{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T23:25:00Z","timestamp":1778628300762,"version":"3.51.4"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2019,4,12]],"date-time":"2019-04-12T00:00:00Z","timestamp":1555027200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Shenzhen Fundamental Research Plan","award":["No. JCYJ20160505175141489"],"award-info":[{"award-number":["No. JCYJ20160505175141489"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1007\/s00371-019-01651-4","type":"journal-article","created":{"date-parts":[[2019,4,12]],"date-time":"2019-04-12T11:04:07Z","timestamp":1555067047000},"page":"717-731","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Simultaneous segmentation and correction model for color medical and natural images with intensity inhomogeneity"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0488-7652","authenticated-orcid":false,"given":"Yunyun","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjing","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boying","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,4,12]]},"reference":[{"issue":"6\u20138","key":"1651_CR1","doi-asserted-by":"publisher","first-page":"1061","DOI":"10.1007\/s00371-017-1379-4","volume":"33","author":"L Bi","year":"2017","unstructured":"Bi, L., Kim, J., Kumar, A., Fulham, M., Feng, D.G.: Stacked fully convolutional networks with multi-channel learning: application to medical image segmentation. Visual Comput. 33(6\u20138), 1061\u20131071 (2017)","journal-title":"Visual Comput."},{"key":"1651_CR2","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.patcog.2018.05.008","volume":"82","author":"Q Cai","year":"2018","unstructured":"Cai, Q., Liu, H.Y., Zhou, S.P., Sun, J.F., Li, J.: An adaptive-scale active contour model for inhomogeneous image segmentation and bias field estimation. Pattern Recognit. 82, 79\u201393 (2018)","journal-title":"Pattern Recognit."},{"issue":"1","key":"1651_CR3","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1023\/A:1007979827043","volume":"22","author":"V Caselles","year":"1997","unstructured":"Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. Int. J. Comput. Vis. 22(1), 61\u201379 (1997)","journal-title":"Int. J. Comput. Vis."},{"issue":"2","key":"1651_CR4","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1006\/jvci.1999.0442","volume":"11","author":"TE Chan","year":"2000","unstructured":"Chan, T.E., Sandberg, B.Y., Vese, L.A.: Active contours without edges for vector-valued images. J. Vis. Commun. Image Represent. 11(2), 130\u2013141 (2000)","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"5","key":"1651_CR5","doi-asserted-by":"publisher","first-page":"1632","DOI":"10.1137\/040615286","volume":"66","author":"TF Chan","year":"2006","unstructured":"Chan, T.F., Nikolova, M.: Algorithms for finding global minimizers of image segmentation and denoising models. SIAM J. Appl. Math. 66(5), 1632\u20131648 (2006)","journal-title":"SIAM J. Appl. Math."},{"issue":"2","key":"1651_CR6","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1109\/83.902291","volume":"10","author":"TF Chan","year":"2001","unstructured":"Chan, T.F., Vese, L.A.: Active contours without edges. IEEE Trans. Image Process. 10(2), 266\u2013277 (2001)","journal-title":"IEEE Trans. Image Process."},{"key":"1651_CR7","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.neucom.2016.09.008","volume":"219","author":"CL Feng","year":"2017","unstructured":"Feng, C.L., Zhao, D.Z., Huang, M.: Image segmentation and bias correction using local inhomogeneous intensity clustering (LINC): a region-based level set method. Neurocomputing 219, 107\u2013129 (2017)","journal-title":"Neurocomputing"},{"issue":"1\u20133","key":"1651_CR8","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1007\/s10915-009-9331-z","volume":"45","author":"T Goldstein","year":"2010","unstructured":"Goldstein, T., Bresson, X., Osher, S.: Geometric applications of the split Bregman method: segmentation and surface reconstruction. J. Sci. Comput. 45(1\u20133), 272\u2013293 (2010)","journal-title":"J. Sci. Comput."