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Contrast-Based Fully Automatic Segmentation of White Matter Hyperintensities: Method and Validation

by Thomas Samaille, Ludovic Fillon, Eric Jouvent, Hugues Chabriat, Didier Dormont, Olivier Colliot, Marie Chupin
"... White matter hyperintensities (WMH) on T2 or FLAIR sequences have been commonly observed on MR images of elderly people. They have been associated with various disorders and have been shown to be a strong risk factor for stroke and dementia. WMH studies usually required visual evaluation of WMH load ..."
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load or time-consuming manual delineation. This paper introduced WHASA (White matter Hyperintensities Automated Segmentation Algorithm), a new method for automatically segmenting WMH from FLAIR and T1 images in multicentre studies. Contrary to previous approaches that were based on intensities

Automatic identification of grey matter structures from MRI to improve the segmentation of white matter lesions

by Simon Warfield, William M. Wells Iii, Joachim Dengler, Gil J. Ettinger - Journal of Image Guided Surgery , 1995
"... The segmentation of MRI scans of patients with white matter lesions (WML) is difficult because the MRI characteristics of white matter lesions are similar to those of grey matter. Intensity based statistical classification techniques misclassify some WML as grey matter and some grey matter as WML. W ..."
Abstract - Cited by 21 (14 self) - Add to MetaCart
The segmentation of MRI scans of patients with white matter lesions (WML) is difficult because the MRI characteristics of white matter lesions are similar to those of grey matter. Intensity based statistical classification techniques misclassify some WML as grey matter and some grey matter as WML

REVIEW Automatic Detection of White Matter Hyperintensities in Healthy Aging and Pathology Using Magnetic Resonance Imaging: A Review

by Maria Eugenia Caligiuri, Paolo Perrotta, Antonio Augimeri, Federico Rocca, Aldo Quattrone, Andrea Cherubini , 2015
"... # The Author(s) 2015. This article is published with open access at Springerlink.com Abstract White matter hyperintensities (WMH) are commonly seen in the brain of healthy elderly subjects and patients with several neurological and vascular dis-orders. A truly reliable and fully automated method for ..."
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# The Author(s) 2015. This article is published with open access at Springerlink.com Abstract White matter hyperintensities (WMH) are commonly seen in the brain of healthy elderly subjects and patients with several neurological and vascular dis-orders. A truly reliable and fully automated method

Semi-automatic Segmentation of Multiple Sclerosis Lesion Based Active Contours Model and Variational Dirichlet Process

by Foued Derraz, Laurent Peyrodie, Antonio Pinti, Azzeddine Chikh, Patrick Hautecoeur
"... Abstract: We propose a new semi-automatic segmentation based Active Contour Model and statistic prior knowledge of Multiple Sclerosis (MS) Lesions in Regions Of Interest (RIO) within brain Magnetic Resonance Images(MRI). Reliable segmentation of MS lesion is important for at least three types of pra ..."
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Abstract: We propose a new semi-automatic segmentation based Active Contour Model and statistic prior knowledge of Multiple Sclerosis (MS) Lesions in Regions Of Interest (RIO) within brain Magnetic Resonance Images(MRI). Reliable segmentation of MS lesion is important for at least three types

1106 Segmentation of Multiple Sclerosis Lesions in MRI-An Image Analysis Approach

by K. Krishnan, M. S. Atkins
"... This paper describes an intensity-based method for the segmentation of multiple sclerosis lesions in dual-echo PD and T2-weighted magnetic resonance brain images. The method consists of two stages: feature extraction and image analysis. For feature extraction, we use a ratio filter transformation on ..."
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This paper describes an intensity-based method for the segmentation of multiple sclerosis lesions in dual-echo PD and T2-weighted magnetic resonance brain images. The method consists of two stages: feature extraction and image analysis. For feature extraction, we use a ratio filter transformation

Optimizing the Use of Radiologist Seed Points for Improved Multiple Sclerosis Lesion Segmentation

by Jon Mcausl, Roger C. Tam, Erick Wong, Andrew Riddehough, David K. B. Li
"... Abstract—Many current methods for multiple sclerosis (MS) lesion segmentation require radiologist seed points as input, but do not necessarily allow the expert to work in an intuitive or efficient way. Ironically, most methods also assume that the points are placed optimally. This paper examines how ..."
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categories. Index Terms—Magnetic resonance imaging (MRI), multiple sclerosis (MS), seed points, segmentation, white matter lesions (WMLs). I.

Multiple Sclerosis lesion segmentation using Active Contours model and adaptive outlier detection method

by Foued Derraz , Antonio Pinti , Laurent Peyrodie , Miloud Boussahla , Hechmi Toumi , Patrick Hautecoeur
"... Abstract. The segmentation of Multiple Sclerosis (MS) lesions on Magnetic Resonance Imaging (MRI) has become a crucial criterion for diagnosis and predicting prognosis in early disease. Automated MS lesion segmentation is highly desirable for its low time computation, cost, effectiveness and minimu ..."
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and minimum user bias. We proposed to develop and evaluate an automated lesion segmentation method based on Active Contours (AC) model incorporating tissue knowledge issued from T1-weighted and tissues distribution on Attenuated Inversion recovery (FLAIR) image. The Gray Matter (GM) and White Matter (WM

A Rule-Based Approach to Stroke Lesion Analysis from CT Brain Images

by Milan Matein, Sven Lonaric - Proc. of Second International Symposium on Image and Signal Process. and Analysis , 2001
"... This paper presents a method for automatic segmentation and labeling of computed tomography (CT) head images of stroke lesions. The method is composed of three steps. The first step is automatic determination of head symmetry axis, with possibility of manual improvement of result, if necessary. ..."
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This paper presents a method for automatic segmentation and labeling of computed tomography (CT) head images of stroke lesions. The method is composed of three steps. The first step is automatic determination of head symmetry axis, with possibility of manual improvement of result, if necessary

Active Mask Framework for Segmentation of Fluorescence Microscope Images

by Gowri Srinivasa, Advisor Prof, Prof Matthew, C. Fickus, Prof Adam, D. Linstedt, Prof Robert, F. Murphy
"... m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol of ..."
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facilitated the task of understanding complex sys-tems at cellular and molecular levels in recent years. Segmentation, an important yet dif-ficult problem, is often the first processing step following acquisition. Our team previously demonstrated that a stochastic active contour based algorithm together

Classification of Brain Tumor Using Discrete Wavelet Transform, Principal Component Analysis and Probabilistic Neural Network

by Swapnali Sawakare, Dimple Chaudhari
"... The project proposes an automatic support system for stage classification using artificial neural network (learning machine) and to detect Brain Tumor through k-means clustering methods for medical imaging application. The detection of the Brain Tumor is a challenging problem, due to the structure o ..."
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that is benign, malignant or normal. The segmentation results will be used as a base for a Computer Aided Diagnosis (CAD) system for early detection of Brain Tumor which will improves the chances of survival for the patient. This paper describes an efficient method for automatic brain tumor segmentation
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