul F. M.; Planken, R. Nils

2016-01-01

Objectives To determine the prevalence of posterior circumflex humeral artery (PCHA) aneurysms and vessel characteristics of the PCHA and deep brachial artery (DBA) in elite volleyball players. Methods Two-hundred and eighty players underwent standardized ultrasound assessment of the dominant arm by a vascular technologist. Assessment included determination of PCHA aneurysms (defined as segmental vessel dilatation ?150 %), PCHA and DBA anatomy, branching pattern, vessel course and diameter. R...

Improved radiological/nuclear source localization in variable NORM background: An MLEM approach with segmentation data

Energy Technology Data Exchange (ETDEWEB)

Penny, Robert D., E-mail: robert.d.penny@leidos.com [Leidos Inc., 10260 Campus Point Road, San Diego, CA (United States); Crowley, Tanya M.; Gardner, Barbara M.; Mandell, Myron J.; Guo, Yanlin; Haas, Eric B.; Knize, Duane J.; Kuharski, Robert A.; Ranta, Dale; Shyffer, Ryan [Leidos Inc., 10260 Campus Point Road, San Diego, CA (United States); Labov, Simon; Nelson, Karl; Seilhan, Brandon [Lawrence Livermore National Laboratory, Livermore, CA (United States); Valentine, John D. [Lawrence Berkeley National Laboratory, Berkeley, CA (United States)

2015-06-01

A novel approach and algorithm have been developed to rapidly detect and localize both moving and static radiological/nuclear (R/N) sources from an airborne platform. Current aerial systems with radiological sensors are limited in their ability to compensate for variable naturally occurring radioactive material (NORM) background. The proposed approach suppresses the effects of NORM background by incorporating additional information to segment the survey area into regions over which the background is likely to be uniform. The method produces pixelated Source Activity Maps (SAMs) of both target and background radionuclide activity over the survey area. The task of producing the SAMs requires (1) the development of a forward model which describes the transformation of radionuclide activity to detector measurements and (2) the solution of the associated inverse problem. The inverse problem is ill-posed as there are typically fewer measurements than unknowns. In addition the measurements are subject to Poisson statistical noise. The Maximum-Likelihood Expectation-Maximization (MLEM) algorithm is used to solve the inverse problem as it is well suited for under-determined problems corrupted by Poisson noise. A priori terrain information is incorporated to segment the reconstruction space into regions within which we constrain NORM background activity to be uniform. Descriptions of the algorithm and examples of performance with and without segmentation on simulated data are presented.

Segmenting healthcare terminology users: a strategic approach to large scale evolutionary development.

Science.gov (United States)

Price, C; Briggs, K; Brown, P J

1999-01-01

Healthcare terminologies have become larger and more complex, aiming to support a diverse range of functions across the whole spectrum of healthcare activity. Prioritization of development, implementation and evaluation can be achieved by regarding the "terminology" as an integrated system of content-based and functional components. Matching these components to target segments within the healthcare community, supports a strategic approach to evolutionary development and provides essential product differentiation to enable terminology providers and systems suppliers to focus on end-user requirements.

[Pathophysiological changes of umbilical vessels in intrauterine growth restriction].

Science.gov (United States)

Jakó, Mária; Surányi, Andrea; Kaiser, László; Domokos, Dóra; Gáspár, Róbert; Bártfai, György

2014-12-14

The prevalence of intrauterine growth restriction is 4-5000/100,000 births, and they give the majority of perinatal morbidity. The aim of the authors was to compare the pathomorphologic data and vasoreactivity of umbilical vessels and placenta of small for date newborns to that of the normal pregnancies. Samples of the umbilical cord and placenta were divided into case and control groups. Two 10 cm long segments were cut of the umbilical cord at placental insertion. Tissue bath experiment was performed on umbilical vessels and pathomorphologic data were collected according to the Royal College of Pathologists' protocol. After the development of basal tone, oxytocin and desmopressin did not enhance the vascular contraction, but the pathomorphological and ultrasonographic data were significantly different in the two groups. The results indicate that umbilical vessels might not have oxytocin or vasopressin receptors. The pathomorphologic and flowmetric differences could be the causes of small birth weight.

3D CT modeling of hepatic vessel architecture and volume calculation in living donated liver transplantation

International Nuclear Information System (INIS)

Frericks, Bernd B.; Caldarone, Franco C.; Savellano, Dagmar Hoegemann; Stamm, Georg; Kirchhoff, Timm D.; Shin, Hoen-Oh; Galanski, Michael; Nashan, Bjoern; Klempnauer, Juergen; Schenk, Andrea; Selle, Dirk; Spindler, Wolf; Peitgen, Heinz-Otto

2004-01-01

The aim of this study was to evaluate a software tool for non-invasive preoperative volumetric assessment of potential donors in living donated liver transplantation (LDLT). Biphasic helical CT was performed in 56 potential donors. Data sets were post-processed using a non-commercial software tool for segmentation, volumetric analysis and visualisation of liver segments. Semi-automatic definition of liver margins allowed the segmentation of parenchyma. Hepatic vessels were delineated using a region-growing algorithm with automatically determined thresholds. Volumes and shapes of liver segments were calculated automatically based on individual portal-venous branches. Results were visualised three-dimensionally and statistically compared with conventional volumetry and the intraoperative findings in 27 transplanted cases. Image processing was easy to perform within 23 min. Of the 56 potential donors, 27 were excluded from LDLT because of inappropriate liver parenchyma or vascular architecture. Two recipients were not transplanted due to poor clinical conditions. In the 27 transplanted cases, preoperatively visualised vessels were confirmed, and only one undetected accessory hepatic vein was revealed. Calculated graft volumes were 1110±180 ml for right lobes, 820 ml for the left lobe and 270±30 ml for segments II+III. The calculated volumes and intraoperatively measured graft volumes correlated significantly. No significant differences between the presented automatic volumetry and the conventional volumetry were observed. A novel image processing technique was evaluated which allows a semi-automatic volume calculation and 3D visualisation of the different liver segments. (orig.)

Global Kalman filter approaches to estimate absolute angles of lower limb segments.

Science.gov (United States)

Nogueira, Samuel L; Lambrecht, Stefan; Inoue, Roberto S; Bortole, Magdo; Montagnoli, Arlindo N; Moreno, Juan C; Rocon, Eduardo; Terra, Marco H; Siqueira, Adriano A G; Pons, Jose L

2017-05-16

In this paper we propose the use of global Kalman filters (KFs) to estimate absolute angles of lower limb segments. Standard approaches adopt KFs to improve the performance of inertial sensors based on individual link configurations. In consequence, for a multi-body system like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank) are not taken into account in other link angle estimations (e.g., foot). Global KF approaches, on the other hand, correlate the collective contribution of all signals from lower limb segments observed in the state-space model through the filtering process. We present a novel global KF (matricial global KF) relying only on inertial sensor data, and validate both this KF and a previously presented global KF (Markov Jump Linear Systems, MJLS-based KF), which fuses data from inertial sensors and encoders from an exoskeleton. We furthermore compare both methods to the commonly used local KF. The results indicate that the global KFs performed significantly better than the local KF, with an average root mean square error (RMSE) of respectively 0.942° for the MJLS-based KF, 1.167° for the matrical global KF, and 1.202° for the local KFs. Including the data from the exoskeleton encoders also resulted in a significant increase in performance. The results indicate that the current practice of using KFs based on local models is suboptimal. Both the presented KF based on inertial sensor data, as well our previously presented global approach fusing inertial sensor data with data from exoskeleton encoders, were superior to local KFs. We therefore recommend to use global KFs for gait analysis and exoskeleton control.

Strategic market segmentation

Directory of Open Access Journals (Sweden)

Maričić Branko R.

2015-01-01

Full Text Available Strategic planning of marketing activities is the basis of business success in modern business environment. Customers are not homogenous in their preferences and expectations. Formulating an adequate marketing strategy, focused on realization of company's strategic objectives, requires segmented approach to the market that appreciates differences in expectations and preferences of customers. One of significant activities in strategic planning of marketing activities is market segmentation. Strategic planning imposes a need to plan marketing activities according to strategically important segments on the long term basis. At the same time, there is a need to revise and adapt marketing activities on the short term basis. There are number of criteria based on which market segmentation is performed. The paper will consider effectiveness and efficiency of different market segmentation criteria based on empirical research of customer expectations and preferences. The analysis will include traditional criteria and criteria based on behavioral model. The research implications will be analyzed from the perspective of selection of the most adequate market segmentation criteria in strategic planning of marketing activities.

Market Segmentation from a Behavioral Perspective

Science.gov (United States)

Wells, Victoria K.; Chang, Shing Wan; Oliveira-Castro, Jorge; Pallister, John

2010-01-01

A segmentation approach is presented using both traditional demographic segmentation bases (age, social class/occupation, and working status) and a segmentation by benefits sought. The benefits sought in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (BPM). Using data from 1,847…

Approach for estimating post-annual reirradiation embrittlement of reactor vessel steels

International Nuclear Information System (INIS)

Server, W.L.; Taboada, A.

1985-01-01

Thermal annealing of a commercial nuclear reactor pressure vessel is a possible solution for extending lifetime in situations where excessive radiation embrittlement has taken place or when the original design life is approached. Two difficult facets of thermal annealing are the degree of toughness recovery after annealing and the post-anneal reirradiation embrittlement behavior. These aspects of annealing are evaluated in this paper by using simple models and translation of the initial irradiation damage curve either vertically or laterally at the point of residual shift after annealing. Results using this methodology are compared to limited actual weld metal measurements of annealing behavior. A forthcoming ASTM Guide on in-place annealing uses this methodology to assess annealing recovery and re-embrittlement response

PWR internals segmentation and packaging experience in the U.S

International Nuclear Information System (INIS)

Kreitman, P.J.

2008-01-01

Seven commercial nuclear power plants of the Pressurized Water Reactor (PWR) design have been permanently shut down in the US to date. Six of these plants have been decommissioned using dismantling methods. The remaining plant, Indian Point 1, located in Buchanan, NY, has been placed in Safe Storage. Of the six dismantled plants, five underwent extensive segmentation, separation, and packaging of their internal components to allow removal and disposal of the reactor vessel assembly. Only the Trojan Plant in Portland, Oregon, was able to ship the reactor vessel assembly with its internals intact to the final disposal site near Richland, Washington. An important part of the planning for the upcoming decommissioning of similar plants in Europe such as Chooz A in France and Zorita in Spain will be to study the lessons learned from the US efforts and apply the best practices to future projects. This paper will chronicle the evolution of the reactor internals segmentation and packaging process to date, including the planning, methodology, equipment, waste management, and packaging strategy. (author)

Population segmentation: an approach to reducing childhood obesity inequalities.

