{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T09:41:42Z","timestamp":1784626902770,"version":"3.55.0"},"reference-count":73,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T00:00:00Z","timestamp":1702339200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T00:00:00Z","timestamp":1702339200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Thuyloi University Foundation for Science and Technology","award":["TLU.STF.23-05"],"award-info":[{"award-number":["TLU.STF.23-05"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,3]]},"DOI":"10.1007\/s00521-023-09294-2","type":"journal-article","created":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T14:02:11Z","timestamp":1702389731000},"page":"4325-4347","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Medical image fusion based on transfer learning techniques and coupled neural P systems"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8050-4086","authenticated-orcid":false,"given":"Phu-Hung","family":"Dinh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nguyen Long","family":"Giang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,12,12]]},"reference":[{"key":"9294_CR1","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.inffus.2020.07.006","volume":"64","author":"YD Zhang","year":"2020","unstructured":"Zhang YD, Dong Z, Wang SH, Yu X, Yao X, Zhou Q, Hu H, Li M, Jim\u00e9nez-Mesa C, Ramirez J, Martinez FJ, Gorriz JM (2020) Advances in multimodal data fusion in neuroimaging: overview, challenges, and novel orientation. Inf Fusion 64:149\u2013187. https:\/\/doi.org\/10.1016\/j.inffus.2020.07.006","journal-title":"Inf Fusion"},{"key":"9294_CR2","doi-asserted-by":"publisher","first-page":"108036","DOI":"10.1016\/j.sigpro.2021.108036","volume":"183","author":"H Hermessi","year":"2021","unstructured":"Hermessi H, Mourali O, Zagrouba E (2021) Multimodal medical image fusion review: theoretical background and recent advances. Signal Process 183:108036. https:\/\/doi.org\/10.1016\/j.sigpro.2021.108036","journal-title":"Signal Process"},{"key":"9294_CR3","doi-asserted-by":"publisher","first-page":"105253","DOI":"10.1016\/j.compbiomed.2022.105253","volume":"144","author":"MA Azam","year":"2022","unstructured":"Azam MA, Khan KB, Salahuddin S, Rehman E, Khan SA, Khan MA, Kadry S, Gandomi AH (2022) A review on multimodal medical image fusion: compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics. Comput Biol Med 144:105253. https:\/\/doi.org\/10.1016\/j.compbiomed.2022.105253","journal-title":"Comput Biol Med"},{"key":"9294_CR4","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1016\/j.neucom.2016.02.047","volume":"194","author":"J Du","year":"2016","unstructured":"Du J, Li W, Xiao B, Nawaz Q (2016) Union Laplacian pyramid with multiple features for medical image fusion. Neurocomputing 194:326\u2013339. https:\/\/doi.org\/10.1016\/j.neucom.2016.02.047","journal-title":"Neurocomputing"},{"key":"9294_CR5","doi-asserted-by":"publisher","first-page":"103823","DOI":"10.1016\/j.compbiomed.2020.103823","volume":"123","author":"Z Wang","year":"2020","unstructured":"Wang Z, Cui Z, Zhu Y (2020) Multi-modal medical image fusion by Laplacian pyramid and adaptive sparse representation. Comput Biol Med 123:103823. https:\/\/doi.org\/10.1016\/j.compbiomed.2020.103823","journal-title":"Comput Biol Med"},{"key":"9294_CR6","doi-asserted-by":"publisher","first-page":"104048","DOI":"10.1016\/j.compbiomed.2020.104048","volume":"126","author":"J Fu","year":"2020","unstructured":"Fu J, Li W, Du J, Xiao B (2020) Multimodal medical image fusion via Laplacian pyramid and convolutional neural network reconstruction with local gradient energy strategy. Comput Biol Med 126:104048. https:\/\/doi.org\/10.1016\/j.compbiomed.2020.104048","journal-title":"Comput