Multi-institutional development and testing of attention-enhanced deep learning segmentation of thyroid nodules on ultrasound.

Journal: International journal of computer assisted radiology and surgery
Published Date: Jan 3, 2025

Abstract

PURPOSE: Thyroid nodules are common, and ultrasound-based risk stratification using ACR's TIRADS classification is a key step in predicting nodule pathology. Determining thyroid nodule contours is necessary for the calculation of TIRADS scores and can also be used in the development of machine learning nodule diagnosis systems. This paper presents the development, validation, and multi-institutional independent testing of a machine learning system for the automatic segmentation of thyroid nodules on ultrasound.

Authors

  • Joseph L Cozzi
    Department of Radiology, University of Chicago, Chicago, IL, USA. jlcozzi@uchicago.edu.
  • Hui Li
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Jordan D Fuhrman
    Medical Imaging and Data Resource Center (MIDRC), The University of Chicago, Chicago, Illinois, USA.
  • Li Lan
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
  • Jelani Williams
    Department of Surgery, University of Chicago Medicine, Chicago, IL 60637, USA.
  • Brendan Finnerty
    Endocrine Oncology Research Program, Division of Endocrine Surgery, Department of Surgery, New York Presbyterian Hospital-Weill Cornell Medicine, New York, USA.
  • Thomas J Fahey
    Department of Surgery, Weill Cornell Medicine, New York, NY 10065, USA.
  • Abhinay Tumati
    Endocrine Oncology Research Program, Division of Endocrine Surgery, Department of Surgery, New York Presbyterian Hospital-Weill Cornell Medicine, New York, USA.
  • Joshua Genender
    Department of Radiology, University of Chicago, Chicago, IL, USA.
  • Xavier M Keutgen
    Department of Surgery, University of Chicago Medicine, Chicago, IL 60637, USA.
  • Maryellen L Giger
    Department of Radiology, University of Chicago, 5841 S Maryland Ave., Chicago, IL, 60637, USA.

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