Science.gov (United States)

Mahmood, Hashum; Lowe, Susan

2017-05-01

The aims of this study are threefold: (1) to investigate the relationship between socio-economic status (inequality) and childhood obesity prevalence within Birmingham local authority, (2) to identify any change in childhood obesity prevalence between deprivation quintiles and (3) to analyse individualised Birmingham National Child Measurement Programme (NCMP) data using a population segmentation tool to better inform obesity prevention strategies. Data from the NCMP for Birmingham (2010/2011 and 2014/2015) were analysed using the deprivation scores from the Income Domain Affecting Children Index (IDACI 2010). The percentage of children with excess weight was calculated for each local deprivation quintile. Population segmentation was carried out using the Experian's Mosaic Public Sector 6 (MPS6) segmentation tool. Childhood obesity levels have remained static at the national and Birmingham level. For Year 6 pupils, obesity levels have increased in the most deprived deprivation quintiles for boys and girls. The most affluent quintile shows a decreasing trend of obesity prevalence for boys and girls in both year groups. For the middle quintiles, the results show fluctuating trends. This research highlighted the link in Birmingham between obesity and socio-economic factors with the gap increasing between deprivation quintiles. Obesity is a complex problem that cannot simply be addressed through targeting most deprived populations, rather through a range of effective interventions tailored for the various population segments that reside within communities. Using population segmentation enables a more nuanced understanding of the potential barriers and levers within populations on their readiness for change. The segmentation of childhood obesity data will allow utilisation of social marketing methodology that will facilitate identification of suitable methods for interventions and motivate individuals to sustain behavioural change. Sequentially, it will also inform

Validation of the Gatortail method for accurate sizing of pulmonary vessels from 3D medical images.

Science.gov (United States)

O'Dell, Walter G; Gormaley, Anne K; Prida, David A

2017-12-01

Detailed characterization of changes in vessel size is crucial for the diagnosis and management of a variety of vascular diseases. Because clinical measurement of vessel size is typically dependent on the radiologist's subjective interpretation of the vessel borders, it is often prone to high inter- and intra-user variability. Automatic methods of vessel sizing have been developed for two-dimensional images but a fully three-dimensional (3D) method suitable for vessel sizing from volumetric X-ray computed tomography (CT) or magnetic resonance imaging has heretofore not been demonstrated and validated robustly. In this paper, we refined and objectively validated Gatortail, a method that creates a mathematical geometric 3D model of each branch in a vascular tree, simulates the appearance of the virtual vascular tree in a 3D CT image, and uses the similarity of the simulated image to a patient's CT scan to drive the optimization of the model parameters, including vessel size, to match that of the patient. The method was validated with a 2-dimensional virtual tree structure under deformation, and with a realistic 3D-printed vascular phantom in which the diameter of 64 branches were manually measured 3 times each. The phantom was then scanned on a conventional clinical CT imaging system and the images processed with the in-house software to automatically segment and mathematically model the vascular tree, label each branch, and perform the Gatortail optimization of branch size and trajectory. Previously proposed methods of vessel sizing using matched Gaussian filters and tubularity metrics were also tested. The Gatortail method was then demonstrated on the pulmonary arterial tree segmented from a human volunteer's CT scan. The standard deviation of the difference between the manually measured and Gatortail-based radii in the 3D physical phantom was 0.074 mm (0.087 in-plane pixel units for image voxels of dimension 0.85 × 0.85 × 1.0 mm) over the 64 branches

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

Science.gov (United States)

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

2015-08-01

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

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

Science.gov (United States)

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

Recognition Using Classification and Segmentation Scoring

National Research Council Canada - National Science Library

Kimball, Owen; Ostendorf, Mari; Rohlicek, Robin

1992-01-01

.... We describe an approach to connected word recognition that allows the use of segmental information through an explicit decomposition of the recognition criterion into classification and segmentation scoring...

Unique identification code for medical fundus images using blood vessel pattern for tele-ophthalmology applications.

Science.gov (United States)

Singh, Anushikha; Dutta, Malay Kishore; Sharma, Dilip Kumar

2016-10-01

Identification of fundus images during transmission and storage in database for tele-ophthalmology applications is an important issue in modern era. The proposed work presents a novel accurate method for generation of unique identification code for identification of fundus images for tele-ophthalmology applications and storage in databases. Unlike existing methods of steganography and watermarking, this method does not tamper the medical image as nothing is embedded in this approach and there is no loss of medical information. Strategic combination of unique blood vessel pattern and patient ID is considered for generation of unique identification code for the digital fundus images. Segmented blood vessel pattern near the optic disc is strategically combined with patient ID for generation of a unique identification code for the image. The proposed method of medical image identification is tested on the publically available DRIVE and MESSIDOR database of fundus image and results are encouraging. Experimental results indicate the uniqueness of identification code and lossless recovery of patient identity from unique identification code for integrity verification of fundus images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Comparison between 3D eddy current patterns in tokamak in-vessel components generated by disruptions

International Nuclear Information System (INIS)

Sakellaris, J.; Crutzen, Y.

1996-01-01

During plasma disruption events in Tokamaks, a large amount of magnetic energy is associated to the transfer of plasma current into eddy currents in the passive structures. In the ITER program two design concepts have been proposed. One approach (ITER CDA design) is based on copper stabilization loops (i.e., twin loops) attached to box-shaped blanket segments, electrically and mechanically separated along the toroidal direction. For another design concept (ITER EDA design) based on lower plasma elongation there is no need for specific stabilization loops. The passive stabilization is obtained by toroidally continuous components (i.e., the plasma facing wall of the blanket segments allows a continuity along the toroidal direction). Consequently, toroidal currents flow, when electromagnetic transients occur. Electromagnetic loads appear in the blanket structures in case of plasma disruptions and/or vertical displacement events either for the ITER CDA design concept or for the ITER EDA design concept. In this paper the influence of the in-vessel design configuration concepts--insulated segments or electrically continuous structures--in terms of magnetic shielding and electric insulation on the magnitude and the flow pattern of the eddy currents is investigated. This investigation will allow a performance evaluation of the two proposed design concepts

Fast globally optimal segmentation of cells in fluorescence microscopy images.

Science.gov (United States)

Bergeest, Jan-Philip; Rohr, Karl

2011-01-01

Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.

Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method

Directory of Open Access Journals (Sweden)

Yun Tian

2016-01-01

Full Text Available The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis. In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume. The method is built on a statistics region growing together with a heuristic decision. First, the heart region is extracted using a multi-atlas-based approach. Second, the vessel structures are enhanced via a 3D multiscale line filter. Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation. Based on the set of detected seed points, a statistics-based region growing is applied. Finally, results are obtained by setting conservative parameters. A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation. The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA volume data. The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods. Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.

Segmentation of liver tumors on CT images

International Nuclear Information System (INIS)

Pescia, D.

2011-01-01

This thesis is dedicated to 3D segmentation of liver tumors in CT images. This is a task of great clinical interest since it allows physicians benefiting from reproducible and reliable methods for segmenting such lesions. Accurate segmentation would indeed help them during the evaluation of the lesions, the choice of treatment and treatment planning. Such a complex segmentation task should cope with three main scientific challenges: (i) the highly variable shape of the structures being sought, (ii) their similarity of appearance compared with their surrounding medium and finally (iii) the low signal to noise ratio being observed in these images. This problem is addressed in a clinical context through a two step approach, consisting of the segmentation of the entire liver envelope, before segmenting the tumors which are present within the envelope. We begin by proposing an atlas-based approach for computing pathological liver envelopes. Initially images are pre-processed to compute the envelopes that wrap around binary masks in an attempt to obtain liver envelopes from estimated segmentation of healthy liver parenchyma. A new statistical atlas is then introduced and used to segmentation through its diffeomorphic registration to the new image. This segmentation is achieved through the combination of image matching costs as well as spatial and appearance prior using a multi-scale approach with MRF. The second step of our approach is dedicated to lesions segmentation contained within the envelopes using a combination of machine learning techniques and graph based methods. First, an appropriate feature space is considered that involves texture descriptors being determined through filtering using various scales and orientations. Then, state of the art machine learning techniques are used to determine the most relevant features, as well as the hyper plane that separates the feature space of tumoral voxels to the ones corresponding to healthy tissues. Segmentation is then

Quantitative segmentation of fluorescence microscopy images of heterogeneous tissue: Approach for tuning algorithm parameters

Science.gov (United States)

Mueller, Jenna L.; Harmany, Zachary T.; Mito, Jeffrey K.; Kennedy, Stephanie A.; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G.; Willett, Rebecca M.; Brown, J. Quincy; Ramanujam, Nimmi

2013-02-01

The combination of fluorescent contrast agents with microscopy is a powerful technique to obtain real time images of tissue histology without the need for fixing, sectioning, and staining. The potential of this technology lies in the identification of robust methods for image segmentation and quantitation, particularly in heterogeneous tissues. Our solution is to apply sparse decomposition (SD) to monochrome images of fluorescently-stained microanatomy to segment and quantify distinct tissue types. The clinical utility of our approach is demonstrated by imaging excised margins in a cohort of mice after surgical resection of a sarcoma. Representative images of excised margins were used to optimize the formulation of SD and tune parameters associated with the algorithm. Our results demonstrate that SD is a robust solution that can advance vital fluorescence microscopy as a clinically significant technology.

Various design approaches to achieve electric field-driven segmented folding actuation of electroactive polymer (EAP) sheets

Science.gov (United States)

Ahmed, Saad; Hong, Jonathan; Zhang, Wei; Kopatz, Jessica; Ounaies, Zoubeida; Frecker, Mary

2018-03-01

Electroactive polymer (EAPs) based technologies have shown promise in areas such as artificial muscles, aerospace, medical and soft robotics. In this work, we demonstrate ways to harness on-demand segmented folding actuation from pure bending of relaxor-ferroelectric P(VDF-TrFE-CTFE) based films, using various design approaches, such as `stiffener' and `notch' based approaches. The in-plane actuation of the P(VDF-TrFE-CTFE) is converted into bending actuation using unimorph configurations, where one passive substrate layer is attached to the active polymer. First, we experimentally show that placement of thin metal strips as stiffener in between active EAPs and passive substrates leads to segmented actuation as opposed to pure bending actuation; stiffeners made of different materials, such as nickel, copper and aluminum, are studied which reveals that a higher Young's modulus favors more pronounced segmented actuation. Second, notched samples are prepared by mounting passive substrate patches of various materials on top of the passive layers of the unimorph EAP actuators. Effect of notch materials, size of the notches and position of the notches on the folding actuation are studied. The motion of the human finger inspires a finger-like biomimetic actuator, which is realized by assigning multiple notches on the structure; finite element analysis (FEA) is also performed using COMSOL Multiphysics software for the notched finger actuator. Finally, a versatile soft-gripper is developed using the notched approach to demonstrate the capability of a properly designed EAP actuator to hold objects of various sizes and shapes.

Adjustable Two-Tier Cache for IPTV Based on Segmented Streaming

Directory of Open Access Journals (Sweden)

Kai-Chun Liang

2012-01-01

Full Text Available Internet protocol TV (IPTV is a promising Internet killer application, which integrates video, voice, and data onto a single IP network, and offers viewers an innovative set of choices and control over their TV content. To provide high-quality IPTV services, an effective strategy is based on caching. This work proposes a segment-based two-tier caching approach, which divides each video into multiple segments to be cached. This approach also partitions the cache space into two layers, where the first layer mainly caches to-be-played segments and the second layer saves possibly played segments. As the segment access becomes frequent, the proposed approach enlarges the first layer and reduces the second layer, and vice versa. Because requested segments may not be accessed frequently, this work further designs an admission control mechanism to determine whether an incoming segment should be cached or not. The cache architecture takes forward/stop playback into account and may replace the unused segments under the interrupted playback. Finally, we conduct comprehensive simulation experiments to evaluate the performance of the proposed approach. The results show that our approach can yield higher hit ratio than previous work under various environmental parameters.

