Problem / Objective:

Shortage and unavailability of radiologists for breast cancer mass screening programmes are resulting in its late detection and increasing the economic burden on national health programmes. Breast cancer is the most prevalent form of cancer amongst urban Indian women and ate detection of breast cancer is the most common cause of deaths with a 50% mortality rate. There is a need for a ‘go or no-go’ decision in mass screening programmes aimed at early detection, along with a comprehensive standardised report based on globally-accepted standards. 

Solution / Approach:

Telerad Tech was established in 2009 with the aim of optimising radiology productivity and improving patient outcome delivery through transformational medical imaging software solutions. It is now among the global market leaders in providing integrated RIS-PACS software solutions for teleradiology, medical imaging centres, and hospitals of all sizes. In 2018, Telerad Tech launched their first AI product - MammoAssist - and plan to release multiple AI algorithms in 2019. 

MammoAssist is an intelligent AI algorithm developed using deep learning and image processing approach in the field of radiology, which analyses mammograms for early stage breast cancer detection. It is capable of integrating and processing any DICOM images and providing annotation for breast cancer detection with a structured report. Radiologists can agree or disagree with the report and can also share their comments for every AI finding using an in-built feedback mechanism. 

Impact / Implementation:

Telerad Tech’s solution is poised to assist the government and public health organisations in undertaking mass screening of women based on certain signs and symptoms. Early detection will help in executing the care and treatment plan, and hence reduce mortality due to breast cancer. MammoAssist saves time spent by radiologist in typing the report by 60%-70%, and helps increase productivity by more than 50%.

Source: NASSCOM COE-DSAI AI for Good report