FDA Radiology AI Devices

MammoScreen 2.0 is an AI-based software tool designed to assist physicians by automatically analyzing standard screening mammograms including FFDM and DBT images. It marks suspicious soft tissue lesions or calcifications on breast images and provides a level of suspicion score to help radiologists improve detection and characterization of breast cancer findings. This tool acts as a concurrent reading aid to improve diagnostic accuracy but does not replace physician judgment.

Lunit INSIGHT MMG is an AI-powered computer-assisted detection and diagnosis software designed to help radiologists detect, localize, and characterize suspicious areas for breast cancer on mammograms. It works as an adjunct tool viewed after the initial physician read, providing visual marks and scores indicating the likelihood of malignancy to assist clinical decision-making and improve breast cancer detection during mammography screenings.

Transpara 1.7.0 is an AI software tool designed to assist physicians in interpreting breast imaging exams such as digital mammography and tomosynthesis. It uses deep learning algorithms to detect suspicious calcifications and soft tissue lesions, scoring their likelihood of malignancy to aid diagnosis and improve workflow. It processes images to highlight abnormal areas and provides exam-level cancer likelihood scores, supporting better identification of breast cancer indicators.

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.

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.

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.

Transpara is an AI-powered software designed to assist radiologists in detecting and diagnosing breast cancer from screening mammograms. It highlights suspicious soft tissue lesions and calcifications and provides likelihood scores for cancer presence, helping clinicians make more informed decisions during mammogram interpretation.

ProFound AI Software V2.1 is an AI-based software designed to assist radiologists in detecting soft tissue densities and calcifications in 3D digital breast tomosynthesis images. It highlights suspicious breast lesions by marking areas in the images and assigns confidence scores to help physicians identify likely malignant regions, supporting earlier and more accurate breast cancer diagnosis.

PowerLook Tomo Detection V2 Software by iCAD Inc. is an AI-based computer-assisted detection and diagnosis tool that helps physicians identify suspicious lesions and calcifications in digital breast tomosynthesis images. It provides confidence scores to assist in evaluating findings, improving radiologist accuracy and reducing reading time during breast cancer screening exams.