A new iterative method for liver segmentation from perfusion CT scans
Ahmed Draoua, Adélaïde Albouy-Kissi, Antoine Vacavant, Vincent Sauvage · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014
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.