Automatic segmentation of white matter lesions in T1-weighted brain MR images

Songyang Yu, Dzung L. Pham, Dinggang Shen, Edward H. Herskovits, Susan M. Resnick, Christos Davatzikos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

White matter lesions are common brain abnormalities. In this paper, an automatic method for segmentation of white matter lesions in T1-weighted brain magnetic resonance (MR) images is presented. A subject's T1-weighted MR image is first segmented into the three major tissue types, white matter (WM), gray matter (GM) and cerebral spinal fluid (CSF) solely based on each voxel's intensity. Since WM lesions are typically classified as GM based on their intensity characteristics, the GM class is then separated into normal GM and WM lesions. This is accomplished using a statistical model of tissue distribution of healthy brains in a stereotaxic space. The proposed method is tested on 10 MR images with WM lesions and the results of the method are visually compared with WM lesions manually labeled by an experienced radiologist.

Original languageEnglish
Title of host publication2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
PublisherIEEE Computer Society
Pages253-256
Number of pages4
ISBN (Electronic)078037584X
DOIs
StatePublished - 2002
EventIEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States
Duration: 7 Jul 200210 Jul 2002

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2002-January
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

ConferenceIEEE International Symposium on Biomedical Imaging, ISBI 2002
Country/TerritoryUnited States
CityWashington
Period7/07/0210/07/02

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