Localization and Risk Stratification of Thyroid Nodules in Ultrasound Images Through Deep Learning.

Journal: Ultrasound in medicine & biology
Published Date: Mar 16, 2024

Abstract

OBJECTIVE: Deep learning algorithms have commonly been used for the differential diagnosis between benign and malignant thyroid nodules. The aim of the study described here was to develop an integrated system that combines a deep learning model and a clinical standard Thyroid Imaging Reporting and Data System (TI-RADS) for the simultaneous segmentation and risk stratification of thyroid nodules.

Authors

  • Zhipeng Wang
    Department of Pharmacy, Changzheng Hospital, Second Military Medical University, Shanghai, 200003, PR China.
  • Xiuzhu Wang
    Department of Obstetrics, Tai'an City Central Hospital, Tai'an, China.
  • Ting Wang
    CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
  • Jianfeng Qiu
    School of Radiology, Shandong First Medical University & Shandong Academy of Medicine Sciences, Tai'an, Shandong, 271000, China; Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250000, China. Electronic address: jfqiu100@163.com.
  • Weizhao Lu
    Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, 271000, China.

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