title: Performance Evaluation of Abdominal Fat Burden Quantification in CT.
abstract: Abdominal fat accumulation is an important cardiovascular risk ovascular risk factor. In clinical practice, delineation of subcutaneous and visceral fat is performed manually by an expert. This procedure is labor intensive, time consuming, and subject to inter-and intra-observer variability. In this paper, we present an extension of our previous work on automatic fat burden quantification and classification. Our improved method automatically differentiates abdominal fat into subcutaneous and visceral fat components and removes equipment-related artifacts. We evaluated the performance of our method using data from 40 subjects with very encouraging results.
authors.affiliation: Computational Biomedicine Lab (formerly known as Visual Computing Lab), Department of Computer Science, University of Houston, Texas 77204, USA. abandekar@uh.edu.
authors.forename: Alok
authors.initials: A
authors.lastname: Bandekar
authors.forename: Morteza
authors.initials: M
authors.lastname: Naghavi
authors.forename: Ioannis
authors.initials: I
authors.lastname: Kakadiaris