3D liver volume morphing and statistical modeling using Generalized N-dimensional Principal Component Analysis method (医用画像)

概要

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In this paper, we propose a statistical texture modeling method for medical volumes. In order to deal with the problems of high-dimension and Small number of medial samples, we propose an effective image compression method named Generalized N-dimensional Principal Component Analysis(GND-PCA)to construct a statistical model. As the shapes of the human organ are very different from one case to another, we apply 3D volume morphing to normalize all the volume datasets to a same shape for removing shape variations. Then, we use GND-PCA method to get features, which just contain the information of texture. Experiments applied on liver volumes show good property of generalization using our method. We also did a simple experiment to show that the features extracted by our models have capability of discrimination for different types of data, such as normal and abnormal.
社団法人電子情報通信学会の論文
2010-01-21