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: 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.
Subspeciality: Thyroid
Modality: Ultrasound
Source: Vendor
Automated nodule recognition, Quantification and visualization of sonographic features, Risk analysis based on global guidelines
AmCAD-UT® Detection gives physicians a tool to process ultrasound images for sonographic characteristics that assist in making diagnostic decisions. AmCAD-UT® Detection uses statistical pattern recognition and quantification methods to perform analytical processing of images. By processing the image for key characteristics (i.e., echogenic foci, echogenicity, texture, margin, anechoic areas, height/width ratio, nodule shape, and nodule size). AmCAD-UT® Detection provides physicians with quantification and visualization of the sonographic characteristics for informed decision making.
Subspeciality: Neuro
Modality: MR
Source: Vendor
CE
FDA
Brain volume change, Report generation, White matter abnormality quantification
icobrain ms helps physicians assess (sub)clinical disease activity in patients with multiple sclerosis. icobrain ms allows for the objective assessment of lesion dissemination in space and time by: - Quantifying and tracking FLAIR WM hyperintensities and T1 WM hypointensities icobrain ms provides measures of brain volume changes by: - Tracking annualized brain volume changes for whole brain and gray matter - Comparing brain volumes and volume changes to an age-and gender-matched reference population.
Subspeciality: Neuro
Modality: CT
Source: Public
Subspeciality: Abdomen
Modality: MR
Source: Public
CE
FDA
Biliary system segmentation, Width and volume quantification
MRCP+ allows existing MRCP data to be enhanced and quantitatively characterized using image processing techniques. The technology can enhance the data from conventional MRCP without needing to inject contrast agent, enabling 3D visualization of ducts. MRCP+ calculates quantitative 3D biliary system models that enable measurement of bile duct widths and automatic detection of regions of variation of duct widths. MRCP+ includes tools for interactive segmentation and labelling of the biliary system and structures. It allows for regional volumetric analysis of the biliary tree, pancreatic duct, and gallbladder.