FDA Radiology AI Devices

AutoChamber is an AI-powered software tool designed to analyze both non-contrast and contrast-enhanced chest CT scans to automatically measure and report volumes of cardiac chambers including left atrium, left ventricle, right atrium, right ventricle, and left ventricular wall. It assists healthcare providers by providing quantitative imaging data that helps identify conditions such as enlarged heart and left ventricular hypertrophy, thus aiding in further clinical evaluation and management of cardiovascular risk.

HealthCCSng is a software tool that uses artificial intelligence to automatically detect and measure calcified plaques in the coronary arteries from routine non-gated, non-contrast CT scans. It provides an exact calcium score and categorizes the amount of calcium present, with results integrated into the radiologist's workflow to assist in assessing risk for coronary artery disease.

CardIQ Suite is a non-invasive software tool that analyses 2D and 3D CT cardiac images to assist clinicians in visualizing and measuring heart structures and vessels. It provides calcium scoring to evaluate calcified plaques and uses deep learning algorithms to automate segmentation and labeling of heart and coronary arteries, improving diagnostic workflow for cardiovascular diseases.

AVIEW CAC is a software that analyzes non-contrast chest CT scans to quantify calcified plaques in coronary arteries, calculate the Agatston score, and provide risk stratification based on calcium scoring, age, and gender. It helps radiologists and cardiologists by supporting image storage, transfer, and display, facilitating clinical decision-making for coronary artery disease risk assessment.

CT Cardiomegaly is a command-line software tool designed to automatically measure the cardiothoracic ratio from CT chest images. It uses machine learning algorithms to segment the heart and thoracic cavity and calculate both linear and area-based cardiothoracic ratios. This assists physicians in identifying cardiomegaly, providing quantitative measurements to support clinical decisions within healthcare settings.

qXR-CTR is an AI-powered software that helps physicians automatically measure the cardiothoracic ratio—the size of the heart relative to the chest—using chest X-ray images. It analyzes images to provide quick, accurate measurements that support clinical decision-making, making the process more efficient for healthcare providers.

The CorVista System is a non-invasive medical device combining hardware and software to analyze physiological signals from patients with cardiovascular symptoms. Using machine learning, it provides healthcare providers with a likelihood of significant coronary artery disease to aid diagnosis, integrating clinical judgment and patient history. This helps clinicians identify patients who may need further evaluation or treatment.

CAC Software by Imbio, Inc. is a machine learning-based post-processing tool that analyzes non-contrast CT images of the chest to assess calcified plaques in the coronary arteries. It quantifies the calcification burden by producing scores and metrics that help clinicians evaluate coronary artery disease risk. The software outputs annotated images and a detailed report, integrating into the standard DICOM workflow to assist physicians without making standalone diagnoses.

The iCAC Device is a software tool that analyzes routine chest CT scans to automatically detect and quantify coronary artery calcium, which helps physicians assess cardiovascular risk. It provides outputs such as calcium segmentation visualizations and quantitative calcium scores during standard clinical workflows, assisting physicians without replacing original reports or scans.

DTX Studio Clinic 3.0 is an AI-powered software tool designed to assist dentists in detecting dental conditions such as caries, bone loss, periapical radiolucency, root canal filling deficiencies, discrepancy at the margin of restorations, and calculus from intraoral radiographs. It supports review of bitewing and periapical radiographs in patients aged 15 and older, providing highlighted areas of suspicion to aid clinical assessment and diagnosis.