Hologic Receives FDA Clearance for Genius AI Detection Technology for Early Breast Cancer Detection
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By MedImaging International staff writers Posted on 02 Dec 2020 |

Image: The Genius AI Detection software (Photo courtesy of Hologic, Inc.)
Hologic, Inc. (Marlborough, MA, USA) has received US Food and Drug Administration (FDA) clearance for its Genius AI Detection technology, a new deep learning-based software designed to help radiologists detect subtle potential cancers in breast tomosynthesis images.
The new technology which Hologic has now made commercially available represents a pivotal milestone in the early detection of breast cancer, as studies showed Genius AI Detection software aids in the identification and early detection of breast cancer when used with the Genius 3D Mammography exam. The new technology highlights areas with subtle potential cancers that can be difficult to detect for further examination by the radiologist, and is designed to provide higher sensitivity and a false-positive rate much lower than Hologic’s previous generation CAD products.
The new software delivers key metrics at the time of image acquisition to help radiologists categorize and prioritize cases by complexity and expected read time in order to optimize workflow and expedite patient care. It is the only deep learning product on the market that runs on the acquisition workstation of the mammography system without the need for a separate server, providing a simple, convenient and secure environment. The Genius AI Detection software is the only 3D CAD solution that supports Hologic’s latest innovations in tomosynthesis imaging, Clarity HD and 3DQuorum imaging technology, in addition to standard-resolution tomosynthesis.
“As the latest breakthrough in breast cancer screening, Genius AI Detection reinforces Hologic’s commitment to improving cancer detection, optimizing workflow and enhancing the patient experience across every step of the breast health care continuum,” said Jennifer Meade, Hologic’s Division President, Breast and Skeletal Health Solutions. “Not only did studies show that Genius AI Detection aids in image interpretation by highlighting suspicious, and often subtle, areas of interest, it also provides the radiologist the opportunity to prioritize the most concerning patient cases. This is a real game changer as it has the potential to shorten the cycle between screening and diagnostic follow-up, and ultimately improve patient outcomes.”
The new technology which Hologic has now made commercially available represents a pivotal milestone in the early detection of breast cancer, as studies showed Genius AI Detection software aids in the identification and early detection of breast cancer when used with the Genius 3D Mammography exam. The new technology highlights areas with subtle potential cancers that can be difficult to detect for further examination by the radiologist, and is designed to provide higher sensitivity and a false-positive rate much lower than Hologic’s previous generation CAD products.
The new software delivers key metrics at the time of image acquisition to help radiologists categorize and prioritize cases by complexity and expected read time in order to optimize workflow and expedite patient care. It is the only deep learning product on the market that runs on the acquisition workstation of the mammography system without the need for a separate server, providing a simple, convenient and secure environment. The Genius AI Detection software is the only 3D CAD solution that supports Hologic’s latest innovations in tomosynthesis imaging, Clarity HD and 3DQuorum imaging technology, in addition to standard-resolution tomosynthesis.
“As the latest breakthrough in breast cancer screening, Genius AI Detection reinforces Hologic’s commitment to improving cancer detection, optimizing workflow and enhancing the patient experience across every step of the breast health care continuum,” said Jennifer Meade, Hologic’s Division President, Breast and Skeletal Health Solutions. “Not only did studies show that Genius AI Detection aids in image interpretation by highlighting suspicious, and often subtle, areas of interest, it also provides the radiologist the opportunity to prioritize the most concerning patient cases. This is a real game changer as it has the potential to shorten the cycle between screening and diagnostic follow-up, and ultimately improve patient outcomes.”
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