Products

MammoScreen helps radiologists to identify findings on screening mammograms and assess their level of suspicion. MammoScreen® uses a color coded MammoScreen Score™ to provide an at a glance ...

Neurophet AQUA is an artificial intelligence-based degenerative brain disease diagnosis assistant software that helps clinicians to diagnose brain MRI data through quantitative analysis.

Based on the Alberta Stroke Program Early CT Scoring System, Rapid ASPECTS automatically generates a standardized score—based on machine-learning algorithms showing a patient’s ischemic changes.

QIR-MR is a clinical decision support software for the diagnosis, treatment, prevention, or mitigation of cardiovascular conditions. It allows quantitative analyses of cardiovascular Magnetic ...

The AI4CMR software performs a automatic cardiac segmentation and interpretation of Cardiac Magnetic Resonance (CMR), allowing quantification of various parameters without the need for intervention ...

cNeuro cMRI is a tool for quantitative assessment of MRI brain images. Volumes of 133 brain structures, as well as disease specific biomarkers are extracted from T1 images and white matter ...

The concurrent-read, cancer detection and workflow solution from iCAD analyzes each tomosynthesis image, detecting both malignant soft tissue densities and calcifications. Built on deep-learning and ...

ClearRead Bone Suppress removes ribs and clavicles from a standard chest X-ray, providing a soft tissue image, allowing clinicians to see more.

ClearRead Compare is an image registration and enhancement application that accentuates interval change between current and prior chest X-ray exams by forming a subtraction image.

ClearRead Detect identifies regions-of-interest on the bone suppressed soft tissue image that may be early-stage lung cancer.

ClearRead XRay identifies and highlights lines and tubes on portable chest X-ray images.

LVivo AI Cardiac ultrasound analysis solutions provide objective cardiac ultrasound images analysis, aimed at mitigating the challenges of manually capturing and visually analyzing ultrasound images.