{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T15:02:59Z","timestamp":1764687779204,"version":"3.37.3"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2018,7,10]],"date-time":"2018-07-10T00:00:00Z","timestamp":1531180800000},"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":["81471759"],"award-info":[{"award-number":["81471759"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"published-print":{"date-parts":[[2018,10]]},"DOI":"10.1007\/s11548-018-1820-9","type":"journal-article","created":{"date-parts":[[2018,7,10]],"date-time":"2018-07-10T06:08:16Z","timestamp":1531202896000},"page":"1565-1578","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Robust extraction for low-contrast liver tumors using modified adaptive likelihood estimation"],"prefix":"10.1007","volume":"13","author":[{"given":"Qing","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaodong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangzhi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,7,10]]},"reference":[{"key":"1820_CR1","first-page":"7","volume":"68","author":"RL Siegel","year":"2017","unstructured":"Siegel RL, Miller KD, Jemal A (2017) Cancer statistics, 2018 CA: a cancer. J Clin 68:7\u201330","journal-title":"J Clin"},{"key":"1820_CR2","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1007\/s00464-009-0590-4","volume":"24","author":"N Bhardwaj","year":"2010","unstructured":"Bhardwaj N, Strickland AD, Ahmad F, Dennison AR, Lloyd DM (2010) Liver ablation techniques: a review. Surg Endosc 24:254\u2013265","journal-title":"Surg Endosc"},{"key":"1820_CR3","doi-asserted-by":"publisher","first-page":"1965","DOI":"10.1109\/TMI.2012.2211887","volume":"31","author":"MG Linguraru","year":"2012","unstructured":"Linguraru MG, Richbourg WJ, Liu J, Watt JM, Pamulapati V, Wang S, Summers RM (2012) Tumor burden analysis on computed tomography by automated liver and tumor segmentation. IEEE Trans Med Imaging 31:1965\u20131976","journal-title":"IEEE Trans Med Imaging"},{"key":"1820_CR4","unstructured":"LiTS Challenge (2017). https:\/\/competitions.codalab.org\/competitions\/17094"},{"key":"1820_CR5","doi-asserted-by":"crossref","unstructured":"Moltz JH, Bornemann L, Dicken V, Peitgen H-O (2008) Segmentation of liver metastases in CT scans by adaptive thresholding and morphological processing. In: MICCAI workshop, 2008, pp 195","DOI":"10.54294\/msg94u"},{"key":"1820_CR6","unstructured":"Wong D, Liu J, Fengshou Y, Tian Q, Xiong W, Zhou J, Qi Y, Han T, Venkatesh S, Wang S-C (2008) A semi-automated method for liver tumor segmentation based on 2D region growing with knowledge-based constraints. In: MICCAI workshop, 2008, pp 159"},{"key":"1820_CR7","doi-asserted-by":"crossref","unstructured":"Stawiaski J, Decenciere E, Bidault F (2008) Interactive liver tumor segmentation using graph-cuts and watershed. In: Workshop on 3D segmentation in the clinic: a grand challenge II. Liver tumor segmentation challenge. MICCAI, New York, USA, 2008","DOI":"10.54294\/5clvrb"},{"key":"1820_CR8","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.media.2009.09.002","volume":"14","author":"D Smeets","year":"2010","unstructured":"Smeets D, Loeckx D, Stijnen B, De Dobbelaer B, Vandermeulen D, Suetens P (2010) Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification. Med Image Anal 14:13\u201320","journal-title":"Med Image Anal"},{"key":"1820_CR9","doi-asserted-by":"publisher","first-page":"2967","DOI":"10.1109\/TBME.2013.2267212","volume":"60","author":"C Li","year":"2013","unstructured":"Li C, Wang X, Eberl S, Fulham M, Yin Y, Chen J, Feng DD (2013) A likelihood and local constraint level set model for liver tumor segmentation from CT volumes. IEEE Trans Biomed Eng 60:2967\u20132977","journal-title":"IEEE Trans Biomed Eng"},{"key":"1820_CR10","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.media.2017.01.002","volume":"37","author":"A Hoogi","year":"2017","unstructured":"Hoogi A, Beaulieu CF, Cunha GM, Heba E, Sirlin CB, Napel S, Rubin DL (2017) Adaptive local window for level set segmentation of CT and MRI liver lesions. Med Image Anal 37:46\u201355","journal-title":"Med Image Anal"},{"key":"1820_CR11","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1007\/s11554-016-0578-y","volume":"13","author":"F Chaieb","year":"2017","unstructured":"Chaieb F, Said TB, Mabrouk S, Ghorbel F (2017) Accelerated liver tumor segmentation in four-phase computed tomography images. J Real-Time Image Process 13:121\u2013133","journal-title":"J Real-Time Image Process"},{"key":"1820_CR12","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.media.2011.06.006","volume":"16","author":"Y H\u00e4me","year":"2012","unstructured":"H\u00e4me Y, Pollari M (2012) Semi-automatic liver tumor segmentation with hidden Markov measure field model and non-parametric distribution estimation. Med Image Anal 16:140\u2013149","journal-title":"Med Image Anal"},{"key":"1820_CR13","doi-asserted-by":"publisher","first-page":"737","DOI":"10.1007\/s11548-011-0562-8","volume":"6","author":"M Schwier","year":"2011","unstructured":"Schwier M, Moltz JH, Peitgen H-O (2011) Object-based analysis of CT images for automatic detection and segmentation of hypodense liver lesions. Int J Comput Assist Radiol Surg 