Interactive thyroid whole slide image diagnostic system using deep representation.

Journal: Computer methods and programs in biomedicine
Published Date: Jun 27, 2020

Abstract

BACKGROUND AND OBJECTIVES: The vast size of the histopathology whole slide image poses formidable challenges to its automatic diagnosis. With the goal of computer-aided diagnosis and the insights that suspicious regions are generally easy to identify in thyroid whole slide images (WSIs), we develop an interactive whole slide diagnostic system for thyroid frozen sections based on the suspicious regions preselected by pathologists.

Authors

  • Pingjun Chen
    J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.
  • Xiaoshuang Shi
    Shandong Industrial Engineering Laboratory of Biogas Production & Utilization, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China. E-mail: lujun@qibebt.ac.cn (Jun Lu), yangzm@qibebt.ac.cn (Zhiman Yang).
  • Yun Liang
    J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, United States.
  • Yuan Li
    NHC Key Lab of Hormones and Development and Tianjin Key Lab of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Institute of Endocrinology, Tianjin, China.
  • Lin Yang
    National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
  • Paul D Gader
    Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, United States.

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