{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T14:04:27Z","timestamp":1780668267918,"version":"3.54.1"},"reference-count":79,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"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":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1007\/s13042-025-02971-9","type":"journal-article","created":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T06:21:32Z","timestamp":1775024492000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A multi-threshold image segmentation model for breast cancer based on enhanced ant colony algorithm by integrating wormhole strategy and generalized quadratic interpolation"],"prefix":"10.1007","volume":"17","author":[{"given":"Liang","family":"Zuo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Helong","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali Asghar","family":"Heidari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qike","family":"Shao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiling","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,1]]},"reference":[{"issue":"1","key":"2971_CR1","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/1994764","volume":"2021","author":"Y-n Zhang","year":"2021","unstructured":"Y-n Zhang 2021 Review of breast cancer pathologigcal image processing Biomed Res Int 2021 1 1994764","journal-title":"Biomed Res Int"},{"key":"2971_CR2","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-01680-1","author":"L Ahmed","year":"2020","unstructured":"L Ahmed 2020 Images data practices for semantic segmentation of breast cancer using deep neural network J Ambient Intell Humaniz Comput https:\/\/doi.org\/10.1007\/s12652-020-01680-1","journal-title":"J Ambient Intell Humaniz Comput"},{"issue":"1","key":"2971_CR3","first-page":"6841334","volume":"2022","author":"S Chaudhury","year":"2022","unstructured":"S Chaudhury 2022 [Retracted] effective image processing and segmentation-based machine learning techniques for diagnosis of breast cancer Comput Math Methods Med 2022 1 6841334","journal-title":"Comput Math Methods Med"},{"key":"2971_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104910","volume":"138","author":"L Liu","year":"2021","unstructured":"L Liu 2021 Performance optimization of differential evolution with slime mould algorithm for multilevel breast cancer image segmentation Comput Biol Med 138 104910","journal-title":"Comput Biol Med"},{"key":"2971_CR5","unstructured":"Fazilov SK, Yusupov O, Abdiyeva KS (2022) Mammography image segmentation in breast cancer identification using the Otsu method"},{"key":"2971_CR6","volume-title":"2022 4th International conference on applied machine learning (ICAML)","author":"S Gao","year":"2022","unstructured":"S Gao X Wang C Jin 2022 Analysis of multi-threshold image segmentation method based on improved sparrow search algorithm 2022 4th International conference on applied machine learning (ICAML) IEEE Geneva"},{"issue":"3","key":"2971_CR7","first-page":"804","volume":"2","author":"SS Al-Amri","year":"2010","unstructured":"SS Al-Amri N Kalyankar S Khamitkar 2010 Image segmentation by using edge detection Int J Comput Sci Eng 2 3 804 807","journal-title":"Int J Comput Sci Eng"},{"key":"2971_CR8","volume-title":"2009 Fifth international conference on intelligent information hiding and multimedia signal processing","author":"HG Kaganami","year":"2009","unstructured":"HG Kaganami Z Beiji 2009 Region-based segmentation versus edge detection 2009 Fifth international conference on intelligent information hiding and multimedia signal processing IEEE Geneva"},{"issue":"7","key":"2971_CR9","first-page":"3523","volume":"44","author":"S Minaee","year":"2021","unstructured":"S Minaee 2021 Image segmentation using deep learning: a survey IEEE Trans Pattern Anal Mach Intell 44 7 3523 3542","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2971_CR10","unstructured":"Al-Amri SS, Kalyankar NV (2010) Image segmentation by using threshold techniques. arXiv preprint arXiv:1005.4020, 2010."