Biol Med"},{"key":"9294_CR7","doi-asserted-by":"publisher","first-page":"20811","DOI":"10.1109\/access.2019.2898111","volume":"7","author":"Z Zhu","year":"2019","unstructured":"Zhu Z, Zheng M, Qi G, Wang D, Xiang Y (2019) A phase congruency and local Laplacian energy based multi-modality medical image fusion method in NSCT domain. IEEE Access 7:20811\u201320824. https:\/\/doi.org\/10.1109\/access.2019.2898111","journal-title":"IEEE Access"},{"key":"9294_CR8","doi-asserted-by":"publisher","DOI":"10.1049\/iet-ipr.2019.1319","author":"S Wang","year":"2020","unstructured":"Wang S, Shen Y (2020) Multi-modal image fusion based on saliency guided in NSCT domain. IET Image Proc. https:\/\/doi.org\/10.1049\/iet-ipr.2019.1319","journal-title":"IET Image Proc"},{"key":"9294_CR9","doi-asserted-by":"publisher","first-page":"114574","DOI":"10.1016\/j.eswa.2021.114574","volume":"171","author":"Z Wang","year":"2021","unstructured":"Wang Z, Li X, Duan H, Su Y, Zhang X, Guan X (2021) Medical image fusion based on convolutional neural networks and non-subsampled contourlet transform. Expert Syst Appl 171:114574. https:\/\/doi.org\/10.1016\/j.eswa.2021.114574","journal-title":"Expert Syst Appl"},{"key":"9294_CR10","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1016\/j.bspc.2017.10.001","volume":"40","author":"X Liu","year":"2018","unstructured":"Liu X, Mei W, Du H (2018) Multi-modality medical image fusion based on image decomposition framework and nonsubsampled Shearlet transform. Biomed Signal Process Control 40:343\u2013350. https:\/\/doi.org\/10.1016\/j.bspc.2017.10.001","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2020\/6265708","volume":"2020","author":"Z Ding","year":"2020","unstructured":"Ding Z, Zhou D, Nie R, Hou R, Liu Y (2020) Brain medical image fusion based on dual-branch CNNs in NSST domain. Biomed Res Int 2020:1\u201315. https:\/\/doi.org\/10.1155\/2020\/6265708","journal-title":"Biomed Res Int"},{"key":"9294_CR12","doi-asserted-by":"publisher","first-page":"165742","DOI":"10.1016\/j.ijleo.2020.165742","volume":"225","author":"RR Nair","year":"2021","unstructured":"Nair RR, Singh T (2021) An optimal registration on shearlet domain with novel weighted energy fusion for multi-modal medical images. Optik 225:165742. https:\/\/doi.org\/10.1016\/j.ijleo.2020.165742","journal-title":"Optik"},{"issue":"12","key":"9294_CR13","doi-asserted-by":"publisher","first-page":"19079","DOI":"10.1007\/s11042-020-10439-x","volume":"80","author":"RR Nair","year":"2021","unstructured":"Nair RR, Singh T (2021) MAMIF: multimodal adaptive medical image fusion based on b-spline registration and non-subsampled shearlet transform. Multimed Tools Appl 80(12):19079\u201319105. https:\/\/doi.org\/10.1007\/s11042-020-10439-x","journal-title":"Multimed Tools Appl"},{"issue":"30","key":"9294_CR14","doi-asserted-by":"publisher","first-page":"36401","DOI":"10.1007\/s11042-021-11379-w","volume":"80","author":"L Wang","year":"2021","unstructured":"Wang L, Dou J, Qin P, Lin S, Gao Y, Wang R, Zhang J (2021) Multimodal medical image fusion based on nonsubsampled shearlet transform and convolutional sparse representation. Multimed Tools Appl 80(30):36401\u201336421. https:\/\/doi.org\/10.1007\/s11042-021-11379-w","journal-title":"Multimed Tools Appl"},{"key":"9294_CR15","doi-asserted-by":"publisher","first-page":"102852","DOI":"10.1016\/j.bspc.2021.102852","volume":"69","author":"Y Gao","year":"2021","unstructured":"Gao Y, Ma S, Liu J, Liu Y, Zhang X (2021) Fusion of medical images based on salient features extraction by PSO optimized fuzzy logic in NSST domain. Biomed Signal Process Control 