{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T16:46:04Z","timestamp":1781541964297,"version":"3.54.5"},"reference-count":22,"publisher":"Allerton Press","issue":"1","license":[{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Aut. Control Comp. Sci."],"published-print":{"date-parts":[[2022,2]]},"DOI":"10.3103\/s0146411622010047","type":"journal-article","created":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T02:02:55Z","timestamp":1647309775000},"page":"67-82","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Fully Integrated Spatial Information to Improve FCM Algorithm for Brain MRI Image Segmentation"],"prefix":"10.3103","volume":"56","author":[{"family":"Fouzia Chighoub","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"family":"Rachida Saouli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1627","published-online":{"date-parts":[[2022,3,15]]},"reference":[{"key":"7467_CR1","volume-title":"Pattern Recognition and Image Analysis","author":"E. Gose","year":"1996","unstructured":"Gose, E., Johnsbaugh, R., and Jost, S., Pattern Recognition and Image Analysis, Upper Saddle River, N.J.: Prentice Hall, 1996."},{"key":"7467_CR2","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1109\/42.996338","volume":"21","author":"M.N. Ahmed","year":"2002","unstructured":"Ahmed, M.N., Yamany, S.M., Mohamed, N., and Farag, A.A., and Moriarty, T., A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data, IEEE Trans. Med. Imaging, 2002, vol. 21, no.\u00a03, pp. 193\u2013199.\u00a0https:\/\/doi.org\/10.1109\/42.996338","journal-title":"IEEE Trans. Med. Imaging"},{"key":"7467_CR3","doi-asserted-by":"publisher","unstructured":"Szil\u00e1gyi, L., Benyo, Z., Szil\u00e1gyi, S.M., and Adam, H.S., MR brain image segmentation using an enhanced fuzzy C-means algorithm, Proc. 25th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No. 03CH37439), Cancun, 2003, IEEE, 2003, vol.\u00a01, pp.\u00a0724\u2013726. \u00a0https:\/\/doi.org\/10.1109\/IEMBS.2003.1279866","DOI":"10.1109\/IEMBS.2003.1279866"},{"key":"7467_CR4","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.compmedimag.2005.10.001","volume":"30","author":"K.-S. Chuang","year":"2006","unstructured":"Chuang, K.-S., Tzeng, H.-L., Chen, S.W., Wu, J., and Chen, T.-J., Fuzzy c-means clustering with spatial information for image segmentation, Comput. Med. Imaging Graphics, 2006, vol.\u00a030, no. 1, pp. 9\u201315. \u00a0https:\/\/doi.org\/10.1016\/j.compmedimag.2005.10.001","journal-title":"Comput. Med. Imaging Graphics"},{"key":"7467_CR5","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1016\/j.patcog.2006.07.011","volume":"40","author":"W. Cai","year":"2007","unstructured":"Cai, W., Chen, S., and Zhang, D., Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation, Pattern Recognit., 2007, vol. 40, no.\u00a03, pp. 825\u2013838. \u00a0https:\/\/doi.org\/10.1016\/j.patcog.2006.07.011","journal-title":"Pattern Recognit."},{"key":"7467_CR6","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1016\/j.compmedimag.2008.08.004","volume":"32","author":"J. Wang","year":"2008","unstructured":"Wang, J., Kong, J., Lu, Y., Qi, M., and Zhang, B., A modified FCM algorithm for MRI brain image segmentation using both local and non-local spatial constraints, Comput. Med. Imaging Graphics, 2008, vol. 32, no. 8, pp. 685\u2013698. \u00a0https:\/\/doi.org\/10.1016\/j.compmedimag.2008.08.004","journal-title":"Comput. Med. Imaging Graphics"},{"key":"7467_CR7","doi-asserted-by":"publisher","first-page":"1328","DOI":"10.1109\/TIP.2010.2040763","volume":"19","author":"S. Krinidis","year":"2010","unstructured":"Krinidis, S. and Chatzis, V., A robust fuzzy local information c-means clustering algorithm, IEEE Trans. Image Process., 2010, vol. 19, no. 5, pp. 1328\u20131337.