Coronary angiography (CAG) as a typical imaging modality for the diagnosis of coronary diseases hasbeen widely employed in clinical practices. For CAG-based computer-aided diagnosis systems, accurate vessel segmentation plays a fundamental role. However, patients with bradycardia usually have a pacemaker which frequently interferes the vessel segmentation. In this case, the segmentation of vessels will be hard. To mitigate interferences of pacemakers and then extract main vessels more effectively in CAG images, we propose an approach. At first, a pseudo CAG (pCAG) image is generated through a part of a CAG sequence, in which the pacemaker exists. Then, a local feature descriptor is employed to register the relative location of pacemaker between the pCAG image and the target CAG image. Finally, combining the registration result and segmentation results of main vessels and pacemaker, interferences of pacemaker are removed and the segmentation of main vessels is improved. The proposed method is evaluated based on 11 CAG images with pacemakers acquired in clinical practices. An optimization ratio of the Dice coefficient is 12.04%, which demonstrates that our method can remove overlapping pacemakers and achieve the improvement of main vessel segmentation in CAG images.Our method can further become a helpful component in a CAG-based computer-aided diagnosis system, improving its diagnosis accuracy and efficiency.
Citation： HUANG Yi, YANG Hongbo, XIA Menghua, QU Yanan, GUO Yi, ZHOU Guohui, ZHANG Feng, WANG Yuanyuan. An optimized segmentation of main vessel in coronary angiography images via removing the overlapping pacemaker. Journal of Biomedical Engineering, 2022, 39(5): 853-861. doi: 10.7507/1001-5515.202104023 Copy