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http://dx.doi.org/10.5351/KJAS.2003.16.2.305

EM Algorithm-based Segmentation of Magnetic Resonance Image Corrupted by Bias Field  

김승구 (상지대학교 응용통계학과)
Publication Information
The Korean Journal of Applied Statistics / v.16, no.2, 2003 , pp. 305-319 More about this Journal
Abstract
This paper provides a non-Bayesian method based on the expanded EM algorithm for segmenting the magnetic resonance images degraded by bias field. For the images with the intensity as a pixel value, many segmentation methods often fail to segment it because of the bias field(with low frequency) as well as noise(with high frequency). Our contextual approach is appropriately designed by using normal mixture model incorporated with Markov random field for noise-corrective segmentation and by using the penalized likelihood to estimate bias field for efficient bias filed-correction.
Keywords
MRI; MRI; image segmentation; bias field; normal mixture model; penalized EM algorithm; ECM algorithm;
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