},{"issue":"2","key":"1651_CR9","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1137\/080725891","volume":"2","author":"T Goldstein","year":"2009","unstructured":"Goldstein, T., Osher, S.: The split Bregman method for L1-regularized problems. SIAM J. Imaging Sci. 2(2), 323\u2013343 (2009)","journal-title":"SIAM J. Imaging Sci."},{"key":"1651_CR10","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.patcog.2016.12.011","volume":"65","author":"R Hettiarachchi","year":"2017","unstructured":"Hettiarachchi, R., Peters, J.F.: Voronoi region-based adaptive unsupervised color image segmentation. Pattern Recognit. 65, 119\u2013135 (2017)","journal-title":"Pattern Recognit."},{"issue":"4","key":"1651_CR11","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1007\/BF00133570","volume":"1","author":"M Kass","year":"1988","unstructured":"Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. Comput. Vis. 1(4), 321\u2013331 (1988)","journal-title":"Int. J. Comput. Vis."},{"issue":"10","key":"1651_CR12","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1049\/iet-ipr.2014.0439","volume":"9","author":"Y Le","year":"2015","unstructured":"Le, Y., Xu, X.Z., Zha, L., Zhao, W.C., Zhu, Y.Y.: Tumour localisation in ultrasound-guided high-intensity focused ultrasound ablation using improved gradient and direction vector flow. IET Image Process. 9(10), 857\u2013865 (2015)","journal-title":"IET Image Process."},{"issue":"7","key":"1651_CR13","doi-asserted-by":"publisher","first-page":"913","DOI":"10.1016\/j.mri.2014.03.010","volume":"32","author":"C Li","year":"2014","unstructured":"Li, C., Gore, J.C., Davatzikos, C.: Multiplicative intrinsic component optimization (MICO) for MRI bias field estimation and tissue segmentation. Magn. Reson. Imaging 32(7), 913\u2013923 (2014)","journal-title":"Magn. Reson. Imaging"},{"issue":"10","key":"1651_CR14","doi-asserted-by":"publisher","first-page":"1940","DOI":"10.1109\/TIP.2008.2002304","volume":"17","author":"C Li","year":"2008","unstructured":"Li, C., Kao, C.Y., Gore, J.C., Ding, Z.: Minimization of region-scalable fitting energy for image segmentation. IEEE Trans. Image Process. 17(10), 1940\u20131949 (2008)","journal-title":"IEEE Trans. Image Process."},{"key":"1651_CR15","unstructured":"Li, C., Li, F., Kao, C.Y., Xu, C.: Image segmentation with simultaneous illumination and reflectance estimation: an energy minimization approach. In: 2009 IEEE 12th International Conference on Computer Vision (ICCV), Kyoto, Japan, pp. 702\u2013708 (2009)"},{"issue":"12","key":"1651_CR16","doi-asserted-by":"publisher","first-page":"3243","DOI":"10.1109\/TIP.2010.2069690","volume":"19","author":"C Li","year":"2010","unstructured":"Li, C., Xu, C., Gui, C., Fox, M.D.: Distance regularized level set evolution and its application to image segmentation. IEEE Trans. Image Process. 19(12), 3243\u20133254 (2010)","journal-title":"IEEE Trans. Image Process."},{"issue":"7","key":"1651_CR17","doi-asserted-by":"publisher","first-page":"2007","DOI":"10.1109\/TIP.2010.2103950","volume":"20","author":"CM Li","year":"2011","unstructured":"Li, C.M., Huang, R., Ding, Z.H., Gatenby, J.C., Metaxas, D.N., Gore, J.C.: A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI. IEEE Trans. Image Process. 20(7), 2007\u20132016 (2011)","journal-title":"IEEE Trans. Image Process."},{"issue":"2","key":"1651_CR18","doi-asserted-by":"publisher","first-page":"322","DOI":"10.3390\/s18020322","volume":"18","author":"Y Li","year":"2018","unstructured":"Li, Y., Shen, L.: Skin lesion analysis towards melanoma detection using deep learning network. Sensors 18(2), 322\u2013329 (2018)","journal-title":"Sensors"},{"issue":"10","key":"1651_CR19","doi-asserted-by":"publisher","first-page":"5016","DOI":"10.1109\/TIP.2018.2848471","volume":"27","author":"H Min","year":"2018","unstructured":"Min, H., Jia, W., Zhao, Y., Zuo, W.M., Ling, H.B., Luo, Y.T.: LATE: a level-set method based on local approximation of Taylor expansion for segmenting intensity inhomogeneous images. IEEE Trans. Image Process. 