{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:27:47Z","timestamp":1740122867552,"version":"3.37.3"},"reference-count":18,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:00:00Z","timestamp":1661904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:00:00Z","timestamp":1661904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Department of Science and Technology, Ministry of Science and Technology","award":["SR\/WOS-A\/ET-153\/2017"],"award-info":[{"award-number":["SR\/WOS-A\/ET-153\/2017"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1007\/s11042-022-13660-y","type":"journal-article","created":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T04:04:35Z","timestamp":1661918675000},"page":"10421-10443","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Border to border distance based lung parenchyma segmentation including juxta-pleural nodules"],"prefix":"10.1007","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2017-3067","authenticated-orcid":false,"given":"R. Jenkin","family":"Suji","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"W. Wilfred","family":"Godfrey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joydip","family":"Dhar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,31]]},"reference":[{"issue":"2","key":"13660_CR1","first-page":"82","volume":"16","author":"J Amin","year":"2016","unstructured":"Amin J, Sharif M, Yasmin M (2016) Segmentation and classification of lung cancer: a review. Immunol Endoc Metabol Agents Med Chemist (Formerly Current Med Chemist-Immunol Endoc Metabolic Agents) 16(2):82\u201399","journal-title":"Immunol Endoc Metabol Agents Med Chemist (Formerly Current Med Chemist-Immunol Endoc Metabolic Agents)"},{"issue":"2","key":"13660_CR2","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1118\/1.3528204","volume":"38","author":"III Armato","year":"2011","unstructured":"Armato III, Samuel G, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR, Reeves AP, Zhao B, Aberle DR, Henschke CI, Hoffman EA et al (2011) The lung image database consortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans. Medical Phys 38(2):915\u2013931","journal-title":"Medical Phys"},{"issue":"9","key":"13660_CR3","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1016\/j.acra.2004.06.005","volume":"11","author":"III Armato","year":"2004","unstructured":"Armato III, Samuel G, Nsakovic WF (2004) Automated lung segmentation for thoracic ct: impact on computer-aided diagnosis1. Acad Radiology 11 (9):1011\u20131021","journal-title":"Acad Radiology"},{"key":"13660_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JTEHM.2018.2837901","volume":"6","author":"H Chung","year":"2018","unstructured":"Chung H, Ko H, Jeon SJ, Yoon KH, Lee J (2018) Automatic lung segmentation with juxta-pleural nodule identification using active contour model and bayesian approach. IEEE J Trans Eng Health Med 6:1\u201313","journal-title":"IEEE J Trans Eng Health Med"},{"key":"13660_CR5","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.cmpb.2016.07.031","volume":"135","author":"M Javaid","year":"2016","unstructured":"Javaid M, Javid M, Rehman MZU, Shah SIA (2016) A novel approach to cad system for the detection of lung nodules in ct images. Comput Methods Prog Biomed 135:125\u2013139","journal-title":"Comput Methods Prog Biomed"},{"key":"13660_CR6","doi-asserted-by":"publisher","first-page":"102032","DOI":"10.1016\/j.bspc.2020.102032","volume":"61","author":"C Liu","year":"2020","unstructured":"Liu C, Pang M (2020) Automatic lung segmentation based on image decomposition and wavelet transform. Biomed Signal Process Control 61:102032","journal-title":"Biomed Signal Process Control"},{"issue":"1","key":"13660_CR7","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1007\/s10278-015-9801-9","volume":"29","author":"S Mukhopadhyay","year":"2016","unstructured":"Mukhopadhyay S (2016) A segmentation framework of pulmonary nodules in lung ct images. J Digital Imaging 29(1):86\u2013103","journal-title":"J Digital Imaging"},{"key":"13660_CR8","doi-asserted-by":"crossref","unstructured":"Nurfauzi R, Nugroho HA, Ardiyanto I (2017) Lung detection using adaptive border correction. In: 2017 3rd International conference on science and technology-computer (ICST). IEEE, pp 57\u201360","DOI":"10.1109\/ICSTC.2017.8011852"},{"issue":"5","key":"13660_CR9","first-page":"518","volume":"33","author":"R Nurfauzi","year":"2021","unstructured":"Nurfauzi R, Nugroho H, Ardiyanto I, Frannita E (2021) Autocorrection of lung boundary on 3d ct lung cancer images. J King Saud University-Comput Inf Sci 