{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T06:19:29Z","timestamp":1777357169134,"version":"3.51.4"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T00:00:00Z","timestamp":1644969600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T00:00:00Z","timestamp":1644969600000},"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":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s11042-022-12168-9","type":"journal-article","created":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T19:02:25Z","timestamp":1645038145000},"page":"4979-5010","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Automatic multilevel image thresholding segmentation using hybrid bio-inspired algorithm and artificial neural network for histopathology images"],"prefix":"10.1007","volume":"82","author":[{"given":"Surbhi","family":"Vijh","sequence":"first","affiliation":[]},{"given":"Mukesh","family":"Saraswat","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0205-8412","authenticated-orcid":false,"given":"Sumit","family":"Kumar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,2,16]]},"reference":[{"key":"12168_CR1","doi-asserted-by":"crossref","unstructured":"Abd El Aziz M, Ewees AA, Hassanien AE, Mudhsh M, Xiong S (2018) Multi-objective whale optimization algorithm for multilevel thresholding segmentation. In: Advances in soft computing and machine learning in image processing, Springer, pp 23\u201339","DOI":"10.1007\/978-3-319-63754-9_2"},{"key":"12168_CR2","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.eswa.2017.04.023","volume":"83","author":"M Abd El aziz","year":"2017","unstructured":"Abd El aziz M, Ewees AA, Hassanien AE (2017) Whale optimization algorithm and moth-flame optimization for multilevel thresholding image segmentation. Expert Syst Appl 83:242\u2013256","journal-title":"Expert Syst Appl"},{"issue":"1","key":"12168_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-019-38813-2","volume":"9","author":"M Abdolhoseini","year":"2019","unstructured":"Abdolhoseini M, Kluge MG, Walker FR, Johnson SJ (2019) Segmentation of heavily clustered nuclei from histopathological images. Sci Report 9 (1):1\u201313","journal-title":"Sci Report"},{"key":"12168_CR4","first-page":"7","volume":"5","author":"N Almezeini","year":"2017","unstructured":"Almezeini N, Hafez A (2017) Task scheduling in cloud computing using lion optimization algorithm. Algorithms 5:7","journal-title":"Algorithms"},{"issue":"23","key":"12168_CR5","doi-asserted-by":"publisher","first-page":"12331","DOI":"10.1007\/s00500-019-03773-2","volume":"23","author":"P Bansal","year":"2019","unstructured":"Bansal P, Gupta S, Kumar S, Sharma S, Sharma S (2019) Mlp-loa: a metaheuristic approach to design an optimal multilayer perceptron. Soft Comput 23(23):12331\u201312345","journal-title":"Soft Comput"},{"issue":"4","key":"12168_CR6","first-page":"23","volume":"3","author":"A Belsare","year":"2012","unstructured":"Belsare A, Mushrif M (2012) Histopathological image analysis using image processing techniques: an overview. Signal & Image Process 3(4):23","journal-title":"Signal & Image Process"},{"key":"12168_CR7","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.eswa.2016.06.044","volume":"63","author":"AK Bhandari","year":"2016","unstructured":"Bhandari AK, Kumar A, Chaudhary S, Singh GK (2016) A novel color image multilevel thresholding based segmentation using nature inspired optimization algorithms. Expert Syst Appl 63:112\u2013133","journal-title":"Expert Syst Appl"},{"issue":"3","key":"12168_CR8","doi-asserted-by":"publisher","first-page":"1573","DOI":"10.1016\/j.eswa.2014.09.049","volume":"42","author":"AK Bhandari","year":"2015","unstructured":"Bhandari AK, Kumar A, Singh GK (2015) Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using kapur\u2019s, otsu and tsallis functions. Expert Syst Appl 42(3):1573\u20131601","journal-title":"Expert Syst Appl"},{"key":"12168_CR9","doi-asserted-by":"publisher","first-page":"101029","DOI":"10.1016\/j.pmcj.2019.05.010","volume":"58","author":"R Bhardwaj","year":"2019","unstructured":"Bhardwaj R, Kumar D (2019) Mofpl: multi-objective fractional particle lion algorithm for the energy aware routing in the wsn. Pervasive Mobile Comput 58:101029","journal-title":"Pervasive