69:102852. https:\/\/doi.org\/10.1016\/j.bspc.2021.102852","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR16","doi-asserted-by":"publisher","first-page":"103535","DOI":"10.1016\/j.bspc.2022.103535","volume":"74","author":"Y Zhang","year":"2022","unstructured":"Zhang Y, Jin M, Huang G (2022) Medical image fusion based on improved multi-scale morphology gradient-weighted local energy and visual saliency map. Biomed Signal Process Control 74:103535. https:\/\/doi.org\/10.1016\/j.bspc.2022.103535","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR17","doi-asserted-by":"publisher","first-page":"102789","DOI":"10.1016\/j.bspc.2021.102789","volume":"69","author":"DS Shibu","year":"2021","unstructured":"Shibu DS, Priyadharsini SS (2021) Multi scale decomposition based medical image fusion using convolutional neural network and sparse representation. Biomed Signal Process Control 69:102789. https:\/\/doi.org\/10.1016\/j.bspc.2021.102789","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR18","doi-asserted-by":"publisher","first-page":"103357","DOI":"10.1016\/j.bspc.2021.103357","volume":"72","author":"AS Yousif","year":"2022","unstructured":"Yousif AS, Omar Z, Sheikh UU (2022) An improved approach for medical image fusion using sparse representation and Siamese convolutional neural network. Biomed Signal Process Control 72:103357. https:\/\/doi.org\/10.1016\/j.bspc.2021.103357","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR19","doi-asserted-by":"publisher","first-page":"104239","DOI":"10.1016\/j.compbiomed.2021.104239","volume":"131","author":"Q Li","year":"2021","unstructured":"Li Q, Wang W, Chen G, Zhao D (2021) Medical image fusion using segment graph filter and sparse representation. Comput Biol Med 131:104239. https:\/\/doi.org\/10.1016\/j.compbiomed.2021.104239","journal-title":"Comput Biol Med"},{"issue":"6","key":"9294_CR20","doi-asserted-by":"publisher","first-page":"4393","DOI":"10.1007\/s00500-020-05448-9","volume":"25","author":"Q Hu","year":"2021","unstructured":"Hu Q, Hu S, Zhang F (2021) Multi-modality image fusion combining sparse representation with guidance filtering. Soft Comput 25(6):4393\u20134407. https:\/\/doi.org\/10.1007\/s00500-020-05448-9","journal-title":"Soft Comput"},{"key":"9294_CR21","doi-asserted-by":"publisher","first-page":"103096","DOI":"10.1016\/j.bspc.2021.103096","volume":"71","author":"L Barba-J","year":"2022","unstructured":"Barba-J L, Vargas-Quintero L, Calder\u00f3n-Agudelo JA (2022) Bone SPECT\/CT image fusion based on the discrete Hermite transform and sparse representation. Biomed Signal Process Control 71:103096. https:\/\/doi.org\/10.1016\/j.bspc.2021.103096","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114576","author":"PH Dinh","year":"2021","unstructured":"Dinh PH (2021) A novel approach based on grasshopper optimization algorithm for medical image fusion. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2021.114576","journal-title":"Expert Syst Appl"},{"key":"9294_CR23","doi-asserted-by":"publisher","first-page":"102535","DOI":"10.1016\/j.bspc.2021.102535","volume":"68","author":"M Das","year":"2021","unstructured":"Das M, Gupta D, Radeva P, Bakde AM (2021) Optimized CT-MR neurological image fusion framework using biologically inspired spiking neural model in hybrid l1\u2013l0 layer decomposition domain. Biomed Signal Process Control 68:102535. https:\/\/doi.org\/10.1016\/j.bspc.2021.102535","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR24","doi-asserted-by":"publisher","first-page":"101810","DOI":"10.1016\/j.bspc.2019.101810","volume":"57","author":"S Maqsood","year":"2020","unstructured":"Maqsood S, Javed U (2020) Multi-modal medical image fusion based on two-scale image decomposition and sparse representation. Biomed Signal Process Control 