33(5):518\u2013527","journal-title":"J King Saud University-Comput Inf Sci"},{"issue":"6","key":"13660_CR10","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1016\/j.compmedimag.2008.04.005","volume":"32","author":"J Pu","year":"2008","unstructured":"Pu J, Roos J, Chin AY, Napel S, Rubin GD, Paik DS (2008) Adaptive border marching algorithm: automatic lung segmentation on chest ct images. Comput Med Imaging Graph 32(6):452\u2013462","journal-title":"Comput Med Imaging Graph"},{"key":"13660_CR11","doi-asserted-by":"crossref","unstructured":"Rachmawati E, Khodra ML, Supriana I (2016) Shape based recognition using freeman chain code and modified needleman-wunsch. In: 2016 8th International conference on information technology and electrical engineering (ICITEE). IEEE, pp 1\u20136","DOI":"10.1109\/ICITEED.2016.7863307"},{"issue":"4","key":"13660_CR12","doi-asserted-by":"publisher","first-page":"1151","DOI":"10.1109\/JBHI.2020.3004296","volume":"25","author":"P Sahu","year":"2020","unstructured":"Sahu P, Zhao Y, Bhatia P, Bogoni L, Jerebko A, Qin H (2020) Structure correction for robust volume segmentation in presence of tumors. IEEE J Biomed Health Inf 25(4):1151\u20131162","journal-title":"IEEE J Biomed Health Inf"},{"key":"13660_CR13","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.compbiomed.2014.12.008","volume":"57","author":"S Shen","year":"2015","unstructured":"Shen S, Bui AA, Cong J, Hsu W (2015) An automated lung segmentation approach using bidirectional chain codes to improve nodule detection accuracy. Comput Biol Med 57:139\u2013149","journal-title":"Comput Biol Med"},{"issue":"8","key":"13660_CR14","first-page":"975","volume":"33","author":"G Singadkar","year":"2021","unstructured":"Singadkar G, Mahajan A, Thakur M, Talbar S (2021) Automatic lung segmentation for the inclusion of juxtapleural nodules and pulmonary vessels using curvature based border correction. J King Saud Univ-Comp Inf Sci 33 (8):975\u2013987","journal-title":"J King Saud Univ-Comp Inf Sci"},{"issue":"7","key":"13660_CR15","doi-asserted-by":"publisher","first-page":"2934","DOI":"10.1118\/1.3147146","volume":"36","author":"EM Van Rikxoort","year":"2009","unstructured":"Van Rikxoort EM, de Hoop B, Viergever MA, Prokop M, van Ginneken B (2009) Automatic lung segmentation from thoracic computed tomography scans using a hybrid approach with error detection. Med Phys 36(7):2934\u20132947","journal-title":"Med Phys"},{"issue":"3","key":"13660_CR16","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1007\/s10278-012-9528-9","volume":"26","author":"Y Wei","year":"2013","unstructured":"Wei Y, Shen G, Li JJ (2013) A fully automatic method for lung parenchyma segmentation and repairing. J Digital Imaging 26(3):483\u2013495","journal-title":"J Digital Imaging"},{"issue":"5","key":"13660_CR17","doi-asserted-by":"publisher","first-page":"832","DOI":"10.3390\/app8050832","volume":"8","author":"X Xiao","year":"2018","unstructured":"Xiao X, Zhao J, Qiang Y, Wang H, Xiao Y, Zhang X, Zhang Y (2018) An automated segmentation method for lung parenchyma image sequences based on fractal geometry and convex hull algorithm. Appl Sci 8(5):832","journal-title":"Appl Sci"},{"key":"13660_CR18","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.bspc.2014.03.010","volume":"13","author":"S Zhou","year":"2014","unstructured":"Zhou S, Cheng Y, Tamura S (2014) Automated lung segmentation and smoothing techniques for inclusion of juxtapleural nodules and pulmonary vessels on chest ct images. Biomed Signal Process Control 13:62\u201370","journal-title":"Biomed Signal Process Control"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13660-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-13660-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13660-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,2]],"date-time":"2023-03-02T16:27:29Z","timestamp":1677774449000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-13660-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,31]]},"references-count":18,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["13660"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-13660-y","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2022,8,31]]},"assertion":[{"value":"30 April 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 June 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 August 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 August 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All the authors declare that he\/she has no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}