Mobile Comput"},{"issue":"1-2","key":"12168_CR10","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1007\/s12065-018-0168-y","volume":"11","author":"R Boothalingam","year":"2018","unstructured":"Boothalingam R (2018) Optimization using lion algorithm: a biological inspiration from lion\u2019s social behavior. Evol Intel 11(1-2):31\u201352","journal-title":"Evol Intel"},{"key":"12168_CR11","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1007\/978-3-030-17297-8_17","volume":"1","author":"RNvD Bosna cki","year":"2019","unstructured":"Bosna cki RNvD, VM (2019) Deep learning with convolutional neural networks for histopathology image analysis. Autom Reason Syst Biology Med 1:453\u2013469","journal-title":"Autom Reason Syst Biology Med"},{"issue":"1","key":"12168_CR12","first-page":"163","volume":"3","author":"S-C Chu","year":"2007","unstructured":"Chu S-C, Tsai P-W et al (2007) Computational intelligence based on the behavior of cats. Int J Innov Comput Inf Control 3(1):163\u2013173","journal-title":"Int J Innov Comput Inf Control"},{"key":"12168_CR13","doi-asserted-by":"crossref","unstructured":"Crawford B, Soto R, Caballero H, Olgu\u00edn E, Misra S (2016) Solving biobjective set covering problem using binary cat swarm optimization algorithm. In: international conference on computational science and its applications, Springer, pp 220\u2013231","DOI":"10.1007\/978-3-319-42085-1_17"},{"key":"12168_CR14","doi-asserted-by":"crossref","unstructured":"Cruz MA, Roa AA, Ovalle JEA, OFAG (2013) A deep learning architecture for image representation, visual interpretability and automated basal cell carcinoma cancer detection. In: international conference on medical image computing and computer-assisted intervention, Nagoya, Japan, pp 403\u2013410","DOI":"10.1007\/978-3-642-40763-5_50"},{"key":"12168_CR15","doi-asserted-by":"crossref","unstructured":"\u00c7etin M, Dokur Z, \u00d6lmez T (2019) Fuzzy local information c-means algorithm for histopathological image segmentation. In: Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT). IEEE, vol 2019, pp 1\u20136","DOI":"10.1109\/EBBT.2019.8742034"},{"issue":"3","key":"12168_CR16","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1134\/S1054661819030052","volume":"29","author":"KG Dhal","year":"2019","unstructured":"Dhal KG, Das A, Ray S, Das S (2019) A clustering based classification approach based on modified cuckoo search algorithm. Pattern Recogn Image Anal 29(3):344\u2013359","journal-title":"Pattern Recogn Image Anal"},{"issue":"03","key":"12168_CR17","first-page":"126","volume":"2","author":"SP Duraisamy","year":"2010","unstructured":"Duraisamy SP, Kayalvizhi R et al (2010) A new multilevel thresholding method using swarm intelligence algorithm for image segmentation. J Intell Learn Syst Appl 2(03):126","journal-title":"J Intell Learn Syst Appl"},{"issue":"4","key":"12168_CR18","doi-asserted-by":"publisher","first-page":"934","DOI":"10.1109\/TIM.2009.2030931","volume":"59","author":"H Gao","year":"2009","unstructured":"Gao H, Xu W, Sun J, Tang Y (2009) Multilevel thresholding for image segmentation through an improved quantum-behaved particle swarm algorithm. IEEE Trans Instrument Measure 59(4):934\u2013946","journal-title":"IEEE Trans Instrument Measure"},{"issue":"1","key":"12168_CR19","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/s10044-018-0729-9","volume":"23","author":"F Garc\u00eda-Lamont","year":"2020","unstructured":"Garc\u00eda-Lamont F, Cervantes J, L\u00f3pez-Chau A, Yee-Rend\u00f3n A (2020) Automatic computing of number of clusters for color image segmentation employing fuzzy c-means by extracting chromaticity features of colors. Pattern Anal Applic 23(1):59\u201384","journal-title":"Pattern Anal Applic"},{"key":"12168_CR20","doi-asserted-by":"crossref","unstructured":"Geetha K, Anitha V, Elhoseny M, Kathiresan S, Shamsolmoali P, Selim MM (2020) An evolutionary lion optimization algorithm-based image compression technique for biomedical applications. Expert Syst, e12508","DOI":"10.1111\/exsy.12508"},{"key":"12168_CR21","doi-asserted-by":"crossref","unstructured":"Ghosh M, Chakraborty C, Ray AK (2013) Yager\u2019s measure based fuzzy divergence for microscopic color image segmentation. In: 2013 Indian