Key Features

  • Heatmap of abnormality score
  • Tuberculosis risk score

General Information

Product name

CAD4TB

Subspeciality

Chest

Modality

X-ray

Disease targeted

Tuberculosis

Main task

Not specified

Technical Specifications

Population

All chest X-rays

Patient population age

Not specified

Input

Posterior-anterior chest X-rays

Input format

DICOM

Output

Segmentation overlay, heatmap of abnormality, risk score

Output format

Dicom, Png, Txt

Integration

Integration in standard reading environment (PACS), Stand-alone third party application, Stand-alone webbased

Deployment

Cloud-based, Hybrid solution, Locally on dedicated hardware

Trigger for analysis

Automatically, Etc., Image upload, On demand, Right after the image acquisition, Triggered by a user through e.g. a button click

Processing time

3 - 10 seconds

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIb

Verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

10-2014

AI Platforms

Not specified

Resellers

Not specified

Countries present

30+

Paying clinical customers

10+

Research/test users

40+

Pricing Information

Pricing model

Pay-per-use

Based on

Number of analyses

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

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Clinical evaluation of computer-aided digital x-ray detection of pulmonary tuberculosis during community-based screening or active case-finding: a case–control study

Peer-Reviewed

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Comparative analysis of the impact of portable digital X-ray on TB screening in hard-to-reach areas in Nigeria

Peer-Reviewed

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Diagnostic Accuracy of Chest X-ray Computer-Aided Detection Software for Detection of Prevalent and Incident Tuberculosis in Household Contacts

Peer-Reviewed

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Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage

Peer-Reviewed

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Evaluation of C-Reactive Protein and Computer-Aided Analysis of Chest X-rays as Tuberculosis Triage Tests at Health Facilities in Lesotho and South Africa

Peer-Reviewed

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Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software

Peer-Reviewed

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Evaluation of a population-wide, systematic screening initiative for tuberculosis on Daru island, Western Province, Papua New Guinea

Peer-Reviewed

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Comparing different versions of computer-aided detection products when reading chest X-rays for tuberculosis

Peer-Reviewed

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Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system

Other Articles

Other

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Early user perspectives on using computer-aided detection software for interpreting chest X-ray images to enhance access and quality of care for persons with tuberculosis

Source: vendor | First published: May 2, 2024 | Last updated: Jul 10, 2025