{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T13:23:24Z","timestamp":1777382604020,"version":"3.51.4"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"22","license":[{"start":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T00:00:00Z","timestamp":1750377600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T00:00:00Z","timestamp":1750377600000},"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":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2025,8]]},"DOI":"10.1007\/s00521-025-11391-3","type":"journal-article","created":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T04:59:24Z","timestamp":1750395564000},"page":"18609-18631","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Improved grasshopper optimization and modified moth\u2013flame optimization (IGH-MMFO) algorithm for identifying optimal threshold in image segmentation"],"prefix":"10.1007","volume":"37","author":[{"given":"K.","family":"Manikandan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B.","family":"Sudhakar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,20]]},"reference":[{"key":"11391_CR1","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/j.eswa.2018.09.008","volume":"116","author":"MH Merzban","year":"2019","unstructured":"Merzban MH, Elbayoumi M (2019) Efficient solution of Otsu multilevel image thresholding: a comparative study. Exp Syst Appl 116:299\u2013309","journal-title":"Exp Syst Appl"},{"issue":"1","key":"11391_CR2","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1007\/s10278-018-0111-x","volume":"32","author":"B Khorram","year":"2019","unstructured":"Khorram B, Yazdi M (2019) A new optimized thresholding method using ant colony algorithm for MR brain image segmentation. J Digit Imaging 32(1):162\u2013174","journal-title":"J Digit Imaging"},{"key":"11391_CR3","first-page":"1","volume":"16","author":"X Yang","year":"2022","unstructured":"Yang X, Ye X, Zhao D, Heidari AA, Zhangze Xu, Chen H, Li Y (2022) Multi-threshold image segmentation for melanoma based on Kapur\u2019s entropy using enhanced ant colony optimization. Neuroinform 16:1\u201327","journal-title":"Neuroinform"},{"issue":"6","key":"11391_CR4","doi-asserted-by":"publisher","first-page":"1471","DOI":"10.1109\/JAS.2017.7510697","volume":"6","author":"S Pare","year":"2019","unstructured":"Pare S, Kumar A, Bajaj V, Singh GK (2019) A context sensitive multilevel thresholding using swarm based algorithms. IEEE\/CAA J Automat Sinica 6(6):1471\u20131486","journal-title":"IEEE\/CAA J Automat Sinica"},{"issue":"1","key":"11391_CR5","first-page":"305","volume":"39","author":"XM ZhaoFeng","year":"2020","unstructured":"ZhaoFeng XM, Hanqiang L, Jiuluna F, Ronga L, XieWena ZY (2020) Adaptive multilevel thresholding based on multiobjective artificial bee colony optimization for noisy image segmentation. J Intell Fuzzy Syst 39(1):305\u2013323","journal-title":"J Intell Fuzzy Syst"},{"key":"11391_CR6","doi-asserted-by":"publisher","first-page":"26304","DOI":"10.1109\/ACCESS.2020.2971249","volume":"8","author":"AA Ewees","year":"2020","unstructured":"Ewees AA, Elaziz MA, Al-Qaness MAA, Khalil HA, Kim S (2020) Improved artificial bee colony using sine-cosine algorithm for multilevel thresholding image segmentation. IEEE Access 8:26304\u201326315","journal-title":"IEEE Access"},{"key":"11391_CR7","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.comcom.2020.08.010","volume":"162","author":"I Hilali-Jaghdam","year":"2020","unstructured":"Hilali-Jaghdam I, Ishak AB, Abdel-Khalek S, Jamal A (2020) Quantum and classical genetic algorithms for multilevel segmentation of medical images: a comparative study. Comput Commun 162:83\u201393","journal-title":"Comput Commun"},{"key":"11391_CR8","doi-asserted-by":"publisher","first-page":"76529","DOI":"10.1109\/ACCESS.2019.2921545","volume":"7","author":"X Bao","year":"2019","unstructured":"Bao X, Jia H, Lang C (2019) A novel hybrid harris hawks optimization for color image multilevel thresholding segmentation. IEEE Access 7:76529\u201376546","journal-title":"IEEE