57:101810. https:\/\/doi.org\/10.1016\/j.bspc.2019.101810","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR25","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1016\/j.ins.2021.04.052","volume":"569","author":"X Li","year":"2021","unstructured":"Li X, Zhou F, Tan H, Zhang W, Zhao C (2021) Multimodal medical image fusion based on joint bilateral filter and local gradient energy. Inf Sci 569:302\u2013325. https:\/\/doi.org\/10.1016\/j.ins.2021.04.052","journal-title":"Inf Sci"},{"key":"9294_CR26","doi-asserted-by":"publisher","first-page":"102536","DOI":"10.1016\/j.bspc.2021.102536","volume":"67","author":"PH Dinh","year":"2021","unstructured":"Dinh PH (2021) A novel approach based on three-scale image decomposition and marine predators algorithm for multi-modal medical image fusion. Biomed Signal Process Control 67:102536. https:\/\/doi.org\/10.1016\/j.bspc.2021.102536","journal-title":"Biomed Signal Process Control"},{"issue":"6","key":"9294_CR27","doi-asserted-by":"publisher","first-page":"4367","DOI":"10.1007\/s00521-021-06577-4","volume":"34","author":"PH Dinh","year":"2021","unstructured":"Dinh PH (2021) An improved medical image synthesis approach based on marine predators algorithm and maximum Gabor energy. Neural Comput Appl 34(6):4367\u20134385. https:\/\/doi.org\/10.1007\/s00521-021-06577-4","journal-title":"Neural Comput Appl"},{"issue":"11","key":"9294_CR28","doi-asserted-by":"publisher","first-page":"8416","DOI":"10.1007\/s10489-021-02282-w","volume":"51","author":"PH Dinh","year":"2021","unstructured":"Dinh PH (2021) Multi-modal medical image fusion based on equilibrium optimizer algorithm and local energy functions. Appl Intell 51(11):8416\u20138431. https:\/\/doi.org\/10.1007\/s10489-021-02282-w","journal-title":"Appl Intell"},{"key":"9294_CR29","doi-asserted-by":"publisher","first-page":"102696","DOI":"10.1016\/j.bspc.2021.102696","volume":"68","author":"PH Dinh","year":"2021","unstructured":"Dinh PH (2021) Combining Gabor energy with equilibrium optimizer algorithm for multi-modality medical image fusion. Biomed Signal Process Control 68:102696. https:\/\/doi.org\/10.1016\/j.bspc.2021.102696","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR30","doi-asserted-by":"publisher","first-page":"104794","DOI":"10.1016\/j.bspc.2023.104794","volume":"84","author":"X Feng","year":"2023","unstructured":"Feng X, Fang C, Qiu G (2023) Multimodal medical image fusion based on visual saliency map and multichannel dynamic threshold neural p systems in sub-window variance filter domain. Biomed Signal Process Control 84:104794. https:\/\/doi.org\/10.1016\/j.bspc.2023.104794","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR31","doi-asserted-by":"publisher","first-page":"104387","DOI":"10.1016\/j.bspc.2022.104387","volume":"80","author":"Y Yang","year":"2023","unstructured":"Yang Y, Cao S, Wan W, Huang S (2023) Multi-modal medical image super-resolution fusion based on detail enhancement and weighted local energy deviation. Biomed Signal Process Control 80:104387. https:\/\/doi.org\/10.1016\/j.bspc.2022.104387","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR32","doi-asserted-by":"publisher","first-page":"104353","DOI":"10.1016\/j.bspc.2022.104353","volume":"80","author":"X Li","year":"2023","unstructured":"Li X, Wan W, Zhou F, Cheng X, Jie Y, Tan H (2023) Medical image fusion based on sparse representation and neighbor energy activity. Biomed Signal Process Control 80:104353. https:\/\/doi.org\/10.1016\/j.bspc.2022.104353","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR33","doi-asserted-by":"publisher","first-page":"105004","DOI":"10.1016\/j.bspc.2023.105004","volume":"85","author":"Y Feng","year":"2023","unstructured":"Feng Y, Wu J, Hu X, Zhang W, Wang G, Zhou X, Zhang X (2023) Medical image fusion using bilateral