Tuberculosis Publications
Delft Imaging’s AI-powered CAD4TB is the most rigorously validated CAD technology for TB screening and triaging. Over 100 publications highlight its technicality, operational performance, cost-effectiveness and reliability.
Various studies suggest that CAD4TB performs significantly better than human readers and meets the WHO’s Target Product Profile, reduces Xpert MTB/RIF cartridges consumption, and increases daily screening throughput, thus contributing to reducing cost and making TB services more accessible, accurate, efficient and effective.
View our publications per category:
2024

The role of Artificial Intelligence as a community screening tool for Pulmonary Tuberculosis in Tanzania
2024

Continuous quality improvement in a community-wide TB screening and prevention programme in Papua New Guinea
2024

Prior tuberculosis, radiographic lung abnormalities and prevalent diabetes in rural South Africa

Diagnostic accuracy of Chest X-Ray Computer Aided Detection software and blood biomarkers for detection of prevalent and incident tuberculosis in household contacts followed up for 5 years
2024

Prevalence of pulmonary tuberculosis among casual labourers working in selected road construction sites in central Uganda
2024

Enhanced tuberculosis diagnosis with computer-aided chest X-ray and urine LAM in adults with HIV admitted to hospital (CASTLE study): A cluster randomised trial

Integrating molecular and radiological screening tools during community-based active case-finding for tuberculosis and COVID-19 in southern Africa

Evaluation of a population-wide, systematic screening initiative for tuberculosis on Daru island, Western Province, Papua New Guinea
2024

Serial Mass Screening for Tuberculosis Among Incarcerated Persons in Brazil

Diagnostic Accuracy of Computer-Aided Detection During Active Case Finding for Pulmonary Tuberculosis in Africa: A Systematic Review and Meta-analysis

Iterative evaluation of mobile computer assisted digital chest x-ray screening for TB improves efficiency, yield, and outcomes in Nigeria

National cross-sectional cluster survey of tuberculosis prevalence in TimorLeste: a study protocol
2024

Breaking the threshold – Developing multi variable models using computer-aided chest X-ray analysis for tuberculosis triage

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

Head-to-head comparison of diagnostic accuracy of TB screening tests: Chest-X-ray, Xpert TB host response, and C-reactive protein
2024

An independent, multi-country head-to-head accuracy comparison of automated chest x-ray algorithms for the triage of pulmonary tuberculosis
2024

Computer-aided detection thresholds for digital chest x-ray interpretation in tuberculosis diagnostic algorithms
2024

Policies, practices, opportunities, and challenges for TB screening – A survey of sixty National TB Programmes
2024

Assessment of scattered and leakage radiation from ultra-portable digital chest Xray systems: An independent study
2024

Finding the missed millions: innovations to bring tuberculosis diagnosis closer to key populations

Tweaking algorithms. Techno-political issues associated with artificial intelligence based tuberculosis detection in global health
2024
2023

Computer-aided diagnostic accuracy of pulmonary tuberculosis on chest radiography among lower respiratory tract symptoms patients
2023

Impact of a multi-disease integrated screening and diagnostic model for COVID-19, TB, and HIV in Lesotho

Improving TB control: efficiencies of case-finding interventions in Nigeria
2023

Diagnostic accuracy of three computer-aided detection systems for detecting pulmonary tuberculosis on chest radiography when used for screening: Analysis of an international, multicenter migrants screening study

Optimising computer aided detection to identify intra-thoracic tuberculosis on chest x-ray in South African children

The performance of computer-aided detection digital chest X-ray reading technologies for triage of active Tuberculosis among persons with a history of previous Tuberculosis

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

Evaluation of tuberculosis diagnostic test accuracy using Bayesian latent class analysis in the presence of conditional dependence between the diagnostic tests used in a community-based tuberculosis screening study
2023

CAD4TB software updates: different triaging thresholds require caution by users and regulation by authorities

Evaluation of chest X-ray with automated interpretation algorithms for mass tuberculosis screening in prisons: A cross-sectional study

Early user experience and lessons learned using ultra-portable digital X-ray with computer-aided detection (DXR-CAD) products: A qualitative study from the perspective of healthcare providers
2023

Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians
2023

Artificial intelligence-based computer aided detection (AI-CAD) in the fight against tuberculosis: Effects of moving health technologies in global health

