RU-Net for Heart Segmentation from CXR. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Lyu, Yu; Huo, Wei-Liang; Tian, Xiao-Lin
• Is Part Of: Journal of physics. Volume 1769:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Chest X-ray radiography -- heart segmentation -- U-Net -- Res path -- convolutional neural network; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1769/1/012015
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Cardiovascular disease is one of the top causes of death in the world. In order to release heavy workload for doctor, automated segmentation methods using deep learning are proposed by researchers. Due to limitation of medical images, we proposed a novel model RU-Net based on the combination of U-Net and Residual Network for heart segmentation. We replaced Res path from direct skip connection from encoder to decoder. We use Jaccard similarity coefficient to compare the result of our method and U-Net with public dataset called Japanese Society of Radiological Technology (JSRT). The experiment result demonstrates the accuracy of our method.