Automatic segmentation of 4D cardiac MR images for extraction of ventricular chambers using a spatio-temporal approach

Science.gov (United States)

Atehortúa, Angélica; Zuluaga, Maria A.; Ourselin, Sébastien; Giraldo, Diana; Romero, Eduardo

2016-03-01

An accurate ventricular function quantification is important to support evaluation, diagnosis and prognosis of several cardiac pathologies. However, expert heart delineation, specifically for the right ventricle, is a time consuming task with high inter-and-intra observer variability. A fully automatic 3D+time heart segmentation framework is herein proposed for short-axis-cardiac MRI sequences. This approach estimates the heart using exclusively information from the sequence itself without tuning any parameters. The proposed framework uses a coarse-to-fine approach, which starts by localizing the heart via spatio-temporal analysis, followed by a segmentation of the basal heart that is then propagated to the apex by using a non-rigid-registration strategy. The obtained volume is then refined by estimating the ventricular muscle by locally searching a prior endocardium- pericardium intensity pattern. The proposed framework was applied to 48 patients datasets supplied by the organizers of the MICCAI 2012 Right Ventricle segmentation challenge. Results show the robustness, efficiency and competitiveness of the proposed method both in terms of accuracy and computational load.

Brain tumor segmentation based on a hybrid clustering technique

Directory of Open Access Journals (Sweden)

Eman Abdel-Maksoud

2015-03-01

This paper presents an efficient image segmentation approach using K-means clustering technique integrated with Fuzzy C-means algorithm. It is followed by thresholding and level set segmentation stages to provide an accurate brain tumor detection. The proposed technique can get benefits of the K-means clustering for image segmentation in the aspects of minimal computation time. In addition, it can get advantages of the Fuzzy C-means in the aspects of accuracy. The performance of the proposed image segmentation approach was evaluated by comparing it with some state of the art segmentation algorithms in case of accuracy, processing time, and performance. The accuracy was evaluated by comparing the results with the ground truth of each processed image. The experimental results clarify the effectiveness of our proposed approach to deal with a higher number of segmentation problems via improving the segmentation quality and accuracy in minimal execution time.

A thresholding based technique to extract retinal blood vessels from fundus images

Directory of Open Access Journals (Sweden)

Jyotiprava Dash

2017-12-01

Full Text Available Retinal imaging has become the significant tool among all the medical imaging technology, due to its capability to extract many data which is linked to various eye diseases. So, the accurate extraction of blood vessel is necessary that helps the eye care specialists and ophthalmologist to identify the diseases at the early stages. In this paper, we have proposed a computerized technique for extraction of blood vessels from fundus images. The process is conducted in three phases: (i pre-processing where the image is enhanced using contrast limited adaptive histogram equalization and median filter, (ii segmentation using mean-C thresholding to extract retinal blood vessels, (iii post-processing where morphological cleaning operation is used to remove isolated pixels. The performance of the proposed method is tested on and experimental results show that our method achieve an accuracies of 0.955 and 0.954 on Digital retinal images for vessel extraction (DRIVE and Child heart and health study in England (CHASE_DB1 databases respectively.

Quantification of tumor vessels in glioblastoma patients using time-of-flight angiography at 7 Tesla: a feasibility study.

Directory of Open Access Journals (Sweden)

Alexander Radbruch

Full Text Available PURPOSE: To analyze if tumor vessels can be visualized, segmented and quantified in glioblastoma patients with time of flight (ToF angiography at 7 Tesla and multiscale vessel enhancement filtering. MATERIALS AND METHODS: Twelve patients with newly diagnosed glioblastoma were examined with ToF angiography (TR = 15 ms, TE = 4.8 ms, flip angle = 15°, FOV = 160 × 210 mm(2, voxel size: 0.31 × 0.31 × 0.40 mm(3 on a whole-body 7 T MR system. A volume of interest (VOI was placed within the border of the contrast enhancing part on T1-weighted images of the glioblastoma and a reference VOI was placed in the non-affected contralateral white matter. Automated segmentation and quantification of vessels within the two VOIs was achieved using multiscale vessel enhancement filtering in ImageJ. RESULTS: Tumor vessels were clearly visible in all patients. When comparing tumor and the reference VOI, total vessel surface (45.3 ± 13.9 mm(2 vs. 29.0 ± 21.0 mm(2 (p<0.035 and number of branches (3.5 ± 1.8 vs. 1.0 ± 0.6 (p<0.001 per cubic centimeter were significantly higher, while mean vessel branch length was significantly lower (3.8 ± 1.5 mm vs 7.2 ± 2.8 mm (p<0.001 in the tumor. DISCUSSION: ToF angiography at 7-Tesla MRI enables characterization and quantification of the internal vascular morphology of glioblastoma and may be used for the evaluation of therapy response within future studies.

Investigation on the Weighted RANSAC Approaches for Building Roof Plane Segmentation from LiDAR Point Clouds

Directory of Open Access Journals (Sweden)

Bo Xu

2015-12-01

Full Text Available RANdom SAmple Consensus (RANSAC is a widely adopted method for LiDAR point cloud segmentation because of its robustness to noise and outliers. However, RANSAC has a tendency to generate false segments consisting of points from several nearly coplanar surfaces. To address this problem, we formulate the weighted RANSAC approach for the purpose of point cloud segmentation. In our proposed solution, the hard threshold voting function which considers both the point-plane distance and the normal vector consistency is transformed into a soft threshold voting function based on two weight functions. To improve weighted RANSAC’s ability to distinguish planes, we designed the weight functions according to the difference in the error distribution between the proper and improper plane hypotheses, based on which an outlier suppression ratio was also defined. Using the ratio, a thorough comparison was conducted between these different weight functions to determine the best performing function. The selected weight function was then compared to the existing weighted RANSAC methods, the original RANSAC, and a representative region growing (RG method. Experiments with two airborne LiDAR datasets of varying densities show that the various weighted methods can improve the segmentation quality differently, but the dedicated designed weight functions can significantly improve the segmentation accuracy and the topology correctness. Moreover, its robustness is much better when compared to the RG method.

Unsupervised information extraction by text segmentation

CERN Document Server

Cortez, Eli

2013-01-01

A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors' approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content-based features. The effectiveness of the content-based features is also exploited to directly learn from test data structure-based features, with no previous human-driven training, a feature unique to the presented approach. Based on the approach, a

Vessel wall MRI of the thoracic aorta: correlation to histology and transesophageal ultrasound. Preliminary results

International Nuclear Information System (INIS)

Abolmaali, N.; Schick, C.; Thalhammer, A.; Schmitt, J.; Vogl, T.J.; Langenfeld, M.; Schaechinger, V.; Krahforst, R.; Schulze, T.

2002-01-01

Purpose: To visualise the vessel wall of the descending thoracic aorta using magnetic resonance imaging. To evaluate the diagnostic potential of tailored T 1 -weighted sequences with contrast enhancement to assess systemic atherosclerotic disease. Methods: This study was performed on a clinical 1.5 Tesla scanner using a gradient strength of 30 mT/m and the phased array spine coil. A cadaver was examined to optimise a magnetic resonance imaging (MRI) protocol to evaluate atherosclerotic aortic wall disease. The acquired MR images were compared to gross specimens and histology. Subsequently seven patients who had undergone transesophageal ultrasound (TEU) with detailed assessment of the descending thoracic aorta were examined with MRI. The optimised protocol included untriggered and fat suppressed T 2 -weighted turbo spin echo sequences and ECG-triggered and fat suppressed T 1 -weighted spin echo sequences before and after iv administration of Gd-DTPA. Findings of the MR images were compared to the results of TEU. Contrast enhancement measurements were performed in normal and thickened vessel wall segments. Results: For the cadaver study a good correlation of the degree of vessel wall thickening and the extent of plaque imaged with the applied MR protocol was found. Tissue characterisation was limited due to post mortem changes. In vivo ECG-triggered T 1 -weighted images showed good correlation to TEU in terms of vessel wall thickness and plaque extension as verified by means of consensus reading. Differentiation of the plaque components fat, calcium and fibrous tissue was possible. In thickened aortic wall segments and fibrous caps a mean contrast enhancement of 50.4%±23.5% was measurable while normal wall segments showed an enhancement of 6.7%±3.1%. (orig.) [de

Template-based CTA to x-ray angio rigid registration of coronary arteries in frequency domain with automatic x-ray segmentation

Energy Technology Data Exchange (ETDEWEB)

Aksoy, Timur; Unal, Gozde [Sabanci University, Tuzla, Istanbul 34956 (Turkey); Demirci, Stefanie; Navab, Nassir [Computer Aided Medical Procedures (CAMP), Technical University of Munich, Garching, 85748 (Germany); Degertekin, Muzaffer [Yeditepe University Hospital, Istanbul 34752 (Turkey)

2013-10-15

Purpose: A key challenge for image guided coronary interventions is accurate and absolutely robust image registration bringing together preinterventional information extracted from a three-dimensional (3D) patient scan and live interventional image information. In this paper, the authors present a novel scheme for 3D to two-dimensional (2D) rigid registration of coronary arteries extracted from preoperative image scan (3D) and a single segmented intraoperative x-ray angio frame in frequency and spatial domains for real-time angiography interventions by C-arm fluoroscopy.Methods: Most existing rigid registration approaches require a close initialization due to the abundance of local minima and high complexity of search algorithms. The authors' method eliminates this requirement by transforming the projections into translation-invariant Fourier domain for estimating the 3D pose. For 3D rotation recovery, template Digitally Reconstructed Radiographs (DRR) as candidate poses of 3D vessels of segmented computed tomography angiography are produced by rotating the camera (image intensifier) around the DICOM angle values with a specific range as in C-arm setup. The authors have compared the 3D poses of template DRRs with the segmented x-ray after equalizing the scales in three domains, namely, Fourier magnitude, Fourier phase, and Fourier polar. The best rotation pose candidate was chosen by one of the highest similarity measures returned by the methods in these domains. It has been noted in literature that frequency domain methods are robust against noise and occlusion which was also validated by the authors' results. 3D translation of the volume was then recovered by distance-map based BFGS optimization well suited to convex structure of the authors' objective function without local minima due to distance maps. A novel automatic x-ray vessel segmentation was also performed in this study.Results: Final results were evaluated in 2D projection space for

Template-based CTA to x-ray angio rigid registration of coronary arteries in frequency domain with automatic x-ray segmentation

International Nuclear Information System (INIS)

Aksoy, Timur; Unal, Gozde; Demirci, Stefanie; Navab, Nassir; Degertekin, Muzaffer

