FDA Radiology AI Devices

MammoScreen® is an AI-based software designed to assist radiologists in detecting and diagnosing lesions that may be indicative of breast cancer from mammography images. It helps improve accuracy and efficiency by highlighting suspicious areas, supporting earlier and more reliable cancer detection.

MammoScreen 3 is an artificial intelligence software tool designed to assist physicians in interpreting screening mammograms from digital mammography and digital breast tomosynthesis systems. It provides graphical marks indicating suspicious soft-tissue lesions or calcifications, along with a suspicion score and lesion characterization, helping radiologists in their diagnosis and reporting. The software is intended as an aid to, but not a replacement for, the physician's clinical judgment.

VinDr-Mammo is a software tool designed to assist radiologists in prioritizing mammogram exams by flagging those that may contain suspicious findings. It analyzes 2D digital mammograms using artificial intelligence to identify potentially concerning cases and alerts radiologists, enabling more efficient workflow and faster patient care. It does not replace the physician's final diagnosis.

TumorSight Viz is software developed by SimBioSys, Inc. that helps doctors visualize and analyze breast MRI images from patients with early-stage or locally advanced breast cancer. It supports dynamic MRI data evaluation by processing images to provide measurements, 3D renderings, and visualizations, which aid clinicians in planning treatment and assessing tumor characteristics. The system is cloud-based and used as a tool to support but not replace clinical decision-making.

The 6440 MyLabX90 by Esaote is an advanced multifunctional ultrasound scanner that supports real-time imaging and analysis during diagnostic ultrasound procedures. It integrates AI features like automated endocardial border detection for cardiac function assessment and lesion contouring for breast exams, helping clinicians improve diagnostic accuracy and efficiency across multiple body regions.

Lunit INSIGHT DBT is an AI-powered software designed to assist physicians in detecting and characterizing suspicious lesions for breast cancer in digital breast tomosynthesis (DBT) images. It analyzes DBT scans to identify and highlight regions of soft tissue lesions and calcifications with scores indicating malignancy likelihood, thereby supporting better screening and diagnosis of breast cancer in women.

Genius AI Detection 2.0 with CC-MLO Correlation is an AI-powered software designed to assist radiologists by analyzing digital breast tomosynthesis images to detect and mark suspicious soft tissue densities and calcifications. It provides confidence scores for each detected lesion, helping clinicians interpret breast cancer screening exams more effectively, including correlation between different standard mammographic views for better diagnosis workflow.

Genius AI Detection 2.0 is a software device that uses deep learning AI models to analyze digital breast tomosynthesis (DBT) images. It identifies and marks suspicious soft tissue densities and calcifications, providing confidence scores to aid radiologists during breast cancer screening. The AI improves detection specificity and reduces false positives, supporting clinicians in interpreting 3D mammography exams efficiently and accurately.

CogNet QmTRIAGE is an AI-powered software tool designed to analyze 2D digital mammograms to prioritize patients with suspicious breast findings. It flags exams suggestive of cancer to help mammography interpreting physicians prioritize their workflow, aiding early detection without replacing full diagnostic evaluation.

Transpara 1.7.2 is an AI-based software tool that helps radiologists detect and assess suspicious regions in breast mammography and tomosynthesis exams. It highlights potential cancerous lesions, scores their likelihood of malignancy, and provides an overall exam score to assist in clinical decision making, enhancing the accuracy and efficiency of breast cancer screening.