Abstract
Breast cancer ranks top incidence rate among all malignant tumors for women, globally. Early detection through regular preliminary screening is critical to decreasing the breast cancer’s fatality rate. However, the promotion of preliminary screening faces major limitations of human diagnosis capacity, cost, and technical reliability in China and most of the world. To meet these challenges, we developed a solution featuring an innovative division of labor model by incorporating artificial intelligence (AI) with ultrasonography and cloud computing. The objective of this research was to develop a solution named “Dr.J”, which applies AI to process real-time video live feed from ultrasonography, which is physically safe and more suitable for Asian women. It can automatically detect and highlight the suspected breast cancer lesions and provide BI-RADS (Breast Imaging-Reporting and Data System) ratings to assist human diagnosis. “Dr.J” does not require its frontline operators to have prior medical or IT background and thus significantly lowers manpower threshold for preliminary screening promotion. Furthermore, its cloud computing platform can store detailed breast cancer data such as images and BI-RADS ratings for further essential needs in medical treatment, research and health management, etc. as well as establishing a hierarchy medical service network for this disease. Therefore, “Dr.J” significantly enhances the availability and accessibility of preliminary screening service for breast cancer at grassroots.
Highlights
The survival rate for breast cancer is over 90% if found and treated in early stages and can overcome the leading cancer fatality rates in women
We developed a solution featuring an innovative division of labor model by incorporating artificial intelligence (AI) with ultrasonography and cloud computing
It follows the track of capacity building for training deep neural network model for lesion detection and classifications, real-time www.ijacsa.thesai.org processing of video feed of breast ultrasound, and a big data platform for the sharing and storage of information based on cloud computing
Summary
The survival rate for breast cancer is over 90% if found and treated in early stages and can overcome the leading cancer fatality rates in women. In China, only 15.7% of breast cancer patients were found when in BI-RADS category 1, while 44.9% and 18.7% were in BI-RADS category 2 and 3 respectively. We excluded breast clinical exam, tissue sampling, mammography, MRI, and CT scanning for their inadequate sensitivity, invasiveness, radioactivity, high false positive rates, non-cost effectiveness, and high hardware installation threshold. These vulnerabilities or disadvantages, alone or combined, were detrimental to their promotion in community or grassroots scenarios. In 2017, China recorded near 270,000 new breast cancer cases which continued to rank top among all the malignant tumors found in Chinese women. The breast cancer pervasiveness is assessed to reach high since fewer than 60 cases according to 100,000 females matured inside 55-69 age to exceed 100 cases
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