2013-01-01

Purpose: A key challenge for image guided coronary interventions is accurate and absolutely robust image registration bringing together preinterventional information extracted from a three-dimensional (3D) patient scan and live interventional image information. In this paper, the authors present a novel scheme for 3D to two-dimensional (2D) rigid registration of coronary arteries extracted from preoperative image scan (3D) and a single segmented intraoperative x-ray angio frame in frequency and spatial domains for real-time angiography interventions by C-arm fluoroscopy.Methods: Most existing rigid registration approaches require a close initialization due to the abundance of local minima and high complexity of search algorithms. The authors' method eliminates this requirement by transforming the projections into translation-invariant Fourier domain for estimating the 3D pose. For 3D rotation recovery, template Digitally Reconstructed Radiographs (DRR) as candidate poses of 3D vessels of segmented computed tomography angiography are produced by rotating the camera (image intensifier) around the DICOM angle values with a specific range as in C-arm setup. The authors have compared the 3D poses of template DRRs with the segmented x-ray after equalizing the scales in three domains, namely, Fourier magnitude, Fourier phase, and Fourier polar. The best rotation pose candidate was chosen by one of the highest similarity measures returned by the methods in these domains. It has been noted in literature that frequency domain methods are robust against noise and occlusion which was also validated by the authors' results. 3D translation of the volume was then recovered by distance-map based BFGS optimization well suited to convex structure of the authors' objective function without local minima due to distance maps. A novel automatic x-ray vessel segmentation was also performed in this study.Results: Final results were evaluated in 2D projection space for patient data; and

Improvements in the Quantitative Assessment of Cerebral Blood Volume and Flow with the Removal of Vessel Voxels from MR Perfusion Images

Directory of Open Access Journals (Sweden)

Michael Mu Huo Teng

2013-01-01

Full Text Available Objective. To improve the quantitative assessment of cerebral blood volume (CBV and flow (CBF in the brain voxels from MR perfusion images. Materials and Methods. Normal brain parenchyma was automatically segmented with the time-to-peak criteria after cerebrospinal fluid removal and preliminary vessel voxel removal. Two scaling factors were calculated by comparing the relative CBV and CBF of the segmented normal brain parenchyma with the absolute values in the literature. Using the scaling factors, the relative values were converted to the absolute CBV and CBF. Voxels with either CBV > 8 mL/100 g or CBF > 100 mL/100 g/min were characterized as vessel voxels and were excluded from the quantitative measurements. Results. The segmented brain parenchyma with normal perfusion was consistent with the angiographic findings for each patient. We confirmed the necessity of dual thresholds including CBF and CBV for proper removal of vessel voxels. The scaling factors were 0.208 ± 0.041 for CBV, and 0.168 ± 0.037, 0.172 ± 0.037 for CBF calculated using standard and circulant singular value decomposition techniques, respectively. Conclusion. The automatic scaling and vessel removal techniques provide an alternative method for obtaining improved quantitative assessment of CBV and CBF in patients with thromboembolic cerebral arterial disease.

A rapid Kano-based approach to identify optimal user segments

DEFF Research Database (Denmark)

Atlason, Reynir Smari; Stefansson, Arnaldur Smari; Wietz, Miriam

2018-01-01

The Kano model of customer satisfaction provides product developers valuable information about if, and then how much a given functional requirement (FR) will impact customer satisfaction if implemented within a product, system or a service. A limitation of the Kano model is that it does not allow...... developers to visualise which combined sets of FRs would provide the highest satisfaction between different customer segments. In this paper, a stepwise method to address this shortcoming is presented. First, a traditional Kano analysis is conducted for the different segments of interest. Second, for each FR...... to the biggest target group. The proposed extension should assist product developers within to more effectively evaluate which FRs should be implemented when considering more than one combined customer segment. It shows which segments provide the highest possibility for high satisfaction of combined FRs. We...

A deep learning approach for real time prostate segmentation in freehand ultrasound guided biopsy.

Science.gov (United States)

Anas, Emran Mohammad Abu; Mousavi, Parvin; Abolmaesumi, Purang

2018-06-01

Targeted prostate biopsy, incorporating multi-parametric magnetic resonance imaging (mp-MRI) and its registration with ultrasound, is currently the state-of-the-art in prostate cancer diagnosis. The registration process in most targeted biopsy systems today relies heavily on accurate segmentation of ultrasound images. Automatic or semi-automatic segmentation is typically performed offline prior to the start of the biopsy procedure. In this paper, we present a deep neural network based real-time prostate segmentation technique during the biopsy procedure, hence paving the way for dynamic registration of mp-MRI and ultrasound data. In addition to using convolutional networks for extracting spatial features, the proposed approach employs recurrent networks to exploit the temporal information among a series of ultrasound images. One of the key contributions in the architecture is to use residual convolution in the recurrent networks to improve optimization. We also exploit recurrent connections within and across different layers of the deep networks to maximize the utilization of the temporal information. Furthermore, we perform dense and sparse sampling of the input ultrasound sequence to make the network robust to ultrasound artifacts. Our architecture is trained on 2,238 labeled transrectal ultrasound images, with an additional 637 and 1,017 unseen images used for validation and testing, respectively. We obtain a mean Dice similarity coefficient of 93%, a mean surface distance error of 1.10 mm and a mean Hausdorff distance error of 3.0 mm. A comparison of the reported results with those of a state-of-the-art technique indicates statistically significant improvement achieved by the proposed approach. Copyright © 2018 Elsevier B.V. All rights reserved.

Concept for a vertical maintenance remote handling system for multi module blanket segments in DEMO

International Nuclear Information System (INIS)

Coleman, M.; Sykes, N.; Cooper, D.; Iglesias, D.; Bastow, R.; Loving, A.; Harman, J.

2014-01-01

Highlights: •A conceptual architectural model for a vertical maintenance DEMO is presented. •Novel concepts for a set of DEMO remote handling equipment are put forward. •Remote maintenance of a multi module segment blanket is found to be feasible. •The criticality of space in the vertical port is highlighted. -- Abstract: The anticipated high neutron flux, and the consequent damage to plasma-facing components in DEMO, results in the need to regularly replace the tritium breeding and radiation shielding blanket. The current European multi module segment (MMS) blanket concept favours a less invasive small port entry maintenance system over large sector transport concepts, because of the reduced impact on other tokamak systems – particularly the magnetic coils. This paper presents a novel conceptual remote maintenance strategy for a Vertical Maintenance Scheme DEMO, incorporating substantiated designs for an in-vessel mover, to detach and attach the blanket segments, and cask-housed vertical maintenance devices to open and close access ports, cut and join service connections, and extract blanket segments from the vessel. In addition, a conceptual architectural model for DEMO was generated to capture functional and spatial interfaces between the remote maintenance equipment and other systems. Areas of further study are identified in order to comprehensively establish the feasibility of the proposed maintenance system

Marginal space learning for medical image analysis efficient detection and segmentation of anatomical structures

CERN Document Server

Zheng, Yefeng

2014-01-01

Presents an award winning image analysis technology (Thomas Edison Patent Award, MICCAI Young Investigator Award) that achieves object detection and segmentation with state-of-the-art accuracy and efficiency Flexible, machine learning-based framework, applicable across multiple anatomical structures and imaging modalities Thirty five clinical applications on detecting and segmenting anatomical structures such as heart chambers and valves, blood vessels, liver, kidney, prostate, lymph nodes, and sub-cortical brain structures, in CT, MRI, X-Ray and Ultrasound.

Statistics-based segmentation using a continuous-scale naive Bayes approach

DEFF Research Database (Denmark)

Laursen, Morten Stigaard; Midtiby, Henrik Skov; Kruger, Norbert

2014-01-01

Segmentation is a popular preprocessing stage in the field of machine vision. In agricultural applications it can be used to distinguish between living plant material and soil in images. The normalized difference vegetation index (NDVI) and excess green (ExG) color features are often used...... segmentation over the normalized vegetation difference index and excess green. The inputs to this color feature are the R, G, B, and near-infrared color wells, their chromaticities, and NDVI, ExG, and excess red. We apply the developed technique to a dataset consisting of 20 manually segmented images captured...

Application of artificial neural networks to segmentation and classification of topographic profiles of ridge-flank seafloor

Digital Repository Service at National Institute of Oceanography (India)

Chakraborty, B.; Lourenco, E.; Kodagali, V.N.; Baracho, J.

In this paper, we have utilized Artificial Neural Networks (ANN) for seafloor topographic data segmentation and roughness classification using the multibeam- Hydrosweep system (installed onboard ocean research vessel Sagar Kanya) data. Bathymetric...

Safety and feasibility of performing staged non-culprit vessel percutaneous coronary intervention within the index hospitalization in patients with ST-segment elevation myocardial infarction and multivessel disease

International Nuclear Information System (INIS)

Loh, Joshua P.; Kitabata, Hironori; Torguson, Rebecca; Satler, Lowell F.; Kent, Kenneth M.; Suddath, William O.; Pichard, Augusto D.; Lindsay, Joseph; Waksman, Ron

2013-01-01

Objectives: To determine whether staged percutaneous coronary intervention (PCI) within the same hospitalization as primary PCI is safe. Background: In ST-segment elevation myocardial infarction (STEMI) patients with multivessel disease undergoing primary PCI, staged non-culprit vessel PCI at a separate session is recommended. Methods: We conducted a retrospective analysis of 282 consecutive STEMI patients with multivessel disease who underwent primary PCI followed by staged PCI of the non-culprit vessel. Patients were categorized into staged PCI in the same hospitalization (n = 184) and staged PCI at a separate hospitalization within 8 weeks of primary PCI (n = 98). Results: Baseline characteristics, presentation of STEMI, and procedural characteristics were similar in both groups. Contrast amount was higher in the separate hospitalization group for both index (175 vs. 153 ml, p = 0.011) and staged (144 vs. 120 ml, p = 0.004) procedures. More staged left main PCI was performed in the separate hospitalization group (3.9 vs. 0.3%, p = 0.008). Angiographic success of staged PCI was similar in both groups, with similar rates of vascular complications and major bleeding. Following staged PCI, in-hospital major adverse cardiac events (3.3 vs. 1.0%, p = 0.43) and mortality (2.7 vs. 0%, p = 0.17) were similar in both groups. Conclusions: Our study supports the safety and feasibility of staged PCI within the same hospitalization as primary PCI, achieving similar procedural success and in-hospital outcomes as staged PCI at a separate hospitalization. Higher contrast amount used during primary PCI and presence of left main lesion in non-culprit vessels may influence the decision to stage the PCI at a separate hospitalization

Concept of a Prestressed Cast Iron Pressure Vessel for a Modular High Temperature Reactor

International Nuclear Information System (INIS)

Steinwarz, Wolfgang; Bounin, Dieter

2014-01-01

High Temperature Reactors (HTR) are representing one of the most interesting solutions for the upcoming generation of nuclear technology, especially with view to their inherent safety characteristics. To complete the safety concept of such plants already in the first phase of the technical development, Prestressed Cast Iron Pressure Vessels (PCIV) instead of the established forged steel reactor pressure vessels have been considered under the aspect of safety against bursting. A longterm research and development work, mainly performed in Germany, showed the excellent features of this technical solution. Diverse prototypic vessels were tested and officially proven. Design studies confirmed the feasibility of such a vessel concept also for Light Water Reactor types, too. The main concept elements of such a burst-proof vessel are: Strength and tightness functions are structurally separated. The tensile forces are carried by the prestressing systems consisting of a large number of independent wires. Compressive forces are applied to the vessel walls and heads. These are segmented into blocks of ductile cast iron. All cast iron blocks are prestressed to high levels of compression. The sealing function is assigned to a steel liner fixed to the cast iron blocks. The prestressing system is designed for an ultimate pressure of 2.3 times the design pressure. The prestress of the lids is designed for gapping at a much smaller pressure. Therefore, a drop of pressure will always occur before loss of strength (“leakage before failure”). In addition to these safety features further technical as well as economic aspects generate favorable assessment criteria: high design flexibility, feasibility of large vessel diameters; advantageous conditions for transport, assembly and decommissioning due to the segmented construction; advantage of workshop manufacturing; high-level quality control of components. Nowadays, considering the globally newly standardized safety requirements

Results of reactor pressure vessels ISI

International Nuclear Information System (INIS)

Cepcek, S.

