{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T12:28:16Z","timestamp":1780489696578,"version":"3.54.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2018,4,11]],"date-time":"2018-04-11T00:00:00Z","timestamp":1523404800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001412","name":"Council of Scientific and Industrial Research","doi-asserted-by":"crossref","award":["09\/263(1016)\/2014-EMR-I"],"award-info":[{"award-number":["09\/263(1016)\/2014-EMR-I"]}],"id":[{"id":"10.13039\/501100001412","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Department of Science and Technology, Ministry of Science and Technology","award":["PURSE"],"award-info":[{"award-number":["PURSE"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2019,5]]},"DOI":"10.1007\/s11042-018-5954-0","type":"journal-article","created":{"date-parts":[[2018,4,10]],"date-time":"2018-04-10T21:42:45Z","timestamp":1523396565000},"page":"12663-12687","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["A modified intuitionistic fuzzy c-means clustering approach to segment human brain MRI image"],"prefix":"10.1007","volume":"78","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8902-5022","authenticated-orcid":false,"given":"Dhirendra","family":"Kumar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanuman","family":"Verma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aparna","family":"Mehra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R. K.","family":"Agrawal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,4,11]]},"reference":[{"issue":"6","key":"5954_CR1","doi-asserted-by":"publisher","first-page":"1469","DOI":"10.1007\/s00138-014-0606-5","volume":"25","author":"S Alipour","year":"2014","unstructured":"Alipour S, Shanbehzadeh J (2014) Fast automatic medical image segmentation based on spatial kernel fuzzy c-means on level set method. Mach Vis Appl 25 (6):1469\u20131488","journal-title":"Mach Vis Appl"},{"issue":"1","key":"5954_CR2","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/S0165-0114(86)80034-3","volume":"20","author":"KT Atanassov","year":"1986","unstructured":"Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87\u201396","journal-title":"Fuzzy Sets Syst"},{"key":"5954_CR3","unstructured":"Atanassov KT (2003) Intuitionistic fuzzy sets: past, present and future. In: EUSFLAT conference, pp 12\u201319"},{"issue":"3","key":"5954_CR4","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1007\/s10462-010-9155-0","volume":"33","author":"MA Balafar","year":"2010","unstructured":"Balafar MA, Ramli AR, Saripan MI, Mashohor S (2010) Review of brain mri image segmentation methods. Artif Intell Rev 33(3):261\u2013274","journal-title":"Artif Intell Rev"},{"issue":"5","key":"5954_CR5","doi-asserted-by":"publisher","first-page":"1390","DOI":"10.1016\/j.dsp.2013.07.005","volume":"23","author":"A Benaichouche","year":"2013","unstructured":"Benaichouche A, Oulhadj H, Siarry P (2013) Improved spatial fuzzy c-means clustering for image segmentation using pso initialization, mahalanobis distance and post-segmentation correction. Digital Signal Process 23(5):1390\u20131400","journal-title":"Digital Signal Process"},{"key":"5954_CR6","doi-asserted-by":"crossref","unstructured":"Bezdek JC (1981) Objective Function Clustering. In: Pattern recognition with fuzzy objective function algorithms. Springer, pp 43\u201393","DOI":"10.1007\/978-1-4757-0450-1_3"},{"issue":"3","key":"5954_CR7","doi-asserted-by":"publisher","first-page":"485","DOI":"10.1016\/S0165-0114(98)00279-6","volume":"114","author":"H Bustince","year":"2000","unstructured":"Bustince H, Kacprzyk J, Mohedano V (2000) Intuitionistic fuzzy generators application to intuitionistic fuzzy complementation. Fuzzy Sets Syst 114(3):485\u2013504","journal-title":"Fuzzy Sets Syst"},{"issue":"2","key":"5954_CR8","doi-asserted-by":"publisher","first-page":"1711","DOI":"10.1016\/j.asoc.2010.05.005","volume":"11","author":"T Chaira","year":"2011","unstructured":"Chaira T (2011) A novel intuitionistic fuzzy c means clustering algorithm and its application to medical images. Appl Soft Comput 11(2):1711\u20131717","journal-title":"Appl Soft Comput"},{"key":"5954_CR9","unstructured":"Chen X, Nguyen BP, Chui CK, Ong SH (2016) Automated brain tumor segmentation using kernel dictionary learning and superpixel-level features. In: 2016 IEEE international conference on systems, man, and cybernetics (SMC). IEEE, pp 002,547\u2013002,552"},{"issue":"1","key":"5954_CR10","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.compmedimag.2005.10.001","volume":"30","author":"KS Chuang","year":"2006","unstructured":"Chuang KS, Tzeng HL, Chen S, Wu J, Chen TJ (2006) Fuzzy c-means clustering with spatial information for image segmentation. Comput Med Imaging Graph 30(1):9\u201315","journal-title":"Comput Med Imaging Graph"},{"key":"5954_CR11","unstructured":"Cocosco CA, Kollokian V, Kwan RKS, Pike GB, Evans AC (1997) Brainweb: online interface to a 3d mri simulated brain database. In: