FDA Radiology AI Devices

inHEART Models is a suite of medical imaging software tools designed to assist physicians, cardiologists, and radiologists by automatically processing CT images to create 3D models of the heart. It uses AI for automatic segmentation and visualization, helping clinicians better interpret cardiac anatomy for diagnosis and treatment planning.

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%.

Viz HDS by Viz.ai is an AI-powered software that automatically labels, visualizes, and measures critical brain structures such as intracranial hyperdensities, lateral ventricles, and midline shift on non-contrast head CT scans. This automation helps radiologists quickly and accurately assess brain abnormalities by providing detailed volumetric data and annotated images, improving workflow and diagnostic efficiency.

NemoScan is a dental implant and surgery planning software that reads CT or CBCT medical images to simulate and evaluate patient anatomy, plan implant placement, and design surgical guides. It helps dental professionals prepare customized surgical plans and export guides for manufacturing, improving precision and treatment outcomes.

Rapid (6.0) by iSchemaView, Inc. is a medical imaging software designed to process and analyze dynamic and functional imaging data from CT and MRI scans. It aids clinicians by providing advanced visualization, quantification, and analysis tools to help select acute stroke patients for treatment, enhancing diagnostic confidence and workflow efficiency.

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.

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.

iQ-solutions is a software device designed to automatically identify, annotate, and measure specific brain structures on MRI scans. It helps clinicians by accelerating the quantification process, providing detailed volume analysis reports that support the assessment of brain anatomy and changes over time. The software improves workflow efficiency and consistency in brain MRI analysis.