Conference on Medical Informatics and Telemedicine (ICMIT). IEEE, pp 13\u201316","DOI":"10.1109\/IndianCMIT.2013.6529400"},{"key":"12168_CR22","doi-asserted-by":"crossref","unstructured":"Ghosh M, Das D, Chakraborty C (2010) Entropy based divergence for leukocyte image segmentation. In: 2010 International Conference on Systems in Medicine and Biology. IEEE, pp 409\u2013413","DOI":"10.1109\/ICSMB.2010.5735414"},{"issue":"3","key":"12168_CR23","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1007\/s00500-016-2385-6","volume":"22","author":"S Gu","year":"2018","unstructured":"Gu S, Cheng R, Jin Y (2018) Feature selection for high-dimensional classification using a competitive swarm optimizer. Soft Comput 22(3):811\u2013822","journal-title":"Soft Comput"},{"key":"12168_CR24","first-page":"7","volume":"1","author":"J Guo","year":"2015","unstructured":"Guo J, Sun Z, Tang H, Yin L, Zhang Z (2015) Improved cat swarm optimization algorithm for assembly sequence planning. Open Autom Control Syst J 1:7","journal-title":"Open Autom Control Syst J"},{"issue":"2","key":"12168_CR25","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.cviu.2007.09.001","volume":"109","author":"K Hammouche","year":"2008","unstructured":"Hammouche K, Diaf M, Siarry P (2008) A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation. Comput Vis Image Underst 109(2):163\u2013175","journal-title":"Comput Vis Image Underst"},{"key":"12168_CR26","doi-asserted-by":"crossref","unstructured":"Huang X, He H, Wei P, Zhang C, Zhang J, Chen J (2019) Tumor tissue segmentation for histopathological images. In: Proceedings of the ACM Multimedia Asia, pp 1\u20134","DOI":"10.1145\/3338533.3372210"},{"issue":"10","key":"12168_CR27","doi-asserted-by":"publisher","first-page":"1926","DOI":"10.1109\/TIP.2008.2001047","volume":"17","author":"DE Ilea","year":"2008","unstructured":"Ilea DE, Whelan PF (2008) Ctex\u2014an adaptive unsupervised segmentation algorithm based on color-texture coherence. IEEE Trans Image Process 17(10):1926\u20131939","journal-title":"IEEE Trans Image Process"},{"key":"12168_CR28","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1109\/RBME.2013.2295804","volume":"7","author":"H Irshad","year":"2013","unstructured":"Irshad H, Veillard A, Roux L, Racoceanu D (2013) Methods for nuclei detection, segmentation, and classification in digital histopathology: a review\u2014current status and future potential. IEEE Rev Biomed Eng 7:97\u2013114","journal-title":"IEEE Rev Biomed Eng"},{"key":"12168_CR29","doi-asserted-by":"crossref","unstructured":"Jayaraman V, Sultana HP (2019) Artificial gravitational cuckoo search algorithm along with particle bee optimized associative memory neural network for feature selection in heart disease classification, J Ambient Intell Human Comput, 1\u201310","DOI":"10.1007\/s12652-019-01193-6"},{"issue":"1","key":"12168_CR30","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1007\/s10462-016-9494-6","volume":"48","author":"JAA Jothi","year":"2017","unstructured":"Jothi JAA, Rajam VMA (2017) A survey on automated cancer diagnosis from histopathology images. Artif Intell Rev 48(1):31\u201381","journal-title":"Artif Intell Rev"},{"key":"12168_CR31","doi-asserted-by":"crossref","unstructured":"Jothi J. A. a., Rajam VMA (2015) Segmentation of nuclei from breast histopathology images using pso-based otsu\u2019s multilevel thresholding. In: artificial intelligence and evolutionary algorithms in engineering systems, Springer, pp 835\u2013843","DOI":"10.1007\/978-81-322-2135-7_88"},{"key":"12168_CR32","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1016\/j.asoc.2016.02.030","volume":"46","author":"JAA Jothi","year":"2016","unstructured":"Jothi JAA, Rajam VMA (2016) Effective segmentation and classification of thyroid histopathology images. Appl Soft Comput 46:652\u2013664","journal-title":"Appl Soft Comput"},{"key":"12168_CR33","doi-asserted-by":"crossref","unstructured":"Kate V, Shukla P (2020) Image segmentation of breast cancer histopathology images using pso-based clustering technique. In: Social Networking and Computational Intelligence, Springer, pp 207\u2013216","DOI":"10.1007\/978-981-15-2071-6_17"},{"issue":"8","key":"12168_CR34","first-page":"1349","volume":"2","author":"A