FDA Radiology AI Devices

MPXA-2000 is a software tool intended for cardiologists and radiologists to automatically analyze X-ray angiographic images of the coronary arteries. It uses deep learning and computer vision algorithms to segment blood vessels, classify vessel types, quantify vessel dimensions, and support clinical decisions related to coronary artery disease. The software provides validated, reproducible quantitative results to aid in diagnosis and treatment evaluation, with results available for review and export.

BoneMRI v1.6 is an AI-powered software that enhances MRI images to improve visualization of bone structures in the pelvic and lumbar spine regions. It uses advanced algorithms, including convolutional neural networks, to generate 3D images with enhanced bone contrast. This allows clinicians such as radiologists and orthopedic surgeons to better assess bone morphology and tissue density without the need for CT scans, improving diagnostic capabilities in these regions.

Videa Perio Assist is an AI-powered software that helps dentists and dental hygienists measure and visualize bone levels between teeth using bitewing and periapical dental X-rays. It provides precise measurements that support evaluations related to periodontal health but is not meant to replace full clinical diagnosis.

LVivo IQS is a software application that processes ultrasound images of the heart to detect, measure, and calculate key medical parameters for patients with suspected cardiac disease. It provides real-time quality score feedback on image quality, helping clinicians ensure the accuracy and usefulness of cardiac ultrasound scans, particularly the left ventricle function from the 4 chamber apical view. This tool assists clinicians by improving the reliability of echocardiographic assessments.

Rapid RV/LV is a medical imaging software designed to assist clinicians by automatically measuring the sizes of the right and left heart ventricles from CT pulmonary angiography scans. It provides annotated images and quantitative measurements to help assess right-heart strain, supporting clinical decision-making in cardiopulmonary conditions. The software uses machine learning to locate the ventricles and report their size ratio.

Clarius AI is software integrated with the Clarius Ultrasound Scanner that uses artificial intelligence to semi-automatically measure tendon thickness on ultrasound images of musculoskeletal structures such as the Achilles’ tendon and patellar tendon. It helps healthcare professionals by segmenting ultrasound images and automatically placing measurement calipers, streamlining the quantification process while allowing manual adjustment by trained clinicians.

AVIEW is a medical imaging software by Coreline Soft that helps clinicians analyze CT scans of the lungs and heart. It automatically segments lung structures, characterizes lung nodules with detailed measurements, and provides calcium scoring of coronary arteries to assess cardiovascular risk. It integrates with AI-based CAD tools and offers cloud and mobile access, making it easier and faster for doctors to diagnose lung and heart conditions.

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.

BrainInsight is an automated software that processes low-field MRI brain images to provide automatic labeling, spatial measurement, and volumetric quantification of brain structures. It produces annotated and segmented brain images with color overlays and detailed reports, helping clinicians assess brain anatomy and abnormalities efficiently, particularly using low-field MRIs.

The SIS System version 5.6.0 is a medical imaging software that helps surgeons, neurologists, and radiologists visualize specific brain structures in 3D to assist with planning neurological surgeries such as deep brain stimulation. It uses advanced image processing and machine learning techniques to create patient-specific anatomical models from MRI and CT images, improving precision during surgical interventions.