{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T14:17:47Z","timestamp":1775312267105,"version":"3.50.1"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2022,1]]},"DOI":"10.1007\/s11042-021-11221-3","type":"journal-article","created":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T08:05:47Z","timestamp":1635235547000},"page":"2333-2363","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A new intelligent system for diagnosing tumors with MR images using type-2 fuzzy neural network (T2FNN)"],"prefix":"10.1007","volume":"81","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5446-3479","authenticated-orcid":false,"given":"Vahid","family":"Rezaie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amir","family":"Parnianifard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,26]]},"reference":[{"key":"11221_CR1","doi-asserted-by":"publisher","first-page":"758","DOI":"10.1016\/j.asoc.2015.05.038","volume":"34","author":"SK Adhikari","year":"2015","unstructured":"Adhikari SK, Sing JK, Basu DK, Nasipuri M (2015) Conditional spatial fuzzy C-means clustering algorithm for segmentation of MRI images. Appl Soft Comput J 34:758\u2013769. https:\/\/doi.org\/10.1016\/j.asoc.2015.05.038","journal-title":"Appl Soft Comput J"},{"key":"11221_CR2","doi-asserted-by":"publisher","unstructured":"Ahmmed R, Rahman MA, Hossain MF (2018) Fuzzy logic based algorithm to classify tumor categories with position from brain MRI images. In: 3rd Int. Conf. Electr. Inf. Commun. Technol. EICT 2017, vol. 2018-Janua, no. December, pp 1\u20136. https:\/\/doi.org\/10.1109\/EICT.2017.8275232.","DOI":"10.1109\/EICT.2017.8275232"},{"key":"11221_CR3","doi-asserted-by":"publisher","unstructured":"Al-Badarneh A, Alrazqi A, Najadat H (2015) Performance impact of texture features on MRI image classification. In: ACM Int. Conf. Proceeding Ser., vol. 24\u201326-Sept. https:\/\/doi.org\/10.1145\/2832987.2833063","DOI":"10.1145\/2832987.2833063"},{"key":"11221_CR4","doi-asserted-by":"publisher","unstructured":"Behzadfar N, Soltanian-Zadeh H (2012) Automatic segmentation of brain tumors in magnetic resonance images. In: Proc. - IEEE-EMBS Int. Conf. Biomed. Heal. Informatics Glob. Gd. Chall. Heal. Informatics, BHI 2012, vol 21, pp. 329\u2013332. https:\/\/doi.org\/10.1109\/BHI.2012.6211580.","DOI":"10.1109\/BHI.2012.6211580"},{"key":"11221_CR5","doi-asserted-by":"publisher","unstructured":"Benson CC, Lajish VL, Rajamani K (2017) Robust classification of MR brain images based on fractal dimension analysis. In: 2017 Int. Conf. Adv. Comput. Commun. Informatics, ICACCI 2017, pp 1135\u20131140 https:\/\/doi.org\/10.1109\/ICACCI.2017.8125994.","DOI":"10.1109\/ICACCI.2017.8125994"},{"key":"11221_CR6","first-page":"38","volume":"626","author":"SAPS Blessy","year":"2014","unstructured":"Blessy SAPS, Sulochana CH (2014) Review on MRI brain tumor segmentation. Proc Comput Sci 626:38\u201343","journal-title":"Proc Comput Sci"},{"key":"11221_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-019-04635-7","author":"S Chatterjee","year":"2019","unstructured":"Chatterjee S, Das A (2019) A novel systematic approach to diagnose brain tumor using integrated type-II fuzzy logic and ANFIS (adaptive neuro-fuzzy inference system ) model. Soft Comput. https:\/\/doi.org\/10.1007\/s00500-019-04635-7","journal-title":"Soft Comput"},{"key":"11221_CR8","doi-asserted-by":"publisher","unstructured":"Chauhan S, More A, Uikey R, Malviya P, Moghe A (2018) Brain tumor detection and classification in MRI images using image and data mining. In: Int. Conf. Recent Innov. Signal