Study on Medical Imaging Reports Tagging Extraction Based on Bi-LSTM + CRF

Abstract

As an important information carrier for hospital to record medical activities for patients, medical imaging report contains a large amount of technical terms and medical knowledge. In order to automatically generate computer-aided diagnosis reports, it is necessary to extract effective information from medical image reports, so as to reduce the pressure of professional physicians and better serve clinical decision-making. This paper mainly focuses on mammography medical imaging reports, analyzes the structure and contents of the reports, and deals with the imaging reports using the machine learning model, called Bi-LSTM + CRF (Bidirectional Long Short Term Memory with a Conditional Random Fields layer), in order to extract tags of the lesion, such as the position, size and shape in the imaging reports. The experimental results achieved satisfactory effort.