1. A case-oriented web-based training system for breast cancer diagnosis
- Author
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Xingzhang Long, Yidi Lin, Xuelong Li, Xianhai Huang, Longzhong Liu, and Qinghua Huang
- Subjects
medicine.medical_specialty ,Breast imaging ,Biopsy ,education ,Training system ,Health Informatics ,BI-RADS ,Breast Neoplasms ,02 engineering and technology ,030218 nuclear medicine & medical imaging ,Causes of cancer ,Diagnosis, Differential ,03 medical and health sciences ,User-Computer Interface ,0302 clinical medicine ,Breast cancer ,Image Interpretation, Computer-Assisted ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Humans ,Medical physics ,Computer Simulation ,Breast ,Diagnosis, Computer-Assisted ,Breast ultrasound ,Exercise ,Probability ,Retrospective Studies ,Ultrasonography ,Internet ,medicine.diagnostic_test ,business.industry ,Cancer ,Reproducibility of Results ,medicine.disease ,Computer Science Applications ,Computer-aided diagnosis ,020201 artificial intelligence & image processing ,Female ,Ultrasonography, Mammary ,business ,Radiology ,Case Management ,Software - Abstract
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). 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.
- Published
- 2017