{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T14:51:12Z","timestamp":1773327072504,"version":"3.50.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2018,6,6]],"date-time":"2018-06-06T00:00:00Z","timestamp":1528243200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["60973059; 81171407"],"award-info":[{"award-number":["60973059; 81171407"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004602","name":"Program for New Century Excellent Talents in University","doi-asserted-by":"publisher","award":["NCET-10-0044"],"award-info":[{"award-number":["NCET-10-0044"]}],"id":[{"id":"10.13039\/501100004602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1007\/s11517-018-1850-z","type":"journal-article","created":{"date-parts":[[2018,6,5]],"date-time":"2018-06-05T22:24:01Z","timestamp":1528237441000},"page":"2201-2212","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Automatic recognition of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNNs"],"prefix":"10.1007","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9043-722X","authenticated-orcid":false,"given":"Guanghui","family":"Han","sequence":"first","affiliation":[]},{"given":"Xiabi","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Guangyuan","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Murong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Shan","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,6,6]]},"reference":[{"issue":"3","key":"1850_CR1","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1148\/radiol.2203001701","volume":"220","author":"T Aoki","year":"2001","unstructured":"Aoki T, Tomoda Y, Watanabe H, Nakata H, Kasai T, Hashimoto H, Kodate M, Osaki T, Yasumoto K (2001) Peripheral lung adenocarcinoma: correlation of thin-section CT findings with histologic prognostic factors and survival. Radiology 220(3):803\u2013809","journal-title":"Radiology"},{"issue":"3","key":"1850_CR2","doi-asserted-by":"publisher","first-page":"739","DOI":"10.1148\/radiol.2323032035","volume":"232","author":"SG Armato III","year":"2004","unstructured":"Armato SG III, McLennan G, McNitt-Gray MF, Meyer CR, Yankelevitz D et al (2004) Lung image database consortium: developing a resource for the medical imaging research community 1. Radiology 232(3):739\u2013748","journal-title":"Radiology"},{"issue":"2","key":"1850_CR3","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1118\/1.3528204","volume":"38","author":"SG Armato III","year":"2011","unstructured":"Armato SG III, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR 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. Med Phys 38(2):915\u2013931","journal-title":"Med Phys"},{"issue":"5\u20136","key":"1850_CR4","first-page":"425","volume":"106","author":"G Battista","year":"2003","unstructured":"Battista G, Sassi C, Zompatori M, Palmarini D, Canini R (2003) Ground-glass opacity: interpretation of high resolution CT findings. Radiol Med 106(5\u20136):425\u2013442 quiz 443-424","journal-title":"Radiol Med"},{"key":"1850_CR5","doi-asserted-by":"publisher","first-page":"24454","DOI":"10.1038\/srep24454","volume":"6","author":"J-Z Cheng","year":"2016","unstructured":"Cheng J-Z, Ni D, Chou Y-H, Qin J, Tiu C-M, Chang YC, Huang CS, Shen D, Chen CM (2016) Computer-aided diagnosis with deep learning architecture: applications to breast lesions in US images and pulmonary nodules in CT scans. Sci Rep 6:24454","journal-title":"Sci Rep"},{"key":"1850_CR6","doi-asserted-by":"publisher","first-page":"27755","DOI":"10.1038\/srep27755","volume":"6","author":"RM Cichy","year":"2016","unstructured":"Cichy RM, Khosla A, Pantazis D, Torralba A, Oliva A (2016) Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence. Sci Rep 6:27755","journal-title":"Sci Rep"},{"issue":"1","key":"1850_CR7","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.media.2015.08.001","volume":"26","author":"F