| Literature DB >> 26415164 |
Karteek Popuri, Dana Cobzas, Nina Esfandiari, Vickie Baracos, Martin Jägersand.
Abstract
The proportions of muscle and fat tissues in the human body, referred to as body composition is a vital measurement for cancer patients. Body composition has been recently linked to patient survival and the onset/recurrence of several types of cancers in numerous cancer research studies. This paper introduces a fully automatic framework for the segmentation of muscle and fat tissues from CT images to estimate body composition. We developed a novel finite element method (FEM) deformable model that incorporates a priori shape information via a statistical deformation model (SDM) within the template-based segmentation framework. The proposed method was validated on 1000 abdominal and 530 thoracic CT images and we obtained very good segmentation results with Jaccard scores in excess of 90% for both the muscle and fat regions.Entities:
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Year: 2015 PMID: 26415164 DOI: 10.1109/TMI.2015.2479252
Source DB: PubMed Journal: IEEE Trans Med Imaging ISSN: 0278-0062 Impact factor: 10.048