27(10), 5016\u20135031 (2018)","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"1651_CR20","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1002\/cpa.3160420503","volume":"42","author":"D Mumford","year":"1989","unstructured":"Mumford, D., Shah, J.: Optimal approximations by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math. 42(5), 577\u2013685 (1989)","journal-title":"Commun. Pure Appl. Math."},{"issue":"6\u20138","key":"1651_CR21","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1007\/s00371-014-0963-0","volume":"30","author":"F Paulano","year":"2014","unstructured":"Paulano, F., Jimenez, J.J., Pulido, R.: 3d Segmentation and labeling of fractured bone from ct images. Visual Comput. 30(6\u20138), 939\u2013948 (2014)","journal-title":"Visual Comput."},{"issue":"5","key":"1651_CR22","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1006\/nimg.2000.0730","volume":"13","author":"DW Shattuck","year":"2001","unstructured":"Shattuck, D.W., Sandor-Leahy, S.R., Schaper, K.A., Rottenberg, D.A., Leahy, R.M.: Magnetic resonance image tissue classification using a partial volume model. Neuroimage 13(5), 856\u2013876 (2001)","journal-title":"Neuroimage"},{"issue":"10","key":"1651_CR23","doi-asserted-by":"publisher","first-page":"1854027","DOI":"10.1142\/S0218001418540277","volume":"32","author":"L Song","year":"2018","unstructured":"Song, L.: Image segmentation based on supervised discriminative learning. Int. J. Pattern Recognit. Artif. Intell. 32(10), 1854027 (2018)","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"issue":"7","key":"1651_CR24","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1016\/j.compmedimag.2009.04.010","volume":"33","author":"L Wang","year":"2009","unstructured":"Wang, L., Li, C., Sun, Q., Xia, D., Kao, C.Y.: Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation. J. Comput. Med. Imaging Graph. 33(7), 520\u2013531 (2009)","journal-title":"J. Comput. Med. Imaging Graph."},{"issue":"3","key":"1651_CR25","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1137\/080724265","volume":"1","author":"YL Wang","year":"2008","unstructured":"Wang, Y.L., Yang, J.F., Yin, W.T., Zhang, Y.: A new alternating minimization algorithm for total variation image reconstruction. SIAM J. Imaging Sci. 1(3), 248\u2013272 (2008)","journal-title":"SIAM J. Imaging Sci."},{"key":"1651_CR26","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1016\/j.patcog.2018.02.012","volume":"79","author":"M Xian","year":"2018","unstructured":"Xian, M., Zhang, Y.T., Cheng, H.D., Xu, F., Zhang, B.Y., Ding, J.R.: Automatic breast ultrasound image segmentation: a survey. Pattern Recognit. 79, 340\u2013355 (2018)","journal-title":"Pattern Recognit."},{"issue":"1","key":"1651_CR27","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s00371-012-0672-5","volume":"29","author":"CX Xiao","year":"2013","unstructured":"Xiao, C.X., Gan, J.J., Hu, X.Y.: Fast level set image and video segmentation using new evolution indicator operators. Visual Comput. 29(1), 27\u201339 (2013)","journal-title":"Visual Comput."},{"issue":"2","key":"1651_CR28","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1109\/TMI.2015.2481436","volume":"35","author":"FY Xing","year":"2016","unstructured":"Xing, F.Y., Xie, Y.P., Yang, L.: An automatic learning-based framework for robust nucleus segmentation. IEEE Trans. Med. Imaging 35(2), 550\u2013566 (2016)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"3","key":"1651_CR29","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1109\/83.661186","volume":"7","author":"C Xu","year":"1998","unstructured":"Xu, C., Prince, J.L.: Snakes, shapes, and gradient vector flow. IEEE Trans. Image Process. 7(3), 359\u2013369 (1998)","journal-title":"IEEE Trans. Image Process."},{"key":"1651_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neucom.2018.04.010","volume":"306","author":"G Xu","year":"2018","unstructured":"Xu, G., Li, X., Lei, B., Lv, K.: Unsupervised color image segmentation with color-alone feature using region growing pulse coupled neural network. Neurocomputing 306, 1\u201316 (2018)","journal-title":"Neurocomputing"},{"issue":"1","key":"1651_CR31","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1016\/j.jmaa.2011.11.073","volume":"389","author":"Y Yang","year":"2012","unstructured":"Yang, Y., Boying, W.: Split Bregman method for minimization of improved active contour model combining local and global information dynamically. J. Math. Anal. Appl. 389(1), 351\u2013366 (2012)","journal-title":"J. Math. Anal. Appl."