Artificial Intelligence Development for Detecting Microcalcification within Mammography

Abstract

Background: Artificial Intelligence (AI) is the recently advanced technology in machine learning that is increasingly used to help radiologists, especially when working in arduous conditions. Microsoft Corporation offered a free-trial service called Custom Vision to develop AI for images. Objective: To study the possibility of AI development from free-trial service for detecting microcalcification within mammography. Materials and Methods: Radiological images of breast cancer-proven patients who underwent mammography between 2018 and 2019 were used to train AI to detect microcalcification. The training processes were divided into five iterations of 30, 60, 100, 130, and 160 lesion datasets. After each training, the AI was tested as “Performance Per Tag” and clinical performance. There were three types of training, quick, 1-hour, and 2-hour trainings. Results: The present study included 116 microcalcification images with 206 lesions from 56 breast cancer patients. The 160-tag iteration presented the best performance with a precision of 80.0%, a recall of 12.5%, a mean average precision of 30.5%, and a prediction rate of 32.14%. The performance of the 1-hour training was better than the quick training but was not different from the 2-hour training. Conclusion: Health personnel can easily develop AI for the detection of microcalcification in mammography. However, the AI development is further required, and the result should be interpreted along with radiologist. Keywords: AI, Microcalcification, Mammography, Machine learning