A deep learning aided bone marrow segmentation of quantitative fat MRI for myelofibrosis patients.

Journal: Frontiers in oncology
Published Date: May 23, 2025

Abstract

PURPOSE: To automate bone marrow segmentation within pelvic bones in quantitative fat MRI of myelofibrosis (MF) patients using deep-learning (DL) U-Net models.

Authors

  • Humera Tariq
    Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA.
  • Lubomir Hadjiiski
    Department of Radiology, The University of Michigan, Ann Arbor, Michigan 48109-0904.
  • Dariya Malyarenko
    Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA.
  • Moshe Talpaz
    Department of Internal Medicine-Hematology/Oncology, University of Michigan, Ann Arbor, MI, United States.
  • Kristen Pettit
    Department of Internal Medicine-Hematology/Oncology, University of Michigan, Ann Arbor, MI, United States.
  • Gary D Luker
    Department of Radiology, Center for Molecular Imaging, University of Michigan, 109 Zina Pitcher Place, A526 BSRB, Ann Arbor, MI, 48109-2200, USA.
  • Brian D Ross
    Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA.
  • Thomas L Chenevert
    Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA.

Keywords

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