Intracranial vessel wall segmentation with deep learning using a novel tiered loss function incorporating class inclusion.

Journal: Medical physics
PMID: 35815927

Abstract

PURPOSE: To develop an automated vessel wall segmentation method on T1-weighted intracranial vessel wall magnetic resonance images, with a focus on modeling the inclusion relation between the inner and outer boundaries of the vessel wall.

Authors

  • Hanyue Zhou
    Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
  • Jiayu Xiao
    Department of Radiology, University of Southern California, Los Angeles, California, USA.
  • Debiao Li
  • Zhaoyang Fan
  • Dan Ruan
    Departments of Radiation Oncology, Biomedical Physics and Bioengineering, UCLA, Los Angeles, CA, 90095, USA.

Keywords

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