Quantification of Epicardial and Thoracic Adipose Tissue using WOA Optimized CNN

Cardiac fat depots are associated with the heart diseases. Epicardial fat and thoracic fat plays the major role in the development of cardiovascular disease. The increased thickness of the epicardial and thoracic fat leads to several diseases such as metabolic syndrome, coronary atherosclerosis, etc...

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Vydáno v:International journal of innovative technology and exploring engineering Ročník 8; číslo 9S2; s. 720 - 724
Médium: Journal Article
Jazyk:angličtina
Vydáno: 31.08.2019
ISSN:2278-3075, 2278-3075
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Shrnutí:Cardiac fat depots are associated with the heart diseases. Epicardial fat and thoracic fat plays the major role in the development of cardiovascular disease. The increased thickness of the epicardial and thoracic fat leads to several diseases such as metabolic syndrome, coronary atherosclerosis, etc. It is necessary to quantify the epicardial adipose tissue and thoracic adipose tissue. There are different imaging and assessing techniques for epicardial and thoracic adipose tissue quantification. These tissues can be quantified automatically or manually from the CT and MRI cardiac scans. The quantification of the epicardial fat and thoracic fat requires segmentation of these fats by various segmentation methods and then they are quantified. This project proposes the fully automatic segmentation and quantification of the epicardial and thoracic adipose tissues from the cardiac CT scan images using the krill herd optimization algorithm and fuzzy c-means segmentation algorithm. The whale optimization algorithm performs the feature selection process. The fuzzy cmeans algorithm is used for the segmentation process by means of clustering which segments the epicardial fat and paracardial adipose tissue(EAT &PAT) from the input image. The segmented epicardial and paracardial fat region are then used for the quantification process which provides the epicardial and thoracic fat volume. The thoracic fat is the combination of the epicardial and paracardial fat. This proposed system is implemented by using the MATLAB code. The proposed system is simple, fully automatic and produces accurate results.
ISSN:2278-3075
2278-3075
DOI:10.35940/ijitee.I1150.0789S219