{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T06:04:12Z","timestamp":1705557852826},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2017,9,19]],"date-time":"2017-09-19T00:00:00Z","timestamp":1505779200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"published-print":{"date-parts":[[2017,11]]},"DOI":"10.1007\/s10916-017-0821-5","type":"journal-article","created":{"date-parts":[[2017,9,19]],"date-time":"2017-09-19T01:18:39Z","timestamp":1505783919000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Metaheuristically Tuned Interval Type 2 Fuzzy System to Reduce Segmentation Uncertainty in Brain MRI Images"],"prefix":"10.1007","volume":"41","author":[{"given":"Abolfazl","family":"Taghribi","sequence":"first","affiliation":[]},{"given":"Saeed","family":"Sharifian","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,19]]},"reference":[{"key":"821_CR1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2007\/25487","volume":"2007","author":"R Sitaram","year":"2007","unstructured":"Sitaram, R., Caria, A., Veit, R., Gaber, T., Rota, G., Kuebler, A., and Birbaumer, N., fMRI brain-computer Interface: A tool for neuroscientific research and treatment. Comput. Intell. Neurosci. 2007:1\u201310, 2007.","journal-title":"Comput. Intell. Neurosci."},{"issue":"6","key":"821_CR2","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1006\/nimg.2000.0582","volume":"11","author":"J Ashburner","year":"2000","unstructured":"Ashburner, J., and Friston, K., Voxel-based morphometry\u2014The methods. NeuroImage. 11(6):805\u2013821, 2000.","journal-title":"NeuroImage"},{"key":"821_CR3","first-page":"ch.5","volume-title":"Human brain function","author":"R Frackowiak","year":"2004","unstructured":"Frackowiak, R., Human brain function. Elsevier Academic Press, Amsterdam, p. ch.5, 2004."},{"issue":"3","key":"821_CR4","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1109\/42.996338","volume":"21","author":"M Ahmed","year":"2002","unstructured":"Ahmed, M., Yamany, S., Mohamed, N., Farag, A., and Moriarty, T., A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Trans. Med. Imaging. 21(3):193\u2013199, 2002.","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"1","key":"821_CR5","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1109\/TBME.2006.884645","volume":"54","author":"Y Zhou","year":"2007","unstructured":"Zhou, Y., and Bai, J., Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI. IEEE Trans. Biomed. Eng. 54(1):122\u2013129, 2007.","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"1","key":"821_CR6","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1109\/42.906424","volume":"20","author":"Y Zhang","year":"2001","unstructured":"Zhang, Y., Brady, M., and Smith, S., Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans. Med. Imaging. 20(1):45\u201357, 2001.","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"7","key":"821_CR7","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1016\/j.mri.2014.05.003","volume":"32","author":"Y Chen","year":"2014","unstructured":"Chen, Y., Zhao, B., Zhang, J., and Zheng, Y., Automatic segmentation for brain MR images via a convex optimized segmentation and bias field correction coupled model. Magn. Reson. Imaging. 32(7):941\u2013955, 2014.","journal-title":"Magn. Reson. Imaging"},{"issue":"4","key":"821_CR8","doi-asserted-by":"crossref","first-page":"238","DOI":"10.4103\/2228-7477.168653","volume":"5","author":"A Karimian","year":"2015","unstructured":"Karimian, A., and Jafari, S., A new method to segment the multiple sclerosis lesions on brain magnetic resonance images. J. Med. Signal Sens. 5(4):238\u2013244, 2015.","journal-title":"J. Med. Signal Sens."