13 March 2006 Quantitative analysis of multiple sclerosis: a feasibility study
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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.
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Lihong Li, Lihong Li, Xiang Li, Xiang Li, Xinzhou Wei, Xinzhou Wei, Deborah Sturm, Deborah Sturm, Hongbing Lu, Hongbing Lu, Zhengrong Liang, 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); doi: 10.1117/12.654181; https://doi.org/10.1117/12.654181
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