A Comprehensive Review on Advancement in Deep Learning Techniques for Automatic Detection of Tuberculosis from Chest X-ray Images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11831-023-09987-w.pdf
Reference91 articles.
1. World Health Organization (2020) Global tuberculosis report. Geneva
2. Dinesh Jackson Samuel R, Rajesh Kanna B (2019) Tuberculosis (TB) detection system using deep neural networks. Neural Comput Appl 31:1533–1545. https://doi.org/10.1007/s00521-018-3564-4
3. World Health Organization (2021) Global tuberculosis report
4. Ryu YJ (2015) Diagnosis of pulmonary tuberculosis: recent advances and diagnostic algorithms. Tuberc Respir Dis (Seoul) 78(2):64–71. https://doi.org/10.4046/trd.2015.78.2.64
5. Lo CM, Wu YH, Li YC, Lee CC (2020) Computer-aided bacillus detection in whole-slide pathological images using a deep convolutional neural network. Appl Sci. https://doi.org/10.3390/APP10124059
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