Deep learning-based multimodal segmentation of oropharyngeal squamous cell carcinoma on CT and MRI using self-configuring nnU-Net.

Journal: European radiology
Published Date: Jan 20, 2024

Abstract

PURPOSE: To evaluate deep learning-based segmentation models for oropharyngeal squamous cell carcinoma (OPSCC) using CT and MRI with nnU-Net.

Authors

  • Yangsean Choi
    Department of Radiology, Seoul Saint Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Jooin Bang
    Department of Otolaryngology-Head and Neck Surgery, Seoul St. Mary's Hospital, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea.
  • Sang-Yeon Kim
    Department of Biosystems and Biomaterials Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea. yskra@snu.ac.kr.
  • Minkook Seo
    Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, 06591, Republic of Korea.
  • Jinhee Jang
    GenesisEgo, Seoul, Republic of Korea.

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