Automated Breast Arterial Calcifications Segmentation and Quantification on Mammograms Using Deep Learning

Application
Software for the quantification of breast arterial calcifications on routine mammograms to be used for risk stratification for cardiovascular outcomes.

Key Benefits
Optimized image segmentation accuracy with reduced software complexity.
Integrated calcium scoring.
Screens patients who would not normally be indicated for cardiac CT.Potential to synergize and complement HPV E6/7-specific TCR therapies currently undergoing clinical trials.
Reduces costs associates with cardiac CT.
Market Summary
One in five women in the United States die from cardiovascular disease (CVD.) Women’s symptoms often differ from men’s, especially for heart attacks, making it difficult to recognize CVD. CVD commonly manifests as arterial calcifications. Inventors at Emory University have developed software that analyzes mammogram images to quantify breast arterial calcification (BAC), which is known to correlate with calcification of other arteries. This invention will contribute to the global market for healthcare analytics, and more specifically the global market for healthcare data analytics used by hospitals which is expected to reach $2.569 billion by 2022 at a CAGR of 17.1% FROM 2017-2022 (BCC Research HLC187B).

Technical Summary
The invention consists of a software designed for automatic detection and quantification breast arterial calcification (BAC) in female patients at risk for cardiovascular events and to assist in follow the progression of vascular calcifications while avoiding additional radiation exposure or cost to the patient. The software called Simple Context U-Net (SCU-Net) processes large image size of mammograms by breaking the image into smaller high-resolution patches. The software performs image segmentation to distinguish BAC from the rest of the image using reduced training parameters making it ideal for real-time clinical implementation. Furthermore, the soft quantified BAC using 5 metrics that produce a “calcium score” for each image and the associated vessel.

Developmental Stage
Early-stage.

Website

https://emoryott.technologypublisher.com/techcase/21005

Contact Information

TTO Home Page: https://emoryott.technologypublisher.com

Name: Hyeon (Sean) Kim

Title: Licensing Associate

Email: hkim70@emory.edu

Phone: 404-727-7218