Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system
Keelin Murphy, Shifa Salman Habib, Syed Mohammad Asad Zaidi, Saira, Khowaja, Aamir Khan, Jaime Melendez, Ernst T. Scholten, Farhan Amad, Steven, Schalekamp, Maurits Verhagen, Rick H. H. M. Philipsen, Annet Meijers, Bram, van Ginneken

TL;DR
This study evaluates the latest CAD4TB v6 system for automated tuberculosis detection on chest X-rays, demonstrating improved accuracy, efficiency, and cost-effectiveness over previous versions and expert assessments.
Contribution
The paper provides a comprehensive independent evaluation of CAD4TB v6, showing its superior performance and cost efficiency in TB screening compared to earlier versions and human experts.
Findings
CAD4TB v6 outperforms previous versions in ROC AUC.
Achieves 76% specificity at 90% sensitivity against Xpert.
Processes more subjects per day at lower cost than earlier versions.
Abstract
There is a growing interest in the automated analysis of chest X-Ray (CXR) as a sensitive and inexpensive means of screening susceptible populations for pulmonary tuberculosis. In this work we evaluate the latest version of CAD4TB, a commercial software platform designed for this purpose. Version 6 of CAD4TB was released in 2018 and is here tested on a fully independent dataset of 5565 CXR images with GeneXpert (Xpert) sputum test results available (854 Xpert positive subjects). A subset of 500 subjects (50% Xpert positive) was reviewed and annotated by 5 expert observers independently to obtain a radiological reference standard. The latest version of CAD4TB is found to outperform all previous versions in terms of area under receiver operating curve (ROC) with respect to both Xpert and radiological reference standards. Improvements with respect to Xpert are most apparent at high…
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