},{"key":"2971_CR11","doi-asserted-by":"publisher","first-page":"110587","DOI":"10.1016\/j.knosys.2023.110587","volume":"272","author":"SJ Mousavirad","year":"2023","unstructured":"SJ Mousavirad 2023 How effective are current population-based metaheuristic algorithms for variancE\u2013based multi-level image thresholding Knowl-Based Syst 272 110587","journal-title":"Knowl-Based Syst"},{"key":"2971_CR12","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1007\/978-3-030-70542-8_11","volume-title":"Metaheuristics in machine learning: theory and applications","author":"EH Houssein","year":"2021","unstructured":"EH Houssein 2021 Multi-level thresholding image segmentation based on nature-inspired optimization algorithms: a comprehensive review Metaheuristics in machine learning: theory and applications Springer Cham 239 265"},{"key":"2971_CR13","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.compstruc.2012.07.010","volume":"110","author":"H Eskandar","year":"2012","unstructured":"H Eskandar 2012 Water cycle algorithm\u2014a novel metaheuristic optimization method for solving constrained engineering optimization problems Comput Struct 110 151 166","journal-title":"Comput Struct"},{"issue":"8","key":"2971_CR14","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevD.93.086006","volume":"93","author":"AR Brown","year":"2016","unstructured":"AR Brown 2016 Complexity, action, and black holes Phys Rev D 93 8 086006","journal-title":"Phys Rev D"},{"issue":"1","key":"2971_CR15","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"2002","unstructured":"DH Wolpert WG Macready 2002 No free lunch theorems for optimization IEEE Trans Evol Comput 1 1 67 82","journal-title":"IEEE Trans Evol Comput"},{"issue":"3","key":"2971_CR16","doi-asserted-by":"publisher","first-page":"1155","DOI":"10.1016\/j.ejor.2006.06.046","volume":"185","author":"K Socha","year":"2008","unstructured":"K Socha M Dorigo 2008 Ant colony optimization for continuous domains Eur J Oper Res 185 3 1155 1173","journal-title":"Eur J Oper Res"},{"issue":"2","key":"2971_CR17","first-page":"125","volume":"3","author":"A Dariane","year":"2009","unstructured":"A Dariane A Moradi 2009 Reservoir operating by ant colony optimization for continuous domains (ACOR) case study: Dez reservoir Int J Math Phys Eng Sci 3 2 125 129","journal-title":"Int J Math Phys Eng Sci"},{"issue":"18","key":"2971_CR18","doi-asserted-by":"publisher","first-page":"3734","DOI":"10.1049\/gtd2.12560","volume":"16","author":"B Moradi","year":"2022","unstructured":"B Moradi A Kargar S Abazari 2022 Transient stability constrained optimal power flow solution using ant colony optimization for continuous domains (ACOR) IET Gener Transm Distrib 16 18 3734 3747","journal-title":"IET Gener Transm Distrib"},{"issue":"3","key":"2971_CR19","first-page":"1007","volume":"9","author":"D Zhao","year":"2022","unstructured":"D Zhao 2022 Opposition-based ant colony optimization with all-dimension neighborhood search for engineering design J Comput Des Eng 9 3 1007 1044","journal-title":"J Comput Des Eng"},{"key":"2971_CR20","volume-title":"Proceedings of the future of HVAC 2019 conference","author":"K Bamdad Masouleh","year":"2019","unstructured":"K Bamdad Masouleh 2019 Optimisation of HVAC systems using ACOr algorithm Proceedings of the future of HVAC 2019 conference The Australian Institute of Refrigeration, Air Conditioning and Heating (Inc) Melbourne"},{"key":"2971_CR21","doi-asserted-by":"publisher","first-page":"1063048","DOI":"10.3389\/fninf.2022.1063048","volume":"16","author":"Y Li","year":"2023","unstructured":"Y Li 2023 bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease Front Neuroinform 16 1063048","journal-title":"Front Neuroinform"},{"key":"2971_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107293","volume":"164","author":"Y Li","year":"2023","unstructured":"Y Li 2023 An optimized machine learning method for predicting wogonin therapy for the treatment of pulmonary hypertension Comput Biol Med 164 107293","journal-title":"Comput Biol Med"},{"key":"2971_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106704","volume":"213","author":"Y Fan","year":"2021","unstructured":"Y Fan 2021 A bioinformatic variant fruit fly optimizer for tackling optimization problems Knowl-Based Syst 213 106704","journal-title":"Knowl-Based Syst"},{"key":"2971_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107574","volume":"109","author":"AA Dehkordi","year":"2021","unstructured":"AA Dehkordi 2021 Nonlinear-based chaotic Harris hawks optimizer: algorithm and internet of vehicles application Appl Soft Comput 109 107574","journal-title":"Appl Soft