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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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: Multiple
Modality: MR
Source: Vendor
CE
FDA
MRI image enhancement, MRI scan acceleration
SwiftMR aims to accelerate MRI scans by up to 50% by enhancing low-quality initial outputs from accelerated scans. The deep-learning model improves SNR and resolution of MRI inputs, irrespective of body part or vendor type. Operating in DICOM format, SwiftMR receives assigned scans from connected MRIs and dispatches results to PACS. Installable via cloud or on-premise. *Product coverage and supported types may vary by region depending on regulatory status.
Subspeciality: Abdomen
Modality: MR
Source: Vendor
Exporting results in rtss format, Lesion candidate localization and classification, Pre-populated pi-rads report, Prostate gland segmentation and volumetric assessment, Suspicion map highlighting the lesion candidates
Currently only available with Siemens Healthineers' syngo.via Siemens Healthineers Prostate MR on syngo.via supports prostate MRI reading and reporting. By deploying artificial intelligence, Prostate MR assists in the interpretation of multiparametric Prostate MRI. The deep neural networks of Prostate MR are designed to aid the detection and classification of prostate lesions and generate a pre-populated report. The results can be exported as a RTSS object which is then used in TRUS-guided biopsy by the urologist. The product is not commercially available in some countries, e.g. the US. Due to regulatory reasons the future availability cannot be guaranteed. Please contact your local Siemens Healthineers organization for further details.
Subspeciality: Abdomen
Modality: MR
Source: Vendor
Automated comparison to earlier examinations., Automated segmentation of the prostate with volume calculation, Classification of lesions according to pi-rads 2.1 and determination of relevant parameters (e.g., Detection and evaluation of suspicious lesions, EPE, Extent, Index lesion)
mdprostate enables AI-based static and longitudinal evaluations of prostate MRIs through automatic identification and classification of lesions according to PI-RADS 2.1. The output includes quantitative reports and visual overlays directly integrated into the PACS, with all relevant lesions marked on a sector map.
Subspeciality: Neuro
Modality: CT
Source: Vendor
Brain pathology detection, Hemorrhage detection, Localization of pathology
BrainScan CT is an advanced AI-powered radiology tool that analyzes brain CT scans, automatically detecting and highlighting pathological changes. It identifies and classifies 30 key brain pathologies – covering over 90% of findings in non-contrast CT imaging – with an average accuracy of 95% and up to 99% for hemorrhages. Trained on a diverse dataset of 350,000 scans, BrainScan delivers fast, reliable results in seconds, presented in an intuitive infographic format. The system supports both cloud and on-premise deployment, integrates with any PACS or DICOM viewer, and works in any language – offering hospitals a simple, scalable AI solution for neuroimaging.
Subspeciality: Neuro
Modality: CT
Source: Vendor
Collateral assessment, Report generation, Vessel occlusion detection
e-CTA is a decision support software that uses algorithms, artificial intelligence and data analytics to automatically detect LVO and standardize the assessment of collaterals on CT angiography. e-CTA supports single and multi-phase CTA and fully automates the CTA-CS collateral score supported by a color heat-map representing the difference in collaterals between hemispheres. e-CTA estimates phases of CTA image from automatic arterial input and venous output, and provides visualization of major vessels and the location of any detected LVO.
Subspeciality: Multiple
Modality: CT
Source: Vendor
CT Image denoising for any body part
ClariCT.AI is an AI-powered CT image denoising solution to provide increased image clarity in CT examinations with excessive image noise due to either low dose or large patient. It is trained to work in a vendor-agnostic way, to reduce noise and enhance image quality for low-dose and ultra-low-dose DICOM CT images. ClariCT.AI separates image noise selectively while enhancing underlying structures; thus, providing clarity restored images.
Subspeciality: MSK
Modality: X-ray
Source: Vendor
Automatic , Opportunistic, Risk score
Rho is a screening tool that analyzes frontal radiographs of the lumbar spine, thoracic spine, chest, pelvis, knee, or hand performed for any clinical indication in patients aged 50 years and older. The algorithm was developed using machine learning to generate a risk score that correlates with a patient's likelihood of having low bone mineral density.
Subspeciality: MSK
Modality: X-ray
Source: Vendor
Editable report, Fracture risk assessment (bmd t-score & frax adjusted with tbs), Trabecular Bone Score (TBS) calculation
TBS Osteo is an AI-ready technology and software powered by TBS iNsight to evaluate bone microarchitecture in patients during a DXA bone densitometry scan. It aims to identify more patients at risk of fracture.
Subspeciality: Neuro
Modality: MR
Source: Vendor
CE
FDA
Disease activity, Image annotation, Lesional volume quantification, Lesion classification, Lesion quantification, Longitudinal analysis, McDonald MRI criteria
Pixyl.Neuro.MS integrates into the routine workflow, to extract pertinent information on the size and location of Multiple Sclerosis (MS)-specific lesions, aimed at supporting the diagnosis and monitoring of patients. In case of multiple visits, the longitudinal analysis also provides data on the evolution of the lesions, and therefore on the activity of the disease with respect to diagnostic criteria. The software outputs both a quantitative report on lesion location, volume and evolution, as well as annotated MRI images with lesions labeled according to their evolution.
Subspeciality: Cardiac
Modality: Ultrasound
Source: Vendor
CE
FDA
Automated segmentation, Risk prediction
Outcomes-based AI system that predicts coronary artery disease.