Epicardial Adipose Tissue Segmentation from CT Images with A Semi-3D Neural Network (CROSBI ID 707817)
Prilog sa skupa u zborniku | ostalo | međunarodna recenzija
Podaci o odgovornosti
Benčević, Marin ; Habijan, Marija ; Galić, Irena
engleski
Epicardial Adipose Tissue Segmentation from CT Images with A Semi-3D Neural Network
Epicardial adipose tissue is a type of adipose tissue located between the heart wall and a protective layer around the heart called the pericardium. The volume and thickness of epicardial adipose tissue are linked to various cardiovascular diseases. It is shown to be an independent cardiovascular disease risk factor. Fully automatic and reliable measurements of epicardial adipose tissue from CT scans could provide better disease risk assessment and enable the processing of large CT image data sets for a systemic epicardial adipose tissue study. This paper proposes a method for fully automatic semantic segmentation of epicardial adipose tissue from CT images using a deep neural network. The proposed network uses a U-Net-based architecture with slice depth information embedded in the input image to segment a pericardium region of interest, which is used to obtain an epicardial adipose tissue segmentation. Image augmentation is used to increase model robustness. Cross-validation of the proposed method yields a Dice score of 0.86 on the CT scans of 20 patients.
Cardiovascular imaging ; Deep neural networks ; Epicardial adipose tissue ; Medical image processing ; Semantic segmentation ;
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
87-90.
2021.
objavljeno
10.1109/elmar52657.2021.9550936
Podaci o matičnoj publikaciji
Institute of Electrical and Electronics Engineers (IEEE)
Podaci o skupu
63rd International Symposium ELMAR 2021
predavanje
12.09.2021-15.09.2021
Zadar, Hrvatska