PlaqueViT: a vision transformer model for fully automatic vessel and plaque segmentation in coronary computed tomography angiography.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To develop and evaluate a deep learning model for segmentation of the coronary artery vessels and coronary plaques in coronary computed tomography angiography (CCTA).

Authors

  • Jennifer Alvén
    Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
  • Richard Petersen
    Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
  • David Hagerman
    Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
  • Mårten Sandstedt
    Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. martensandstedt@gmail.com.
  • Pieter Kitslaar
    Medis Medical Imaging Systems Leiden the Netherlands.
  • Göran Bergström
    Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Box 428, 40530, Gothenburg, Sweden. goran.bergstrom@hjl.gu.se.
  • Erika Fagman
    Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden.
  • Ola Hjelmgren
    Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Box 428, 40530, Gothenburg, Sweden.