},{"key":"1651_CR32","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/978-3-642-17274-8_12","volume-title":"Advances in Visual Computing","author":"Yunyun Yang","year":"2010","unstructured":"Yang, Y., Li, C., Kao, C.Y., Osher, S.: Split Bregman method for minimization of region-scalable fitting energy for image segmentation. In: International Symposium on Visual Computing (ISVC). Lecture Notes in Computer Science, vol 6454, pp. 117\u2013128. Springer, Berlin (2010)"},{"key":"1651_CR33","first-page":"494761","volume":"2012","author":"Y Yang","year":"2012","unstructured":"Yang, Y., Wu, B.: A new and fast multiphase image segmentation model for color images. Math. Probl. Eng. 2012, 494761 (2012)","journal-title":"Math. Probl. Eng."},{"issue":"8","key":"1651_CR34","doi-asserted-by":"publisher","first-page":"1559","DOI":"10.1016\/j.camwa.2014.01.017","volume":"67","author":"Y Yang","year":"2014","unstructured":"Yang, Y., Zhao, Y., Wu, B., Wang, H.: A fast multiphase image segmentation model for gray images. Comput. Math. Appl. 67(8), 1559\u20131581 (2014)","journal-title":"Comput. Math. Appl."},{"issue":"1","key":"1651_CR35","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/s00371-016-1318-9","volume":"34","author":"ZY Zha","year":"2018","unstructured":"Zha, Z.Y., Liu, X., Zhang, X.G., Chen, Y., Tang, L., Bai, Y., Wang, Q., Shang, Z.H.: Compressed sensing image reconstruction via adaptive sparse nonlocal regularization. Visual Comput. 34(1), 117\u2013137 (2018)","journal-title":"Visual Comput."},{"issue":"11","key":"1651_CR36","doi-asserted-by":"publisher","first-page":"3902","DOI":"10.1109\/TIP.2015.2456503","volume":"24","author":"HZ Zhang","year":"2015","unstructured":"Zhang, H.Z., Xie, X.H.: Divergence of gradient convolution: deformable segmentation with arbitrary initializations. IEEE Trans. Image Process. 24(11), 3902\u20133914 (2015)","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"1651_CR37","doi-asserted-by":"publisher","first-page":"1857005","DOI":"10.1142\/S0218001418570057","volume":"32","author":"T Zhang","year":"2018","unstructured":"Zhang, T.: Optimized fuzzy clustering algorithms for brain MRI image segmentation based on local Gaussian probability and anisotropic weight models. Int. J. Pattern Recognit. Artif. Intell. 32(9), 1857005 (2018)","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"issue":"6\u20138","key":"1651_CR38","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/s00371-011-0588-5","volume":"27","author":"F Zhong","year":"2011","unstructured":"Zhong, F., Qin, X.Y., Peng, Q.S.: Robust image segmentation against complex color distribution. Visual Comput. 27(6\u20138), 707\u2013716 (2011)","journal-title":"Visual Comput."},{"issue":"11","key":"1651_CR39","doi-asserted-by":"publisher","first-page":"2281","DOI":"10.1109\/TCSVT.2016.2589781","volume":"27","author":"YF Zhou","year":"2017","unstructured":"Zhou, Y.F., Pan, X., Wang, W.P., Yin, Y.L., Zhang, C.M.: Superpixels by bilateral geodesic distance. IEEE Trans. Circuits Syst. Video 27(11), 2281\u20132293 (2017)","journal-title":"IEEE Trans. Circuits Syst. Video"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-019-01651-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00371-019-01651-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-019-01651-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,10]],"date-time":"2020-04-10T23:35:59Z","timestamp":1586561759000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00371-019-01651-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,12]]},"references-count":39,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,4]]}},"alternative-id":["1651"],"URL":"https:\/\/doi.org\/10.1007\/s00371-019-01651-4","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,12]]},"assertion":[{"value":"12 April 2019","order":1,"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":"We declare that we have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}