Performance Evaluation of Abdominal Fat Burden Quantification in CT

Alok Bandekar; Morteza Naghavi; Ioannis Kakadiaris

doi:10.1109/IEMBS.2005.1617177

Performance Evaluation of Abdominal Fat Burden Quantification in CT

Conf Proc IEEE Eng Med Biol Soc. 2005:2005:3280-3. doi: 10.1109/IEMBS.2005.1617177.

Authors

Alok Bandekar¹, Morteza Naghavi, Ioannis Kakadiaris

Affiliation

¹ Computational Biomedicine Lab (formerly known as Visual Computing Lab), Department of Computer Science, University of Houston, Texas 77204, USA. abandekar@uh.edu.

PMID: 17282946
DOI: 10.1109/IEMBS.2005.1617177

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.