Catheter detection and segmentation in X-ray images via multi-task learning.

Journal: International journal of computer assisted radiology and surgery
Published Date: Jun 27, 2025

Abstract

PURPOSE: Automated detection and segmentation of surgical devices, such as catheters or wires, in X-ray fluoroscopic images have the potential to enhance image guidance in minimally invasive heart surgeries.

Authors

  • Lin Xi
    Laboratory of Developmental Nutrition, Department of Animal Sciences, North Carolina State University, Raleigh, NC 27695, USA. lin_xi@ncsu.edu.
  • Yingliang Ma
    School of Computing, Electronics and Mathematics, Coventry University, Coventry, UK.
  • Ethan Koland
    School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.
  • Sandra Howell
    Cardiology Department, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom; School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
  • Aldo Rinaldi
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, SE1 7EH, UK.
  • Kawal S Rhode
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

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