Process. Embed. Syst. RISE, pp. 223\u2013231. https:\/\/doi.org\/10.1109\/RISE.2017.8378158.","DOI":"10.1109\/RISE.2017.8378158"},{"key":"11221_CR9","unstructured":"de Oliveira JMP (2011) Diagnostic techniques and surgical management of brain tumors. InTech"},{"issue":"2","key":"11221_CR10","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1148\/radiology.174.2.2153310","volume":"174","author":"BL Dean","year":"1990","unstructured":"Dean BL et al (1990) Gliomas: classification with MR imaging. Radiology 174(2):411\u2013415. https:\/\/doi.org\/10.1148\/radiology.174.2.2153310","journal-title":"Radiology"},{"key":"11221_CR11","doi-asserted-by":"crossref","unstructured":"Demirkaya O, Asyali MH, Sahoo PK (2008) Image processing with {MATLAB}: applications in medicine and biology","DOI":"10.1201\/9781420008937"},{"key":"11221_CR12","doi-asserted-by":"publisher","first-page":"257","DOI":"10.17482\/uumfd.270102","volume":"21","author":"B Dogan","year":"2016","unstructured":"Dogan B, Kazdal\u00c7alik S, Demir \u00d6 (2016) Computer-aided detection of brain tumors using morphological reconstruction. Uluda\u011f Univ J Fac Eng 21:257\u2013257. https:\/\/doi.org\/10.17482\/uumfd.270102","journal-title":"Uluda\u011f Univ J Fac Eng"},{"key":"11221_CR13","doi-asserted-by":"crossref","unstructured":"Drevelegas A (2011) Imaging of brain tumors with histological correlations","DOI":"10.1007\/978-3-540-87650-2"},{"key":"11221_CR14","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1016\/j.asoc.2009.11.019","volume":"11","author":"MH FazelZarandi","year":"2011","unstructured":"FazelZarandi MH, Zarinbal M, Izadi M (2011) Systematic image processing for diagnosing brain tumors: a Type-II fuzzy expert system approach. Appl Soft Comput J 11:285\u2013294. https:\/\/doi.org\/10.1016\/j.asoc.2009.11.019","journal-title":"Appl Soft Comput J"},{"key":"11221_CR15","first-page":"33","volume-title":"Digital image acquisition. Steganography in digital media","author":"J Fridrich","year":"2014","unstructured":"Fridrich J (2014) Digital image acquisition. Steganography in digital media. Cambridge University Press, Cambridge, pp 33\u201346"},{"issue":"4","key":"11221_CR16","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1007\/s00500-018-3053-9","volume":"23","author":"S Ghaemi","year":"2019","unstructured":"Ghaemi S, Sabahi K, Badamchizadeh MA (2019) Lyapunov\u2013Krasovskii stable T2FNN controller for a class of nonlinear time-delay systems. Soft Comput 23(4):1407\u20131419. https:\/\/doi.org\/10.1007\/s00500-018-3053-9","journal-title":"Soft Comput"},{"key":"11221_CR17","doi-asserted-by":"crossref","unstructured":"Gurbin\u0103 M, Lascu M, Lascu D (2019) Tumor detection and classification of MRI brain image using different wavelet transforms and support vector machines. pp 505\u2013508","DOI":"10.1109\/TSP.2019.8769040"},{"key":"11221_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105758","volume":"85","author":"A Halder","year":"2019","unstructured":"Halder A, Talukdar NA (2019) Robust brain magnetic resonance image segmentation using modified rough-fuzzy C-means with spatial constraints. Appl Soft Comput J 85:105758. https:\/\/doi.org\/10.1016\/j.asoc.2019.105758","journal-title":"Appl Soft Comput J"},{"key":"11221_CR19","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/j.neucom.2019.07.004","volume":"365","author":"HG Han","year":"2019","unstructured":"Han HG, Li JM, Wu XL, Qiao JF (2019) Cooperative strategy for constructing interval type-2 fuzzy neural network. Neurocomputing 