The Vivid iq is a high-performance compact diagnostic ultrasound system made by GE Medical Systems Ultrasound. It supports a wide range of clinical applications including cardiovascular, abdominal, fetal, musculoskeletal, and more. The system enables automatic AI-based cardiac measurements and spectrum recognition to assist clinicians in analysis and diagnosis. It is intended for use by trained healthcare professionals in hospitals and private medical offices.
FractureDetect (FX) is an AI-powered software that analyzes X-ray images of bones to help doctors detect fractures. It highlights areas on radiographs where fractures are detected, improving accuracy and efficiency in diagnosis for various bone regions in adults.
The Vivid E80, Vivid E90, and Vivid E95 are advanced diagnostic ultrasound systems specialized for cardiac imaging but also capable of vascular and general radiology applications. Featuring AI-driven tools for cardiac image analysis, these systems enable clinicians to perform automated measurements and enhanced visualization to improve efficiency and reduce variability. They support various clinical settings including hospitals and private offices with a range of imaging modes and transducers.
The Vivid S60N and Vivid S70N are advanced general-purpose ultrasound imaging systems by GE Healthcare, specialized for cardiac imaging but also supporting a broad range of diagnostic ultrasound applications across the human body. These systems facilitate ultrasound imaging, measurement, display, and analysis to assist physicians in clinical environments such as hospitals and private offices, enhancing diagnostic accuracy and workflow efficiency through digital acquisition, processing, and semi-automated AI-based measurement features.
InferRead Lung CT.AI is software that helps radiologists detect lung nodules in chest CT scans. It uses AI algorithms to identify and mark nodules, providing measurements and characterization to aid diagnosis, specifically targeting an asymptomatic population. The software integrates with existing PACS systems and assists clinicians by enhancing nodule detection sensitivity and reducing interpretation times.
Syngo.CT CaScoring by Siemens is an AI-based software that evaluates non-contrasted cardiac CT images to identify and score calcified coronary lesions. It helps clinicians by automatically marking these lesions, assigning them to specific coronary arteries, and calculating clinically relevant scores such as the Agatston score, facilitating better assessment and documentation of coronary artery disease.
AVIEW LCS by Coreline Soft Co., Ltd. is a diagnostic software tool that reviews, analyzes, and reports on thoracic CT images to help clinicians characterize lung nodules. It automatically measures nodule size, volume, density, and growth over time, integrates with FDA-cleared CAD for nodule detection, and provides lung cancer risk scoring and standardized Lung-RADS categorization. This helps clinicians detect, monitor, and manage lung nodules more accurately and efficiently.
NinesAI is a software tool that uses artificial intelligence to automatically analyze head CT images for signs of intracranial hemorrhage and mass effect. It helps prioritize critical cases by notifying radiologists of potential emergencies to assist in timely and effective patient care. The software works alongside standard workflows and does not replace full clinical evaluation or diagnosis.
CuraRad-ICH is an AI-powered software that helps radiologists quickly identify and prioritize head CT scans that may show acute intracranial hemorrhage (bleeding in the brain). By automatically analyzing CT images, it assists in faster diagnosis and treatment decisions to improve patient outcomes.
MammoScreen is an AI-based software that assists physicians in interpreting full-field digital mammograms (FFDM) by identifying suspicious breast lesions such as soft tissue lesions and calcifications. It provides marks on the mammogram images alongside a suspicion score to help detect potential breast cancer, supporting radiologists during their reading process to improve cancer detection without replacing clinical judgment.
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