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Here, an automatic algorithm for segmenting lungs from thoracic CT images accurately is presented. This scheme consists of three principal steps: image preprocessing, lung extracting and contour correcting. To cope with inhomogeneous intensities of CT images, a novel preprocessing approach based on empirical mode decomposition and bilateral filter is proposed, which has abilities of denoising, smoothing and edge keeping. Lung region is then extracted with a novel gray correlation\u2010based clustering approach. A new lung contour correction technology is finally employed to repair the concave regions caused by pulmonary nodules, vessels and so on. Experimental results show that the preprocessing approach outperforms other methods on image denoising and smoothing. Meanwhile, the lung segmentation algorithm is tested on a group of lung CT images affected with interstitial lung diseases and achieves a high segmentation accuracy. Compared with several existing lung segmentation methods, this algorithm exhibits a better performance on lung\u00a0segmentation.<\/jats:p>","DOI":"10.1049\/ipr2.12744","type":"journal-article","created":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T04:26:39Z","timestamp":1674620799000},"page":"1658-1667","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Segmenting lung parenchyma from CT images with gray correlation\u2010based clustering"],"prefix":"10.1049","volume":"17","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-1941-0248","authenticated-orcid":false,"given":"Caixia","family":"Liu","sequence":"first","affiliation":[{"name":"College of Intelligent Education Jiangsu Normal University Xuzhou China"},{"name":"Jiangsu Engineering Research Center of Educational Informationization Jiangsu Normal University Xuzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanli","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Communication Qufu Normal University Rizhao China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruibin","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Intelligent Education Jiangsu Normal University Xuzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingyong","family":"Pang","sequence":"additional","affiliation":[{"name":"Institute of EduInfo Science &amp; Engineering Nanjing Normal Univeristy Nanjing China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"265","published-online":{"date-parts":[[2023,1,25]]},"reference":[{"key":"e_1_2_11_2_1","volume-title":"Clinical atlas of interstitial lung disease","author":"Pero\u0161\u2010Golubi\u010di\u0107 T.","year":"2006"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/occmed\/kqt082"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1117\/12.381681"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.2003.1123"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2014.07.007"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2004.06.005"},{"key":"e_1_2_11_8_1","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1016\/j.jksuci.2018.07.005","article-title":"Automatic lung segmentation for the inclusion of juxtapleural nodules and pulmonary vessels using curvature based border correction","volume":"33","author":"Singadkar G.","year":"2018","journal-title":"J. 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