FDA Radiology AI Devices

Saige-Q is a software tool that analyzes digital breast mammograms using artificial intelligence to identify exams that may contain suspicious findings suggestive of breast cancer. It helps radiologists prioritize these exams in their worklist, enabling faster review of potentially concerning cases. The tool provides passive notification codes but does not provide diagnostic decisions and supports both full-field digital mammography and digital breast tomosynthesis images.

ProFound AI Software V3.0 is an AI-based medical imaging software that aids radiologists by detecting and highlighting suspicious soft tissue densities and calcifications in 3D digital breast tomosynthesis images. It provides confidence scores that help clinicians identify potentially malignant findings more quickly and accurately during breast cancer screening and diagnosis.

Visage Breast Density is a software application designed to analyze mammography images and classify breast density into categories according to the ACR BI-RADS Atlas 5th Edition. It uses a convolutional neural network to assist radiologists by providing adjunctive information about breast tissue composition, making breast density assessment more efficient.

The Imagio Breast Imaging System is a diagnostic tool that combines optoacoustic imaging and ultrasound to provide detailed structural and functional information about breast abnormalities. It uses AI-based software to help healthcare providers better classify breast masses, thereby improving diagnosis. The device is designed to assist, not replace, mammographic screening or biopsy.

Genius AI Detection is an AI software designed to assist radiologists by automatically identifying potential abnormalities such as masses and calcifications in digital breast tomosynthesis exams. It highlights suspicious regions on breast images, provides confidence scores, and helps improve diagnostic accuracy and workflow efficiency for breast cancer screening and diagnosis.

WRDensity by Whiterabbit.ai is a software tool that uses deep learning to analyze digital mammography images and automatically assess breast tissue composition according to the ACR BI-RADS 5th Edition breast density categories. It helps radiologists by providing breast density categorization and probability scores, which can improve breast cancer risk assessment and patient management. The software works with various mammography systems and outputs results to PACS and RIS for clinician review.

HealthMammo is an AI-enabled software tool designed to analyze 2D full-field digital mammograms to identify and flag suspicious findings. It assists radiologists by prioritizing mammogram cases in the PACS/worklist, helping clinicians review critical cases faster and improve workflow efficiency without replacing diagnostic evaluation.

MammoScreen is an AI-based software that assists physicians in interpreting full-field digital mammograms (FFDM) by identifying suspicious breast lesions such as soft tissue lesions and calcifications. It provides marks on the mammogram images alongside a suspicion score to help detect potential breast cancer, supporting radiologists during their reading process to improve cancer detection without replacing clinical judgment.

Transpara is an AI-powered software designed to assist physicians in interpreting full-field digital mammography and digital breast tomosynthesis exams. It highlights suspicious regions that may indicate breast cancer, providing scores that indicate the likelihood of malignancy. This helps radiologists improve detection accuracy and workflow efficiency while supporting clinical decisions during breast cancer screening.

Densitas densityai is a software application that analyzes digital mammography and breast tomosynthesis images to automatically assess breast tissue density. It provides a Breast Density Grade according to the American College of Radiology's BI-RADS 5th Edition to assist physicians in evaluating breast composition. This adjunctive tool helps interpret breast density consistently and efficiently, enhancing clinical decision-making in breast cancer screening.