6:737","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"1820_CR14","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1148\/radiol.2262012198","volume":"226","author":"T Livraghi","year":"2003","unstructured":"Livraghi T, Solbiati L, Meloni MF, Gazelle GS, Halpern EF, Goldberg SN (2003) Treatment of focal liver tumors with percutaneous radio-frequency ablation: complications encountered in a multicenter study. Radiology 226:441\u2013451","journal-title":"Radiology"},{"key":"1820_CR15","doi-asserted-by":"crossref","unstructured":"Abdel-massieh NH, Hadhoud MM, Amin KM (2010) A novel fully automatic technique for liver tumor segmentation from CT scans with knowledge-based constraints. In: 2010 10th International conference on intelligent systems design and applications, 2010, pp 1253\u20131258","DOI":"10.1109\/ISDA.2010.5687080"},{"key":"1820_CR16","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1109\/83.661190","volume":"7","author":"J Weickert","year":"1998","unstructured":"Weickert J, Romeny BMTH, Viergever MA (1998) Efficient and reliable schemes for nonlinear diffusion filtering. IEEE Trans Image Process 7:398\u2013410","journal-title":"IEEE Trans Image Process"},{"key":"1820_CR17","doi-asserted-by":"publisher","first-page":"655","DOI":"10.1109\/TPAMI.1981.4767166","volume":"3","author":"PM Narendra","year":"1981","unstructured":"Narendra PM, Fitch RC (1981) Real-time adaptive contrast enhancement. IEEE Trans Pattern Anal Mach Intell 3:655\u2013661","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1820_CR18","doi-asserted-by":"publisher","first-page":"2787","DOI":"10.1109\/TIP.2007.908073","volume":"16","author":"O Michailovich","year":"2007","unstructured":"Michailovich O, Rathi Y, Tannenbaum A (2007) Image segmentation using active contours driven by the Bhattacharyya gradient flow. IEEE Trans Image Process 16:2787\u20132801","journal-title":"IEEE Trans Image Process"},{"key":"1820_CR19","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.1109\/TMI.2009.2013851","volume":"28","author":"T Heimann","year":"2009","unstructured":"Heimann T, Van Ginneken B, Styner MA, Arzhaeva Y, Aurich V, Bauer C, Beck A, Becker C, Beichel R, Bekes G (2009) Comparison and evaluation of methods for liver segmentation from CT datasets. IEEE Trans Med Imaging 28:1251\u20131265","journal-title":"IEEE Trans Med Imaging"},{"key":"1820_CR20","doi-asserted-by":"publisher","first-page":"3243","DOI":"10.1109\/TIP.2010.2041414","volume":"19","author":"C Li","year":"2010","unstructured":"Li C, Xu C, Gui C, Fox MD (2010) Distance regularized level set evolution and its application to image segmentation. IEEE Trans Image Process 19:3243\u20133254","journal-title":"IEEE Trans Image Process"},{"key":"1820_CR21","doi-asserted-by":"publisher","first-page":"1267","DOI":"10.1007\/s11548-015-1323-x","volume":"11","author":"AH Foruzan","year":"2016","unstructured":"Foruzan AH, Chen Y-W (2016) Improved segmentation of low-contrast lesions using sigmoid edge model. Int J Comput Assist Radiol Surg 11:1267\u20131283","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"1820_CR22","first-page":"11","volume":"2017","author":"W Wu","year":"2017","unstructured":"Wu W, Wu S, Zhou Z, Zhang R, Zhang Y (2017) 3D liver tumor segmentation in CT images using improved fuzzy C-means and graph cuts. Biomed Res Int 2017:11","journal-title":"Biomed Res Int"},{"key":"1820_CR23","unstructured":"Christ PF, Ettlinger F, Gr\u00fcn F, Elshaera MEA, Lipkova J, Schlecht S, Ahmaddy F, Tatavarty S, Bickel M, Bilic P (2017) Automatic liver and tumor segmentation of ct and MRI volumes using cascaded fully convolutional neural networks, arXiv preprint arXiv:1702.05970"},{"key":"1820_CR24","unstructured":"Lipkov\u00e1 J, Rempfler M, Christ P, Lowengrub J, Menze BH (2017) Automated unsupervised segmentation of liver lesions in CT scans via Cahn-Hilliard phase separation, arXiv preprint arXiv:1704.02348"},{"key":"1820_CR25","unstructured":"Li X, Chen H, Qi X, Dou Q, Fu C-W, Heng PA (2017) H-DenseUNet: hybrid densely connected UNet for liver and liver tumor segmentation from CT volumes, arXiv preprint arXiv:1709.07330"}],"container-title":["International Journal of Computer Assisted Radiology and Surgery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11548-018-1820-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-018-1820-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-018-1820-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,27]],"date-time":"2022-08-27T04:31:46Z","timestamp":1661574706000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11548-018-1820-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,10]]},"references-count":25,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2018,10]]}},"alternative-id":["1820"],"URL":"https:\/\/doi.org\/10.1007\/s11548-018-1820-9","relation":{},"ISSN":["1861-6410","1861-6429"],"issn-type":[{"type":"print","value":"1861-6410"},{"type":"electronic","value":"1861-6429"}],"subject":[],"published":{"date-parts":[[2018,7,10]]},"assertion":[{"value":"10 January 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 July 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 July 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 conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"For this type of study, formal consent is not required.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}