NeuroImage. Citeseer"},{"issue":"1","key":"5954_CR12","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garc\u00eda S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3\u201318","journal-title":"Swarm Evol Comput"},{"issue":"200","key":"5954_CR13","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1080\/01621459.1937.10503522","volume":"32","author":"M Friedman","year":"1937","unstructured":"Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. J Am Stat Assoc 32(200):675\u2013701","journal-title":"J Am Stat Assoc"},{"issue":"2","key":"5954_CR14","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s00500-014-1264-2","volume":"19","author":"CW Huang","year":"2015","unstructured":"Huang CW, Lin KP, Wu MC, Hung KC, Liu GS, Jen CH (2015) Intuitionistic fuzzy c-means clustering algorithm with neighborhood attraction in segmenting medical image. Soft Comput 19(2):459\u2013470","journal-title":"Soft Comput"},{"key":"5954_CR15","doi-asserted-by":"crossref","unstructured":"Iakovidis D, Pelekis N, Kotsifakos E, Kopanakis I (2008) Intuitionistic fuzzy clustering with applications in computer vision. In: Advanced concepts for intelligent vision systems. Springer, pp 764\u2013774","DOI":"10.1007\/978-3-540-88458-3_69"},{"issue":"6","key":"5954_CR16","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1080\/03610928008827904","volume":"9","author":"RL Iman","year":"1980","unstructured":"Iman RL, Davenport JM (1980) Approximations of the critical region of the fbietkan statistic. Communications in Statistics-Theory and Methods 9(6):571\u2013595","journal-title":"Communications in Statistics-Theory and Methods"},{"issue":"12","key":"5954_CR17","doi-asserted-by":"publisher","first-page":"3979","DOI":"10.1016\/j.patcog.2014.08.005","volume":"47","author":"ZX Ji","year":"2014","unstructured":"Ji ZX, Sun QS, Xia DS (2014) A framework with modified fast fcm for brain mr images segmentation (retraction of vol 44, pg 999, 2011). Pattern Recogn 47 (12):3979\u20133979","journal-title":"Pattern Recogn"},{"issue":"2","key":"5954_CR18","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.compbiomed.2012.10.002","volume":"43","author":"S Kannan","year":"2013","unstructured":"Kannan S, Devi R, Ramathilagam S, Takezawa K (2013) Effective fcm noise clustering algorithms in medical images. Comput Biol Med 43(2):73\u201383","journal-title":"Comput Biol Med"},{"issue":"5","key":"5954_CR19","doi-asserted-by":"publisher","first-page":"1328","DOI":"10.1109\/TIP.2010.2040763","volume":"19","author":"S Krinidis","year":"2010","unstructured":"Krinidis S, Chatzis V (2010) A robust fuzzy local information c-means clustering algorithm. IEEE Trans Image Process 19(5):1328\u20131337","journal-title":"IEEE Trans Image Process"},{"issue":"2","key":"5954_CR20","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1109\/91.227387","volume":"1","author":"R Krishnapuram","year":"1993","unstructured":"Krishnapuram R, Keller JM (1993) A possibilistic approach to clustering. IEEE Trans Fuzzy Syst 1(2):98\u2013110","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"7","key":"5954_CR21","doi-asserted-by":"publisher","first-page":"2007","DOI":"10.1109\/TIP.2010.2103950","volume":"20","author":"C Li","year":"2011","unstructured":"Li C, Huang R, Ding Z, Gatenby JC, Metaxas DN, Gore JC (2011) 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","journal-title":"IEEE Trans Image Process"},{"key":"5954_CR22","unstructured":"Murofushi T, Sugeno M (2000) Fuzzy measures and fuzzy integrals. In: Fuzzy measures and integrals: theory and applications, pp 3\u201341"},{"issue":"2","key":"5954_CR23","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/S1361-8415(00)00041-4","volume":"5","author":"SD Olabarriaga","year":"2001","unstructured":"Olabarriaga SD, Smeulders AW (2001) Interaction in the segmentation of medical images: a survey. Med Image Anal 5(2):127\u2013142","journal-title":"Med Image Anal"},{"issue":"1","key":"5954_CR24","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1504\/IJBIDM.2008.017975","volume":"3","author":"N Pelekis","year":"2008","unstructured":"Pelekis N, Iakovidis DK, Kotsifakos EE, Kopanakis I (2008) Fuzzy clustering of intuitionistic fuzzy data. International Journal of Business Intelligence and Data Mining 3(1):45\u201365","journal-title":"International Journal of Business Intelligence and Data Mining"},{"issue":"1","key":"5954_CR25","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1146\/annurev.bioeng.2.1.315","volume":"2","author":"DL Pham","year":"2000","unstructured":"Pham DL, Xu C, Prince JL (2000) Current methods in medical image segmentation 1. Annu Rev Biomed Eng 2(1):315\u2013337","journal-title":"Annu Rev Biomed Eng"},{"issue":"12","key":"5954_CR26","doi-asserted-by":"publisher","first-page":"1329","DOI":"10.1016\/j.patrec.2013.04.021","volume":"34","author":"C Qiu","year":"2013","unstructured":"Qiu C, Xiao J, Yu L, Han L, Iqbal MN (2013) A modified interval type-2 fuzzy c-means algorithm with application in mr image segmentation. Pattern Recogn Lett 