Automatic segmentation of liver from CT images using probabilistic atlas and template matching

Yen Wei Chen, Amir H. Foruzan, Chunhua Dong, Tomoko Tateyama, Xianhua Han

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

2 被引用数 (Scopus)

抄録

A framework is proposed for automatic liver segmentation from CT volumes using probabilistic atlases and template matching techniques. Probabilistic atlases of human anatomy have been widely used for organ segmentation, which is used as a prior probability in a Bayes framework. The challenge is how to register the atlas to the patient volume. In this paper, we propose a template matching based technique for probabilistic atlas based organ segmentation. In our proposed method, we first find a Region of Interest (ROI) of the organ, which is based on human anatomic structure, and then the probabilistic atlas is used as a template to find the organ in the ROI by the use of template matching.

本文言語英語
ホスト出版物のタイトルSmart Digital Futures 2014
出版社IOS Press BV
ページ412-420
ページ数9
ISBN(印刷版)9781614994046
DOI
出版ステータス出版済み - 2014
外部発表はい

出版物シリーズ

名前Frontiers in Artificial Intelligence and Applications
262
ISSN(印刷版)0922-6389
ISSN(電子版)1879-8314

All Science Journal Classification (ASJC) codes

  • 人工知能

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