},{"key":"821_CR9","doi-asserted-by":"crossref","unstructured":"Bourouis, S., Hamrouni, K., and Betrouni, N., Automatic MRI brain segmentation with combined atlas-based classification and level-set approach. In: Image Analysis and Recognition International Conference Image Analysis and Recognition. Berlin Heidelberg: Springer, pp 770\u2013778, 2008.","DOI":"10.1007\/978-3-540-69812-8_76"},{"issue":"5","key":"821_CR10","doi-asserted-by":"crossref","first-page":"1240","DOI":"10.1109\/TMI.2016.2538465","volume":"35","author":"S Pereira","year":"2016","unstructured":"Pereira, S., Pinto, A., Alves, V., and Silva, C., Brain tumor segmentation using convolutional neural networks in MRI images. IEEE Trans. Med. Imaging. 35(5):1240\u20131251, 2016.","journal-title":"IEEE Trans. Med. Imaging"},{"key":"821_CR11","doi-asserted-by":"crossref","unstructured":"Desrosiers, C., An unsupervised random walk approach for the segmentation of brain MRI. In: IEEE 11th International Symposium on Biomedical Imaging (ISBI). IEEE, 2014.","DOI":"10.1109\/ISBI.2014.6867877"},{"key":"821_CR12","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.eswa.2016.01.005","volume":"52","author":"S Saha","year":"2016","unstructured":"Saha, S., Alok, A., and Ekbal, A., Brain image segmentation using semi-supervised clustering. Expert Syst. Appl. 52:50\u201363, 2016.","journal-title":"Expert Syst. Appl."},{"key":"821_CR13","unstructured":"Dong, Z., and Wenhua, Z., An improved MRI Brain Segmentation algorithm based on AntPart. In: Computer and Automation Engineering (ICCAE), The 2nd International Conference on. vol. 3. IEEE, 2010."},{"key":"821_CR14","doi-asserted-by":"crossref","unstructured":"Chenling, L., Wenhua, Z., and Jiahe, Z., An improved AntTree algorithm for MRI brain segmentation. In: IT in Medicine and Education(ITME), IEEE International Symposium, pp. 679\u2013683, 2008.","DOI":"10.1109\/ITME.2008.4743952"},{"key":"821_CR15","doi-asserted-by":"crossref","unstructured":"Paul, G., Varghese, T., Purushothaman, K. V., and Albert Singh, N., A fuzzy c mean clustering algorithm for automated segmentation of brain MRI. In: Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA), Springer International Publishing, pp. 59\u201365, 2014.","DOI":"10.1007\/978-3-319-02931-3_8"},{"issue":"2","key":"821_CR16","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/j.bbe.2016.01.001","volume":"36","author":"Y Dubey","year":"2016","unstructured":"Dubey, Y., Mushrif, M., and Mitra, K., Segmentation of brain MR images using rough set based intuitionistic fuzzy clustering. Biocybern. Biomed. Eng. 36(2):413\u2013426, 2016.","journal-title":"Biocybern. Biomed. Eng."},{"key":"821_CR17","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.ins.2012.08.026","volume":"223","author":"J Ghasemi","year":"2013","unstructured":"Ghasemi, J., Ghaderi, R., Karami Mollaei, M., and Hojjatoleslami, S., A novel fuzzy Dempster\u2013Shafer inference system for brain MRI segmentation. Inf. Sci. 223:205\u2013220, 2013.","journal-title":"Inf. Sci."},{"key":"821_CR18","doi-asserted-by":"crossref","unstructured":"Yazdani, S., Yusof, R., Pashna, M., and Karimian, A., A hybrid method for brain MRI classification. In: Control Conference (ASCC), 10th Asian, pp. 1\u20135, 2015.","DOI":"10.1109\/ASCC.2015.7244809"},{"key":"821_CR19","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4614-6666-6","volume-title":"Advances in type-2 fuzzy sets and systems","author":"A Sadeghian","year":"2013","unstructured":"Sadeghian, A., Mendel, J., and Tahayori, H., Advances in type-2 fuzzy sets and systems. Springer, New York, NY, 2013."},{"key":"821_CR20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.artmed.2016.04.004","volume":"69","author":"J Wang","year":"2016","unstructured":"Wang, J., Hu, Y., Xiao, F., Deng, X., and Deng, Y., A novel method to use fuzzy soft sets in decision making based on ambiguity measure and Dempster\u2013Shafer theory of evidence: An application in medical diagnosis. Artif. Intell. Med. 69:1\u201311, 2016.","journal-title":"Artif. Intell. Med."