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RadNet, Hologic Announce AI Collaboration

RadNet Inc. and Hologic Inc. have entered into a definitive collaboration to advance the use of artificial intelligence (A.I.) in breast health.

Hologic will contribute capabilities and insights behind its market-leading hardware and software, and will benefit from access to data produced by RadNet’s fleet of high-resolution mammography systems, the largest in the nation, to train and refine current and future products based on A.I., according to a news release emailed to ICE magazine.

“RadNet will share data from its extensive network of imaging centers, as well as provide in-depth knowledge of the patient pathway and workflow needs to help make a positive impact across the breast care continuum. The collaboration will enable new joint market opportunities and further efforts to build clinician confidence and develop and integrate new A.I. technologies,” the release adds.

“We believe the future of breast health will rely heavily on the integration of A.I. tools, such as our 3DQuorum imaging technology, as well as next generation CAD software, that aid in the early detection of breast cancer,” said Pete Valenti, Hologic’s division president, breast and skeletal health solutions. “We are energized by the opportunities this transformative collaboration with RadNet creates for patients and clinicians alike. Access to data is critical in training and refining A.I. algorithms. With this collaboration, we now have the opportunity to leverage data from the largest fleet of high-resolution mammography systems to develop new tools across the continuum of care, provide workflow efficiencies and improve patient satisfaction and outcomes.”

“As part of its collaboration with Hologic, RadNet intends to upgrade its entire fleet of Hologic mammography systems to feature Hologic’s 3DQuorum imaging technology, powered by Genius AI. This technology works in tandem with Clarity HD high resolution imaging technology to reduce tomosynthesis image volume for radiologists by 66 percent. Additionally, all of RadNet’s Hologic systems are anticipated to feature the Genius3D Mammography exam, the only mammogram clinically proven and FDA approved as superior for all women, including those with dense breasts, compared with 2D mammography alone,” the release states.

The collaboration will be bolstered by RadNet’s recent acquisition of DeepHealth, which uses machine learning to develop software tools to improve cancer detection and provide clinical decision support. Led by Dr. Gregory Sorensen, DeepHealth’s team of A.I. experts is focused on enabling industry-leading care by providing products that clinicians and patients can trust. In addition, the DeepHealth team will integrate its A.I. tools within the Hologic ecosystem.

“When seeking a partner and reviewing options amongst all mammography vendors, we selected to integrate our tools with Hologic’s market-leading technology,” said Sorensen. “Hologic’s systems produce the highest level of spatial resolution in the market. Hologic also has the largest domestic footprint and market share in 3D mammography systems. This integration will allow the DeepHealth team to train its algorithms for use with the most advanced screening technology possible. As Hologic and RadNet share their respective capabilities and tools, greater efficiency and accuracy can be achieved by our radiologists.”

“Much like RadNet, Hologic is a highly innovative company and market leader in breast health,” said Howard Berger, MD, RadNet’s chairman and CEO. “When Hologic’s leading screening technology is paired with RadNet’s approximately 1.2 million annual screening mammograms, the resulting dataset becomes a powerful tool to train algorithms. We see the future as being transformative for both of our organizations.”

“We have witnessed how the application of our Genius AI technology platform has improved cancer detection, operational efficiency and clinical decision support across the breast cancer care continuum,” said Samir Parikh, Hologic’s global vice president for research and development, breast and skeletal health solutions. “We look forward to building upon these advances in collaboration with Dr. Sorensen and the RadNet team to expand the use of machine learning, big data applications and automated algorithms impacting global breast care.”

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