Kaur","year":"2012","unstructured":"Kaur A, Singh M (2012) An overview of pso-based approaches in image segmentation. Int J Eng Technol 2(8):1349\u20131357","journal-title":"Int J Eng Technol"},{"issue":"2","key":"12168_CR35","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1007\/s11042-012-1003-6","volume":"64","author":"A Khan","year":"2013","unstructured":"Khan A, Jaffar MA, Choi T-S (2013) Som and fuzzy based color image segmentation. Multimed Tool Appl 64(2):331\u2013344","journal-title":"Multimed Tool Appl"},{"key":"12168_CR36","doi-asserted-by":"crossref","unstructured":"Kirti AS (2020) Csbiist: cuckoo search-based intelligent image segmentation, Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications, 323","DOI":"10.1016\/B978-0-12-819714-1.00028-2"},{"issue":"3-4","key":"12168_CR37","first-page":"143","volume":"1","author":"C-C Lai","year":"2004","unstructured":"Lai C-C, Tseng D-C (2004) A hybrid approach using gaussian smoothing and genetic algorithm for multilevel thresholding. Int J Hybrid Intell Syst 1 (3-4):143\u2013152","journal-title":"Int J Hybrid Intell Syst"},{"issue":"2","key":"12168_CR38","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/0734-189X(90)90053-X","volume":"52","author":"SU Lee","year":"1990","unstructured":"Lee SU, Chung SY, Park RH (1990) A comparative performance study of several global thresholding techniques for segmentation. Comput Vis Graph Image Process 52(2):171\u2013190","journal-title":"Comput Vis Graph Image Process"},{"key":"12168_CR39","doi-asserted-by":"crossref","unstructured":"Lei X, Fu A (2008) Two-dimensional maximum entropy image segmentation method based on quantum-behaved particle swarm optimization algorithm. In: 2008 fourth international conference on natural computation, vol 3. IEEE, pp 692\u2013696","DOI":"10.1109\/ICNC.2008.822"},{"issue":"1","key":"12168_CR40","doi-asserted-by":"publisher","first-page":"16","DOI":"10.3390\/info8010016","volume":"8","author":"L Li","year":"2017","unstructured":"Li L, Sun L, Guo J, Han C, Zhou J, Li S (2017) A quick artificial bee colony algorithm for image thresholding. Information 8(1):16","journal-title":"Information"},{"issue":"12","key":"12168_CR41","doi-asserted-by":"publisher","first-page":"89949","DOI":"10.17485\/ijst\/2016\/v9i12\/89949","volume":"9","author":"KS Manic","year":"2016","unstructured":"Manic KS, Priya RK, Rajinikanth V (2016) Image multithresholding based on kapur\/tsallis entropy and firefly algorithm. Indian J Sci Technol 9 (12):89949","journal-title":"Indian J Sci Technol"},{"key":"12168_CR42","doi-asserted-by":"crossref","unstructured":"Masood A, Al-Jumaily A (2015) Differential evolution based advised svm for histopathalogical image analysis for skin cancer detection. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, pp 781\u2013784","DOI":"10.1109\/EMBC.2015.7318478"},{"key":"12168_CR43","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Lewis A (2016) The whale optimization algorithm. Advan Eng Software 95:51\u201367","journal-title":"Advan Eng Software"},{"key":"12168_CR44","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.engappai.2018.03.001","volume":"71","author":"H Mittal","year":"2018","unstructured":"Mittal H, Saraswat M (2018) An optimum multi-level image thresholding segmentation using non-local means 2d histogram and exponential kbest gravitational search algorithm. Eng Appl Artif Intell 71:226\u2013235","journal-title":"Eng Appl Artif Intell"},{"key":"12168_CR45","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/j.eswa.2016.08.046","volume":"65","author":"U Mlakar","year":"2016","unstructured":"Mlakar U, Poto\u010dnik B, Best J (2016) A hybrid differential evolution for optimal multilevel image thresholding. Expert Syst Appl 65:221\u2013232","journal-title":"Expert Syst Appl"},{"key":"12168_CR46","doi-asserted-by":"crossref","unstructured":"Olorunda O, Engelbrecht AP (2008) Measuring exploration\/exploitation in particle swarms using swarm diversity. In: 2008 IEEE congress on evolutionary computation (IEEE world congress on computational intelligence). IEEE, pp 1128\u20131134","DOI":"10.1109\/CEC.2008.4630938"},{"key":"12168_CR47","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.procs.2018.05.057","volume":"132","author":"\u015e \u00d6zt\u00fcrk","year":"2018","unstructured":"\u00d6zt\u00fcrk \u015e, Akdemir B (2018) Application of feature extraction and classification methods for histopathological image using glcm, lbp, lbglcm, glrlm and sfta. Procedia Comput Sci 132:40\u201346","journal-title":"Procedia Comput Sci"},{"issue":"4","key":"12168_CR48","first-page":"267","volume":"6","author":"AD Purohit","year":"2017","unstructured":"Purohit AD, Khandare S (2017) A survey on different color image segmentation techniques using multilevel thresholding. Int J Comput Sci Mobile Comput 6(4):267\u2013273","journal-title":"Int J Comput Sci Mobile Comput"},{"key":"12168_CR49","doi-asserted-by":"crossref","unstructured":"Rajakumar B (2014) Lion algorithm for standard and large scale bilinear system identification: a global optimization based on lion\u2019s social behavior. In: in 2014 IEEE congress on evolutionary computation (CEC). IEEE, pp 2116\u20132123","DOI":"10.1109\/CEC.2014.6900561"},{"issue":"10","key":"12168_CR50","doi-asserted-by":"publisher","first-page":"4209","DOI":"10.1007\/s00330-017-4813-0","volume":"27","author":"M Rusu","year":"2017","unstructured":"Rusu M, Rajiah P, Gilkeson R, Yang M, Donatelli C, Thawani R, Jacono FJ, Linden P, Madabhushi A (2017) Co-registration of pre-operative ct with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study. Eur Radiol 27(10):4209\u20134217","journal-title":"Eur Radiol"},{"issue":"2","key":"12168_CR51","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/0734-189X(88)90022-9","volume":"41","author":"PK Sahoo","year":"1988","unstructured":"Sahoo PK, Soltani S, Wong AK (1988) A survey of thresholding techniques. Comput Vis Graph Image Process 41(2):233\u2013260","journal-title":"Comput Vis Graph Image Process"},{"key":"12168_CR52","unstructured":"Samantaa S, Dey N, Das P, Acharjee S, Chaudhuri SS (2013) Multilevel threshold based gray scale image segmentation using cuckoo search, arXiv:https:\/\/doi.org\/abs\/1307.0277"},{"key":"12168_CR53","unstructured":"Shu J, Fu H, Qiu G, Kaye P, Ilyas M (2013) Segmenting overlapping cell nuclei in digital histopathology images. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, pp 5445\u20135448"},{"issue":"10","key":"12168_CR54","doi-asserted-by":"publisher","first-page":"3225","DOI":"10.1093\/bioinformatics\/btaa107","volume":"36","author":"J Shu","year":"2020","unstructured":"Shu J, Liu J, Zhang Y, Fu H, Ilyas M, Faraci G, Della Mea V, Liu B, Qiu G (2020) Marker controlled superpixel nuclei segmentation and automatic counting on immunohistochemistry staining images. Bioinformatics 36 (10):3225\u20133233","journal-title":"Bioinformatics"},{"issue":"7","key":"12168_CR55","doi-asserted-by":"publisher","first-page":"1455","DOI":"10.1109\/TBME.2015.2496264","volume":"63","author":"FA Spanhol","year":"2015","unstructured":"Spanhol FA, Oliveira LS, Petitjean C, Heutte L (2015) A dataset for breast cancer histopathological image classification. IEEE Trans Biomed Eng 63 (7):1455\u20131462","journal-title":"IEEE Trans Biomed Eng"},{"issue":"2","key":"12168_CR56","first-page":"202","volume":"22","author":"Y-G Tang","year":"2007","unstructured":"Tang Y-G, Liu D, Guan X-P (2007) Fast image segmentation based on particle swarm optimization and two-dimension otsu method. Control Decision 22 (2):202","journal-title":"Control Decision"},{"issue":"3","key":"12168_CR57","doi-asserted-by":"publisher","first-page":"356","DOI":"10.3390\/pr8030356","volume":"8","author":"A-Q Tian","year":"2020","unstructured":"Tian A-Q, Chu S-C, Pan J-S, Liang Y (2020) A novel pigeon-inspired optimization based mppt technique for pv systems. Processes 8(3):356","journal-title":"Processes"},{"issue":"7","key":"12168_CR58","doi-asserted-by":"publisher","first-page":"e70221","DOI":"10.1371\/journal.pone.0070221","volume":"8","author":"M Veta","year":"2013","unstructured":"Veta M, Van Diest PJ, Kornegoor R, Huisman A, Viergever MA, Pluim JP (2013) Automatic nuclei segmentation in h&e stained breast cancer histopathology images. PloS One 8(7):e70221","journal-title":"PloS One"},{"key":"12168_CR59","doi-asserted-by":"crossref","unstructured":"Vijh S, Sharma S, Gaurav P (2020) Brain tumor segmentation using otsu embedded adaptive