FDA Radiology AI Devices

AI Platform 2.0 (AIP002) by Exo Imaging is an AI-powered software tool designed to assist healthcare professionals by analyzing ultrasound images of the heart and lungs. It helps detect lung structures and artifacts, and quantifies cardiac functions such as left ventricular ejection fraction and myocardium wall thickness. The tool also provides real-time quality feedback to improve ultrasound image acquisition, aiding clinicians in making better diagnostic assessments for adult patients.

VEA Align and spineEOS are cloud-based medical imaging software products by EOS imaging designed to assist healthcare professionals. VEA Align helps assess spinal and lower limb alignment using 2D X-rays with AI-generated anatomical landmarks for precise angle and length measurements. spineEOS facilitates preoperative planning for spine surgeries with access to 3D spine datasets and clinical measurements, enabling tailored surgical strategies. Both tools support clinicians by improving diagnostic accuracy and surgical planning through advanced image analysis and AI.

BriefCase-Quantification is an AI-powered software that analyzes CT scans of the abdominal aorta to measure its maximum diameter. It helps trained medical specialists by providing preliminary diameter measurements to assist with evaluating normal and aneurysmal abdominal aortas, improving the efficiency of radiological assessments. The software is cloud-based, processes images from DICOM format, and integrates output with PACS for clinician review.

InVision Precision LVEF is a software tool that analyzes previously acquired transthoracic cardiac ultrasound images to automatically estimate the left ventricular ejection fraction, helping clinicians with cardiac evaluation. The software processes DICOM ultrasound videos, uses machine learning to segment the left ventricle, and allows clinicians to review and adjust the measurements for precise cardiac function assessment.

Us2.v2 is software that processes cardiac ultrasound images to automatically measure various heart structures and functions, helping clinicians analyze echocardiograms more efficiently and accurately. It supports qualified healthcare professionals by providing automated measurements of cardiac size and function, improving workflow and aiding diagnosis in adult patients.

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.

Overjet Charting Assist is an AI-powered medical image processing system that helps dental professionals detect and identify dental structures such as teeth anatomy and past restorative treatments on various dental radiographs. It assists in creating dental charts more efficiently by analyzing bitewing, periapical, and panoramic images, helping reduce manual charting efforts by over 80%.

DASI Dimensions (V1.0) is a clinical decision support software that processes multiphase CTA chest images to generate automated measurements of cardiovascular structures. It helps cardiologists and radiologists by providing detailed images and numerical data to support planning for aortic valve replacement procedures, improving accuracy and efficiency of pre-operative assessments.

VEA Align is a cloud-based software developed by EOS imaging that uses 2D X-ray images acquired from EOS imaging systems to assist healthcare professionals in assessing global alignment in orthopedic patients. It applies machine learning algorithms to automatically place anatomical landmarks on images, helping clinicians analyze spinal deformities, degenerative diseases, and lower limb disorders with precise angle and length measurements. It supports both pediatric and adult patients and enhances clinical decision-making through interactive landmark adjustment and comparison to normative values.