Automated Lung Cancer Segmentation Using a PET and CT Dual-Modality Deep Learning Neural Network.

Journal: International journal of radiation oncology, biology, physics
Published Date: Aug 4, 2022

Abstract

PURPOSE: To develop an automated lung tumor segmentation method for radiation therapy planning based on deep learning and dual-modality positron emission tomography (PET) and computed tomography (CT) images.

Authors

  • Siqiu Wang
    Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia.
  • Rebecca Mahon
    Washington University School of Medicine in St Louis, St Louis, Missouri.
  • Elisabeth Weiss
    Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia.
  • Nuzhat Jan
    Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia.
  • Ross James Taylor
    Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia.
  • Philip Reed McDonagh
    Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia.
  • Bridget Quinn
    Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia.
  • Lulin Yuan
    Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia. Electronic address: Lulin.yuan@vcuhealth.org.

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