365:249\u2013260. https:\/\/doi.org\/10.1016\/j.neucom.2019.07.004","journal-title":"Neurocomputing"},{"issue":"3","key":"11221_CR20","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/S1470-2045(05)01767-5","volume":"6","author":"JW Henson","year":"2005","unstructured":"Henson JW, Gaviani P, Gonzalez RG (2005) MRI in treatment of adult gliomas. Lancet Oncol 6(3):167\u2013175. https:\/\/doi.org\/10.1016\/S1470-2045(05)01767-5","journal-title":"Lancet Oncol"},{"key":"11221_CR21","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1016\/j.asoc.2016.03.014","volume":"46","author":"H Inbarani","year":"2016","unstructured":"Inbarani H (2016) Hybrid Tolerance Rough Set-Firefly based supervised feature selection for MRI brain tumor image classification. Appl Soft Comput J 46:639\u2013651. https:\/\/doi.org\/10.1016\/j.asoc.2016.03.014","journal-title":"Appl Soft Comput J"},{"key":"11221_CR22","doi-asserted-by":"publisher","unstructured":"Ismael MR, Abdel-Qader I (2018) Brain tumor classification via statistical features and back-propagation neural network. In: IEEE Int. Conf. Electro Inf. Technol. vol. 2018-May, pp 252\u2013257. https:\/\/doi.org\/10.1109\/EIT.2018.8500308.","DOI":"10.1109\/EIT.2018.8500308"},{"key":"11221_CR23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7091-8876-7","volume-title":"Therapy of Malignant Brain Tumors","author":"K Jellinger","year":"1986","unstructured":"Jellinger K (1986) Therapy of Malignant Brain Tumors. Springer Vienna, Vienna"},{"key":"11221_CR24","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1016\/j.asoc.2017.07.001","volume":"60","author":"S Kahali","year":"2017","unstructured":"Kahali S, Adhikari SK, Sing JK (2017) A two-stage fuzzy multi-objective framework for segmentation of 3D MRI brain image data. Appl Soft Comput J 60:312\u2013327. https:\/\/doi.org\/10.1016\/j.asoc.2017.07.001","journal-title":"Appl Soft Comput J"},{"key":"11221_CR25","doi-asserted-by":"publisher","DOI":"10.1007\/s10147-017-1110-5","author":"S Kar","year":"2017","unstructured":"Kar S, Majumder DD (2017) A mathematical theory of shape and neuro - fuzzy methodology - based diagnostic analysis\u202f: a comparative study on early detection and treatment planning of brain cancer. Int J Clin Oncol. https:\/\/doi.org\/10.1007\/s10147-017-1110-5","journal-title":"Int J Clin Oncol"},{"key":"11221_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105685","volume":"84","author":"R Karthik","year":"2019","unstructured":"Karthik R, Gupta U, Jha A, Rajalakshmi R, Menaka R (2019) A deep supervised approach for ischemic lesion segmentation from multimodal MRI using Fully Convolutional Network. Appl Soft Comput J 84:105685. https:\/\/doi.org\/10.1016\/j.asoc.2019.105685","journal-title":"Appl Soft Comput J"},{"key":"11221_CR27","first-page":"1","volume-title":"\u201cHistorical perspective\u201d, in Brain tumors","author":"AH Kaye","year":"2012","unstructured":"Kaye AH, Laws ER (2012) \u201cHistorical perspective\u201d, in Brain tumors. Elsevier, Amsterdam, pp 1\u20135"},{"key":"11221_CR28","doi-asserted-by":"publisher","DOI":"10.1109\/COASE.2019.8843018","author":"PM Kebria","year":"2019","unstructured":"Kebria PM, Khosravi A, Jalali SMJ, Nahavandi S (2019) Type-2 fuzzy neural network synchronization of teleoperation systems with delay and uncertainties. IEEE Int Conf Autom Sci Eng. https:\/\/doi.org\/10.1109\/COASE.2019.8843018","journal-title":"IEEE Int Conf Autom Sci Eng"},{"key":"11221_CR29","doi-asserted-by":"publisher","unstructured":"Keerthana T, Xavier S (2018) An intelligent system for early assessment and classification of brain tumor. In: Proc. Int. Conf. Inven. Commun. Comput. Technol. ICICCT 