Comput"},{"key":"2971_CR25","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1016\/j.matcom.2021.04.006","volume":"188","author":"C Chen","year":"2021","unstructured":"C Chen 2021 Dealing with multi-modality using synthesis of Moth-flame optimizer with sine cosine mechanisms Math Comput Simul 188 291 318","journal-title":"Math Comput Simul"},{"key":"2971_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104609","volume":"136","author":"L Liu","year":"2021","unstructured":"L Liu 2021 Ant colony optimization with Cauchy and greedy Levy mutations for multilevel COVID 19 X-ray image segmentation Comput Biol Med 136 104609","journal-title":"Comput Biol Med"},{"key":"2971_CR27","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2022.1041799","volume":"16","author":"X Yang","year":"2022","unstructured":"X Yang 2022 Multi-threshold image segmentation for melanoma based on Kapur\u2019s entropy using enhanced ant colony optimization Front Neuroinform 16 1041799","journal-title":"Front Neuroinform"},{"key":"2971_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106510","volume":"216","author":"D Zhao","year":"2021","unstructured":"D Zhao 2021 Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy Knowl-Based Syst 216 106510","journal-title":"Knowl-Based Syst"},{"key":"2971_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105810","volume":"148","author":"A Qi","year":"2022","unstructured":"A Qi 2022 Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation Comput Biol Med 148 105810","journal-title":"Comput Biol Med"},{"key":"2971_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2023.116446","volume":"417","author":"W Zhao","year":"2023","unstructured":"W Zhao 2023 Quadratic interpolation optimization (QIO): a new optimization algorithm based on generalized quadratic interpolation and its applications to real-world engineering problems Comput Methods Appl Mech Eng 417 116446","journal-title":"Comput Methods Appl Mech Eng"},{"issue":"2","key":"2971_CR31","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"S Mirjalili SM Mirjalili A Hatamlou 2016 Multi-verse optimizer: a naturE\u2013inspired algorithm for global optimization Neural Comput Appl 27 2 495 513","journal-title":"Neural Comput Appl"},{"key":"2971_CR32","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, 2017 9:2017"},{"issue":"10","key":"2971_CR33","doi-asserted-by":"publisher","first-page":"2044","DOI":"10.1016\/j.ins.2009.12.010","volume":"180","author":"S Garc\u00eda","year":"2010","unstructured":"S Garc\u00eda 2010 Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power Inf Sci 180 10 2044 2064","journal-title":"Inf Sci"},{"issue":"1","key":"2971_CR34","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"J Derrac 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 18","journal-title":"Swarm Evol Comput"},{"issue":"8","key":"2971_CR35","doi-asserted-by":"publisher","first-page":"2378","DOI":"10.1109\/TIP.2011.2109730","volume":"20","author":"L Zhang","year":"2011","unstructured":"L Zhang 2011 FSIM: a feature similarity index for image quality assessment IEEE Trans Image Process 20 8 2378 2386","journal-title":"IEEE Trans Image Process"},{"issue":"13","key":"2971_CR36","doi-asserted-by":"publisher","first-page":"800","DOI":"10.1049\/el:20080522","volume":"44","author":"Q Huynh-Thu","year":"2008","unstructured":"Q Huynh-Thu M Ghanbari 2008 Scope of validity of PSNR in image\/video quality assessment Electron Lett 44 13 800 801","journal-title":"Electron Lett"},{"key":"2971_CR37","volume-title":"2010 20th international conference on pattern recognition","author":"A Hore","year":"2010","unstructured":"A Hore D Ziou 2010 Image quality metrics: PSNR vs. SSIM 2010 20th international conference on pattern recognition IEEE Geneva"},{"issue":"1","key":"2971_CR38","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/0734-189X(89)90051-0","volume":"47","author":"AS Abutaleb","year":"1989","unstructured":"AS Abutaleb 1989 Automatic thresholding of gray-level pictures using two-dimensional entropy Computer Vis Graphics Image Process 47 1 22 32","journal-title":"Computer Vis Graphics Image Process"},{"issue":"285\u2013296","key":"2971_CR39","first-page":"23","volume":"11","author":"N Otsu","year":"1975","unstructured":"N Otsu 1975 A threshold selection method from gray-level histograms Automatica 11 285\u2013296 23 