Products
Find the artificial intelligence based software for radiology that you are looking for.
All products listed are available for the European market (CE marked).
16/181 results
Modality: CT
Lung lobe segmentation, Low Attenuation Analysis (LAA), Emphysema, Vessel Analysis, Fissure ...
AVIEW COPD gives COPD information based on a non-enhanced CT-scan of the thorax. Evaluation includes segmentation of lungs and lung lobes, low attenuation analysis, emphysema, vessel analysis, ...
Modality: CT
Nodule detection, nodule classification, nodule volume quantification, VDT, Lung-RADS score, ...
The LCS+ software from Coreline Soft provides information on the 3 main lung diseases: lung cancer, COPD and coronary artery calcification based on a Low Dose, non-enhanced, non-gated CT-scan
Modality: X-ray
pneumothorax detection, pleural effusion detection, worklist prioritization, notification
Zebra-Med’s Chest Solutions are a suite of radiological software that can provide multiple capabilities including triage, visualization of findings, and automatic separation between normal and ...
Modality: X-ray
Pneumothorax detection, on-device notifications, worklist prioritization, quality checks on ...
**Currently only available with GE Healthcare systems.** Critical Care Suite, powered by Edison, is a collection of AI algorithms for triage and quality control embedded on an X-ray system. The ...
Modality: CT
lung nodule detection, report generation, multi-timepoint analysis
InferRead CT Lung is a processing solution for lung cancer screening. It recognizes the core features of lung cancer, determine the characteristics of suspected lung nodules in different image ...
Modality: CT
Lung density quantification, abnormal lung region mapping, report generation
Lung Density Analysis™ applies big data analysis to paired inspiratory / expiratory chest CT studies to provide visualization and quantification of lung regions with abnormal tissue density. ...
Modality: CT
Noise reduction of low dose CT
PixelShine is an algorithm for de-noising CT datasets supporting new CT protocols to drive patient dose down, while image quality is maintained. PixelShine may aid detectability of subtle pathologies ...
Modality: CT
nodule detection, segmentation and quantification, temporal registration and nodule comparison, ...
Veolity is a reading platform dedicated to lung screening program. It combines lung CAD of solid pulmonary nodules, integration and automatic registration of prior studies and creates the associated ...
Modality: CT
Lung disease biomarkers, lung (lobe) volume quantification, scan suitability quality check, ...
VIDA Insights™ is a lung intelligence solution providing quantitative data and visualizations. VIDA’s biomarkers measure lung destruction, inflammation, function and more, to aid the detection, ...
Modality: CT
multiple time-point analysis
Nodule tracking for differential measurements. Utilizing ClearRead CT Detect, ClearRead CT Compare tracks nodules and provides nodule volumetric changes over time for solid, part-solid, and ground ...
Modality: CT
lung nodule detection
Riverain’s ClearRead CT Detect detects lung nodules in CT images.
Modality: CT
vessel suppression
Riverain’s ClearRead CT Vessel Suppress is powered by machine learning and advanced modeling and suppresses vascular structures. The vessel suppression algorithm works with contrast and non-contrast ...
Modality: X-ray
bone suppression
ClearRead Bone Suppress removes ribs and clavicles from a standard chest X-ray, providing a soft tissue image, allowing clinicians to see more and detect more.
Modality: X-ray
multiple time-point analysis
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.
Modality: X-ray
line and tube identification
ClearRead XRay identifies and highlights lines and tubes on portable chest X-ray images. Radiologists can minimise imaging adjustments and decrease reading time.
Modality: X-ray
abnormality detection, explaining heatmaps, worklist prioritization
The red dot® algorithm is based on deep learning models. The training process teaches the algorithm to both classify a CXR and localize its findings. This localization is rendered through heatmaps ...