A parametric statistic model and fast algorithm for brain MR image segmentation and bias correction

Tianming Zhan; Zhihui Wei; Liang Xiao; Ling Qian

doi:10.1117/12.910782

14 February 2012 A parametric statistic model and fast algorithm for brain MR image segmentation and bias correction

Tianming Zhan, Zhihui Wei, Liang Xiao, Ling Qian

Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83142I (2012) https://doi.org/10.1117/12.910782
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

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.

Citation Download Citation

Tianming Zhan, Zhihui Wei, Liang Xiao, and Ling Qian "A parametric statistic model and fast algorithm for brain MR image segmentation and bias correction", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83142I (14 February 2012); https://doi.org/10.1117/12.910782

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available