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An Automated Cardiac Ventricle Segmentation on CMR Images Using Grey-Level Mask R-CNN

Authors :
Chun-Ku Chen
Kuan-Yu Chen
Shih-Hsien Sung
Hsiao-Chi Li
Source :
ICCE-TW
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

Myocardial fibrosis is a pathological change in the progress of modern heart disease. It is mainly characterized by dysregulation or marked increase of collagen volume in myocardial components. The physiological mechanism of fibrosis in different pathologies is very diverse. It has been proved that the use of MRI for the detection of heart failure patients can provide accurate measurements of left ventricle and right ventricle and assessment of myocardial function, but the accurate segmentation of myocardial contour is still an important prerequisite for the detection of fibrosis. This study uses Mask R-CNN on the ACDC challenge Database to repeatedly adjust the characteristics of the boundary of the Bounding box, and separately divided the left ventricular area and the right ventricular area. The proposed method can achieve up to 95% hit rate with 0.89 IoU.

Details

Database :
OpenAIRE
Journal :
2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)
Accession number :
edsair.doi...........32c541a2ce42ad01dc3ca348ae4ff43e