{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T01:06:16Z","timestamp":1781658376787,"version":"3.54.5"},"reference-count":46,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,10,6]],"date-time":"2022-10-06T00:00:00Z","timestamp":1665014400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2020R1G1A1099559"],"award-info":[{"award-number":["2020R1G1A1099559"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2022,10,6]]},"abstract":"<jats:p>Lung abnormality in humans is steadily increasing due to various causes, and early recognition and treatment are extensively suggested. Tuberculosis (TB) is one of the lung diseases, and due to its occurrence rate and harshness, the World Health Organization (WHO) lists TB among the top ten diseases which lead to death. The clinical level detection of TB is usually performed using bio-medical imaging methods, and a chest X-ray is a commonly adopted imaging modality. This work aims to develop an automated procedure to detect TB from X-ray images using VGG-UNet-supported joint segmentation and classification. The various phases of the proposed scheme involved; (i) image collection and resizing, (ii) deep-features mining, (iii) segmentation of lung section, (iv) local-binary-pattern (LBP) generation and feature extraction, (v) optimal feature selection using spotted hyena algorithm (SHA), (vi) serial feature concatenation, and (vii) classification and validation. This research considered 3000 test images (1500 healthy and 1500\u2009TB class) for the assessment, and the proposed experiment is implemented using Matlab\u00ae. This work implements the pretrained models to detect TB in X-rays with improved accuracy, and this research helped achieve a classification accuracy of &gt;99% with a fine-tree classifier.<\/jats:p>","DOI":"10.1155\/2022\/9263379","type":"journal-article","created":{"date-parts":[[2022,10,6]],"date-time":"2022-10-06T22:50:12Z","timestamp":1665096612000},"page":"1-12","source":"Crossref","is-referenced-by-count":14,"title":["Tuberculosis Detection in Chest Radiographs Using Spotted Hyena Algorithm Optimized Deep and Handcrafted Features"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1939-4842","authenticated-orcid":true,"given":"Seifedine","family":"Kadry","sequence":"first","affiliation":[{"name":"Department of Applied Data Science, Noroff University College, Kristinasand 4612, Norway"},{"name":"Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon"},{"name":"Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9851-4103","authenticated-orcid":true,"given":"Gautam","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Brandon University, Brandon, R7A 6A9, Canada"},{"name":"Research Center for Interneural Computing, China Medical University, Taichung 40402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3897-4460","authenticated-orcid":true,"given":"Venkatesan","family":"Rajinikanth","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1936-6785","authenticated-orcid":true,"given":"Seungmin","family":"Rho","sequence":"additional","affiliation":[{"name":"Department of Industrial Security, Chung-Ang University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8243-0981","authenticated-orcid":true,"given":"Yongsung","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Technology Education, Chungnam National University, Daejeon, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.564"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.3390\/app10020559"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics11081395"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.5755\/j01.itc.50.2.28087"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8894694"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/9269173"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-020-00950-0"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-02149-6"},{"key":"9"},{"key":"10","volume-title":"Global tuberculosis report","author":"G. 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