Ciompi","year":"2015","unstructured":"Ciompi F, de Hoop B, van Riel SJ, Chung K, Scholten ET, Oudkerk M, de Jong PA, Prokop M, Ginneken B (2015) Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box. Med Image Anal 26(1):195\u2013202","journal-title":"Med Image Anal"},{"issue":"7","key":"1850_CR8","doi-asserted-by":"publisher","first-page":"1470","DOI":"10.1109\/TMI.2017.2673121","volume":"36","author":"BD Vos de","year":"2017","unstructured":"de Vos BD, Wolterink JM, de Jong PA, Leiner T, Viergever MA, Isgum I (2017) ConvNet-based localization of anatomical structures in 3-D medical images. IEEE Trans Med Imaging 36(7):1470\u20131481","journal-title":"IEEE Trans Med Imaging"},{"issue":"7","key":"1850_CR9","doi-asserted-by":"publisher","first-page":"1558","DOI":"10.1109\/TBME.2016.2613502","volume":"64","author":"Q Dou","year":"2016","unstructured":"Dou Q, Chen H, Yu L, Qin J, Heng PA (2016) Multi-level contextual 3D CNNs for false positive reduction in pulmonary nodule detection. IEEE Trans Biomed Eng 64(7):1558\u20131567","journal-title":"IEEE Trans Biomed Eng"},{"key":"1850_CR10","unstructured":"Frangi A.F. (2001) Three-dimensional model-based analysis of vascular and cardiac images"},{"key":"1850_CR11","doi-asserted-by":"crossref","unstructured":"Frangi AF, Niessen WJ, Vincken KL, Viergever MA (1998) Multiscale vessel enhancement filtering. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, pp 130\u2013137","DOI":"10.1007\/BFb0056195"},{"key":"1850_CR12","first-page":"3842659","volume":"2017","author":"G Han","year":"2017","unstructured":"Han G, Liu X, Soomro NQ, sun J, Zhao Y et al (2017) Empirical driven automatic detection of lobulation imaging signs in lung CT. BioMed Res Int 2017:3842659 15 pages","journal-title":"BioMed Res Int"},{"issue":"3","key":"1850_CR13","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1148\/radiol.2462070712","volume":"246","author":"DM Hansell","year":"2008","unstructured":"Hansell DM, Bankier AA, MacMahon H, McLoud TC, M\u00fcller NL, Remy J (2008) Fleischner society: glossary of terms for thoracic imaging. Radiology 246(3):697\u2013722","journal-title":"Radiology"},{"issue":"4465","key":"1850_CR14","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1126\/science.6997993","volume":"210","author":"G Hounsfield","year":"1980","unstructured":"Hounsfield G (1980) Computed medical imaging. Science 210(4465):22\u201328","journal-title":"Science"},{"key":"1850_CR15","unstructured":"Krizhevsky A (2009) Learning multiple layers of features from tiny images. Toronto, Canada: Toronto"},{"issue":"1","key":"1850_CR16","doi-asserted-by":"publisher","first-page":"20","DOI":"10.2174\/1573405612666160606104405","volume":"13","author":"L Linying","year":"2017","unstructured":"Linying L, Xiabi L, Chunwu Z, Xinming Z, Yanfeng Z (2017) A review of ground glass opacity detection methods in lung CT images. Current Medical Imaging Reviews 13(1):20\u201331","journal-title":"Current Medical Imaging Reviews"},{"key":"1850_CR17","doi-asserted-by":"crossref","unstructured":"Manniesing R, Niessen W (2005) Multiscale vessel enhancing diffusion in CT angiography noise filtering. In: Biennial International Conference on Information Processing in Medical Imaging. Springer, pp 138\u2013149","DOI":"10.1007\/11505730_12"},{"issue":"1","key":"1850_CR18","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"9","author":"N Otsu","year":"1979","unstructured":"Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics 9(1):62\u201366","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics"},{"issue":"10","key":"1850_CR19","doi-asserted-by":"publisher","first-page":"5642","DOI":"10.1118\/1.4929562","volume":"42","author":"AA Setio","year":"2015","unstructured":"Setio AA, Jacobs C, Gelderblom J, van Ginneken B (2015) Automatic detection of large pulmonary solid nodules in