texture filtering. Biomed Signal Process Control 85:105004. https:\/\/doi.org\/10.1016\/j.bspc.2023.105004","journal-title":"Biomed Signal Process Control"},{"issue":"7","key":"9294_CR34","doi-asserted-by":"publisher","first-page":"9277","DOI":"10.1007\/s11042-021-11549-w","volume":"81","author":"L Zhang","year":"2022","unstructured":"Zhang L, Li H, Zhu R, Du P (2022) An infrared and visible image fusion algorithm based on ResNet-152. Multimed Tools Appl 81(7):9277\u20139287. https:\/\/doi.org\/10.1007\/s11042-021-11549-w","journal-title":"Multimed Tools Appl"},{"key":"9294_CR35","doi-asserted-by":"publisher","first-page":"103039","DOI":"10.1016\/j.infrared.2019.103039","volume":"102","author":"H Li","year":"2019","unstructured":"Li H, Xj Wu, Durrani TS (2019) Infrared and visible image fusion with ResNet and zero-phase component analysis. Infrared Phys Technol 102:103039. https:\/\/doi.org\/10.1016\/j.infrared.2019.103039","journal-title":"Infrared Phys Technol"},{"key":"9294_CR36","doi-asserted-by":"publisher","first-page":"106923","DOI":"10.1016\/j.compbiomed.2023.106923","volume":"159","author":"Z Ding","year":"2023","unstructured":"Ding Z, Li H, Guo Y, Zhou D, Liu Y, Xie S (2023) M4fnet: multimodal medical image fusion network via multi-receptive-field and multi-scale feature integration. Comput Biol Med 159:106923. https:\/\/doi.org\/10.1016\/j.compbiomed.2023.106923","journal-title":"Comput Biol Med"},{"key":"9294_CR37","doi-asserted-by":"publisher","first-page":"104402","DOI":"10.1016\/j.bspc.2022.104402","volume":"80","author":"W Li","year":"2023","unstructured":"Li W, Zhang Y, Wang G, Huang Y, Li R (2023) DFENet: a dual-branch feature enhanced network integrating transformers and convolutional feature learning for multimodal medical image fusion. Biomed Signal Process Control 80:104402. https:\/\/doi.org\/10.1016\/j.bspc.2022.104402","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR38","doi-asserted-by":"publisher","first-page":"103534","DOI":"10.1016\/j.bspc.2022.103534","volume":"74","author":"W Li","year":"2022","unstructured":"Li W, Li R, Fu J, Peng X (2022) MSENet: a multi-scale enhanced network based on unique features guidance for medical image fusion. Biomed Signal Process Control 74:103534. https:\/\/doi.org\/10.1016\/j.bspc.2022.103534","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR39","doi-asserted-by":"publisher","first-page":"166413","DOI":"10.1016\/j.ijleo.2021.166413","volume":"231","author":"S Shehanaz","year":"2021","unstructured":"Shehanaz S, Daniel E, Guntur SR, Satrasupalli S (2021) Optimum weighted multimodal medical image fusion using particle swarm optimization. Optik 231:166413. https:\/\/doi.org\/10.1016\/j.ijleo.2021.166413","journal-title":"Optik"},{"issue":"1","key":"9294_CR40","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/s11045-019-00662-7","volume":"31","author":"A Tannaz","year":"2019","unstructured":"Tannaz A, Mousa S, Sabalan D, Masoud P (2019) Fusion of multimodal medical images using nonsubsampled shearlet transform and particle swarm optimization. Multidimens Syst Signal Process 31(1):269\u2013287. https:\/\/doi.org\/10.1007\/s11045-019-00662-7","journal-title":"Multidimens Syst Signal Process"},{"key":"9294_CR41","doi-asserted-by":"publisher","first-page":"104343","DOI":"10.1016\/j.bspc.2022.104343","volume":"80","author":"PH Dinh","year":"2023","unstructured":"Dinh PH (2023) Combining spectral total variation with dynamic threshold neural p systems for medical image fusion. Biomed Signal Process Control 80:104343. https:\/\/doi.org\/10.1016\/j.bspc.2022.104343","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR42","doi-asserted-by":"publisher","first-page":"101885","DOI":"10.1016\/j.bspc.2020.101885","volume":"59","author":"L