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Open AccessJournal ArticleDOI

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

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TLDR
A computer-assisted WML segmentation method, based on local features extracted from multiparametric magnetic resonance imaging (MRI) sequences, that reduces false positives by using anatomic knowledge and measures of distance from the training set.
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This article is published in Academic Radiology.The article was published on 2008-03-01 and is currently open access. It has received 235 citations till now. The article focuses on the topics: Population.

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Citations
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A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions.

TL;DR: Evaluation with both simulated and real data sets demonstrates that the method has an accuracy competitive with state-of-the-art MS lesion segmentation methods, while simultaneously segmenting the whole brain.
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BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities.

TL;DR: The findings suggest that BIANCA, which will be freely available as part of the FSL package, is a reliable method for automated WMH segmentation in large cross-sectional cohort studies.
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Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches

TL;DR: The main features of the segmentation algorithms are analysed and the most recent important techniques are classified into different strategies according to their main principle, pointing out their strengths and weaknesses and suggesting new research directions.
References
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Statistical learning theory

TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
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A Tutorial on Support Vector Machines for Pattern Recognition

TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
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Advances in functional and structural MR image analysis and implementation as FSL.

TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.
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Fast robust automated brain extraction

TL;DR: An automated method for segmenting magnetic resonance head images into brain and non‐brain has been developed and described and examples of results and the results of extensive quantitative testing against “gold‐standard” hand segmentations, and two other popular automated methods.
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