Reconnection of fragmented parts of coronary arteries using local geometric features in X-ray angiography images.

Journal: Computers in biology and medicine
Published Date:

Abstract

UNLABELLED: The segmentation of coronary arteries in X-ray images is essential for image-based guiding procedures and the diagnosis of cardiovascular disease. However, owing to the complex and thin structures of the coronary arteries, it is challenging to accurately segment arteries in X-ray images using only a single neural network model. Consequently, coronary artery images obtained by segmentation with a single model are often fragmented, with parts of the arteries missing. Sophisticated post-processing is then required to identify and reconnect the fragmented regions. In this paper, we propose a method to reconstruct the missing regions of coronary arteries using X-ray angiography images.

Authors

  • Kyunghoon Han
    Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul, 03 722, South Korea; CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, 03 721, South Korea.
  • Jaeik Jeon
    CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, 03 721, South Korea.
  • Yeonggul Jang
  • Sunghee Jung
    CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, 03 721, South Korea.
  • Sekeun Kim
    CONNECT-AI Research Center, Yonsei University College of Medicine, Seoul, 03 721, South Korea; Graduate School of Biomedical Engineering, Yonsei University, Seoul, 03 722, South Korea.
  • Hackjoon Shim
    Connect AI Research Center, Yonsei University College of Medicine, 03772 Seoul, Republic of Korea.
  • Byunghwan Jeon
    School of Computer Science, Kyungil University, Gyeongsan, 38 428, South Korea. Electronic address: byunghwanjeon@gmail.com.
  • Hyuk-Jae Chang
    Department of Cardiology, Yonsei University College of Medicine, Seoul, Republic Of Korea.