Radiology

Head CT scans are a first line diagnostic modality for patients with head injury or stroke. qER is designed for triage or diagnostic assistance in this setting. The most critical scans are ...

IB Lab SQUIRREL is a radiological image processing software that aims to support physicians in the assessment of spinal morphology and scoliosis evaluation using frontal radiographs of the spine, ...

qCT-Lung aids lung cancer screening programs and facilitates opportunistic screening using AI. It provides pre-read assistance to clinicians by detecting lung nodules & emphysema.

ChestEye Quality is an automatic Quality Assurance (QA) chest X-ray solution. It automatically double-reads all chest x-rays, by analyzing radiologists' reports and comparing them with AI analysis of ...

**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 ...

CoLumbo is an AI assistant software for the interpretation of lumbar spine MR scans. It is a deep learning algorithm that aims to help radiologists reduce the patient examination reading and ...

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 ...

Aidoc’s Incidental Pulmonary Embolism algorithm is a triage and notification software that flags and communicates suspected positive findings of pulmonary embolism and runs automatically on contrast ...

IB Lab’s diagnostic support tool LAMA uses deep learning technology for automated measuring of leg geometry to evaluate lower limb deformities, such as leg or lower extremity length discrepancy and ...

Annalise Enterprise CTB is an AI clinical decision-support solution for non-contrast head CT, detecting up to 130 findings. Features include: • customisable, interactive viewer that integrates into ...

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 ...