\u00a0https:\/\/doi.org\/10.1109\/TIP.2010.2040763","journal-title":"IEEE Trans. Image Process."},{"key":"7467_CR8","doi-asserted-by":"publisher","first-page":"758","DOI":"10.1016\/j.asoc.2015.05.038","volume":"34","author":"S.K. Adhikari","year":"2015","unstructured":"Adhikari, S.K., Sing, J.K., Basu, D.K., and Nasipuri, M., Conditional spatial fuzzy C-means clustering algorithm for segmentation of MRI images, Appl. Soft Comput., 2015, vol. 34, pp.\u00a0758\u2013769. \u00a0https:\/\/doi.org\/10.1016\/j.asoc.2015.05.038","journal-title":"Appl. Soft Comput."},{"key":"7467_CR9","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/j.asoc.2015.12.022","volume":"46","author":"H. Verma","year":"2015","unstructured":"Verma, H., Agrawal, R.K., and Sharan, A., An improved intuitionistic fuzzy c-means clustering algorithm incorporating local information for brain image segmentation, Appl. Soft Comput., 2015, vol. 46, pp. 543\u2013557. \u00a0https:\/\/doi.org\/10.1016\/j.asoc.2015.12.022","journal-title":"Appl. Soft Comput."},{"key":"7467_CR10","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.irbm.2015.01.007","volume":"36","author":"Q. Mahmood","year":"2015","unstructured":"Mahmood, Q., Chodorowski, A., and Persson, M., Automated MRI brain tissue segmentation based on mean shift and fuzzy c-means using a priori tissue probability maps, IRBM, 2015, vol. 36, no. 3, pp. 185\u2013196. \u00a0https:\/\/doi.org\/10.1016\/j.irbm.2015.01.007","journal-title":"IRBM"},{"key":"7467_CR11","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1002\/ima.22166","volume":"26","author":"R. Meena Prakash","year":"2016","unstructured":"Meena Prakash, R. and Shantha Selva Kumari, R., Fuzzy C means integrated with spatial information and contrast enhancement for segmentation of MR brain images, Int. J. Imaging Syst. Technol., 2016, vol. 26, no. 12, pp.\u00a0116\u2013123.\u00a0https:\/\/doi.org\/10.1002\/ima.22166","journal-title":"Int. J. Imaging Syst. Technol."},{"key":"7467_CR12","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1016\/j.neucom.2018.05.116","volume":"312","author":"F. Zhao","year":"2018","unstructured":"Zhao, F., Liu, H., Fan, J., Chen, C.W., Lan, R., and Li, N., Intuitionistic fuzzy set approach to multi-objective evolutionary clustering with multiple spatial information for image segmentation, Neurocomputing, 2018, vol.\u00a0312, pp. 296\u2013309.\u00a0https:\/\/doi.org\/10.1016\/j.neucom.2018.05.116","journal-title":"Neurocomputing"},{"key":"7467_CR13","doi-asserted-by":"publisher","first-page":"3027","DOI":"10.1109\/TFUZZ.2018.2796074","volume":"26","author":"T. Lei","year":"2018","unstructured":"Lei, T., Jia, X., Zhang, Y., He, L., Meng, H., and Nandi, A.K., Significantly fast and robust fuzzy c-means clustering algorithm based on morphological reconstruction and membership filtering, IEEE Trans. Fuzzy Syst., 2018, vol. 26, no. 5, pp. 3027\u20133041. \u00a0https:\/\/doi.org\/10.1109\/TFUZZ.2018.2796074","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"7467_CR14","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1109\/TFUZZ.2018.2852289","volume":"27","author":"F. Zhao","year":"2018","unstructured":"Zhao, F., Fan, J., Liu, H., Lan, R., and Chen, C.W., Noise robust multiobjective evolutionary clustering image segmentation motivated by the intuitionistic fuzzy information, IEEE Trans. Fuzzy Syst., 2018, vol. 27, no. 2, pp.\u00a0387\u2013401. \u00a0https:\/\/doi.org\/10.1109\/TFUZZ.2018.2852289","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"7467_CR15","doi-asserted-by":"publisher","first-page":"102615","DOI":"10.1016\/j.dsp.2019.102615","volume":"97","author":"C. Wu","year":"2020","unstructured":"Wu, C. and Yang, X., Robust credibilistic fuzzy local information clustering with spatial information constraints, Digital Signal Process., 2020, vol. 97, p. 102615.