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.
BriefCase is an AI-powered software by Aidoc Medical that automatically analyzes chest CT scans to identify cases with three or more acute rib fractures. It sends notifications with preview images to help radiologists prioritize these critical cases for faster review, enhancing clinical workflow and patient care without altering original images or providing primary diagnoses.
TruPlan Computed Tomography (CT) Imaging Software is designed to help clinicians visualize and measure the left atrial appendage and surrounding heart structures from CT scans. It supports pre-procedural planning and post-procedural evaluation of the left atrial appendage closure (LAAC) procedure by providing segmentation, image visualization, and measurement tools. Machine learning enhances segmentation and landing zone detection for improved workflow. The software aids in clinical decision-making but does not replace existing standard care procedures.
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.
The Philips CT 3500 is a computed tomography X-ray system designed to produce detailed images of the head, whole body, cardiac, and vascular regions. It supports diagnostic imaging and low dose lung cancer screening using advanced imaging features and includes AI-based image reconstruction for improved image quality at reduced dose, helping clinicians with early detection and diagnosis.
BriefCase by Aidoc Medical, Ltd. is an AI-powered software that assists radiologists by automatically analyzing chest and abdominal CT scans to detect and flag suspected vertebral compression fractures. It helps prioritize medical images for review, enabling faster triage without altering original images or workflows, thus improving the efficiency of radiological diagnosis and patient care.
Cina is an AI-powered software designed to assist radiologists by automatically analyzing head CT and CT angiography images to detect intracranial hemorrhage and large vessel occlusion. It provides notifications and preview images to help prioritize and triage cases, enhancing workflow efficiency and potentially enabling faster diagnosis and treatment without replacing standard diagnostic procedures.
AVIEW RT ACS is a software solution developed by Coreline Soft Co., Ltd. that uses deep learning AI to automatically segment organs and generate contours from CT scans. It is intended to assist clinicians, particularly in radiation oncology, by providing initial organ contours for treatment planning, saving time and improving accuracy.
Viz LVO is an AI-based software tool designed for hospital networks and clinicians to detect and notify specialists about suspected large vessel occlusions in brain CT angiograms. It facilitates rapid communication and prioritization of cases to improve stroke patient management, providing image previews via a mobile app for informational use to assist timely specialist review.
AI-Rad Companion (Musculoskeletal) is an AI-powered software that analyzes previously acquired CT images to assist radiologists and physicians in evaluating musculoskeletal diseases. It segments, labels vertebrae, measures vertebral heights, and computes mean Hounsfield values to provide detailed quantitative and qualitative analysis, improving assessment and workflow efficiency for clinicians.
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