A New Iterative Method for Liver Segmentation from Perfusion CT Scans

被引：2

作者：

Draoua, Ahmed ^{[1
]}

Kissi, Adelaide Albouy ^{[1
]}

Vacavant, Antoine ^{[1
]}

Sauvage, Vincent ^{[1
]}

机构：

[1] Univ Auvergne, CNRS, UMR6284, ISIT, F-63001 Clermont Ferrand, France

来源：

MEDICAL IMAGING 2014: IMAGE PERCEPTION, OBSERVER PERFORMANCE, AND TECHNOLOGY ASSESSMENT | 2014年 / 9037卷

关键词：

Liver segmentation; Fuzzy C-means; Fast marching; Mutual information; FAST MARCHING METHOD; REGISTRATION; IMAGES; DIFFUSION;

D O I：

10.1117/12.2043576

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Liver cancer is the third most common cancer in the world, and the majority of patients with liver cancer will die within one year as a result of the cancer. Liver segmentation in the abdominal area is critical for diagnosis of tumor and for surgical procedures. Moreover, it is a challenging task as liver tissue has to be separated from adjacent organs and substantially the heart. In this paper we present a novel liver segmentation iterative method based on Fuzzy C-means (FCM) coupled with a fast marching segmentation and mutual information. A prerequisite for this method is the determination of slice correspondences between ground truth that is, a few images segmented by an expert, and images that contain liver and heart at the same time.

引用

页数：9

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