34(12):1329\u20131338","journal-title":"Pattern Recogn Lett"},{"key":"5954_CR27","unstructured":"Sato M, Lakare S, Wan M, Kaufman A, Nakajima M (2000) A gradient magnitude based region growing algorithm for accurate segmentation. In: 2000 international conference on image processing, 2000. Proceedings, vol 3. IEEE, pp 448\u2013451"},{"issue":"3","key":"5954_CR28","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1016\/S0165-0114(98)00244-9","volume":"114","author":"E Szmidt","year":"2000","unstructured":"Szmidt E, Kacprzyk J (2000) Distances between intuitionistic fuzzy sets. Fuzzy Sets Syst 114(3):505\u2013518","journal-title":"Fuzzy Sets Syst"},{"issue":"05","key":"5954_CR29","doi-asserted-by":"publisher","first-page":"1550,016","DOI":"10.1142\/S0218213015500165","volume":"24","author":"H Verma","year":"2015","unstructured":"Verma H, Agrawal R (2015) Possibilistic intuitionistic fuzzy c-means clustering algorithm for mri brain image segmentation. Int J Artif Intell Tools 24(05):1550,016","journal-title":"Int J Artif Intell Tools"},{"key":"5954_CR30","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/j.asoc.2015.12.022","volume":"46","author":"H Verma","year":"2016","unstructured":"Verma H, Agrawal R, Sharan A (2016) An improved intuitionistic fuzzy c-means clustering algorithm incorporating local information for brain image segmentation. Appl Soft Comput 46:543\u2013557","journal-title":"Appl Soft Comput"},{"key":"5954_CR31","unstructured":"Vlachos IK, Sergiadis GD (2007) The role of entropy in intuitionistic fuzzy contrast enhancement. In: International fuzzy systems association world congress. Springer, pp 104\u2013113"},{"issue":"3","key":"5954_CR32","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1109\/TMI.2006.891486","volume":"26","author":"U Vovk","year":"2007","unstructured":"Vovk U, Pernus F, Likar B (2007) A review of methods for correction of intensity inhomogeneity in mri. IEEE Trans Med Imaging 26(3):405\u2013421","journal-title":"IEEE Trans Med Imaging"},{"issue":"2","key":"5954_CR33","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1016\/j.jneumeth.2010.03.004","volume":"188","author":"L Wang","year":"2010","unstructured":"Wang L, Chen Y, Pan X, Hong X, Xia D (2010) Level set segmentation of brain magnetic resonance images based on local gaussian distribution fitting energy. J Neurosci Methods 188(2):316\u2013325","journal-title":"J Neurosci Methods"},{"issue":"10","key":"5954_CR34","doi-asserted-by":"publisher","first-page":"1412","DOI":"10.1016\/j.cviu.2013.05.001","volume":"117","author":"Z Wang","year":"2013","unstructured":"Wang Z, Song Q, Soh YC, Sim K (2013) An adaptive spatial information-theoretic fuzzy clustering algorithm for image segmentation. Comput Vis Image Underst 117(10):1412\u20131420","journal-title":"Comput Vis Image Underst"},{"issue":"4","key":"5954_CR35","doi-asserted-by":"publisher","first-page":"580","DOI":"10.3969\/j.issn.1004-4132.2010.04.009","volume":"21","author":"Z Xu","year":"2010","unstructured":"Xu Z, Wu J (2010) Intuitionistic fuzzy c-means clustering algorithms. J Syst Eng Electron 21(4):580\u2013590","journal-title":"J Syst Eng Electron"},{"issue":"4","key":"5954_CR36","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1080\/03081077908547452","volume":"5","author":"RR Yager","year":"1979","unstructured":"Yager RR (1979) On the measure of fuzziness and negation part i: membership in the unit interval. Int J Gen Syst 5(4):221\u2013229","journal-title":"Int J Gen Syst"},{"issue":"3","key":"5954_CR37","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1016\/S0019-9958(80)90156-4","volume":"44","author":"RR Yager","year":"1980","unstructured":"Yager RR (1980) On the measure of fuzziness and negation. II. Lattices. Inf Control 44(3):236\u2013260","journal-title":"Inf Control"},{"issue":"3","key":"5954_CR38","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1016\/S0019-9958(65)90241-X","volume":"8","author":"LA Zadeh","year":"1965","unstructured":"Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338\u2013353","journal-title":"Inf Control"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-018-5954-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-018-5954-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-018-5954-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,1,19]],"date-time":"2020-01-19T01:09:40Z","timestamp":1579396180000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-018-5954-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,11]]},"references-count":38,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2019,5]]}},"alternative-id":["5954"],"URL":"https:\/\/doi.org\/10.1007\/s11042-018-5954-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,4,11]]},"assertion":[{"value":"2 August 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 March 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 April 2018","order":4,"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":"<!--Emphasis Type='Bold' removed-->Conflict of interests"}}]}}