Model-based 3-D segmentation of multiple sclerosis lesions in dual-echo MRI data

Micheline Kamber; D. Louis Collins; Rajjan Shinghal; G. S. Francis; Alan C. Evans

doi:10.1117/12.131112

22 September 1992 Model-based 3-D segmentation of multiple sclerosis lesions in dual-echo MRI data

Micheline Kamber, D. Louis Collins, Rajjan Shinghal, G. S. Francis, Alan C. Evans

Proceedings Volume 1808, Visualization in Biomedical Computing '92; (1992) https://doi.org/10.1117/12.131112
Event: Visualization in Biomedical Computing, 1992, Chapel Hill, NC, United States

Abstract

This paper describes the development and use of a brain tissue probability model for the segmentation of multiple sclerosis lesions in magnetic resonance (MR) images of the human brain. Based on MR data obtained from a group of healthy volunteers, the model was constructed to provide prior probabilities of grey matter, white matter, ventricular cerebrospinal fluid (CSF), and external CSF distribution per unit voxel in a standardized 3- dimensional `brain space.' In comparison to purely data-driven segmentation, the use of the model to guide the segmentation of multiple sclerosis lesions reduced the volume of false positive lesions by 50%.

Citation Download Citation

Micheline Kamber, D. Louis Collins, Rajjan Shinghal, G. S. Francis, and Alan C. Evans "Model-based 3-D segmentation of multiple sclerosis lesions in dual-echo MRI data", Proc. SPIE 1808, Visualization in Biomedical Computing '92, (22 September 1992); https://doi.org/10.1117/12.131112

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