27","journal-title":"Automatica"},{"issue":"4","key":"2971_CR40","doi-asserted-by":"publisher","first-page":"617","DOI":"10.1016\/0031-3203(93)90115-D","volume":"26","author":"CH Li","year":"1993","unstructured":"CH Li C Lee 1993 Minimum cross entropy thresholding Pattern Recognit 26 4 617 625","journal-title":"Pattern Recognit"},{"issue":"3","key":"2971_CR41","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/0734-189X(85)90125-2","volume":"29","author":"JN Kapur","year":"1985","unstructured":"JN Kapur PK Sahoo AK Wong 1985 A new method for gray-level picture thresholding using the entropy of the histogram Computer Vis Graphics Image Process 29 3 273 285","journal-title":"Computer Vis Graphics Image Process"},{"key":"2971_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105522","volume":"97","author":"P Upadhyay","year":"2020","unstructured":"P Upadhyay JK Chhabra 2020 Kapur\u2019s entropy based optimal multilevel image segmentation using crow search algorithm Appl Soft Comput 97 105522","journal-title":"Appl Soft Comput"},{"issue":"3","key":"2971_CR43","doi-asserted-by":"publisher","first-page":"318","DOI":"10.3390\/e21030318","volume":"21","author":"C Lang","year":"2019","unstructured":"C Lang H Jia 2019 Kapur\u2019s entropy for color image segmentation based on a hybrid whale optimization algorithm Entropy 21 3 318","journal-title":"Entropy"},{"key":"2971_CR44","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/978-3-030-12931-6_8","volume-title":"Metaheuristic algorithms for image segmentation: theory and applications","author":"D Oliva","year":"2019","unstructured":"D Oliva M Abd Elaziz S Hinojosa 2019 Image segmentation using Kapur\u2019s entropy and a hybrid optimization algorithm Metaheuristic algorithms for image segmentation: theory and applications Springer Cham 85 99"},{"key":"2971_CR45","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.116511","volume":"194","author":"Y Chen","year":"2022","unstructured":"Y Chen 2022 Multi-threshold image segmentation using a multi-strategy shuffled frog leaping algorithm Expert Syst Appl 194 116511","journal-title":"Expert Syst Appl"},{"issue":"20","key":"2971_CR46","doi-asserted-by":"publisher","first-page":"14759","DOI":"10.1007\/s00500-023-08513-1","volume":"27","author":"G Ma","year":"2023","unstructured":"G Ma X Yue J Zhu 2023 Multi-threshold segmentation of grayscale and color images based on Kapur entropy by bald eagle search optimization algorithm with horizontal crossover and vertical crossover Soft Comput 27 20 14759 14790","journal-title":"Soft Comput"},{"issue":"4","key":"2971_CR47","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"R Storn K Price 1997 Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces J Glob Optim 11 4 341 359","journal-title":"J Glob Optim"},{"key":"2971_CR48","doi-asserted-by":"crossref","unstructured":"B\u00e4ck T (1995) Evolution strategies an alternative evolutionary algorithm. In: European conference on artificial evolution. Springer, Cham","DOI":"10.1007\/3-540-61108-8_27"},{"issue":"1","key":"2971_CR49","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","volume":"267","author":"JH Holland","year":"1992","unstructured":"JH Holland 1992 Genetic algorithms Sci Am 267 1 66 73","journal-title":"Sci Am"},{"issue":"6","key":"2971_CR50","doi-asserted-by":"publisher","first-page":"702","DOI":"10.1109\/TEVC.2008.919004","volume":"12","author":"D Simon","year":"2008","unstructured":"D Simon 2008 Biogeography-based optimization IEEE Trans Evol Comput 12 6 702 713","journal-title":"IEEE Trans Evol Comput"},{"key":"2971_CR51","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","volume":"96","author":"S Mirjalili","year":"2016","unstructured":"S Mirjalili 2016 SCA: a sine cosine algorithm for solving optimization problems Knowl-Based Syst 96 120 133","journal-title":"Knowl-Based Syst"},{"key":"2971_CR52","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121744","volume":"238","author":"S Zhao","year":"2024","unstructured":"S Zhao 2024 Triangulation topology aggregation optimizer: a novel mathematics-based meta-heuristic algorithm for continuous optimization and engineering applications Expert Syst Appl 238 121744","journal-title":"Expert Syst Appl"},{"issue":"1","key":"2971_CR53","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1214\/ss\/1177011077","volume":"8","author":"D Bertsimas","year":"1993","unstructured":"D Bertsimas J Tsitsiklis 