Artificial Intelligence-Based Software with CE Mark for Chest X-ray Interpretation: Opportunities and Challenges
2023

The rise of artificial intelligence reading of chest X-rays for enhanced TB diagnosis and elimination
2022

Digital Chest X-Ray with Computer-aided Detection for Tuberculosis Screening within Correctional Facilities
2022

Accuracy of computer-aided chest X-ray in community-based tuberculosis screening: Lessons from the 2016 Kenya National Tuberculosis Prevalence Survey

Portable digital X-ray for TB pre-diagnosis screening in rural communities in Nigeria
2022

Population-wide active case finding and prevention for tuberculosis and leprosy elimination in Kiribati: the PEARL study protocol
2022

Diagnostic accuracy of computer aided reading of chest x-ray in screening for pulmonary tuberculosis in comparison with Gene-Xpert

Economic analysis of different throughput scenarios and implementation strategies of computer-aided detection software as a screening and triage test for pulmonary TB
2022

Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The Last 5 Years Review

Computer-Aided Detection of Tuberculosis from Chest Radiographs in TB Prevalence Survey: External Validation and Modelled Impacts of Commercially Available Artificial Intelligence Software
2022

Comparing different versions of computer-aided detection products when reading chest X-rays for tuberculosis
2022

“Similar performances but markedly different triaging thresholds in three CAD4TB versions risk systematic errors in TB screening programs”
2022

Diagnostic accuracy of chest X-ray interpretation for tuberculosis by three artificial intelligence-based software in a screening use-case: an individual patient meta-analysis of global data
2022

Conditions required for the artificial-intelligence-based computer-aided detection of tuberculosis to attain its global health potential

User perspectives on the use of X-rays and computer-aided detection for TB
2021

Triage of Persons With Tuberculosis Symptoms Using Artificial Intelligence–Based Chest Radiograph Interpretation: A Cost-Effectiveness Analysis

Early TB case detection by community-based mobile X-ray screening and Xpert testing in Balochistan
2021

Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis
2021

Use of targeted mobile X-ray screening and computer-aided detection software to identify tuberculosis among high-risk groups in Romania: descriptive results of the E-DETECT TB active case-finding project
2021

Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa
2021

Identifying barriers and facilitators to implementation of community-based tuberculosis active case finding with mobile X-ray units in Lima, Peru: a RE-AIM evaluation
2021

Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis

Costs and cost-effectiveness of a comprehensive tuberculosis case finding strategy in Zambia
2021

Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms

Chest X-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: an individual patient data meta-analysis of diagnostic accuracy

Can artificial intelligence (AI) be used to accurately detect tuberculosis (TB) from chest X-rays? An evaluation of five AI products for TB screening and triaging in a high TB burden setting

Application of artificial intelligence in digital chest radiography reading for pulmonary tuberculosis screening

A new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers
2021
2020

Automated chest radiography and mass systematic screening for tuberculosis

Evaluation of computer aided detection of tuberculosis on chest radiography among people with diabetes in Karachi Pakistan

Computer Aided Detection of Tuberculosis on Chest Radiographs: An Evaluation of the CAD4TB v6 system

Symptom and Digital Chest X-ray TB Screening in South African Prisons: Yield and Cost Effectiveness

A Public-Private Model to Scale Up Diabetes Mellitus Screening Among People Accessing Tuberculosis Diagnostics in Dhaka, Bangladesh

Yield, Efficiency and Costs of Mass Screening Algorithms for Tuberculosis in Brazilian Prisons

Deep learning, Computer-Aided Radiography Reading for Tuberculosis: a Diagnostic Accuracy Study from a Tertiary Hospital in India

Chest X-ray Analysis with Deep Learning-Based Software as a Triage Test for Pulmonary Tuberculosis: a Prospective Study of Diagnostic Accuracy for Culture-Confirmed Disease

Can Artificial Intelligence Be Used to Accurately Detect Tuberculosis (TB) from Chest X-ray? A Multi-Platform Evaluation of Five AI Products Used for TB Screening in a High-Burden setting
2020
2019

Prevalence of Tuberculosis, HIV/AIDS, and Hepatitis; in a Prison of Balochistan: a Cross-Sectional Survey
2019

