FDA Radiology AI Devices

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.

ViewFinder Software Version 1.1 by Elaitra Ltd is a specialized software tool designed for clinicians to review digital breast tomosynthesis images. It dynamically matches tissue across different breast views using AI to reduce cognitive load, helping radiologists to compare images more efficiently and accurately during breast cancer screening and diagnosis.

Saige-Density is a medical software that uses AI deep learning techniques to analyze digital mammograms, producing breast density categories based on ACR BI-RADS guidelines. It helps radiologists assess breast tissue composition by providing adjunctive information, improving breast cancer risk assessment and screening interpretation.

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.

Saige-Dx is an AI-based software that analyzes digital breast tomosynthesis mammograms to detect suspicious soft tissue lesions and calcifications that may indicate cancer. It provides radiologists with a suspicion level for each finding and the entire case, helping improve detection accuracy and reduce reading time during breast cancer screening.

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.

ClariSIGMAM is a software tool designed to automatically analyze digital mammograms to estimate breast density by calculating the ratio of fibroglandular tissue to the total breast area. It categorizes breast density using BI-RADS groups to assist radiologists in assessing breast tissue composition, providing adjunctive information to support interpretation but is not a diagnostic aid.