Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Jul 1, 2019

Abstract

OBJECTIVE: Quantitative PET/MR imaging is challenged by the accuracy of synthetic CT (sCT) generation from MR images. Deep learning-based algorithms have recently gained momentum for a number of medical image analysis applications. In this work, a novel sCT generation algorithm based on deep learning adversarial semantic structure (DL-AdvSS) is proposed for MRI-guided attenuation correction in brain PET/MRI.

Authors

  • Hossein Arabi
    Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland.
  • Guodong Zeng
    Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland.
  • Guoyan Zheng
    Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland. guoyan.zheng@istb.unibe.ch.
  • Habib Zaidi
    Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland. habib.zaidi@hcuge.ch.

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