Automated Chest X-ray Reading for Tuberculosis in the Philippines to Improve Case Detection: a Cohort Study

Using Artificial Intelligence to Read Chest Radiographs for Tuberculosis Detection: A Multi-Site Evaluation of the Diagnostic Accuracy of Three Deep Learning Systems

A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest X-rays for pulmonary tuberculosis
2019
2018

Computer-Assisted Chest Radiography Reading for Tuberculosis Screening in People Living with Diabetes Mellitus

Evaluation of the Diagnostic Accuracy of Computer-Aided Detection of Tuberculosis on Chest Radiography Among Private Sector Patients in Pakistan

Accuracy of an Automated System for Tuberculosis Detection on Chest Radiographs in High-risk Screening
2017

Computer-Aided Reading of Tuberculosis Chest Radiography: Moving the Research Agenda Forward to Inform Policy

Automatic Versus Human Reading of Chest X-rays in the Zambia National Tuberculosis Prevalence Survey

Digital CXR with Computer-Aided Diagnosis Versus Symptom Screen to Define Presumptive Tuberculosis Among Households Contacts and Impact on Tuberculosis Diagnosis

An Evaluation of Automated Chest Radiography Reading Software for Tuberculosis Screening Among Public- and Private-sector Patients

Fast and Effective Quantification of Symmetry in Medical Images for Pathology Detection: Application to Chest Radiography
2017
2016

An Automated Tuberculosis Screening Strategy Combining X-ray Based Computer-Aided Detection and Clinical Information

Computer-Aided Detection of Pulmonary Tuberculosis on Digital Chest Radiographs: a Systematic Review
2015

Screening for Pulmonary Tuberculosis in a Tanzanian Prison and Computer-Aided Interpretation of Chest X-rays
2015

Automated Chest-radiography as a Triage for Xpert Testing in Resource-Constrained Settings: a Prospective Study of Diagnostic Accuracy and Costs

Computerized Reading of Chest Radiographs in The Gambia National Tuberculosis Prevalence Survey: Retrospective Comparison with Human Experts

Objective Computerized Chest Radiography Screening to Detect Tuberculosis in the Philippines

On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis

Localized energy-based normalization of medical images: application to chest radiography

Automatic Detection of Tuberculosis in Chest Radiographs Using a Combination of Textural, Focal, and Shape Abnormality Analysis
2014

Diagnostic Accuracy of Computer-Aided Detection of Pulmonary Tuberculosis in Chest Radiographs: A Validation Study from Sub-Saharan Africa
2014

The Sensitivity and Specificity of Using a Computer Aided Diagnosis Program for Automatically Scoring Chest X-Rays of Presumptive TB Patients Compared with Xpert MTB/RIF in Lusaka Zambia
2014

Detection of Chest X-ray abnormalities and tuberculosis using computer-aided detection vs interpretation by radiologists and a clinical officer

A Novel Multiple-Instance Learning-Based Approach to Computer-Aided Detection of Tuberculosis on Chest X-Rays

Cavity Contour Segmentation in Chest Radiographs Using Supervised Learning and Dynamic Programming
2014
2013

Detection of Tuberculosis Using Digital Chest Radiography: Automated Reading vs. Interpretation by Clinical Officers

Suppression of Translucent Elongated Structures: Applications in Chest Radiography

Foreign Object Detection and Removal to Improve Automated Analysis of Chest Radiographs
2013

Automated Localization of Costophrenic Recesses and Costophrenic Angle Measurement on Frontal Chest Radiographs

Improved Texture Analysis for Automatic Detection of Tuberculosis (TB) on Chest Radiographs with Bone Suppression Images
2012
2010

Fusion of local and global detection systems to detect tuberculosis in chest radiographs

Rib Suppression in Chest Radiographs to Improve Classification of Textural Abnormalities
2009

Dissimilarity-based Classification in the Absence of Local Ground Truth: Application to the Diagnostic Interpretation of Chest Radiographs
2009
2007

Computer-aided detection of interstitial abnormalities in chest radiographs using a reference standard based on computed tomography
2007
2006

Segmentation of Anatomical Structures in Chest Radiographs Using Supervised Methods: a Comparative Study on a Public Database
2002

Automatic Detection of Abnormalities in Chest Radiographs Using Local Texture Analysis
Read other publications