particle swarm optimization method and convolutional neural network. In: data visualization and knowledge engineering, Springer, pp 171\u2013194","DOI":"10.1007\/978-3-030-25797-2_8"},{"key":"12168_CR60","doi-asserted-by":"crossref","unstructured":"Vishnoi S, Jain AK, Sharma PK (2019) A nuclei segmentation method based on whale optimization algorithm fuzzy clustering in histopathological images. In: 2019 4th International Conference on Information Systems and Computer Networks (ISCON), IEEE, pp 728\u2013732","DOI":"10.1109\/ISCON47742.2019.9036184"},{"issue":"10","key":"12168_CR61","doi-asserted-by":"publisher","first-page":"2369","DOI":"10.1007\/s11432-012-4548-0","volume":"55","author":"B Wang","year":"2012","unstructured":"Wang B, Jin X, Cheng B (2012) Lion pride optimizer: an optimization algorithm inspired by lion pride behavior. Sci China Inf Sci 55(10):2369\u20132389","journal-title":"Sci China Inf Sci"},{"key":"12168_CR62","unstructured":"Wu G, Mallipeddi R, Suganthan PN (2017) Problem definitions and evaluation criteria for the cec 2017 competition on constrained real-parameter optimization, National University of Defense Technology, Changsha, Hunan, PR China and Kyungpook National University, Daegu, South Korea and Nanyang Technological University, Singapore, Technical Report"},{"key":"12168_CR63","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1016\/j.neucom.2016.01.034","volume":"191","author":"J Xu","year":"2016","unstructured":"Xu J, Luo X, Wang G, Gilmore H, Madabhushi A (2016) A deep convolutional neural network for segmenting and classifying epithelial and stromal regions in histopathological images. Neurocomputing 191:214\u2013223","journal-title":"Neurocomputing"},{"issue":"1","key":"12168_CR64","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1109\/TMI.2015.2458702","volume":"35","author":"J Xu","year":"2015","unstructured":"Xu J, Xiang L, Liu Q, Gilmore H, Wu J, Tang J, Madabhushi A (2015) Stacked sparse autoencoder (ssae) for nuclei detection on breast cancer histopathology images. IEEE Trans Med Imag 35(1):119\u2013130","journal-title":"IEEE Trans Med Imag"},{"issue":"3-4","key":"12168_CR65","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/0020-0255(94)00030-F","volume":"82","author":"RR Yager","year":"1995","unstructured":"Yager RR (1995) Measures of entropy and fuzziness related to aggregation operators. Inf Sci 82(3-4):147\u2013166","journal-title":"Inf Sci"},{"issue":"5","key":"12168_CR66","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1016\/S0031-3203(99)00094-1","volume":"33","author":"Y Yang","year":"2000","unstructured":"Yang Y, Yan H (2000) An adaptive logical method for binarization of degraded document images. Pattern Recogn 33(5):787\u2013807","journal-title":"Pattern Recogn"},{"issue":"1","key":"12168_CR67","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.jcde.2015.06.003","volume":"3","author":"M Yazdani","year":"2016","unstructured":"Yazdani M, Jolai F (2016) Lion optimization algorithm (loa): a nature-inspired metaheuristic algorithm. J Comput Design Eng 3(1):24\u201336","journal-title":"J Comput Design Eng"},{"issue":"2","key":"12168_CR68","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/S0165-1684(98)00167-4","volume":"72","author":"P-Y Yin","year":"1999","unstructured":"Yin P-Y (1999) A fast scheme for optimal thresholding using genetic algorithms. Signal Process 72(2):85\u201395","journal-title":"Signal Process"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-12168-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-12168-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-12168-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T08:19:08Z","timestamp":1674634748000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-12168-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,16]]},"references-count":68,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["12168"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-12168-9","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,16]]},"assertion":[{"value":"16 December 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 January 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 February 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}