Quantitative analysis of multiple sclerosis: a feasibility study

Lihong Li; Xiang Li; Xinzhou Wei; Deborah Sturm; Hongbing Lu; Zhengrong Liang

doi:10.1117/12.654181

13 March 2006 Quantitative analysis of multiple sclerosis: a feasibility study

Lihong Li, Xiang Li, Xinzhou Wei, Deborah Sturm, Hongbing Lu, Zhengrong Liang

Proceedings Volume 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images; 61430U (2006) https://doi.org/10.1117/12.654181
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

Multiple Sclerosis (MS) is an inflammatory and demyelinating disorder of the central nervous system with a presumed immune-mediated etiology. For treatment of MS, the measurements of white matter (WM), gray matter (GM), and cerebral spinal fluid (CSF) are often used in conjunction with clinical evaluation to provide a more objective measure of MS burden. In this paper, we apply a new unifying automatic mixture-based algorithm for segmentation of brain tissues to quantitatively analyze MS. The method takes into account the following effects that commonly appear in MR imaging: 1) The MR data is modeled as a stochastic process with an inherent inhomogeneity effect of smoothly varying intensity; 2) A new partial volume (PV) model is built in establishing the maximum a posterior (MAP) segmentation scheme; 3) Noise artifacts are minimized by a priori Markov random field (MRF) penalty indicating neighborhood correlation from tissue mixture. The volumes of brain tissues (WM, GM) and CSF are extracted from the mixture-based segmentation. Experimental results of feasibility studies on quantitative analysis of MS are presented.

Citation Download Citation

Lihong Li, Xiang Li, Xinzhou Wei, Deborah Sturm, Hongbing Lu, and Zhengrong Liang "Quantitative analysis of multiple sclerosis: a feasibility study", Proc. SPIE 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, 61430U (13 March 2006); https://doi.org/10.1117/12.654181

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