1 October, 2021

RadNet Utilizes Cutting Edge AI Technology in Breast Imaging -- for the Most Accurate Results

Artificial Intelligence (AI) sounds like the stuff of science fiction – humanoid robots, talking computers, flying cars, and home appliances that anticipate our every need. And while we’re not quite there yet, AI is very real in our everyday lives. Amazon uses AI to learn your buying habits, music streaming services use it to make song suggestions, and Apple’s Siri and face ID are also products of AI. If you use any social media, you’re coming into contact with AI in those platforms as well. The technological advances in AI continue to grow, and machine learning is becoming more sophisticated and enhanced, so much so that it is even being integrated into healthcare.

RadNet has long been at the forefront of cutting-edge technology, making great strides to bring the most sophisticated equipment into our centers so that our patients can receive the most accurate screening results possible. When the FDA cleared the AI software tool for breast imaging called “Saige-Q,” created by DeepHealth, a division of RadNet, we began to immediately install the software at our centers. It will soon be in every state where we have facilities, including Maryland, Delaware, New York, New Jersey, Florida, California and Arizona.

Saige-Q is an artificial intelligence “deep learning” tool. The purpose of the software is to help sort mammograms so that your breast radiologist can give the suspicious cases prioritized attention. Early scientific data suggests that AI may be able to identify breast cancer one to two years earlier than current practice.1

What exactly is “Deep Learning?”

Machine learning tools are not new to RadNet. We recently upgraded all of our mammography equipment to include Hologic’s Intelligent 2D™ and Clarity HD™ mammogram software, which are components of machine learning, and which significantly improve image quality and reduce the number of unnecessary follow-up visits. Essentially, machine learning uses algorithms to organize the data, learn from it and make informed predictions on what it has learned. Deep Learning is a type of machine learning, which uses artificial neural networks to learn and make decisions. An artificial neural network is inspired by how the brain works, and is particularly good at processing images.

Breakthrough Technologies & Clinical Expertise

RadNet also uses the 3DQuorum™ program that assists with 3D mammograms and helps the radiologist by reducing the number of images to view, which expedites their reading time, with no compromise in image quality, sensitivity, or accuracy.2 These combined breakthrough screening technologies, along with the introduction of Saige-Q, provide radiologists the opportunity to help improve patient lives. They have the potential to help reduce recall rates and unnecessary follow-up procedures, such as biopsies. This in turn, alleviates patient anxiety and affords you a sense of assurance that your exam is as accurate as possible.

RadNet’s mobile mammography coach is also equipped with AI technology and 3D mammography equipment as part of our comprehensive Enhanced Breast Cancer Detection Network.

What’s Next?

Saige-Q software is the first of many AI tools to come, not just for mammography but also for other modalities. RadNet remains a trailblazer in bringing advanced technology to all of our patients. At RadNet, we believe that knowledge is power, and when you can accurately get the answers you need, you can better take control of your healthcare.


1.             Lotter, W., Diab, A.R., Haslam, B. et al. Nat Med 27, 244–249 (2021).

2.             https://www.hologic.com/hologic-products/breast-health-solutions/3dquorum-imaging-technology

1 October, 2021

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