Xu","year":"2020","unstructured":"Xu L, Si Y, Jiang S, Sun Y, Ebrahimian H (2020) Medical image fusion using a modified shark smell optimization algorithm and hybrid wavelet-homomorphic filter. Biomed Signal Process Control 59:101885. https:\/\/doi.org\/10.1016\/j.bspc.2020.101885","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR43","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.bspc.2017.01.003","volume":"34","author":"E Daniel","year":"2017","unstructured":"Daniel E, Anitha J, Kamaleshwaran K, Rani I (2017) Optimum spectrum mask based medical image fusion using gray wolf optimization. Biomed Signal Process Control 34:36\u201343. https:\/\/doi.org\/10.1016\/j.bspc.2017.01.003","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR44","doi-asserted-by":"publisher","first-page":"105370","DOI":"10.1016\/j.bspc.2023.105370","volume":"87","author":"OC Do","year":"2024","unstructured":"Do OC, Luong CM, Dinh PH, Tran GS (2024) An efficient approach to medical image fusion based on optimization and transfer learning with VGG19. Biomed Signal Process Control 87:105370. https:\/\/doi.org\/10.1016\/j.bspc.2023.105370","journal-title":"Biomed Signal Process Control"},{"issue":"7","key":"9294_CR45","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1080\/13682199.2023.2190947","volume":"71","author":"PH Dinh","year":"2023","unstructured":"Dinh PH (2023) A novel approach using the local energy function and its variations for medical image fusion. Imaging Sci J 71(7):660\u2013676. https:\/\/doi.org\/10.1080\/13682199.2023.2190947","journal-title":"Imaging Sci J"},{"key":"9294_CR46","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.inffus.2013.12.002","volume":"19","author":"AP James","year":"2014","unstructured":"James AP, Dasarathy BV (2014) Medical image fusion: a survey of the state of the art. Inf Fusion 19:4\u201319. https:\/\/doi.org\/10.1016\/j.inffus.2013.12.002","journal-title":"Inf Fusion"},{"key":"9294_CR47","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.inffus.2020.06.013","volume":"64","author":"Y Liu","year":"2020","unstructured":"Liu Y, Wang L, Cheng J, Li C, Chen X (2020) Multi-focus image fusion: a survey of the state of the art. Inf Fusion 64:71\u201391. https:\/\/doi.org\/10.1016\/j.inffus.2020.06.013","journal-title":"Inf Fusion"},{"key":"9294_CR48","doi-asserted-by":"publisher","first-page":"108542","DOI":"10.1016\/j.asoc.2022.108542","volume":"118","author":"Z Chao","year":"2022","unstructured":"Chao Z, Duan X, Jia S, Guo X, Liu H, Jia F (2022) Medical image fusion via discrete stationary wavelet transform and an enhanced radial basis function neural network. Appl Soft Comput 118:108542. https:\/\/doi.org\/10.1016\/j.asoc.2022.108542","journal-title":"Appl Soft Comput"},{"key":"9294_CR49","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05173-2","author":"W Tan","year":"2020","unstructured":"Tan W, Tiwari P, Pandey HM, Moreira C, Jaiswal AK (2020) Multimodal medical image fusion algorithm in the era of big data. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-020-05173-2","journal-title":"Neural Comput Appl"},{"key":"9294_CR50","doi-asserted-by":"publisher","first-page":"102280","DOI":"10.1016\/j.bspc.2020.102280","volume":"64","author":"W Tan","year":"2021","unstructured":"Tan W, Thit\u00f8n W, Xiang P, Zhou H (2021) Multi-modal brain image fusion based on multi-level edge-preserving filtering. Biomed Signal Process Control 64:102280. https:\/\/doi.org\/10.1016\/j.bspc.2020.102280","journal-title":"Biomed Signal Process Control"},{"key":"9294_CR51","doi-asserted-by":"publisher","unstructured":"Zhang Q, Shen X, Xu L, Jia J (2014) Rolling guidance filter. In: Computer Vision\u2014ECCV 2014. Springer International Publishing, pp 