Access"},{"key":"11391_CR9","first-page":"1","volume":"2021","author":"J Qin","year":"2022","unstructured":"Qin J, Wang ChuTing, Qin GuiHe (2022) A multilevel image thresholding method based on subspace elimination optimization. Math Probl Eng 2021:1\u201312","journal-title":"Math Probl Eng"},{"key":"11391_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.engappai.2021.104410","volume":"105","author":"R Kurban","year":"2021","unstructured":"Kurban R, Durmus A, Karakose E (2021) A comparison of novel metaheuristic algorithms on color aerial image multilevel thresholding. Eng Appl Artif Intell 105:1\u201322","journal-title":"Eng Appl Artif Intell"},{"issue":"7","key":"11391_CR11","doi-asserted-by":"publisher","first-page":"4524","DOI":"10.1016\/j.jksuci.2020.10.030","volume":"34","author":"MK Naik","year":"2022","unstructured":"Naik MK, Panda R, Abraham A (2022) Normalized square difference based multilevel thresholding technique for multispectral images using leader slime mold algorithm. J King Saud Univ\u2013Comput Informat Sci 34(7):4524\u20134536","journal-title":"J King Saud Univ\u2013Comput Informat Sci"},{"key":"11391_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.compbiomed.2021.104427","volume":"134","author":"S Zhao","year":"2021","unstructured":"Zhao S, Wang P, Heidari AA, Chen H, Turabieh H, Mafarja M, Li C (2021) Multilevel threshold image segmentation with diffusion association slime mold algorithm and Renyi\u2019s entropy for chronic obstructive pulmonary disease. Comput Biol Med 134:1\u201325","journal-title":"Comput Biol Med"},{"key":"11391_CR13","doi-asserted-by":"publisher","first-page":"115003","DOI":"10.1016\/j.eswa.2021.115003","volume":"178","author":"J Anitha","year":"2021","unstructured":"Anitha J, Pandian SI, Agnes SA (2021) An efficient multilevel color image thresholding based on modified whale optimization algorithm. Exp Syst Appl 178:115003","journal-title":"Exp Syst Appl"},{"key":"11391_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.engappai.2021.104293","volume":"103","author":"B Jena","year":"2021","unstructured":"Jena B, Naik MK, Panda R, Abraham A (2021) Maximum 3D Tsallis entropy based multilevel thresholding of brain MR image using attacking Manta-Ray foraging optimization. Eng Appl Artif Intell 103:1\u201320","journal-title":"Eng Appl Artif Intell"},{"key":"11391_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eswa.2021.115651","volume":"185","author":"EH Houssein","year":"2021","unstructured":"Houssein EH, Emam MM, Ali AA (2021) An efficient multilevel thresholding segmentation method for thermography breast cancer imaging based on improved chimp optimization algorithm. Expert Syst Appl 185:1\u201325","journal-title":"Expert Syst Appl"},{"key":"11391_CR16","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1016\/j.procs.2020.03.418","volume":"167","author":"JD DorathiJayaseeli","year":"2020","unstructured":"DorathiJayaseeli JD, Malathi D (2020) An efficient automated road region extraction from high-resolution satellite images using improved cuckoo search with multilevel thresholding schema. Proc Comput Sci 167:1161\u20131170","journal-title":"Proc Comput Sci"},{"key":"11391_CR17","doi-asserted-by":"publisher","first-page":"114633","DOI":"10.1016\/j.eswa.2021.114633","volume":"174","author":"J Rahaman","year":"2021","unstructured":"Rahaman J, Sing M (2021) An efficient multilevel thresholding based satellite image segmentation approach using a new adaptive cuckoo search algorithm. Exp Syst Appl 174:114633","journal-title":"Exp Syst Appl"},{"key":"11391_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eswa.2020.114159","volume":"167","author":"EH Houssein","year":"2021","unstructured":"Houssein EH, Helmy B-D, Oliva D, Elngar AA, Shaban H (2021) A novel black widow optimization algorithm for multilevel thresholding image segmentation. Exp Syst Appl 167:1\u201347","journal-title":"Exp Syst Appl"},{"key":"11391_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eswa.2021.115107","volume":"181","author":"T Dutta","year":"2021","unstructured":"Dutta