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).
9/220 results
Improved visibility of lines and tubes
ClearRead XRay identifies and highlights lines and tubes on portable chest X-ray images.
Radiologic finding detection, abnormality score, text interpretation
Lunit INSIGHT CXR is deep learning based software that assists radiologists or clinicians in the interpretation of chest x-ray (PA/AP). The AI solution automatically detects 10 radiologic findings ...
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.
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.
Lung nodule detection of nodules of 9 to 30 mm in size
ClearRead Detect identifies regions-of-interest on the bone suppressed soft tissue image that may be early-stage lung cancer.
Endotracheal tube tip to carina measurement, detection and flagging of pneumothorax and ...
**Currently only available with GE Healthcare systems.** Critical Care Suite, powered by Edison, is a collection of AI algorithms for automated measurements, triage and quality control embedded on ...
Pneumothorax detection, pleural effusion detection, worklist prioritization, notification
Nanox.AI'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 ...
Lung nodule detection
**Only available with Samsung Electronics systems.** For Auto Lung Nodule Detection multiple deep learning algorithms help predict lung nodule in general chest radiography as a second reader.
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 ...