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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationSmart Digital Futures 2014
PublisherIOS Press
Pages412-420
Number of pages9
ISBN (Print)9781614994046
DOIs
Publication statusPublished - 2014
Externally publishedYes

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume262
ISSN (Print)0922-6389

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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