A new algorithm for automatic assessment of the degree of TB-infection using images of ZN-stained sputum smear

Author:

Nayak Rohit,Shenoy Vishnu Prasad,Galigekere Ramesh R.

Publisher

IEEE

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automated Methods for Tuberculosis Detection/Diagnosis: A Literature Review;BioMedInformatics;2023-09-01

2. Automatic and Comprehensive Classification of the Morphological Forms of C. albicans;2023 International Conference on Inventive Computation Technologies (ICICT);2023-04-26

3. Identification of Tuberculosis Bacilli from Bright Field Microscopic Sputum Smear Images using U-Net and Random Forest Classification Algorithm;2023 International Conference on Advances in Intelligent Computing and Applications (AICAPS);2023-02-01

4. Principles of Respiratory Diseases - Tuberculosis a Brief Study;Intelligent Diagnosis of Lung Cancer and Respiratory Diseases;2022-07-13

5. Computational techniques for the automated detection of mycobacterium tuberculosis from digitized sputum smear microscopic images: A systematic review;Progress in Biophysics and Molecular Biology;2022-07

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