T, Dey S, Bhattacharyya S, Mukhopadhyay S, Chakrabarti P (2021) Hyperspectral multilevel image thresholding using qutrit genetic algorithm. Expert Syst Appl 181:1\u201319","journal-title":"Expert Syst Appl"},{"key":"11391_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.asoc.2020.106347","volume":"95","author":"MA Elaziz","year":"2020","unstructured":"Elaziz MA, Heidari AA, Fujita H, Moayedi H (2020) A competitive chain-based Harris hawks optimizer for global optimization and multilevel image thresholding problems. Appl Soft Comput 95:1\u201332","journal-title":"Appl Soft Comput"},{"issue":"5","key":"11391_CR21","doi-asserted-by":"publisher","first-page":"528","DOI":"10.1016\/j.jksuci.2018.04.007","volume":"33","author":"KB Resma","year":"2018","unstructured":"Resma KB, Nair MS (2018) Multilevel thresholding for image segmentation using Krill Herd optimization algorithm. J King Saud Univ-Comput Info Sci. 33(5):528\u2013541","journal-title":"J King Saud Univ-Comput Info Sci."},{"key":"11391_CR22","first-page":"1","volume":"97","author":"S JalaleddinMousavirad","year":"2020","unstructured":"JalaleddinMousavirad S, Ebrahimpour-Komleh H (2020) Human mental search-based multilevel thresholding for image segmentation. Appl Soft Comput 97:1\u201315","journal-title":"Appl Soft Comput"},{"issue":"2","key":"11391_CR23","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1002\/ima.22830","volume":"33","author":"Z Ye","year":"2022","unstructured":"Ye Z, Song Z, Li P, Wang M, Hou W (2022) A modified threshold score-based multilevel thresholding segmentation technique for brain magnetic resonance images using opposition-based learning hybrid rice optimization algorithm. Int J Imaging Syst Technol 33(2):622\u2013643","journal-title":"Int J Imaging Syst Technol"},{"issue":"4","key":"11391_CR24","doi-asserted-by":"publisher","first-page":"1256","DOI":"10.1002\/ima.22432","volume":"30","author":"LN Mahdy","year":"2020","unstructured":"Mahdy LN, Ezzat KA, Torad M, Hassanien AE (2020) Automatic segmentation system for liver tumors based on the multilevel thresholding and electromagnetism optimization algorithm. Int J Imaging Syst Technol 30(4):1256\u20131270","journal-title":"Int J Imaging Syst Technol"},{"key":"11391_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.swevo.2019.100591","volume":"51","author":"D Oliva","year":"2019","unstructured":"Oliva D, Nag S, Elaziz MA, Sarkar U, Hinojosa S (2019) Multilevel thresholding by fuzzy type II sets using evolutionary algorithms. Swarm Evolut Comput 51:1\u201337","journal-title":"Swarm Evolut Comput"},{"issue":"1","key":"11391_CR26","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1007\/s11063-024-11514-2","volume":"56","author":"H Alirezapour","year":"2024","unstructured":"Alirezapour H, Mansouri N, Zade BMH (2024) A comprehensive survey on feature selection with grasshopper optimization algorithm. Neural Process Lett 56(1):28","journal-title":"Neural Process Lett"},{"key":"11391_CR27","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.matcom.2023.12.022","volume":"219","author":"X Yu","year":"2024","unstructured":"Yu X, Wang H, Yangchen Lu (2024) An adaptive ranking moth flame optimizer for feature selection. Math Comput Simul 219:164\u2013184","journal-title":"Math Comput Simul"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-025-11391-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-025-11391-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-025-11391-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T20:31:19Z","timestamp":1757190679000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-025-11391-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,20]]},"references-count":27,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2025,8]]}},"alternative-id":["11391"],"URL":"https:\/\/doi.org\/10.1007\/s00521-025-11391-3","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,20]]},"assertion":[{"value":"13 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 June 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}