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
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.
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 ...
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.
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.
Improved visibility of lines and tubes
ClearRead XRay identifies and highlights lines and tubes on portable chest X-ray images.
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 ...
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 ...
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 ...