Computational techniques for the automated detection of mycobacterium tuberculosis from digitized sputum smear microscopic images: A systematic review

Author:

Kotei EvansORCID,Thirunavukarasu RamkumarORCID

Publisher

Elsevier BV

Subject

Molecular Biology,Biophysics

Reference76 articles.

1. Combining deep convolutional neural network with support vector machine to classify microscopic bacteria images;Ahmed,2019

2. Application of a convolutional neural network using transfer learning for tuberculosis detection;Ahsan,2019

3. Lung pattern classification for interstitial lung diseases using a deep convolutional neural network;Anthimopoulos;IEEE Trans. Med. Imag.,2016

4. Random forest-based tuberculosis bacteria classification in images of ZN-stained sputum smear samples;Ayas;Signal, Image Video Process.,2014

5. Detection of tuberculosis patterns in digital photographs of chest X-ray images using deep learning: feasibility study;Becker;Int. J. Tubercul. Lung Dis.,2018

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