815\u2013830. https:\/\/doi.org\/10.1007\/978-3-319-10578-9_53","DOI":"10.1007\/978-3-319-10578-9_53"},{"key":"9294_CR52","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.camwa.2021.12.005","volume":"107","author":"J Yang","year":"2022","unstructured":"Yang J, Guo Z, Zhang D, Wu B, Du S (2022) An anisotropic diffusion system with nonlinear time-delay structure tensor for image enhancement and segmentation. Comput Math Appl 107:29\u201344. https:\/\/doi.org\/10.1016\/j.camwa.2021.12.005","journal-title":"Comput Math Appl"},{"issue":"1","key":"9294_CR53","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1007\/s11042-022-12393-2","volume":"82","author":"K Liu","year":"2022","unstructured":"Liu K, Xu W, Wu H, Yahya AA (2022) Weighted hybrid order total variation model using structure tensor for image denoising. Multimed Tools Appl 82(1):927\u2013943. https:\/\/doi.org\/10.1007\/s11042-022-12393-2","journal-title":"Multimed Tools Appl"},{"key":"9294_CR54","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.inffus.2013.11.005","volume":"20","author":"Z Zhou","year":"2014","unstructured":"Zhou Z, Li S, Wang B (2014) Multi-scale weighted gradient-based fusion for multi-focus images. Inf Fusion 20:60\u201372. https:\/\/doi.org\/10.1016\/j.inffus.2013.11.005","journal-title":"Inf Fusion"},{"issue":"6","key":"9294_CR55","doi-asserted-by":"publisher","first-page":"1672","DOI":"10.1109\/tnnls.2018.2872999","volume":"30","author":"H Peng","year":"2019","unstructured":"Peng H, Wang J (2019) Coupled neural p systems. IEEE Trans Neural Netw Learn Syst 30(6):1672\u20131682. https:\/\/doi.org\/10.1109\/tnnls.2018.2872999","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"01","key":"9294_CR56","doi-asserted-by":"publisher","first-page":"2050050","DOI":"10.1142\/s0129065720500501","volume":"31","author":"B Li","year":"2020","unstructured":"Li B, Peng H, Luo X, Wang J, Song X, P\u00e9rez-Jim\u00e9nez MJ, Riscos-N\u00fa\u00f1ez A (2020) Medical image fusion method based on coupled neural p systems in nonsubsampled shearlet transform domain. Int J Neural Syst 31(01):2050050. https:\/\/doi.org\/10.1142\/s0129065720500501","journal-title":"Int J Neural Syst"},{"key":"9294_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.01.059","author":"G Wang","year":"2022","unstructured":"Wang G, Li W, Gao X, Xiao B, Du J (2022) Multimodal medical image fusion based on multichannel coupled neural p systems and max-cloud models in spectral total variation domain. Neurocomputing. https:\/\/doi.org\/10.1016\/j.neucom.2022.01.059","journal-title":"Neurocomputing"},{"issue":"7","key":"9294_CR58","doi-asserted-by":"publisher","first-page":"2864","DOI":"10.1109\/tip.2013.2244222","volume":"22","author":"S Li","year":"2013","unstructured":"Li S, Kang X, Hu J (2013) Image fusion with guided filtering. IEEE Trans Image Process 22(7):2864\u20132875. https:\/\/doi.org\/10.1109\/tip.2013.2244222","journal-title":"IEEE Trans Image Process"},{"issue":"12","key":"9294_CR59","doi-asserted-by":"publisher","first-page":"1882","DOI":"10.1109\/lsp.2016.2618776","volume":"23","author":"Y Liu","year":"2016","unstructured":"Liu Y, Chen X, Ward RK, Wang ZJ (2016) Image fusion with convolutional sparse representation. IEEE Signal Process Lett 23(12):1882\u20131886. https:\/\/doi.org\/10.1109\/lsp.2016.2618776","journal-title":"IEEE Signal Process Lett"},{"key":"9294_CR60","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1049\/el:20020212","volume":"38","author":"Q Guihong","year":"2002","unstructured":"Guihong Q, Zhang D, Yan P (2002) Information measure for performance of image fusion. Electron Lett 38:313\u2013315","journal-title":"Electron Lett"},{"key":"9294_CR61","doi-asserted-by":"publisher","unstructured":"Wang Q, Shen