A deep learning approach for the classification of TB from NIH CXR dataset-Reference-Cited by-同舟云学术

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A deep learning approach for the classification of TB from NIH CXR dataset

Published:2021-11-30 Issue:3 Volume:16 Page:787-796
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Zaidi S. Zainab Yousuf¹^ORCID,Akram M. Usman²,Jameel Amina³,Alghamdi Norah Saleh⁴

Affiliation:

1. Department of Computer Science Bahria University Islamabad Pakistan

2. Department of Computer and Software Engineering National University of Sciences and Technology (NUST) Islamabad Pakistan

3. Department of Software Engineering Bahria University Karachi Pakistan

4. College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh KSA

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12385

Reference39 articles.

1. Radiological aspects in computed tomography as determinants in the diagnosis of pulmonary tuberculosis in immunocompetent infants

2. Fractional crow search‐based support vector neural network for patient classification and severity analysis of tuberculosis

3. Yang A. Jin X. Li L.:Ct images recognition of pulmonary tuberculosis based on improved faster rcnn and u‐net. In:2019 10th International Conference on Information Technology in Medicine and Education (ITME) pp.93–97.IEEE Piscataway NJ(2019)

4. Automatic Tuberculosis Screening Using Chest Radiographs

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