1994-01-01

To find out the possible influence of the annealing process to reactor pressure vessel integrity, a large in-service inspection programme has been implemented as an associated activity to reactor pressure vessel annealing. In this paper the approach to the RPV in-service inspection is shown. Also, the main results and conclusions following in-service inspection are presented. (author). 3 refs, 1 fig

Extraction of liver volumetry based on blood vessel from the portal phase CT dataset

Science.gov (United States)

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

2012-02-01

At liver surgery planning stage, the liver volumetry would be essential for surgeons. Main problem at liver extraction is the wide variability of livers in shapes and sizes. Since, hepatic blood vessels structure varies from a person to another and covers liver region, the present method uses that information for extraction of liver in two stages. The first stage is to extract abdominal blood vessels in the form of hepatic and nonhepatic blood vessels. At the second stage, extracted vessels are used to control extraction of liver region automatically. Contrast enhanced CT datasets at only the portal phase of 50 cases is used. Those data include 30 abnormal livers. A reference for all cases is done through a comparison of two experts labeling results and correction of their inter-reader variability. Results of the proposed method agree with the reference at an average rate of 97.8%. Through application of different metrics mentioned at MICCAI workshop for liver segmentation, it is found that: volume overlap error is 4.4%, volume difference is 0.3%, average symmetric distance is 0.7 mm, Root mean square symmetric distance is 0.8 mm, and maximum distance is 15.8 mm. These results represent the average of overall data and show an improved accuracy compared to current liver segmentation methods. It seems to be a promising method for extraction of liver volumetry of various shapes and sizes.

Master curve approach to monitor fracture toughness of reactor pressure vessels in nuclear power plants

International Nuclear Information System (INIS)

2009-10-01

A series of coordinated research projects (CRPs) have been sponsored by the IAEA, starting in the early 1970s, focused on neutron radiation effects on reactor pressure vessel (RPV) steels. The purpose of the CRPs was to develop correlative comparisons to test the uniformity of results through coordinated international research studies and data sharing. The overall scope of the eighth CRP (CRP-8), Master Curve Approach to Monitor Fracture Toughness of Reactor Pressure Vessels in Nuclear Power Plants, has evolved from previous CRPs which have focused on fracture toughness related issues. The ultimate use of embrittlement understanding is application to assure structural integrity of the RPV under current and future operation and accident conditions. The Master Curve approach for assessing the fracture toughness of a sampled irradiated material has been gaining acceptance throughout the world. This direct measurement of fracture toughness approach is technically superior to the correlative and indirect methods used in the past to assess irradiated RPV integrity. Several elements have been identified as focal points for Master Curve use: (i) limits of applicability for the Master Curve at the upper range of the transition region for loading quasi-static to dynamic/impact loading rates; (ii) effects of non-homogeneous material or changes due to environment conditions on the Master Curve, and how heterogeneity can be integrated into a more inclusive Master Curve methodology; (iii) importance of fracture mode differences and changes affect the Master Curve shape. The collected data in this report represent mostly results from non-irradiated testing, although some results from test reactor irradiations and plant surveillance programmes have been included as available. The results presented here should allow utility engineers and scientists to directly measure fracture toughness using small surveillance size specimens and apply the results using the Master Curve approach

Segmentation-less Digital Rock Physics

Science.gov (United States)

Tisato, N.; Ikeda, K.; Goldfarb, E. J.; Spikes, K. T.

2017-12-01

In the last decade, Digital Rock Physics (DRP) has become an avenue to investigate physical and mechanical properties of geomaterials. DRP offers the advantage of simulating laboratory experiments on numerical samples that are obtained from analytical methods. Potentially, DRP could allow sparing part of the time and resources that are allocated to perform complicated laboratory tests. Like classic laboratory tests, the goal of DRP is to estimate accurately physical properties of rocks like hydraulic permeability or elastic moduli. Nevertheless, the physical properties of samples imaged using micro-computed tomography (μCT) are estimated through segmentation of the μCT dataset. Segmentation proves to be a challenging and arbitrary procedure that typically leads to inaccurate estimates of physical properties. Here we present a novel technique to extract physical properties from a μCT dataset without the use of segmentation. We show examples in which we use segmentation-less method to simulate elastic wave propagation and pressure wave diffusion to estimate elastic properties and permeability, respectively. The proposed method takes advantage of effective medium theories and uses the density and the porosity that are measured in the laboratory to constrain the results. We discuss the results and highlight that segmentation-less DRP is more accurate than segmentation based DRP approaches and theoretical modeling for the studied rock. In conclusion, the segmentation-less approach here presented seems to be a promising method to improve accuracy and to ease the overall workflow of DRP.

A new approach to study of seabird-fishery overlap: Connecting chick feeding with parental foraging and overlap with fishing vessels

Directory of Open Access Journals (Sweden)

Junichi Sugishita

2015-07-01

Full Text Available Incidental fisheries bycatch is recognised as a major threat to albatross populations worldwide. However, fishery discards and offal produced in large quantities might benefit some scavenging seabirds. Here, we demonstrate an integrated approach to better understand the ecological ramifications of fine-scale overlap between seabirds and fisheries. As a case study, we examined whether foraging in association with a fishing vessel is advantageous for chick provisioning in terms of quantity of food delivered to chicks, in northern royal albatross (Diomedea sanfordi at Taiaroa Head, New Zealand. Fine-scale overlap between albatrosses and vessels was quantified by integrating GPS tracking and Vessel Monitoring Systems (VMS. Meal size delivered to chicks was measured using custom-designed nest balances, and monitoring of attendance of adults fitted with radio transmitters was used in conjunction with time-lapse photography at the nest allowed us to allocate each feeding event to a specific parent. The combination of these techniques enabled comparison of meal sizes delivered to chicks with parental foraging trip durations with or without fishing vessels association. A total of 45 foraging trips and associated chick feeding events were monitored during the chick-rearing period in 2012. Differences in the meal size and foraging trip duration relative to foraging overlap with fisheries were examined using a linear mixed-effect model, adjusted for chick age. Our results, based on three birds, suggest that foraging in association with vessels does not confer an advantage for chick feeding for this population that demonstrated low rates of overlap while foraging. The integrated research design presented can be applied to other seabird species that are susceptible to bycatch, and offers a valuable approach to evaluate habitat quality by linking habitat use and foraging success in terms of total amount of food delivered to offspring.

Systematic review: comparative effectiveness of adjunctive devices in patients with ST-segment elevation myocardial infarction undergoing percutaneous coronary intervention of native vessels

Directory of Open Access Journals (Sweden)

Sobieraj Diana M

2011-12-01

Full Text Available Abstract Background During percutaneous coronary intervention (PCI, dislodgement of atherothrombotic material from coronary lesions can result in distal embolization, and may lead to increased major adverse cardiovascular events (MACE and mortality. We sought to systematically review the comparative effectiveness of adjunctive devices to remove thrombi or protect against distal embolization in patients with ST-segment elevation myocardial infarction (STEMI undergoing PCI of native vessels. Methods We conducted a systematic literature search of Medline, the Cochrane Database, and Web of Science (January 1996-March 2011, http://www.clinicaltrials.gov, abstracts from major cardiology meetings, TCTMD, and CardioSource Plus. Two investigators independently screened citations and extracted data from randomized controlled trials (RCTs that compared the use of adjunctive devices plus PCI to PCI alone, evaluated patients with STEMI, enrolled a population with 95% of target lesion(s in native vessels, and reported data on at least one pre-specified outcome. Quality was graded as good, fair or poor and the strength of evidence was rated as high, moderate, low or insufficient. Disagreement was resolved through consensus. Results 37 trials met inclusion criteria. At the maximal duration of follow-up, catheter aspiration devices plus PCI significantly decreased the risk of MACE by 27% compared to PCI alone. Catheter aspiration devices also significantly increased the achievement of ST-segment resolution by 49%, myocardial blush grade of 3 (MBG-3 by 39%, and thrombolysis in myocardial infarction (TIMI 3 flow by 8%, while reducing the risk of distal embolization by 44%, no reflow by 48% and coronary dissection by 70% versus standard PCI alone. In a majority of trials, the use of catheter aspiration devices increased procedural time upon qualitative assessment. Distal filter embolic protection devices significantly increased the risk of target revascularization

[Duodenum-preserving total pancreatic head resection and pancreatic head resection with segmental duodenostomy].

Science.gov (United States)

Takada, Tadahiro; Yasuda, Hideki; Nagashima, Ikuo; Amano, Hodaka; Yoshiada, Masahiro; Toyota, Naoyuki

2003-06-01

A duodenum-preserving pancreatic head resection (DPPHR) was first reported by Beger et al. in 1980. However, its application has been limited to chronic pancreatitis because of it is a subtotal pancreatic head resection. In 1990, we reported duodenum-preserving total pancreatic head resection (DPTPHR) in 26 cases. This opened the way for total pancreatic head resection, expanding the application of this approach to tumorigenic morbidities such as intraductal papillary mucinous tumor (IMPT), other benign tumors, and small pancreatic cancers. On the other hand, Nakao et al. reported pancreatic head resection with segmental duodenectomy (PHRSD) as an alternative pylorus-preserving pancreatoduodenectomy technique in 24 cases. Hirata et al. also reported this technique as a new pylorus-preserving pancreatoduodenostomy with increased vessel preservation. When performing DPTPHR, the surgeon should ensure adequate duodenal blood supply. Avoidance of duodenal ischemia is very important in this operation, and thus it is necessary to maintain blood flow in the posterior pancreatoduodenal artery and to preserve the mesoduodenal vessels. Postoperative pancreatic functional tests reveal that DPTPHR is superior to PPPD, including PHSRD, because the entire duodenum and duodenal integrity is very important for postoperative pancreatic function.

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

Science.gov (United States)

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

2013-05-01

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

Improvement of retinal blood vessel detection by spur removal and Gaussian matched filtering compensation

Science.gov (United States)

Xiao, Di; Vignarajan, Janardhan; An, Dong; Tay-Kearney, Mei-Ling; Kanagasingam, Yogi

2016-03-01

Retinal photography is a non-invasive and well-accepted clinical diagnosis of ocular diseases. Qualitative and quantitative assessment of retinal images is crucial in ocular diseases related clinical application. In this paper, we proposed approaches for improving the quality of blood vessel detection based on our initial blood vessel detection methods. A blood vessel spur pruning method has been developed for removing the blood vessel spurs both on vessel medial lines and binary vessel masks, which are caused by artifacts and side-effect of Gaussian matched vessel enhancement. A Gaussian matched filtering compensation method has been developed for removing incorrect vessel branches in the areas of low illumination. The proposed approaches were applied and tested on the color fundus images from one publicly available database and our diabetic retinopathy screening dataset. A preliminary result has demonstrated the robustness and good performance of the proposed approaches and their potential application for improving retinal blood vessel detection.