2018, no. Icicct, pp 1265\u20131268 https:\/\/doi.org\/10.1109\/ICICCT.2018.8473297","DOI":"10.1109\/ICICCT.2018.8473297"},{"key":"11221_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/s40815-019-00730-x","author":"T Le","year":"2019","unstructured":"Le T, Huynh T, Lin LLC, Chao F, Lin L (2019) A K-means interval type-2 fuzzy neural network for medical diagnosis. Int J Fuzzy Syst. https:\/\/doi.org\/10.1007\/s40815-019-00730-x","journal-title":"Int J Fuzzy Syst"},{"key":"11221_CR31","doi-asserted-by":"publisher","unstructured":"Le TL, Huynh TT, Lin CM, ChaoCF (2019) Breast cancer diagnosis using K-means type-2 fuzzy neural network. In: Proc 2018 IEEE Int. Conf. Syst. Man, Cybern. SMC 2018, pp 4150\u20134154. https:\/\/doi.org\/10.1109\/SMC.2018.00703","DOI":"10.1109\/SMC.2018.00703"},{"key":"11221_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2017.08.020","author":"X Liao","year":"2017","unstructured":"Liao X, Yin J, Guo S, Li X, Sangaiah AK (2017) Medical JPEG image steganography based on preserving inter-block dependencies. Comput Electr Eng. https:\/\/doi.org\/10.1016\/j.compeleceng.2017.08.020","journal-title":"Comput Electr Eng"},{"key":"11221_CR33","doi-asserted-by":"publisher","unstructured":"Mahmud MR, Mamun MA, Hossain MA, Uddin MP (2018) Comparative analysis of K-means and bisecting k-means algorithms for brain tumor detection. In: Int. Conf. Comput. Commun. Chem. Mater. Electron. Eng. IC4ME2 2018, pp 1\u20134. https:\/\/doi.org\/10.1109\/IC4ME2.2018.8465607.","DOI":"10.1109\/IC4ME2.2018.8465607"},{"issue":"9","key":"11221_CR34","doi-asserted-by":"publisher","first-page":"1689","DOI":"10.1017\/CBO9781107415324.004","volume":"53","author":"metode penelitian Nursalam","year":"2016","unstructured":"metode penelitian Nursalam (2016) Brain tumors practical guide to diagnosis and treatment. J Chem Inf Model 53(9):1689\u20131699. https:\/\/doi.org\/10.1017\/CBO9781107415324.004","journal-title":"J Chem Inf Model"},{"key":"11221_CR35","doi-asserted-by":"publisher","unstructured":"Nurhopipah A, Kusuma BA (2018) Multilevel clustering comparison using self-organizing map and K-means for MIR score clustering. In: Proc. - 2018 3rd Int. Conf. Inf. Technol. Inf. Syst. Electr. Eng. ICITISEE 2018, pp 235\u2013240. https:\/\/doi.org\/10.1109\/ICITISEE.2018.8720977","DOI":"10.1109\/ICITISEE.2018.8720977"},{"key":"11221_CR36","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1016\/j.asoc.2018.01.003","volume":"65","author":"TX Pham","year":"2018","unstructured":"Pham TX, Siarry P, Oulhadj H (2018) Integrating fuzzy entropy clustering with an improved PSO for MRI brain image segmentation. Appl Soft Comput J 65:230\u2013242. https:\/\/doi.org\/10.1016\/j.asoc.2018.01.003","journal-title":"Appl Soft Comput J"},{"issue":"60402021","key":"11221_CR37","doi-asserted-by":"publisher","DOI":"10.1117\/12.755417","volume":"6833","author":"B Qin","year":"2007","unstructured":"Qin B, Gu Z (2007) Robust adaptive non-rigid image registration based on joint salient point sets in the presence of tumor-like gross outliers. Electron Imaging Multimed Technol V 6833(60402021):683320. https:\/\/doi.org\/10.1117\/12.755417","journal-title":"Electron Imaging Multimed Technol V"},{"key":"11221_CR38","unstructured":"Russell J, Norvig P (2013) Artificial intelligence a modern approach"},{"key":"11221_CR39","doi-asserted-by":"publisher","unstructured":"Saeed S, Bin Abdullah A (2019) Investigation of a brain cancer with interfacing of 3-dimensional image processing. In: 2019 Int. Conf. Inf. Sci. Commun. Technol. ICISCT 2019, pp 