Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.

Journal: Medical physics
Published Date: Oct 24, 2020

Abstract

PURPOSE: Contouring intraprostatic lesions is a prerequisite for dose-escalating these lesions in radiotherapy to improve the local cancer control. In this study, a deep learning-based approach was developed for automatic intraprostatic lesion segmentation in multiparametric magnetic resonance imaging (mpMRI) images contributing to clinical practice.

Authors

  • Yizheng Chen
    Department of Radiation Oncology, Stanford University, Stanford, 94305, USA.
  • Lei Xing
    Department of Radiation Oncology, Stanford University, CA, USA.
  • Lequan Yu
  • Hilary P Bagshaw
    Department of Radiation Oncology, Stanford University, Stanford, 94305, USA.
  • Mark K Buyyounouski
    Department of Radiation Oncology, Stanford University, Stanford, California.
  • Bin Han
    2 Department of Radiation Oncology, Stanford University, Stanford, CA, USA.

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