Dipyridamole-induced ST segment depression during thallium-201 imaging in patients with coronary artery disease: angiographic and hemodynamic determinants

International Nuclear Information System (INIS)

Chambers, C.E.; Brown, K.A.

1988-01-01

To examine the angiographic and hemodynamic determinants of dipyridamole-induced ST segment depression in patients with coronary artery disease, 41 patients with angiographically documented coronary disease who underwent dipyridamole-thallium-201 myocardial scintigraphy were studied. Dipyridamole-induced ST depression occurred in 14 (34%) of the 41 patients. Stepwise multivariate logistic regression was performed to compare the predictive value of angiographic findings (good coronary collateral vessels, jeopardized collateral vessels, multivessel disease), hemodynamic changes (changes in heart rate, systolic pressure, diastolic pressure and rate-pressure product), thallium-201 results (perfusion defect, thallium-201 redistribution) and demographic data (age, gender, medications). Only the presence of good coronary collateral vessels (p less than 0.02) and increases in rate-pressure product after dipyridamole infusion (p less than 0.02) were significant multivariate predictors of dipyridamole-induced ST depression. Good collateral vessels were more common in the group with ST depression (11 [79%] of 14) than they were in the group without ST depression (6 [22%] of 27; p less than 0.001). Rate-pressure product increased 2,835 +/- 1,648 beats/min.mm Hg in the group with ST depression compared with 1,179 +/- 1,417 beats/min.mm Hg in patients without ST depression (p less than 0.005). In conclusion, dipyridamole-induced ST segment depression in patients with coronary artery disease appears to be related to 1) the presence of good coronary collateral vessels, which may act by facilitating coronary steal, and 2) increases in rate-pressure product, reflecting increased myocardial oxygen demand. These observations may explain the lack of prognostic value of dipyridamole-induced ST segment depression described in previous reports

Models and Algorithms for Container Vessel Stowage Optimization

DEFF Research Database (Denmark)

Delgado-Ortegon, Alberto

.g., selection of vessels to buy that satisfy specific demands), through to operational decisions (e.g., selection of containers that optimize revenue, and stowing those containers into a vessel). This thesis addresses the question of whether it is possible to formulate stowage optimization models...... container of those to be loaded in a port should be placed in a vessel, i.e., to generate stowage plans. This thesis explores two different approaches to solve this problem, both follow a 2-phase decomposition that assigns containers to vessel sections in the first phase, i.e., master planning...

Vessel wall and indium-111-labelled platelet response to carotid endarterectomy

International Nuclear Information System (INIS)

Lusby, R.J.; Ferrell, L.D.; Englestad, B.L.; Price, D.C.; Lipton, M.J.; Stoney, R.J.

1983-01-01

Postendarterectomy platelet deposition and thrombus formation may play an important role not only in vessel wall healing but also in the small incidence of postoperative cerebral ischemia and postoperative stenosis. A study has been performed using a canine model to investigate the healing response to carotid endarterectomy and the validity of an in vivo indium-111 (In-111) radiotracer technique in the assessment of postendarterectomy deposition of autologous labelled platelets. Sixteen endarterectomized carotid arteries showed uptake of autologous In-111 platelets immediately after infusion, reaching a maximum by 1 hour with little increase at 24 or 48 hours. No uptake was seen in ten control vessels following platelet infusion (P less than 0.05). At autopsy, seven vessels were demonstrated to have In-111 platelet deposition immediately prior to sacrifice of the animals. Postmortem scanning confirmed the localization to the vessel lumens, and microscopy revealed thrombus formation with or without partial endothelialization. Complete reendothelialization had occurred in the vessels that failed to show platelet deposition. Delayed healing was associated with continuing platelet deposition, excessive thrombus formation, and luminal stenosis. Arteriotomy closure with a vein patch altered the healing characteristics of the vessel with segmental thrombus formation over the vein patch. A preliminary study of the postendarterectomy in vivo In-111 platelet response in humans demonstrated platelet deposition that was not influenced by the administration of antiplatelet drugs at currently prescribed levels

Segmental-dependent membrane permeability along the intestine following oral drug administration: Evaluation of a triple single-pass intestinal perfusion (TSPIP) approach in the rat.

Science.gov (United States)

Dahan, Arik; West, Brady T; Amidon, Gordon L

2009-02-15

In this paper we evaluate a modified approach to the traditional single-pass intestinal perfusion (SPIP) rat model in investigating segmental-dependent permeability along the intestine following oral drug administration. Whereas in the traditional model one single segment of the intestine is perfused, we have simultaneously perfused three individual segments of each rat intestine: proximal jejunum, mid-small intestine and distal ileum, enabling to obtain tripled data from each rat compared to the traditional model. Three drugs, with different permeabilities, were utilized to evaluate the model: metoprolol, propranolol and cimetidine. Data was evaluated in comparison to the traditional method. Metoprolol and propranolol showed similar P(eff) values in the modified model in all segments. Segmental-dependent permeability was obtained for cimetidine, with lower P(eff) in the distal parts. Similar P(eff) values for all drugs were obtained in the traditional method, illustrating that the modified model is as accurate as the traditional, throughout a wide range of permeability characteristics, whether the permeability is constant or segment-dependent along the intestine. Three-fold higher statistical power to detect segmental-dependency was obtained in the modified approach, as each subject serves as his own control. In conclusion, the Triple SPIP model can reduce the number of animals utilized in segmental-dependent permeability research without compromising the quality of the data obtained.

Optimally segmented permanent magnet structures

DEFF Research Database (Denmark)

Insinga, Andrea Roberto; Bjørk, Rasmus; Smith, Anders

2016-01-01

We present an optimization approach which can be employed to calculate the globally optimal segmentation of a two-dimensional magnetic system into uniformly magnetized pieces. For each segment the algorithm calculates the optimal shape and the optimal direction of the remanent flux density vector......, with respect to a linear objective functional. We illustrate the approach with results for magnet design problems from different areas, such as a permanent magnet electric motor, a beam focusing quadrupole magnet for particle accelerators and a rotary device for magnetic refrigeration....

Efficient graph-cut tattoo segmentation

Science.gov (United States)

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

2015-03-01

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

Segmented Assimilation Theory and the Life Model: An Integrated Approach to Understanding Immigrants and Their Children

Science.gov (United States)

Piedra, Lissette M.; Engstrom, David W.

2009-01-01

The life model offers social workers a promising framework to use in assisting immigrant families. However, the complexities of adaptation to a new country may make it difficult for social workers to operate from a purely ecological approach. The authors use segmented assimilation theory to better account for the specificities of the immigrant…

FRAMEWORK FOR COMPARING SEGMENTATION ALGORITHMS

Directory of Open Access Journals (Sweden)

G. Sithole

2015-05-01

Full Text Available The notion of a ‘Best’ segmentation does not exist. A segmentation algorithm is chosen based on the features it yields, the properties of the segments (point sets it generates, and the complexity of its algorithm. The segmentation is then assessed based on a variety of metrics such as homogeneity, heterogeneity, fragmentation, etc. Even after an algorithm is chosen its performance is still uncertain because the landscape/scenarios represented in a point cloud have a strong influence on the eventual segmentation. Thus selecting an appropriate segmentation algorithm is a process of trial and error. Automating the selection of segmentation algorithms and their parameters first requires methods to evaluate segmentations. Three common approaches for evaluating segmentation algorithms are ‘goodness methods’, ‘discrepancy methods’ and ‘benchmarks’. Benchmarks are considered the most comprehensive method of evaluation. This paper shortcomings in current benchmark methods are identified and a framework is proposed that permits both a visual and numerical evaluation of segmentations for different algorithms, algorithm parameters and evaluation metrics. The concept of the framework is demonstrated on a real point cloud. Current results are promising and suggest that it can be used to predict the performance of segmentation algorithms.

Muscle gap approach under a minimally invasive channel technique for treating long segmental lumbar spinal stenosis: A retrospective study.

Science.gov (United States)

Bin, Yang; De Cheng, Wang; Wei, Wang Zong; Hui, Li

2017-08-01

This study aimed to compare the efficacy of muscle gap approach under a minimally invasive channel surgical technique with the traditional median approach.In the Orthopedics Department of Traditional Chinese and Western Medicine Hospital, Tongzhou District, Beijing, 68 cases of lumbar spinal canal stenosis underwent surgery using the muscle gap approach under a minimally invasive channel technique and a median approach between September 2013 and February 2016. Both approaches adopted lumbar spinal canal decompression, intervertebral disk removal, cage implantation, and pedicle screw fixation. The operation time, bleeding volume, postoperative drainage volume, and preoperative and postoperative visual analog scale (VAS) score and Japanese Orthopedics Association score (JOA) were compared between the 2 groups.All patients were followed up for more than 1 year. No significant difference between the 2 groups was found with respect to age, gender, surgical segments. No diversity was noted in the operation time, intraoperative bleeding volume, preoperative and 1 month after the operation VAS score, preoperative and 1 month after the operation JOA score, and 6 months after the operation JOA score between 2 groups (P > .05). The amount of postoperative wound drainage (260.90 ± 160 mL vs 447.80 ± 183.60 mL, P gap approach group than in the median approach group (P gap approach under a minimally invasive channel group, the average drainage volume was reduced by 187 mL, and the average VAS score 6 months after the operation was reduced by an average of 0.48.The muscle gap approach under a minimally invasive channel technique is a feasible method to treat long segmental lumbar spinal canal stenosis. It retains the integrity of the posterior spine complex to the greatest extent, so as to reduce the adjacent spinal segmental degeneration and soft tissue trauma. Satisfactory short-term and long-term clinical results were obtained.

Further fields of application for prestressed cast iron pressure vessels (PCIV)

International Nuclear Information System (INIS)

Guelicher, L.; Schilling, F.E.

1977-01-01

The redundancy of the prestressing system of prestressed structures as well as the clear separation of sealing and load-carrying functions of prestressed cast iron pressure vessels offer substantial advantages over conventional welded steel pressure vessels. Because of the temperature resistance of cast iron up to 400 0 C it is possible to build prestressed pressure vessels commercially as hot-working structures. The compressive strength of cast iron, which is 25 times as high as that of concrete allows for a very compact design of the PCIV. Further specific properties of the PCIV like pre-fabrication of the vessel in the production plant - made possible by a structure assembled from segments - short assembly periods at the construction site etc., may open more fields of application. - PCIV as pressurized storage tanks for the emergency shut down system in nuclear power stations. - PCIV as high pressure vessel for the chemical industry. - PCIV as energy storage. - PCIV for light water reactors. - PCIV as burst protection. It is concluded that the application of prestressed cast iron promises to be successful where either structures with large volumes and high pressures and/or temperatures are required or where aspects of safety allow for efficient use of prestressed structures. (Auth.)

