A Survey Paper on Computer Aided Detection of Tuberculosis

Zuber Khan; Tanisha Jain; Ariba Ansari; Ravi Kumar Arya

doi:10.35877/454RI.jinav917

Authors

Zuber Khan Department of Electronics and Communication Engineering, IIIT Delhi, 110020, India https://orcid.org/0000-0001-9683-2685
Tanisha Jain Department of Electronics and Communication Engineering, IIIT Delhi, 110020, India
Ariba Ansari Department of Computational Biology, IIIT Delhi, 110020, India
Ravi Kumar Arya School of Engineering, JNU, Delhi, 110067, India

DOI:

https://doi.org/10.35877/454RI.jinav917

Keywords:

Tuberculosis, Transfer Learning, Deep Convolution Neural Network, Ensemble Learning

Abstract

Tuberculosis (TB) is a disease that claims millions of lives each year, primarily in impoverished places. Traditional TB screening procedures may not only take longer time, but may also be infeasible in areas with inadequate healthcare infrastructure. Artificial intelligence developments have propelled computer-aided diagnostic systems to new heights. The identification of TB using computer-aided approaches offers various benefits and has the potential to be superior to traditional diagnostic procedures, particularly in poor and middle-income countries where medical specialists and machinery are few. This survey article intends to describe the scientific effort done in computer assisted detection of TB and provides light on future research opportunities.

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