A case-oriented web-based training system for breast cancer diagnosis

Qinghua Huang, Xianhai Huang, Longzhong Liu, Yidi Lin, Xingzhang Long, Xuelong Li

科研成果: 期刊稿件文章同行评审

19 引用 (Scopus)

摘要

Background and Objective Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. We aim to provide a web-based breast ultrasound database for online training inexperienced radiologists and giving computer-assisted diagnostic information for detection and classification of the breast tumor. Methods We introduce a web database which stores breast ultrasound images from breast cancer patients as well as their diagnostic information. A web-based training system using a feature scoring scheme based on Breast Imaging Reporting and Data System (BI-RADS) US lexicon was designed. A computer-aided diagnosis (CAD) subsystem was developed to assist the radiologists to make scores on the BI-RADS features for an input case. The training system possesses 1669 scored cases, where 412 cases are benign and 1257 cases are malignant. It was tested by 31 users including 12 interns, 11 junior radiologists, and 8 experienced senior radiologists. Results This online training system automatically creates case-based exercises to train and guide the newly employed or resident radiologists for the diagnosis of breast cancer using breast ultrasound images based on the BI-RADS. After the trainings, the interns and junior radiologists show significant improvement in the diagnosis of the breast tumor with ultrasound imaging (p-value <.05); meanwhile the senior radiologists show little improvement (p-value >.05). Conclusions The online training system can improve the capabilities of early-career radiologists in distinguishing between the benign and malignant lesions and reduce the misdiagnosis of breast cancer in a quick, convenient and effective manner.

源语言英语
页(从-至)73-83
页数11
期刊Computer Methods and Programs in Biomedicine
156
DOI
出版状态已出版 - 3月 2018

指纹

探究 'A case-oriented web-based training system for breast cancer diagnosis' 的科研主题。它们共同构成独一无二的指纹。

引用此