In vivo Observations on a Specialized Microvasculature, the Primary and Secondary Vessels in Fishes

DEFF Research Database (Denmark)

STEFFENSEN, JF; LOMHOLT, JP; VOGEL, WOP

1986-01-01

Microscopical observations have been made on the blood circulation of intact, unanaesthetized specimens of the transparent glass catfish. Along the segmental arteries of the trunk, groups of short, curled vessels of capillary dimensions (termed inter-arterial anastomoses) branch off and reunite...

Automated classification and quantitative analysis of arterial and venous vessels in fundus images

Science.gov (United States)

Alam, Minhaj; Son, Taeyoon; Toslak, Devrim; Lim, Jennifer I.; Yao, Xincheng

2018-02-01

It is known that retinopathies may affect arteries and veins differently. Therefore, reliable differentiation of arteries and veins is essential for computer-aided analysis of fundus images. The purpose of this study is to validate one automated method for robust classification of arteries and veins (A-V) in digital fundus images. We combine optical density ratio (ODR) analysis and blood vessel tracking algorithm to classify arteries and veins. A matched filtering method is used to enhance retinal blood vessels. Bottom hat filtering and global thresholding are used to segment the vessel and skeleton individual blood vessels. The vessel tracking algorithm is used to locate the optic disk and to identify source nodes of blood vessels in optic disk area. Each node can be identified as vein or artery using ODR information. Using the source nodes as starting point, the whole vessel trace is then tracked and classified as vein or artery using vessel curvature and angle information. 50 color fundus images from diabetic retinopathy patients were used to test the algorithm. Sensitivity, specificity, and accuracy metrics were measured to assess the validity of the proposed classification method compared to ground truths created by two independent observers. The algorithm demonstrated 97.52% accuracy in identifying blood vessels as vein or artery. A quantitative analysis upon A-V classification showed that average A-V ratio of width for NPDR subjects with hypertension decreased significantly (43.13%).

Metric Learning for Hyperspectral Image Segmentation

Science.gov (United States)

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

2011-01-01

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

Experimental investigation of natural convection heat transfer in volumetrically heated spherical segments. Final report

International Nuclear Information System (INIS)

Asfia, F.; Dhir, V.

1998-03-01

One strategy for preventing the failure of lower head of a nuclear reactor vessel is to flood the concrete cavity with subcooled water in accidents in which relocation of core material into the vessel lower head occurs. After the core material relocates into the vessel, a crust of solid material forms on the inner wall of the vessel, however, most of the pool remains molten and natural convection exists in the pool. At present, uncertainty exists with respect to natural convection heat transfer coefficients between the pool of molten core material and the reactor vessel wall. In the present work, experiments were conducted to examine natural convection heat transfer in internally heated partially filled spherical pools with external cooling. In the experiments, Freon-113 contained in a Pyrex bell jar was used as a test liquid. The pool was bounded with a spherical segment at the bottom, and was heated with magnetrons taken from a conventional microwave oven. The vessel was cooled from the outside with natural convection of water or with nucleate boiling of liquid nitrogen

A Regions of Confidence Based Approach to Enhance Segmentation with Shape Priors.

Science.gov (United States)

Appia, Vikram V; Ganapathy, Balaji; Abufadel, Amer; Yezzi, Anthony; Faber, Tracy

2010-01-18

We propose an improved region based segmentation model with shape priors that uses labels of confidence/interest to exclude the influence of certain regions in the image that may not provide useful information for segmentation. These could be regions in the image which are expected to have weak, missing or corrupt edges or they could be regions in the image which the user is not interested in segmenting, but are part of the object being segmented. In the training datasets, along with the manual segmentations we also generate an auxiliary map indicating these regions of low confidence/interest. Since, all the training images are acquired under similar conditions, we can train our algorithm to estimate these regions as well. Based on this training we will generate a map which indicates the regions in the image that are likely to contain no useful information for segmentation. We then use a parametric model to represent the segmenting curve as a combination of shape priors obtained by representing the training data as a collection of signed distance functions. We evolve an objective energy functional to evolve the global parameters that are used to represent the curve. We vary the influence each pixel has on the evolution of these parameters based on the confidence/interest label. When we use these labels to indicate the regions with low confidence; the regions containing accurate edges will have a dominant role in the evolution of the curve and the segmentation in the low confidence regions will be approximated based on the training data. Since our model evolves global parameters, it improves the segmentation even in the regions with accurate edges. This is because we eliminate the influence of the low confidence regions which may mislead the final segmentation. Similarly when we use the labels to indicate the regions which are not of importance, we will get a better segmentation of the object in the regions we are interested in.

Segmentation of the lumen and media-adventitia boundaries of the common carotid artery from 3D ultrasound images

Science.gov (United States)

Ukwatta, E.; Awad, J.; Ward, A. D.; Samarabandu, J.; Krasinski, A.; Parraga, G.; Fenster, A.

2011-03-01

Three-dimensional ultrasound (3D US) vessel wall volume (VWV) measurements provide high measurement sensitivity and reproducibility for the monitoring and assessment of carotid atherosclerosis. In this paper, we describe a semiautomated approach based on the level set method to delineate the media-adventitia and lumen boundaries of the common carotid artery from 3D US images to support the computation of VWV. Due to the presence of plaque and US image artifacts, the carotid arteries are challenging to segment using image information alone. Our segmentation framework combines several image cues with domain knowledge and limited user interaction. Our method was evaluated with respect to manually outlined boundaries on 430 2D US images extracted from 3D US images of 30 patients who have carotid stenosis of 60% or more. The VWV given by our method differed from that given by manual segmentation by 6.7% +/- 5.0%. For the media-adventitia and lumen segmentations, respectively, our method yielded Dice coefficients of 95.2% +/- 1.6%, 94.3% +/- 2.6%, mean absolute distances of 0.3 +/- 0.1 mm, 0.2 +/- 0.1 mm, maximum absolute distances of 0.8 +/- 0.4 mm, 0.6 +/- 0.3 mm, and volume differences of 4.2% +/- 3.1%, 3.4% +/- 2.6%. The realization of a semi-automated segmentation method will accelerate the translation of 3D carotid US to clinical care for the rapid, non-invasive, and economical monitoring of atherosclerotic disease progression and regression during therapy.

Novel method for edge detection of retinal vessels based on the model of the retinal vascular network and mathematical morphology

Science.gov (United States)

Xu, Lei; Zheng, Xiaoxiang; Zhang, Hengyi; Yu, Yajun

1998-09-01

Accurate edge detection of retinal vessels is a prerequisite for quantitative analysis of subtle morphological changes of retinal vessels under different pathological conditions. A novel method for edge detection of retinal vessels is presented in this paper. Methods: (1) Wavelet-based image preprocessing. (2) The signed edge detection algorithm and mathematical morphological operation are applied to get the approximate regions that contain retinal vessels. (3) By convolving the preprocessed image with a LoG operator only on the detected approximate regions of retinal vessels, followed by edges refining, clear edge maps of the retinal vessels are fast obtained. Results: A detailed performance evaluation together with the existing techniques is given to demonstrate the strong features of our method. Conclusions: True edge locations of retinal vessels can be fast detected with continuous structures of retinal vessels, less non- vessel segments left and insensitivity to noise. The method is also suitable for other application fields such as road edge detection.

Development of Catamaran Fishing Vessel

Directory of Open Access Journals (Sweden)

A. Jamaluddin

2010-11-01

Full Text Available Multihull due to a couple of advantages has been the topic of extensive research work in naval architecture. In this study, a series of investigation of fishing vessel to save fuel energy was carried out at ITS. Two types of ship models, monohull (round bilge and hard chine and catamaran, a boat with two hulls (symmetrical and asymmetrical were developed. Four models were produced physically and numerically, tested (towing tank and simulated numerically (CFD code. The results of the two approaches indicated that the catamaran mode might have drag (resistance smaller than those of monohull at the same displacement. A layout of catamaran fishing vessel, proposed here, indicates the freedom of setting the deck equipments for fishing vessel.

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

Science.gov (United States)

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

2013-09-01

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

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

Science.gov (United States)

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

2013-01-01

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

A local contrast based approach to threshold segmentation for PET target volume delineation

International Nuclear Information System (INIS)

Drever, Laura; Robinson, Don M.; McEwan, Alexander; Roa, Wilson

2006-01-01

Current radiation therapy techniques, such as intensity modulated radiation therapy and three-dimensional conformal radiotherapy rely on the precise delivery of high doses of radiation to well-defined volumes. CT, the imaging modality that is most commonly used to determine treatment volumes cannot, however, easily distinguish between cancerous and normal tissue. The ability of positron emission tomography (PET) to more readily differentiate between malignant and healthy tissues has generated great interest in using PET images to delineate target volumes for radiation treatment planning. At present the accurate geometric delineation of tumor volumes is a subject open to considerable interpretation. The possibility of using a local contrast based approach to threshold segmentation to accurately delineate PET target cross sections is investigated using well-defined cylindrical and spherical volumes. Contrast levels which yield correct volumetric quantification are found to be a function of the activity concentration ratio between target and background, target size, and slice location. Possibilities for clinical implementation are explored along with the limits posed by this form of segmentation

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

Science.gov (United States)

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

2015-08-01

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

Image segmentation algorithm based on T-junctions cues

Science.gov (United States)

Qian, Yanyu; Cao, Fengyun; Wang, Lu; Yang, Xuejie

2016-03-01

To improve the over-segmentation and over-merge phenomenon of single image segmentation algorithm,a novel approach of combing Graph-Based algorithm and T-junctions cues is proposed in this paper. First, a method by L0 gradient minimization is applied to the smoothing of the target image eliminate artifacts caused by noise and texture detail; Then, the initial over-segmentation result of the smoothing image using the graph-based algorithm; Finally, the final results via a region fusion strategy by t-junction cues. Experimental results on a variety of images verify the new approach's efficiency in eliminating artifacts caused by noise,segmentation accuracy and time complexity has been significantly improved.

Document flow segmentation for business applications

Science.gov (United States)

Daher, Hani; Belaïd, Abdel

2013-12-01

The aim of this paper is to propose a document flow supervised segmentation approach applied to real world heterogeneous documents. Our algorithm treats the flow of documents as couples of consecutive pages and studies the relationship that exists between them. At first, sets of features are extracted from the pages where we propose an approach to model the couple of pages into a single feature vector representation. This representation will be provided to a binary classifier which classifies the relationship as either segmentation or continuity. In case of segmentation, we consider that we have a complete document and the analysis of the flow continues by starting a new document. In case of continuity, the couple of pages are assimilated to the same document and the analysis continues on the flow. If there is an uncertainty on whether the relationship between the couple of pages should be classified as a continuity or segmentation, a rejection is decided and the pages analyzed until this point are considered as a "fragment". The first classification already provides good results approaching 90% on certain documents, which is high at this level of the system.