thoracic CT images. Med Phys 42(10):5642\u20135653","journal-title":"Med Phys"},{"issue":"5","key":"1850_CR20","doi-asserted-by":"publisher","first-page":"1160","DOI":"10.1109\/TMI.2016.2536809","volume":"35","author":"AAA Setio","year":"2016","unstructured":"Setio AAA, Ciompi F, Litjens G, Gerke P, Jacobs C, van Riel SJ, Wille MMW, Naqibullah M, Sanchez CI, van Ginneken B (2016) Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks. IEEE Trans Med Imaging 35(5):1160\u20131169","journal-title":"IEEE Trans Med Imaging"},{"key":"1850_CR21","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.1109\/TMI.2016.2528162","volume":"35","author":"H-C Shin","year":"2016","unstructured":"Shin H-C, Roth HR, Gao M, Lu L, Xu Z et al (2016) Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning. IEEE Trans Med Imaging 35:1285\u20131298","journal-title":"IEEE Trans Med Imaging"},{"issue":"4","key":"1850_CR22","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1109\/TMI.2013.2241448","volume":"32","author":"Y Song","year":"2013","unstructured":"Song Y, Cai W, Zhou Y, Feng DD (2013) Feature-based image patch approximation for lung tissue classification. IEEE Trans Med Imaging 32(4):797\u2013808","journal-title":"IEEE Trans Med Imaging"},{"issue":"6","key":"1850_CR23","doi-asserted-by":"publisher","first-page":"1362","DOI":"10.1109\/TMI.2015.2393954","volume":"34","author":"Y Song","year":"2015","unstructured":"Song Y, Cai W, Huang H, Zhou Y, Feng DD, Wang Y, Fulham MJ, Chen M (2015) Large margin local estimate with applications to medical image classification. IEEE Trans Med Imaging 34(6):1362\u20131377","journal-title":"IEEE Trans Med Imaging"},{"key":"1850_CR24","unstructured":"Sun W, Zheng B, Qian W (2016) Computer aided lung cancer diagnosis with deep learning algorithms. Medical Imaging 2016, pp. 97850Z-97850Z-97858"},{"issue":"5","key":"1850_CR25","doi-asserted-by":"publisher","first-page":"1299","DOI":"10.1109\/TMI.2016.2535302","volume":"35","author":"N Tajbakhsh","year":"2016","unstructured":"Tajbakhsh N, Shin JY, Gurudu SR, Hurst RT, Kendall CB, Gotway MB, Liang J (2016) Convolutional neural networks for medical image analysis: full training or fine tuning? IEEE Trans Med Imaging 35(5):1299\u20131312","journal-title":"IEEE Trans Med Imaging"},{"key":"1850_CR26","unstructured":"Wood DE, Leard LE, Reddy C, Kazerooni E, Leung ANC et al (2014) NCCN clinical practice guidelines in oncology: lung cancer screening (Version 2.2014). J Natl Compr Cancer Netw"},{"issue":"6","key":"1850_CR27","doi-asserted-by":"publisher","first-page":"1399","DOI":"10.2214\/ajr.176.6.1761399","volume":"176","author":"Z-G Yang","year":"2001","unstructured":"Yang Z-G, Sone S, Takashima S, Li F, Honda T, Maruyama Y, Hasegawa M, Kawakami S (2001) High-resolution CT analysis of small peripheral lung adenocarcinomas revealed on screening helical CT. Am J Roentgenol 176(6):1399\u20131407","journal-title":"Am J Roentgenol"}],"container-title":["Medical & Biological Engineering & Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11517-018-1850-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-018-1850-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-018-1850-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,5]],"date-time":"2019-06-05T19:21:01Z","timestamp":1559762461000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11517-018-1850-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6,6]]},"references-count":27,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2018,12]]}},"alternative-id":["1850"],"URL":"https:\/\/doi.org\/10.1007\/s11517-018-1850-z","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,6,6]]},"assertion":[{"value":"4 October 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 May 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 June 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}