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Proceedings Paper

A parametric statistic model and fast algorithm for brain MR image segmentation and bias correction
Author(s): Tianming Zhan; Zhihui Wei; Liang Xiao; Ling Qian
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Paper Abstract

In this paper, we propose an improved method for simultaneous estimation of the bias field and segmentation of tissues for magnetic resonance images, which is an extension of the method in. Firstly, the bias field is modeled as a linear combination of a set of basis functions, and thereby parameterized by the coefficients of the basis functions. Then we model the distribution of intensity in each tissue as a Gaussian distribution, and use the maximum a posteriori probability and total variation (TV) regularization to define our objective energy function. At last, an efficient iterative algorithm based on split Bregman method is used to minimize our energy function at a fast rate. Comparisons with other approaches demonstrate the superior performance of this algorithm.

Paper Details

Date Published: 14 February 2012
PDF: 6 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83142I (14 February 2012); doi: 10.1117/12.910782
Show Author Affiliations
Tianming Zhan, Nanjing Univ. of Science & Technology (China)
Zhihui Wei, Nanjing Univ. of Science & Technology (China)
Liang Xiao, Nanjing Univ. of Science & Technology (China)
Ling Qian, Nanjing Univ. of Science & Technology (China)

Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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