The implementation of natural language processing to extract index lesions from breast magnetic resonance imaging reports.

Journal: BMC medical informatics and decision making
Published Date: Dec 30, 2019

Abstract

BACKGROUND: There are often multiple lesions in breast magnetic resonance imaging (MRI) reports and radiologists usually focus on describing the index lesion that is most crucial to clinicians in determining the management and prognosis of patients. Natural language processing (NLP) has been used for information extraction from mammography reports. However, few studies have investigated NLP in breast MRI data based on free-form text. The objective of the current study was to assess the validity of our NLP program to accurately extract index lesions and their corresponding imaging features from free-form text of breast MRI reports.

Authors

  • Yi Liu
    Department of Interventional Therapy, Ningbo No. 2 Hospital, Ningbo, China.
  • Qing Liu
    School of Chemistry and Chemical Engineering, Shandong University of Technology, 255049, Zibo, PR China.
  • Chao Han
    School of Software Engineering, South China University of Technology, Guangzhou, P. R. China.
  • Xiaodong Zhang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • XiaoYing Wang

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