1\u20136. https:\/\/doi.org\/10.1109\/CISCT.2019.8777404.","DOI":"10.1109\/CISCT.2019.8777404"},{"issue":"3","key":"11221_CR40","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1016\/j.cmpb.2012.10.010","volume":"109","author":"RS Santos","year":"2013","unstructured":"Santos RS, Malheiros SMF, Cavalheiro S, de Oliveira JMP (2013) A data mining system for providing analytical information on brain tumors to public health decision makers. Comput Methods Progr Biomed 109(3):269\u2013282. https:\/\/doi.org\/10.1016\/j.cmpb.2012.10.010","journal-title":"Comput Methods Progr Biomed"},{"key":"11221_CR41","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-012-9568-1","author":"K Selvaganesan","year":"2019","unstructured":"Selvaganesan K et al (2019) Adaptive type-2 fuzzy neural-network control for teleoperation systems with delay and uncertainties. Fuzzy Sets Syst. https:\/\/doi.org\/10.1007\/s10278-012-9568-1","journal-title":"Fuzzy Sets Syst"},{"key":"11221_CR42","doi-asserted-by":"publisher","DOI":"10.1007\/s40708-017-0075-5","author":"NV Shree","year":"2018","unstructured":"Shree NV (2018) Identification and classification of brain tumor MRI images with feature extraction using DWT and probabilistic neural network. Brain Inform. https:\/\/doi.org\/10.1007\/s40708-017-0075-5","journal-title":"Brain Inform"},{"issue":"3","key":"11221_CR43","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/sym9030037","volume":"9","author":"MF Siddiqui","year":"2017","unstructured":"Siddiqui MF, Mujtaba G, Reza AW, Shuib L (2017) Multi-class disease classification in brain MRIs using a computer-aided diagnostic system. Symmetry (Basel) 9(3):1\u201314. https:\/\/doi.org\/10.3390\/sym9030037","journal-title":"Symmetry (Basel)"},{"key":"11221_CR44","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1016\/j.asoc.2018.12.005","volume":"76","author":"C Singh","year":"2019","unstructured":"Singh C, Bala A (2019) A transform-based fast fuzzy C-means approach for high brain MRI segmentation accuracy. Appl Soft Comput J 76:156\u2013173. https:\/\/doi.org\/10.1016\/j.asoc.2018.12.005","journal-title":"Appl Soft Comput J"},{"key":"11221_CR45","doi-asserted-by":"publisher","DOI":"10.1007\/s12029-019-00279-w","author":"FH Siri","year":"2019","unstructured":"Siri FH, Salehiniya H (2019) Pancreatic cancer in Iran: an epidemiological review. J Gastrointest Cancer. https:\/\/doi.org\/10.1007\/s12029-019-00279-w","journal-title":"J Gastrointest Cancer"},{"issue":"1","key":"11221_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-019-12420-1","volume":"10","author":"D Sood","year":"2019","unstructured":"Sood D et al (2019) 3D extracellular matrix microenvironment in bioengineered tissue models of primary pediatric and adult brain tumors. Nat Commun 10(1):1\u201314. https:\/\/doi.org\/10.1038\/s41467-019-12420-1","journal-title":"Nat Commun"},{"key":"11221_CR47","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.automatica.2019.04.033","volume":"106","author":"D Sun","year":"2019","unstructured":"Sun D, Liao Q, Stoyanov T, Kiselev A, Loutfi A (2019) Bilateral telerobotic system using Type-2 fuzzy neural network based moving horizon estimation force observer for enhancement of environmental force compliance and human perception. Automatica 106:358\u2013373. https:\/\/doi.org\/10.1016\/j.automatica.2019.04.033","journal-title":"Automatica"},{"key":"11221_CR48","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.ymssp.2019.04.060","volume":"130","author":"H Taghavifar","year":"2019","unstructured":"Taghavifar H, Rakheja S (2019) Path-tracking of autonomous