Sequential shape similarity for active contour based left ventricle segmentation in cardiac cine MR image

Mathematical Biosciences and Engineering

Ke Bi¹  Yuanquan Wang²  Yue Tan²  Ke Cheng³  Qingfang Chen⁴ 

[1] 1. School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang Jiangsu 212003, China;2. School of Artificial Intelligence, Hebei University of Technology, Tianjin 300401, China;3. School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang Jiangsu 212003, China;4. School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang Jiangsu 212003, China;

关键词: magnetic resonance imaging;    left ventricle;    image segmentation;    active contour;    sequential shape similarity;   

DOI  :  10.3934/mbe.2022074

来源: DOAJ

【 摘 要 】

Delineation of the boundaries of the Left Ventricle (LV) in cardiac Magnetic Resonance Images (MRI) is a hot topic due to its important diagnostic power. In this paper, an approach is proposed to extract the LV in a sequence of MR images. In the proposed paper, all images in the sequence are segmented simultaneously and the shape of the LV in each image is supposed to be similar to that of the LV in nearby images in the sequence. We coined the novel shape similarity constraint, and it is called sequential shape similarity (SSS in short). The proposed segmentation method takes the Active Contour Model as the base model and our previously proposed Gradient Vector Convolution (GVC) external force is also adopted. With the SSS constraint, the snake contour can accurately delineate the LV boundaries. We evaluate our method on two cardiac MRI datasets and the Mean Absolute Distance (MAD) metric and the Hausdorff Distance (HD) metric demonstrate that the proposed approach has good performance on segmenting the boundaries of the LV.

【 授权许可】

Unknown