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Epicardial Adipose Tissue Segmentation from CT Images with A Semi-3D Neural Network (CROSBI ID 707817)

Prilog sa skupa u zborniku | ostalo | međunarodna recenzija

Benčević, Marin ; Habijan, Marija ; Galić, Irena Epicardial Adipose Tissue Segmentation from CT Images with A Semi-3D Neural Network // 2021 International Symposium ELMAR. Institute of Electrical and Electronics Engineers (IEEE), 2021. str. 87-90 doi: 10.1109/elmar52657.2021.9550936

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 ;

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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

Povezanost rada

Računarstvo

Poveznice