vehicles using a novel adaptive robust exponential-like-sliding-mode fuzzy type-2 neural network controller. Mech Syst Signal Process 130:41\u201355. https:\/\/doi.org\/10.1016\/j.ymssp.2019.04.060","journal-title":"Mech Syst Signal Process"},{"key":"11221_CR49","unstructured":"Toxicity Uncertainty (2018) Chapter 15: toxicity uncertainty, vol. 1711"},{"key":"11221_CR50","volume-title":"A deep clustering algorithm based on self-organizing map neural network","author":"Y Tao","year":"2018","unstructured":"Tao Y, Li Y, Lin X (2018) A deep clustering algorithm based on self-organizing map neural network, vol 2. Springer, New York"},{"key":"11221_CR51","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.nicl.2016.10.008","volume":"13","author":"HK van der Burgh","year":"2017","unstructured":"van der Burgh HK, Schmidt R, Westeneng HJ, de Reus MA, van den Berg LH, van den Heuvel MP (2017) Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis. NeuroImage Clin 13:361\u2013369. https:\/\/doi.org\/10.1016\/j.nicl.2016.10.008","journal-title":"NeuroImage Clin"},{"key":"11221_CR52","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.cmpb.2017.04.011","volume":"145","author":"I Varlamis","year":"2017","unstructured":"Varlamis I, Apostolakis I, Sifaki-Pistolla D, Dey N, Georgoulias V, Lionis C (2017) Application of data mining techniques and data analysis methods to measure cancer morbidity and mortality data in a regional cancer registry: The case of the island of Crete, Greece. Comput Methods Progr Biomed 145:73\u201383. https:\/\/doi.org\/10.1016\/j.cmpb.2017.04.011","journal-title":"Comput Methods Progr Biomed"},{"key":"11221_CR53","doi-asserted-by":"publisher","unstructured":"Wu Y, Yang W, Jiang J, Li S (2013) Semi-automatic segmentation of brain tumors using population and individual information. pp 786\u2013796. https:\/\/doi.org\/10.1007\/s10278-012-9568-1","DOI":"10.1007\/s10278-012-9568-1"},{"key":"11221_CR54","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-015-0311-6","volume":"39","author":"M Zarinbal","year":"2015","unstructured":"Zarinbal M, FazelZarandi MH, Turksen IB, Izadi M (2015) A type-2 fuzzy image processing expert system for diagnosing brain tumors. J Med Syst 39:1\u201320. https:\/\/doi.org\/10.1007\/s10916-015-0311-6","journal-title":"J Med Syst"},{"issue":"August","key":"11221_CR55","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1016\/j.engappai.2019.07.019","volume":"85","author":"X Zhu","year":"2019","unstructured":"Zhu X, Wang N (2019) Cuckoo search algorithm with onlooker bee search for modeling PEMFCs using T2FNN. Eng Appl Artif Intell 85(August):740\u2013753. https:\/\/doi.org\/10.1016\/j.engappai.2019.07.019","journal-title":"Eng Appl Artif Intell"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-11221-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-021-11221-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-11221-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T09:27:28Z","timestamp":1643448448000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-021-11221-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":55,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,1]]}},"alternative-id":["11221"],"URL":"https:\/\/doi.org\/10.1007\/s11042-021-11221-3","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,26]]},"assertion":[{"value":"4 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 February 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 July 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 October 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}