Pathology diagnosis of intraoperative frozen thyroid lesions assisted by deep learning.

Journal: BMC cancer
PMID: 39210289

Abstract

BACKGROUND: Thyroid cancer is a common thyroid malignancy. The majority of thyroid lesion needs intraoperative frozen pathology diagnosis, which provides important information for precision operation. As digital whole slide images (WSIs) develop, deep learning methods for histopathological classification of the thyroid gland (paraffin sections) have achieved outstanding results. Our current study is to clarify whether deep learning assists pathology diagnosis for intraoperative frozen thyroid lesions or not.

Authors

  • Tingting He
  • Shanshan Shi
    CICU, Children's Hospital, Zhejiang University School of Medicine, 310052 Hangzhou, Zhejiang, China.
  • Yiqing Liu
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China.
  • Lianghui Zhu
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen, Guangdong, China.
  • Yani Wei
    Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China.
  • Fenfen Zhang
    Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University Guangzhou, China.
  • Huijuan Shi
    Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University Guangzhou, China.
  • Yonghong He
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China.
  • Anjia Han
    Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University Guangzhou, China.

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