ICA Mixture Analysis of Four-Phase Abdominal CT Images

Xuebin HU  Akinobu SHIMIZU  Hidefumi KOBATAKE  Shigeru NAWANO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E87-D   No.11   pp.2521-2525
Publication Date: 2004/11/01
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Biological Engineering
Keyword: 
ICA mixture model,  four-phase CT images,  segmentation,  tumor detection,  

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Summary: 
This paper presents a new analysis result of two-dimensional four-phase abdominal CT images using variational Bayesian mixture of ICA. The four-phase CT images are assumed to be comprised of several exclusive areas, and each area is generated by a set of corresponding independent components. ICA mixture analysis results show that the CT images could be divided into a set of clinically and anatomically meaningful components. Initial analysis of the independent components shows its promising prospects in medical image processing and computer-aided diagnosis.