Abstract:
Pulmonary tuberculosis is a worldwide epidemic that can only be fought effectively with early and accurate diagnosis
and proper disease management. The means of diagnosis and disease management should be easily accessible, cost
effective and be readily available in the high tuberculosis burdened countries where it is most needed. Fortunately, the
fast development of computer science in recent years has ensured that medical images can accurately be quantified.
Radiomics is one such tool that can be used to quantify medical images. This review article focuses on the literature
currently available on the application of radiomics explicitly for the purpose of diagnosis, differentiation from other
pulmonary diseases and disease management of pulmonary tuberculosis. Despite using a formal search strategy, only five
articles could be found on the application of radiomics to pulmonary tuberculosis. In all five articles reviewed, radiomic
feature extraction was successfully used to quantify digital medical images for the purpose of comparing, or
differentiating, pulmonary tuberculosis from other pulmonary diseases. This demonstrates that the use of radiomics for
the purpose of tuberculosis disease management and diagnosis remains a valuable data mining opportunity not yet
realised.