Engraftment of Prevascularized, Tissue Engineered Constructs in a Novel Rabbit Segmental Bone Defect Model

Directory of Open Access Journals (Sweden)

Alexandre Kaempfen

2015-06-01

Full Text Available The gold standard treatment of large segmental bone defects is autologous bone transfer, which suffers from low availability and additional morbidity. Tissue engineered bone able to engraft orthotopically and a suitable animal model for pre-clinical testing are direly needed. This study aimed to evaluate engraftment of tissue-engineered bone with different prevascularization strategies in a novel segmental defect model in the rabbit humerus. Decellularized bone matrix (Tutobone seeded with bone marrow mesenchymal stromal cells was used directly orthotopically or combined with a vessel and inserted immediately (1-step or only after six weeks of subcutaneous “incubation” (2-step. After 12 weeks, histological and radiological assessment was performed. Variable callus formation was observed. No bone formation or remodeling of the graft through TRAP positive osteoclasts could be detected. Instead, a variable amount of necrotic tissue formed. Although necrotic area correlated significantly with amount of vessels and the 2-step strategy had significantly more vessels than the 1-step strategy, no significant reduction of necrotic area was found. In conclusion, the animal model developed here represents a highly challenging situation, for which a suitable engineered bone graft with better prevascularization, better resorbability and higher osteogenicity has yet to be developed.

Extrinsic ureteropelvic junction obstruction from a crossing renal vessel: demography and imaging

Energy Technology Data Exchange (ETDEWEB)

Rooks, V.J.; Lebowitz, R.L. [Children' s Hospital and Harvard Medical School, Dept. of Radiology, Boston, MA (United States)

2001-02-01

Background. The increase in the use of prenatal ultrasound has revolutionized the detection of hydronephrosis and has had an unanticipated consequence. Objective. To describe the new demographics of symptomatic ureteropelvic junction (UPJ) obstruction and the characteristic imaging findings, when the obstruction is extrinsic, from a crossing renal vessel. Materials and methods. From a uroradiology database (1994 through 1999) we identified children with surgically corrected UPJ obstruction from intrinsic and extrinsic causes. Results. One hundred children had symptomatic UPJ obstruction treated by surgery. In 51 (49 %), obstruction was due to a crossing vessel. One hundred and one had UPJ obstruction detected by prenatal sonography. Only 11 (11 %) were due to a vessel. Two clinical and imaging findings were strongly suggestive of obstruction from a vessel: (1) in 5 of the 100 children the symptoms (pain, nausea, and vomiting) were intermittent. Only when symptoms were present were there hydronephrosis and obstruction; (2) in 51 of the 100 children a short segment of ureter, just below the UPJ, was filled with contrast or urine (on renal sonography, intravenous urography, or retrograde/antegrade ureterography). Conclusions. Extrinsic UPJ obstruction caused by a vessel is an uncommon cause of obstruction when all patients are considered. However, in symptomatic older patients whose hydronephrosis was not first identified on prenatal sonography, a vessel was the cause of obstruction in one-half. (orig.)

Simultaneous tomographic reconstruction and segmentation with class priors

DEFF Research Database (Denmark)

Romanov, Mikhail; Dahl, Anders Bjorholm; Dong, Yiqiu

2015-01-01

are combined to produce a reconstruction that is identical to the segmentation. We consider instead a hybrid approach that simultaneously produces both a reconstructed image and segmentation. We incorporate priors about the desired classes of the segmentation through a Hidden Markov Measure Field Model, and we...

A kinematic study of pulsation in the dorsal blood vessel of the blackworm, Lumbriculus variegatus

Directory of Open Access Journals (Sweden)

Kameko Halfmann

2011-01-01

Full Text Available The aquatic oligochaete Lumbriculus variegatus has a segmented, dorsal blood vessel (DBV that acts as a peristaltic pump to move blood through the animal's closed circulatory system. We conducted a kinematic study using videography and computational modeling as a first step toward understanding the control of DBV pulsation. Results suggested that pulse rates were highest in the posterior segments, while interpulse intervals and intersegmental delays were longest in the midbody segments. Differences in the interpulse interval distributions across regions suggest that some peristaltic waves initiated in the posterior segments do not propagate all the way to the anterior segments. A simple model consisting of a chain of excitable neuromuscular units replicated these kinetics. This model may be useful in future research aimed at understanding the modulatory effect of biogenic amines on peristalsis of the DBV. Moreover, research into the mechanisms of peristalsis of the DBV may lead to insights into disorders of peristalsis in human and veterinary medicine

An holistic approach to the problem of reactor ageing. [Pressure vessel embrittlement

Energy Technology Data Exchange (ETDEWEB)

Phythian, W.; McElroy, R.; Druce, S.; Kovan, D. (AEA Reactor Services, Harwell (United Kingdom))

1992-12-01

Understanding the process of ageing in reactors is essential to extending their lives beyond original design. To present a sound case -particularly regarding the level of embrittlement in reactor vessels due to radiation damage - an integrated approach using advanced assessment tools is needed. The techniques developed for the purpose involve, on the microscopic level, advanced neutron dosimetry and high resolution measurement techniques (eg advanced electron beam techniques and small angle neutron scattering) with which an analysis can be done of the radiation damage and the microstructural state of the steel test procedures (tensile, fracture toughness and Charpy impact) on standard and sub-sized specimens, the extent of radiation degradation can be characterised. finally, it is possible to predict how the degradation will evolve using physically-based models of embrittlement. (Author).

Automatic quantification of mammary glands on non-contrast x-ray CT by using a novel segmentation approach

Science.gov (United States)

Zhou, Xiangrong; Kano, Takuya; Cai, Yunliang; Li, Shuo; Zhou, Xinxin; Hara, Takeshi; Yokoyama, Ryujiro; Fujita, Hiroshi

2016-03-01

This paper describes a brand new automatic segmentation method for quantifying volume and density of mammary gland regions on non-contrast CT images. The proposed method uses two processing steps: (1) breast region localization, and (2) breast region decomposition to accomplish a robust mammary gland segmentation task on CT images. The first step detects two minimum bounding boxes of left and right breast regions, respectively, based on a machine-learning approach that adapts to a large variance of the breast appearances on different age levels. The second step divides the whole breast region in each side into mammary gland, fat tissue, and other regions by using spectral clustering technique that focuses on intra-region similarities of each patient and aims to overcome the image variance caused by different scan-parameters. The whole approach is designed as a simple structure with very minimum number of parameters to gain a superior robustness and computational efficiency for real clinical setting. We applied this approach to a dataset of 300 CT scans, which are sampled with the equal number from 30 to 50 years-old-women. Comparing to human annotations, the proposed approach can measure volume and quantify distributions of the CT numbers of mammary gland regions successfully. The experimental results demonstrated that the proposed approach achieves results consistent with manual annotations. Through our proposed framework, an efficient and effective low cost clinical screening scheme may be easily implemented to predict breast cancer risk, especially on those already acquired scans.

Mixed raster content segmentation, compression, transmission

CERN Document Server

Pavlidis, George

2017-01-01

This book presents the main concepts in handling digital images of mixed content, traditionally referenced as mixed raster content (MRC), in two main parts. The first includes introductory chapters covering the scientific and technical background aspects, whereas the second presents a set of research and development approaches to tackle key issues in MRC segmentation, compression and transmission. The book starts with a review of color theory and the mechanism of color vision in humans. In turn, the second chapter reviews data coding and compression methods so as to set the background and demonstrate the complexity involved in dealing with MRC. Chapter three addresses the segmentation of images through an extensive literature review, which highlights the various approaches used to tackle MRC segmentation. The second part of the book focuses on the segmentation of color images for optimized compression, including multi-layered decomposition and representation of MRC and the processes that can be employed to op...

An automated and robust image processing algorithm for glaucoma diagnosis from fundus images using novel blood vessel tracking and bend point detection.

Science.gov (United States)

M, Soorya; Issac, Ashish; Dutta, Malay Kishore

2018-02-01

Glaucoma is an ocular disease which can cause irreversible blindness. The disease is currently identified using specialized equipment operated by optometrists manually. The proposed work aims to provide an efficient imaging solution which can help in automating the process of Glaucoma diagnosis using computer vision techniques from digital fundus images. The proposed method segments the optic disc using a geometrical feature based strategic framework which improves the detection accuracy and makes the algorithm invariant to illumination and noise. Corner thresholding and point contour joining based novel methods are proposed to construct smooth contours of Optic Disc. Based on a clinical approach as used by ophthalmologist, the proposed algorithm tracks blood vessels inside the disc region and identifies the points at which first vessel bend from the optic disc boundary and connects them to obtain the contours of Optic Cup. The proposed method has been compared with the ground truth marked by the medical experts and the similarity parameters, used to determine the performance of the proposed method, have yield a high similarity of segmentation. The proposed method has achieved a macro-averaged f-score of 0.9485 and accuracy of 97.01% in correctly classifying fundus images. The proposed method is clinically significant and can be used for Glaucoma screening over a large population which will work in a real time. Copyright © 2017 Elsevier B.V. All rights reserved.

Aspects of the design and structural analysis of the prestressed cast iron nuclear reactor pressure vessel

International Nuclear Information System (INIS)

Thomas, R.G.

1978-09-01

The development of the prestressed cast iron nuclear reactor pressure vessel up to the present time is reviewed, and the current status is outlined of the techniques used for its structural analysis. Details of the manufacturing processes involved in the production of the castings, and problems of inspecting them to the standards required for a nuclear application are discussed. A method for the detailed modelling of the cast iron segments is proposed, using the finite element technique with plate bending elements, and criteria for obtaining accurate results are derived. The application of the technique to the analysis of a single cast segment situated in the wall of a PCIPV has enabled an accurate determination of the stress field to be made. Account is taken of the effect of the vessel displacements on the tendon stresses at normal vault pressure and at high overpressure. Studies by this method of several different casting designs have identified favourable features, which have been incorporated into an optimised design. The sensitivity of the structure to a machining error in a casting and to the failure or removal of circumferential and axial tendons is examined, making use of axisymmetric and three-dimensional global finite element solutions to provide boundary conditions for detailed local analyses. Some aspects of the economics of the cast iron reactor pressure vessel are discussed, and recommendations are made for further research in areas relevant to the assessment of the reliability of the vessel. (author)

Utilising Tree-Based Ensemble Learning for Speaker Segmentation

DEFF Research Database (Denmark)

Abou-Zleikha, Mohamed; Tan, Zheng-Hua; Christensen, Mads Græsbøll

2014-01-01

In audio and speech processing, accurate detection of the changing points between multiple speakers in speech segments is an important stage for several applications such as speaker identification and tracking. Bayesian Information Criteria (BIC)-based approaches are the most traditionally used...... for a certain condition, the model becomes biased to the data used for training limiting the model’s generalisation ability. In this paper, we propose a BIC-based tuning-free approach for speaker segmentation through the use of ensemble-based learning. A forest of segmentation trees is constructed in which each...... tree is trained using a sampled version of the speech segment. During the tree construction process, a set of randomly selected points in the input sequence is examined as potential segmentation points. The point that yields the highest ΔBIC is chosen and the same process is repeated for the resultant...

Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

Science.gov (United States)

Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong

2016-02-01

Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

A Novel Approach for Bi-Level Segmentation of Tuberculosis Bacilli Based on Meta-Heuristic Algorithms

Directory of Open Access Journals (Sweden)

AYAS, S.

2018-02-01

Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.

Image segmentation evaluation for very-large datasets

Science.gov (United States)

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

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.