\u00a0https:\/\/doi.org\/10.1016\/j.dsp.2019.102615","journal-title":"Digital Signal Process."},{"key":"7467_CR16","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1109\/TFUZZ.2020.2965896","volume":"28","author":"S. Roy","year":"2020","unstructured":"Roy, S. and Maji, P., Medical image segmentation by partitioning spatially constrained fuzzy approximation spaces, IEEE Trans. Fuzzy Syst., 2020, vol. 28, no. 5, pp. 965\u2013977. \u00a0https:\/\/doi.org\/10.1109\/TFUZZ.2020.2965896","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"7467_CR17","doi-asserted-by":"publisher","first-page":"106318","DOI":"10.1016\/j.asoc.2020.106318","volume":"92","author":"Q. Wang","year":"2020","unstructured":"Wang, Q., Wang, X., Fang, C., and Yang, W., Robust fuzzy c-means clustering algorithm with adaptive spatial & intensity constraint and membership linking for noise image segmentation, Appl. Soft Comput., 2020, vol. 92, p.\u00a0106318. \u00a0https:\/\/doi.org\/10.1016\/j.asoc.2020.106318","journal-title":"Appl. Soft Comput."},{"key":"7467_CR18","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1080\/01969727308546047","volume":"3","author":"J.C. Bezdek","year":"1973","unstructured":"Bezdek, J.C., Cluster validity with fuzzy sets, J. Cybern., 1973, vol. 3, no. 3, pp. 58\u201373.\u00a0https:\/\/doi.org\/10.1080\/01969727308546047","journal-title":"J. Cybern."},{"key":"7467_CR19","unstructured":"Bezdek, J.C, Mathematical models for systematic and taxonomy, Proc. 8th Int. Conf. on Numerical Taxonomy, San Francisco, 1975, pp. 143\u2013166."},{"key":"7467_CR20","unstructured":"Fukyama, Y. and Sugeno, T., A new method of choosing the number of clusters for the fuzzy c-means method, Proc. 5th Fuzzy Systems Symp., 1989, pp. 247\u2013250."},{"key":"7467_CR21","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1109\/34.85677","volume":"13","author":"X. Xie","year":"1991","unstructured":"Xie, X. and Beni, G., A validity measure for fuzzy clustering, IEEE Trans. Pattern Anal. Mach. Intell., 1991, vol.\u00a013, no. 8, pp. 841\u2013847. \u00a0https:\/\/doi.org\/10.1109\/34.85677","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"7467_CR22","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/91.493905","volume":"4","author":"A.M. Bensaid","year":"1996","unstructured":"Bensaid, A.M., Hall, L.O., Bezdek, J.C., Clarke, L.P., Silbiger, M.L., Arrington, J.A., and Murtagh, R.F., Validity-guided (re)clustering with applications to image segmentation, IEEE Trans. Fuzzy Syst., 1996, vol. 4, no.\u00a02, pp. 112\u2013123. \u00a0https:\/\/doi.org\/10.1109\/91.493905","journal-title":"IEEE Trans. Fuzzy Syst."}],"container-title":["Automatic Control and Computer Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411622010047.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.3103\/S0146411622010047","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411622010047.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:00:58Z","timestamp":1773612058000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.3103\/S0146411622010047"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2]]},"references-count":22,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,2]]}},"alternative-id":["7467"],"URL":"https:\/\/doi.org\/10.3103\/s0146411622010047","relation":{},"ISSN":["0146-4116","1558-108X"],"issn-type":[{"value":"0146-4116","type":"print"},{"value":"1558-108X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2]]},"assertion":[{"value":"30 November 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 June 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 June 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 March 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no conflicts of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"CONFLICT OF INTEREST"}}]}}