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ProductsCT Eye

Vendor source

Reviewed 11 May 2026

Completeness Strong (67%)

CT Eye

Oxipit

CT Eye™ is a CE-certified Class IIb computer-aided diagnosis (CAD) software intended to support trained radiologists in the analysis of adult chest CT studies. The software identifies radiological signs of pulmonary embolism (on contrast-enhanced CT), lung lesions, and lung consolidation. It provides worklist prioritisation, optional 3D localisation overlays, and post-report comparison using NLP to identify potential discrepancies between AI findings and radiologist reports.

No papers to support — we monitor for new evidence.

CT Eye
CT Eye
CT Eye thumbnail 1
CT Eye thumbnail 2

Key Features

  • 3d localisation overlay
  • Discrepancy flagging
  • Lung consolidation detection
  • Lung lesion detection
  • NLP-based report analysis
  • Pulmonary embolism detection
  • Report-to-image comparison
  • Worklist prioritisation

General Information

Product name

CT Eye

Company

Modality

CT

Main task

Detection

Subspeciality

Chest

Disease targeted

Pulmonary embolism, lung consolidation, pulmonary nodules, lung masses

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIb

Verified by Health AI Register

Other certifications

Not specified

Evidence & Research

No research papers or evidence on file yet.

The registry monitors publications for new evidence.

Technical Specifications

Patient population age

Adult

Input

3D, multi-slice, DICOM, chest CT, contrast-enhanced, non-contrast, volumetric imaging, radiology report text, HL7, DICOM SR

Input format

DICOM

Output

Preliminary findings list, worklist priority level, 3D overlay, image annotations, DICOM SR report, HL7 message, discrepancy flag, email notification

Output format

DICOM overlay, DICOM SR, email notification, HL7

Integration

Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform, Stand-alone third party application

Deployment

Cloud-based, Hybrid solution, Locally on dedicated hardware, Locally virtualized (virtual machine, docker)

Trigger for analysis

Automatically, right after the image acquisition

Processing time

1 - 10 minutes

Population

Intended for adult patients (≥18 years) undergoing diagnostic chest CT examinations in a clinical setting.

Market Presence

On market since

01-2026

AI Platforms

Resellers

Not specified

Countries present

Not specified

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Pay-per-use, Subscription

Based on

Number of analyses

Source: Vendor | First published: Mar 30, 2026 | Last updated: May 11, 2026