1993 Simulated annealing Stat Sci 8 1 10 15","journal-title":"Stat Sci"},{"issue":"13","key":"2971_CR54","doi-asserted-by":"publisher","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","volume":"179","author":"E Rashedi","year":"2009","unstructured":"E Rashedi H Nezamabadi-Pour S Saryazdi 2009 GSA: a gravitational search algorithm Inf Sci 179 13 2232 2248","journal-title":"Inf Sci"},{"key":"2971_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110454","volume":"268","author":"M Abdel-Basset","year":"2023","unstructured":"M Abdel-Basset 2023 Kepler optimization algorithm: a new metaheuristic algorithm inspired by Kepler\u2019s laws of planetary motion Knowl-Based Syst 268 110454","journal-title":"Knowl-Based Syst"},{"key":"2971_CR56","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"S Mirjalili A Lewis 2016 The whale optimization algorithm Adv Eng Softw 95 51 67","journal-title":"Adv Eng Softw"},{"key":"2971_CR57","volume-title":"Proceedings of ICNN\u201995-international conference on neural networks","author":"J Kennedy","year":"1995","unstructured":"J Kennedy R Eberhart 1995 Particle swarm optimization Proceedings of ICNN\u201995-international conference on neural networks IEEE Geneva"},{"key":"2971_CR58","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.110011","volume":"259","author":"M Dehghani","year":"2023","unstructured":"M Dehghani 2023 Coati optimization algorithm: a new bio-inspired metaheuristic algorithm for solving optimization problems Knowl-Based Syst 259 110011","journal-title":"Knowl-Based Syst"},{"issue":"5","key":"2971_CR59","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1119\/1.15620","volume":"56","author":"MS Morris","year":"1988","unstructured":"MS Morris KS Thorne 1988 Wormholes in spacetime and their use for interstellar travel: a tool for teaching general relativity Am J Phys 56 5 395 412","journal-title":"Am J Phys"},{"issue":"9","key":"2971_CR60","doi-asserted-by":"publisher","first-page":"1322","DOI":"10.1109\/83.623195","volume":"6","author":"NA Dodgson","year":"1997","unstructured":"NA Dodgson 1997 Quadratic interpolation for image resampling IEEE Trans Image Process 6 9 1322 1326","journal-title":"IEEE Trans Image Process"},{"key":"2971_CR61","volume-title":"IEEE computer society conference on computer vision and pattern recognition (CVPR\u201905)","author":"A Buades","year":"2005","unstructured":"A Buades B Coll J-M Morel 2005 A non-local algorithm for image denoising IEEE computer society conference on computer vision and pattern recognition (CVPR\u201905) IEEE Geneva"},{"key":"2971_CR62","doi-asserted-by":"publisher","DOI":"10.1016\/j.imu.2020.100341","volume":"19","author":"H Bolhasani","year":"2020","unstructured":"H Bolhasani 2020 A histopathological image dataset for grading breast invasive ductal carcinomas Inf Med Unlocked 19 100341","journal-title":"Inf Med Unlocked"},{"key":"2971_CR63","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.eswa.2019.01.047","volume":"125","author":"M Abd Elaziz","year":"2019","unstructured":"M Abd Elaziz 2019 Multi-level thresholding-based grey scale image segmentation using multi-objective multi-verse optimizer Expert Syst Appl 125 112 129","journal-title":"Expert Syst Appl"},{"key":"2971_CR64","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.neucom.2023.02.010","volume":"532","author":"H Su","year":"2023","unstructured":"H Su 2023 RIME: a physics-based optimization Neurocomputing 532 183 214","journal-title":"Neurocomputing"},{"key":"2971_CR65","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120905","volume":"233","author":"Z Guan","year":"2023","unstructured":"Z Guan 2023 Great wall construction algorithm: a novel meta-heuristic algorithm for engineer problems Expert Syst Appl 233 120905","journal-title":"Expert Syst Appl"},{"issue":"7","key":"2971_CR66","doi-asserted-by":"publisher","first-page":"7305","DOI":"10.1007\/s11227-022-04959-6","volume":"79","author":"J Xue","year":"2023","unstructured":"J Xue B Shen 2023 Dung beetle optimizer: a new meta-heuristic algorithm for global optimization J Supercomput 79 7 7305 7336","journal-title":"J Supercomput"},{"key":"2971_CR67","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105075","volume":"114","author":"S Zhao","year":"2022","unstructured":"S Zhao 2022 Dandelion optimizer: a nature\u2013inspired metaheuristic algorithm for engineering applications Eng Appl Artif Intell 114 105075","journal-title":"Eng Appl Artif Intell"},{"key":"2971_CR68","unstructured":"Karaboga D (2005) An idea based on honey bee swarm for numerical optimization."