Title :
Automated Pericardial Fat Quantification in CT Data
Author :
Bandekar, Alok N. ; Naghavi, Morteza ; Kakadiaris, Ioannis A.
Author_Institution :
Dept. of Comput. Sci., Houston Univ., TX
fDate :
Aug. 30 2006-Sept. 3 2006
Abstract :
Recent evidence indicates that pericardial fat may be a significant cardiovascular risk factor. Although pericardial fat is routinely imaged during computed tomography (CT) for coronary calcium scoring, it is currently ignored in the analysis of CT images. The primary reason for this is the absence of a tool capable of automatic quantification of pericardial fat. Recent studies on pericardial fat imaging were limited to manually outlined regions-of-interest and preset fat attenuation thresholds, which are subject to inter-observer and inter-scan variability. In this paper, we present a method for automatic pericardial fat burden quantification and classification. We evaluate the performance of our method using data from 23 subjects with very encouraging results
Keywords :
biomedical measurement; cardiovascular system; computerised tomography; diagnostic radiography; fats; image classification; learning (artificial intelligence); medical image processing; CT; automated pericardial fat burden quantification; cardiovascular risk factor; computed tomography; coronary calcium; fat attenuation thresholds; image classification; inter-observer variability; inter-scan variability; training phase; Abdomen; Attenuation; Biomedical computing; Blood pressure; Cardiology; Computed tomography; Coronary arteriosclerosis; Heart; Magnetic resonance imaging; Positron emission tomography;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.259259