New Hampshire Patent of the Month – January 2022
Mammograms can be used to help assess the risk of breast cancer by evaluating mammographic density. One of the newer technologies, tomosynthesis, uses digital x-ray mammograms to create 2D or 3D images of breast tissue. Women with dense breasts have both an increased risk of breast cancer and a higher probability of it going undetected. Correctly reading a digital breast tomosynthesis requires the accurate interpretation of extensive amounts of data. Clinicians find themselves too constrained by time and workload to get through these images accurately. iCad, Inc. has developed an AI-based system to analyze images from a mammogram and assess the risk of a breast cancer diagnosis with both accuracy and speed.
The tool uses a CAD system along with deep-learning AI to achieve incredible accuracy in its prediction. The AI was trained with a database made of over 6 million images and accompanying data. It analyzes each tomosynthesis image, detecting malignant soft tissue densities and calcifications and then calculating the patient’s risk. The analysis of these structures can then be combined with additional risk factors including comorbidities, genetic history, lifestyle factors and so on for an even more accurate risk prediction.
Their system has recently earned the U.S. Department of Defense’s authorization to operate. This prediction tool provides a cost effective, individualized breast cancer screening tool which makes it easy to implement without burdening the system through cost or time. The system has been tested and proven to reduce false positives and recalls as well as to provide accuracy in early detection of breast cancer.
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