},{"key":"2971_CR69","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"AA Heidari 2019 Harris hawks optimization: algorithm and applications Future Gener Comput Syst 97 849 872","journal-title":"Future Gener Comput Syst"},{"key":"2971_CR70","first-page":"17","volume":"31","author":"MA Elhosseini","year":"2019","unstructured":"MA Elhosseini 2019 Biped robot stability based on an A\u2013C parametric whale optimization algorithm J Comput Sci 31 17 32","journal-title":"Comput Sci"},{"issue":"6","key":"2971_CR71","doi-asserted-by":"publisher","first-page":"798","DOI":"10.1109\/TEVC.2010.2049361","volume":"15","author":"T-Y Sun","year":"2010","unstructured":"T-Y Sun 2010 Cluster guide particle swarm optimization (CGPSO) for underdetermined blind source separation with advanced conditions IEEE Trans Evol Comput 15 6 798 811","journal-title":"IEEE Trans Evol Comput"},{"key":"2971_CR72","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.07.031","volume":"138","author":"Z Cai","year":"2019","unstructured":"Z Cai 2019 Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy Expert Syst Appl 138 112814","journal-title":"Expert Syst Appl"},{"key":"2971_CR73","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2022.104373","volume":"80","author":"X Yang","year":"2023","unstructured":"X Yang 2023 Multi-level threshold segmentation framework for breast cancer images using enhanced differential evolution Biomed Signal Process Control 80 104373","journal-title":"Biomed Signal Process Control"},{"key":"2971_CR74","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.104592","volume":"82","author":"J Xing","year":"2023","unstructured":"J Xing 2023 Elite levy spreading differential evolution via ABC shrink-wrap for multi-threshold segmentation of breast cancer images Biomed Signal Process Control 82 104592","journal-title":"Biomed Signal Process Control"},{"issue":"1","key":"2971_CR75","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1117\/1.1631315","volume":"13","author":"S Mehmet","year":"2004","unstructured":"S Mehmet S B\u00fclent 2004 Survey over image thresholding techniques and quantitative performance evaluation J Electron Imaging 13 1 146 165","journal-title":"J Electron Imaging"},{"key":"2971_CR76","first-page":"713","volume":"17","author":"PS Liao","year":"2001","unstructured":"PS Liao TS Chen PC Chung 2001 A fast algorithm for multilevel thresholding J Inf Sci Eng 17 713 727","journal-title":"J Inf Sci Eng"},{"key":"2971_CR77","doi-asserted-by":"publisher","DOI":"10.1002\/9780470413791","volume-title":"The engineering design of systems: models and methods","author":"DM Buede","year":"2009","unstructured":"DM Buede 2009 The engineering design of systems: models and methods John Wiley & Sons Hoboken"},{"key":"2971_CR78","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107504","volume":"108","author":"L-L Li","year":"2021","unstructured":"L-L Li 2021 Improved tunicate swarm algorithm: solving the dynamic economic emission dispatch problems Appl Soft Comput 108 107504","journal-title":"Appl Soft Comput"},{"key":"2971_CR79","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2019.103375","volume":"112","author":"B Remeseiro","year":"2019","unstructured":"B Remeseiro V Bolon-Canedo 2019 A review of feature selection methods in medical applications Comput Biol Med 112 103375","journal-title":"Comput Biol Med"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-025-02971-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-025-02971-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-025-02971-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T13:04:17Z","timestamp":1780664657000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-025-02971-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,1]]},"references-count":79,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,5]]}},"alternative-id":["2971"],"URL":"https:\/\/doi.org\/10.1007\/s13042-025-02971-9","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,1]]},"assertion":[{"value":"24 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 September 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"245"}}