FDA Radiology AI Devices

PHAROS is a computed emission tomography system used in radiology to help clinicians obtain detailed three-dimensional images of the body. This technology assists in the diagnosis and monitoring of various medical conditions by providing high-quality images that aid in accurate assessment and treatment planning.

The uMI Panvivo is a system for performing computed emission tomography, which helps clinicians visualize and analyze internal structures in the body for diagnostic purposes. It supports advanced imaging techniques to assist medical professionals in detecting and assessing diseases.

The Biograph Vision and Biograph mCT PET/CT systems by Siemens are advanced imaging devices combining positron emission tomography (PET) and computed tomography (CT). These systems help clinicians detect and diagnose various conditions by providing detailed molecular and anatomical images, facilitating better patient management.

Opulus™ Lymphoma Precision is an AI-powered software tool designed to help physicians analyze whole-body FDG-PET/CT scans of patients with FDG-avid lymphomas. It automatically segments and visualizes lymphoma lesions and calculates the total metabolic tumor volume. This supports physicians by reducing the manual workload and assisting in more efficient interpretation of PET/CT images, although final decisions remain with the radiologist.

HeartSee Cardiac P.E.T. Processing Software is a tool that helps trained clinicians analyze heart PET images to quantify blood flow and heart function. It provides detailed maps and measurements that assist in diagnosing coronary artery disease by measuring myocardial perfusion and coronary flow reserve. This enables better clinical interpretation and patient management based on quantitative PET imaging data.

Clarify DL is a software solution that uses deep learning integrated with iterative image reconstruction techniques to reduce noise and improve image quality in Nuclear Medicine bone SPECT images. It helps clinicians by enhancing image clarity which potentially improves diagnostic confidence and patient outcomes.

The uMI Panvivo is a PET/CT medical imaging system designed to provide combined anatomical and functional images for clinicians. It uses PET to show distribution of radiopharmaceuticals and CT to provide detailed anatomical information. The system supports assessment of metabolic and physiologic functions across various parts of the body including oncology, neurology, and infection imaging. It can also assist in treatment planning for radiotherapy and interventional radiology, improving diagnostic accuracy and patient care.

TRAQinform IQ is a cloud-based software tool designed to aid medical professionals by providing quantitative analysis of lesions identified in PET/CT scans. It uses AI techniques such as machine learning for anatomical and skeletal segmentation and automates matching and quantitative assessment of regions of interest between multiple scans. The device generates detailed reports on lesion volume and tracer uptake changes over time, supporting clinicians in oncology and nuclear medicine to monitor disease progression and treatment response.

The uMI Panorama is a combined PET/CT diagnostic imaging system designed to assist healthcare professionals in detecting and evaluating diseases like cancer, heart, and neurological disorders. It fuses PET metabolic functional imaging and CT anatomical imaging with advanced AI algorithms to improve image quality, reduce artifacts, and enhance diagnostic confidence. It supports PET/CT and single modality CT imaging, including low dose CT lung cancer screening, providing comprehensive information for patient management.

The uMI Panvivo is a combined PET/CT imaging system designed to provide high-quality functional and anatomical images to help clinicians detect, localize, evaluate, and monitor abnormalities such as tumors, lesions, infections, and other conditions across various body areas. It supports better patient experience with a large bore and advanced iterative reconstruction algorithms aided by deep learning, improving image quality and diagnostic accuracy. Additionally, it assists in radiotherapy planning and interventional radiology procedures.