SBIR Phase II: Mammography Analysis and Reporting System

This Small Business Innovation Research (SBIR) Phase II project seeks to improve medical image analysis and reporting. The project proposes research and innovation on quality of diagnosis, richness of knowledge exchange, privacy and scalability of merging analysis and reporting of medical imaging for the detection of breast cancer. The company proposes a system which allows radiologists to focus on analyzing the image while the system automatically produces a report in the background. The reports are image-based, provide audience-specific levels of detail, and are backwards compatible to text-based reports. The SBIR Phase I project established the efficiency improvements that the proposed system can provide. In Phase II, this project will investigate cloud computing as a model for operating and delivering the company's mammography integrated analysis and reporting software. Cloud computing has proven to be a scalable and cost-effective means of delivering software services to customers and will thus be an important capability of health-care IT providers. However, the image storage and security requirements for medical images will necessitate improvements over existing cloud solution architecture. The Phase II project will develop new methods for delivering richer image-based reports and robust security via the cloud. Breast cancer affects nearly one in eight women, at a substantial economic and societal cost. Mammography screening is the most effective way to detect breast cancer in its earliest and most treatable phases. However, there are many inefficiencies and quality problems in screening mammograms. While a shortness of radiologists specializing in mammography is driving up costs, there are significant false-negative rate and false-positive rates in screening mammography. This situation creates a clear opportunity for innovations that can provide increased efficiency while maintaining or improving quality. Changes in health-care legislation are yielding incentives for health-care facilities to transition to all-electronic systems. As they do so, many health-care facilities are embracing cloud-based delivery and Software-as-a-Service models. If successful, the Phase II project will continue with research and innovation for the delivery of an integrated analysis and reporting software that will improve the quality of medical image diagnosis while decreasing costs.