Myocardium segmentation from cardiac MRI images is an important task in clinical diagnosis of the left ventricle (LV) function. In this paper, we proposed a new approach for myocardium segmentation based on deep neural network and Graph cut approach. The proposed method is a framework including two steps: in the first step, the fully convolutional network (FCN) was performed to obtain coarse segmentation of LV from input cardiac MR images. In the second step, Graph cut method was employed to further optimize the coarse segmentation results in order to get fine segmentation of LV. The proposed model was validated in 45 subjects of Sunnybrook database using the Dice coefﬁcient metric and compared with other state-of-the-art approaches. Experimental results show the robustness and feasibility of the proposed method.
224-C1, Hanoi University of Science and Technology 1 Dai Co Viet, Hai Ba Trung, Hanoi, Vietnam Tel: +84 (024) 3623.0949 | email: email@example.com
TẠP CHÍ KHOA HỌC VÀ CÔNG NGHỆ Giấy phép số37/GP-BTTTT (15/01/2021) Giấy phép sửa đổi, bổ sung số140/GP-BTTTT (05/3/2021) Đơn vị cấp phép:Bộ Thông tin và Truyền thông Cơ quan chủ quản:Trường Đại học Bách Khoa Hà Nội Phó tổng biên tập phụ trách:GS. Đinh Văn Phong