Impact of deep learning-based multiorgan segmentation methods on patient-specific internal dosimetry in PET/CT imaging: A comparative study.

Journal: Journal of applied clinical medical physics
PMID: 38214349

Abstract

PURPOSE: Accurate and fast multiorgan segmentation is essential in image-based internal dosimetry in nuclear medicine. While conventional manual PET image segmentation is widely used, it suffers from both being time-consuming as well as subject to human error. This study exploited 2D and 3D deep learning (DL) models. Key organs in the trunk of the body were segmented and then used as a reference for networks.

Authors

  • Mehrnoosh Karimipourfard
    Department of Ray-Medical Engineering, Shiraz University, Shiraz, Iran.
  • Sedigheh Sina
    Department of Ray-Medical Engineering, Shiraz University, Shiraz, Iran.
  • Hojjat Mahani
    Radiation Applications Research School, Nuclear Science and Technology Research Institute, Tehran, Iran.
  • Mehrosadat Alavi
    Department of Nuclear Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Mehran Yazdi
    School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.

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