Publications that evaluate CAD4TB
Please also see Diagnostic Image Analysis Group
- of Radboud University Medical Center. The group has its roots in computer-aided detection of breast cancer in mammograms, and expanded to automated detection and diagnosis in breast MRI, ultrasound and tomosynthesis, chest radiographs and chest CT, prostate MRI, neuro-imaging and the analysis of retinal and digital pathology images. The technology used is primarily deep learning
Actual overview of CAD publications as listed at:
"Economic analysis of different throughput scenarios and implementation strategies of computer-aided detection software as a screening and triage test for pulmonary TB".
The recent study in Pakistan (S. Bashir. et al) shows that CAD4TB is the most economical CAD software for offline deployment.
Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa
Comparing different versions of computer-aided detection products when reading chest X-rays for tuberculosis. CAD4TB v7 had a significantly higher AUC than v6, 0.903 (95% CI: 0.897–0.908) compared to 0.823 (0.816–0.830). CAD4TB v7 significantly improved on its predecessor’s specificity, outperforming human radiologists with specificity and meeting WHO TPP values.
Portable digital X-ray for TB pre-diagnosis screening in rural communities in Nigeria.
New article following up on the WHO’s recommendation on using AI-powered CAD software for TB screening & triage. The study compares CAD4TB ver. 6 and 7, and concludes that CAD4TB 7 significantly outperformed CAD4TB 6, performed better than human readers and met WHO TPP values. Additionally, CAD4TB 7 shows a steep initial increase of Xpert tests saving and suggests greater numbers of Xpert tests to be saved.
Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system.
Accuracy of an automated system for tuberculosis detection on chest radiographs in high-risk screening.
Automatic versus human reading of chest X-rays in the Zambia National Tuberculosis Prevalence Survey.
An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information.
Screening for pulmonary tuberculosis in a Tanzanian prison and computer-aided interpretation of chest X-rays.
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.
Diagnostic accuracy of computer-aided detection of pulmonary tuberculosis in chest radiographs: a validation study from sub-saharan Africa.
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.
Detection of Chest X-ray abnormalities and tuberculosis using computer-aided detection vs interpretation by radiologists and a clinical officer.
Computer-aided diagnosis of X-rays in a screening for pulmonary tuberculosis of a prison population in Tanzania.
Symptomatic screening and computer-aided radiography for active-case finding of tuberculosis: a prediction model for TB case detection.
Detection of tuberculosis with digital chest radiography: automatic reading versus interpretation by clinical officers.
Performance of inexperienced and experienced observers in detection of active tuberculosis on digital chest radiographs with and without the use of computer-aided diagnosis.
Computer-aided detection of tuberculosis among high risk groups: potential for automated triage.
Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms - ScienceDirect.
Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa | medRxiv.
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 (plos.org)
Evaluation of computer aided detection of tuberculosis on chest radiography among people with diabetes in Karachi Pakistan | Scientific Reports (nature.com)
Fast and effective quantification of symmetry in medical images for pathology detection: application to chest radiography.
Automatic detection of pleural effusion in chest radiographs.
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.
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.
Multiple-instance learning for computer-aided detection of tuberculosis.
Suppression of translucent elongated structures: applications in chest radiography.
Foreign object detection and removal to improve automated analysis of chest radiographs.
Automated Scoring of Chest Radiographs for Tuberculosis Prevalence Surveys: A Combined Approach.
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.
Clavicle segmentation in chest radiographs.
Fusion of local and global detection systems to detect tuberculosis in chest radiographs.
Rib suppression in chest radiographs to improve classification of textural abnormalities.
Dissimilarity-based classification in the absence of local ground truth: application to the diagnostic interpretation of chest radiographs.
Computer-aided detection of interstitial abnormalities in chest radiographs using a reference standard based on computed tomography.
Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database.
Automatic detection of abnormalities in chest radiographs using local texture analysis.