DocumentCode
3112537
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
fYear
2006
fDate
Aug. 30 2006-Sept. 3 2006
Firstpage
932
Lastpage
935
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location
New York, NY
ISSN
1557-170X
Print_ISBN
1-4244-0032-5
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2006.259259
Filename
4461906
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