Find the artificial intelligence based software for radiology that you are looking for. All products listed are available for the European market (CE marked).
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Median Technologies
Subspeciality: Chest
Modality: CT
Source: Vendor
No key features available
Eyonis LCS is software that analyses low-dose chest CT examinations in lung cancer screening. It detects and localises pulmonary nodules and assigns each nodule a malignancy risk score. Results are provided in a DICOM report that lists nodules by score, categorised as probably benign, suspicious or very suspicious, with measurements of diameter and volume. The software is intended for use by radiologists.
Subspeciality: Abdomen
Modality: CT
Source: Vendor
Detect and flag findings, Lesion characterization, Track changes over time
LIRVEA™ is a medical device software, based on artificial intelligence, that assists radiologists in the detection and characterization of radiological findings in the liver on CT scans of adult patients. LIRVEA™ integrates with the customer’s PACS (Picture Archiving and Communication System) and RIS (Radiology Information System), ensuring interoperability within the hospital’s workflow.
Subspeciality: Chest
Modality: CT
Source: Vendor
Automated measurements of nodule diameter, Depth, Lung nodule detection, Volume
Riverain's CT Detect technology provides measurements for each detected region of interest including location, type, volume, maximum, minimum, average axial plane diameters, and nodule depth. All nodule types are detected (solid, part-solid, ground glass) at or above 5mm.
Subspeciality: Neuro
Modality: MR
Source: Vendor
Brain structure segmentation and volume quantification, Comparison to reference population, Multiple time-point analysis, White matter hyperintensity detection and quantification
Brain Health (previously Saige Brain and Quantib® ND) offers automated segmentation of brain structures and white matter hyperintensities. This machine learning radiology application provides insight into the possible presence of atrophy related to Alzheimer's disease or other types of dementia. Brain Health's follow-up feature allows for tracking of neuro degeneration over time. Automatic assessment of white matter hyperintensity development supports monitoring of MS patients.The software distinguishes between new and previously identified WMHs, providing a visualization with color-coded lesions super positioned on an anatomical map.
Subspeciality: MSK
Modality: X-ray
Source: Vendor
Detection of fractures, Dislocations and bone lesions, Effusions, Worklist prioritization
BoneView detects fractures, effusions, dislocations and bone lesions, and gives 3 different pre-diagnosis labels on the images: - POSITIVE when the confidence for the presence of a lesion is above 90% (plain bounding box around the region of interest) - DOUBT when the confidence for the presence of a lesion is between 50% and 90% (dotted bounding box around the region of interest) - NEGATIVE otherwise BoneView provides a summary table for quality check and overview of AI outputs at a glance, and can perform worklist prioritization according to the different pre-diagnoses. *In the United States, BoneView has been 510k FDA-cleared for pediatric use and adults (>2 years old for limbs).
Subspeciality: Neuro
Modality: CT
Source: Vendor
Intracranial hemorrhage detection, Volume quantification
hStroke_Suite CT Module is an AI-powered solution specifically designed for emergency neuroimaging with a focus on head CT scans. It enables rapid and accurate detection of intracranial hemorrhages, aiming to support faster diagnosis and timely intervention.
Subspeciality: Breast, Thyroid
Modality: Ultrasound
Source: Vendor
AI independent risk assessment, Alignment to diagnostic classification systems, Auto-population of lesion/nodule descriptors, Lesion/nodule classification, Lesion/nodule segmentation
Koios DS is a software application designed to assist trained interpreting physicians in analyzing breast and thyroid ultrasound images. Koios DS software automatically classifies breast lesions suspicious for cancer based on image data into one of four ACR BI-RADS or European U1-U5 Classification System-aligned categories. Koios DS also categorizes thyroid nodules via the ACR TI-RADS or American Thyroid Association (ATA) risk stratification systems (RSSs) along with a cancer risk assessment presented as the Koios "AI Adapter."
Spimed-AI
Subspeciality: Cardiac
Modality: CT
Source: Vendor
Confidence score, FFR-AI prediction per coronary, Risk prioritization, Stenosis classification according to CAD-RADS
CorEx is artificial intelligence software for cardiac imaging. It prioritizes at-risk patients. It automatically analyzes coronary CT images (CCTA) images independently detecting and classifying coronary lesions quantitatively. CorEx automatically classifies stenosis according to the international CAD-RADS classification. CorEx aids the assessment of artery damage and the severity of the obstruction. It also provides an FFR AI prediction: for each coronary the solution predicts if the threshold of 80% is reached or not.
Subspeciality: Neuro
Modality: MR
Source: Vendor
Brain parcellation
It parcellates the brain into 100+ parts using 3D T1 non-contrast MRI and provides quantitative data describing volume, normative percentiles, and cortical thickness with color overlays. The solution assists the diagnosis of neurodegenerative disorders by analyzing the atrophy of main brain structures.
Subspeciality: MSK
Modality: X-ray
Source: Vendor
And legs, Automated measurements of spine, Feet, Pelvis
BoneMetrics provides automated MSK measurements for the spine, pelvis, feet, shoulder, knee and legs, on X-ray and EOS acquisitions.
Subspeciality: Cardiac
Modality: CT
Source: Vendor
Coronary lesion detection, Pericoronary fat measurement, Plaque analysis, Plaque detection, Reconstructed images (MPR/VR/MIP/Probe/CPR/SCPR), Segmentation and 3D reconstruction of heart and coronary arteries, Stenosis detection, Stenosis evaluation
The CT CCTA application is intended to assist in confirming and evaluating the presence or absence of coronary lesions for CCTA images.