Segmentation of multiple sclerosis lesions in MR images: a review.
about
Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosisIncreasing the contrast of the brain MR FLAIR images using fuzzy membership functions and structural similarity indices in order to segment MS lesions.Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR.Towards automated detection of depression from brain structural magnetic resonance images.A semi-automated measuring system of brain diffusion and perfusion magnetic resonance imaging abnormalities in patients with multiple sclerosis based on the integration of coregistration and tissue segmentation proceduresWhite matter signal abnormality quality differentiates mild cognitive impairment that converts to Alzheimer's disease from nonconverters.Fully automated open-source lesion mapping of T2-FLAIR images with FSL correlates with clinical disability in MSAccurate white matter lesion segmentation by k nearest neighbor classification with tissue type priors (kNN-TTPs).MANIFOLD-CONSTRAINED EMBEDDINGS FOR THE DETECTION OF WHITE MATTER LESIONS IN BRAIN MRI.Accurate GM atrophy quantification in MS using lesion-filling with co-registered 2D lesion masksNeural Network-Based Learning Kernel for Automatic Segmentation of Multiple Sclerosis Lesions on Magnetic Resonance Images.Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images.BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities.White Matter Lesion Assessment in Patients with Cognitive Impairment and Healthy Controls: Reliability Comparisons between Visual Rating, a Manual, and an Automatic Volumetrical MRI Method-The Gothenburg MCI Study.A hybrid approach based on logistic classification and iterative contrast enhancement algorithm for hyperintense multiple sclerosis lesion segmentation.Improving Multiple Sclerosis Plaque Detection Using a Semiautomated Assistive Approach.Neuroradiologists Compared with Non-Neuroradiologists in the Detection of New Multiple Sclerosis Plaques.A subtraction pipeline for automatic detection of new appearing multiple sclerosis lesions in longitudinal studies.Quantitative magnetic resonance imaging in a naturally occurring canine model of spinal cord injury.Application of variable threshold intensity to segmentation for white matter hyperintensities in fluid attenuated inversion recovery magnetic resonance images.Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure
P2860
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P2860
Segmentation of multiple sclerosis lesions in MR images: a review.
description
2011 nî lūn-bûn
@nan
2011 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Segmentation of multiple sclerosis lesions in MR images: a review.
@ast
Segmentation of multiple sclerosis lesions in MR images: a review.
@en
type
label
Segmentation of multiple sclerosis lesions in MR images: a review.
@ast
Segmentation of multiple sclerosis lesions in MR images: a review.
@en
prefLabel
Segmentation of multiple sclerosis lesions in MR images: a review.
@ast
Segmentation of multiple sclerosis lesions in MR images: a review.
@en
P2093
P2860
P1433
P1476
Segmentation of multiple sclerosis lesions in MR images: a review.
@en
P2093
Abbas Z Kouzani
Daryoush Mortazavi
Hamid Soltanian-Zadeh
P2860
P2888
P304
P356
10.1007/S00234-011-0886-7
P577
2011-05-17T00:00:00Z
P6179
1048776620