},{"key":"821_CR21","doi-asserted-by":"crossref","unstructured":"Shahi, A., binti Atan, R., and Sulaiman, M. N., Decision making for uncertain data in dynamic environment using hybrid method. In: IEEE International Conference on Control and Automation, pp. 398\u2013403, 2009.","DOI":"10.1109\/ICCA.2009.5410397"},{"issue":"1\u20134","key":"821_CR22","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0020-0255(01)00069-X","volume":"132","author":"N Karnik","year":"2001","unstructured":"Karnik, N., and Mendel, J., Centroid of a type-2 fuzzy set. Inf. Sci. 132(1\u20134):195\u2013220, 2001.","journal-title":"Inf. Sci."},{"key":"821_CR23","volume-title":"Uncertain rule-based fuzzy logic systems","author":"J Mendel","year":"2001","unstructured":"Mendel, J., Uncertain rule-based fuzzy logic systems. Prentice Hall PTR, Upper Saddle River, NJ, 2001."},{"issue":"1","key":"821_CR24","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.ins.2006.05.003","volume":"177","author":"J Mendel","year":"2007","unstructured":"Mendel, J., Advances in type-2 fuzzy sets and systems. Inf. Sci. 177(1):84\u2013110, 2007.","journal-title":"Inf. Sci."},{"issue":"7","key":"821_CR25","first-page":"26","volume":"3","author":"RA Sadek","year":"2012","unstructured":"Sadek, R.A., SVD based image processing applications: State of the art, contributions and research challenges. Int. J. Adv. Comput. Sci. Appl. 3(7):26\u201334, 2012.","journal-title":"Int. J. Adv. Comput. Sci. Appl"},{"key":"821_CR26","doi-asserted-by":"crossref","unstructured":"Castillo, O., and Melin, P., Type-2 fuzzy logic systems. In: Recent Advances in Interval Type-2 Fuzzy Systems. Berlin Heidelberg: Springer, ch. 2, pp. 7\u201312, 2012.","DOI":"10.1007\/978-3-642-28956-9_2"},{"key":"821_CR27","doi-asserted-by":"crossref","DOI":"10.1002\/9780470512517","volume-title":"Computational intelligence","author":"A Engelbrecht","year":"2007","unstructured":"Engelbrecht, A., Computational intelligence. John Wiley & Sons, Chichester, England, 2007."},{"key":"821_CR28","unstructured":"Cma.mgh.harvard.edu, 2016. [Online]. Available: http:\/\/www.cma.mgh.harvard.edu\/ibsr\/ . Accessed 04 Aug 2016."},{"key":"821_CR29","unstructured":"BrainWeb: Simulated Brain Database, Bic.mni.mcgill.ca, 2016. [Online]. Available: http:\/\/www.bic.mni.mcgill.ca\/brainweb\/ . Accessed 09 Jul 2016."},{"issue":"2","key":"821_CR30","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.engappai.2010.09.008","volume":"24","author":"A Demirhan","year":"2011","unstructured":"Demirhan, A., and G\u00fcler, \u0130., Combining stationary wavelet transform and self-organizing maps for brain MR image1 segmentation. Eng. Appl. Artif. Intell. 24(2):358\u2013367, 2011.","journal-title":"Eng. Appl. Artif. Intell."}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10916-017-0821-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-017-0821-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-017-0821-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,3]],"date-time":"2019-10-03T13:07:04Z","timestamp":1570108024000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10916-017-0821-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,19]]},"references-count":30,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2017,11]]}},"alternative-id":["821"],"URL":"https:\/\/doi.org\/10.1007\/s10916-017-0821-5","relation":{},"ISSN":["0148-5598","1573-689X"],"issn-type":[{"value":"0148-5598","type":"print"},{"value":"1573-689X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,9,19]]},"article-number":"174"}}