Y, Jin J (2008) Performance evaluation of image fusion techniques. In: Image fusion. Elsevier, pp 469\u2013492. https:\/\/doi.org\/10.1016\/b978-0-12-372529-5.00017-2","DOI":"10.1016\/b978-0-12-372529-5.00017-2"},{"issue":"2","key":"9294_CR62","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1109\/tip.2012.2221725","volume":"22","author":"H Yeganeh","year":"2013","unstructured":"Yeganeh H, Wang Z (2013) Objective quality assessment of tone-mapped images. IEEE Trans Image Process 22(2):657\u2013667. https:\/\/doi.org\/10.1109\/tip.2012.2221725","journal-title":"IEEE Trans Image Process"},{"key":"9294_CR63","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1049\/el:20000267","volume":"36","author":"C Xydeas","year":"2000","unstructured":"Xydeas C, Petrovic V (2000) Objective image fusion performance measure. Electron Lett 36:308. https:\/\/doi.org\/10.1049\/el:20000267","journal-title":"Electron Lett"},{"key":"9294_CR64","doi-asserted-by":"publisher","unstructured":"Piella G, Heijmans H (2003) A new quality metric for image fusion. In: Proceedings 2003 international conference on image processing (Cat. No. 03CH37429). IEEE. https:\/\/doi.org\/10.1109\/icip.2003.1247209","DOI":"10.1109\/icip.2003.1247209"},{"key":"9294_CR65","doi-asserted-by":"publisher","first-page":"107793","DOI":"10.1016\/j.sigpro.2020.107793","volume":"178","author":"B Li","year":"2021","unstructured":"Li B, Peng H, Wang J (2021) A novel fusion method based on dynamic threshold neural p systems and nonsubsampled contourlet transform for multi-modality medical images. Signal Process 178:107793. https:\/\/doi.org\/10.1016\/j.sigpro.2020.107793","journal-title":"Signal Process"},{"issue":"3","key":"9294_CR66","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1093\/bioinformatics\/btab721","volume":"38","author":"R Zhu","year":"2021","unstructured":"Zhu R, Li X, Huang S, Zhang X (2021) Multimodal medical image fusion using adaptive co-occurrence filter-based decomposition optimization model. Bioinformatics 38(3):818\u2013826. https:\/\/doi.org\/10.1093\/bioinformatics\/btab721","journal-title":"Bioinformatics"},{"issue":"1","key":"9294_CR67","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1002\/ima.22649","volume":"32","author":"A Sufyan","year":"2021","unstructured":"Sufyan A, Imran M, Shah SA, Shahwani H, Wadood AA (2021) A novel multimodality anatomical image fusion method based on contrast and structure extraction. Int J Imaging Syst Technol 32(1):324\u2013342. https:\/\/doi.org\/10.1002\/ima.22649","journal-title":"Int J Imaging Syst Technol"},{"key":"9294_CR68","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2022.1055451","author":"Y Zhang","year":"2022","unstructured":"Zhang Y, Xiang W, Zhang S, Shen J, Wei R, Bai X, Zhang L, Zhang Q (2022) Local extreme map guided multi-modal brain image fusion. Front Neurosci. https:\/\/doi.org\/10.3389\/fnins.2022.1055451","journal-title":"Front Neurosci"},{"key":"9294_CR69","doi-asserted-by":"publisher","first-page":"108637","DOI":"10.1016\/j.sigpro.2022.108637","volume":"200","author":"FG Veshki","year":"2022","unstructured":"Veshki FG, Ouzir N, Vorobyov SA, Ollila E (2022) Multimodal image fusion via coupled feature learning. Signal Process 200:108637. https:\/\/doi.org\/10.1016\/j.sigpro.2022.108637","journal-title":"Signal Process"},{"key":"9294_CR70","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-022-02588-x","author":"Q Xie","year":"2022","unstructured":"Xie Q, Hu J, Wang X, Zhang D, Qin H (2022) Novel and fast EMD-based image fusion via morphological filter. Vis Comput. https:\/\/doi.org\/10.1007\/s00371-022-02588-x","journal-title":"Vis Comput"},{"issue":"6","key":"9294_CR71","doi-asserted-by":"publisher","first-page":"2198","DOI":"10.1002\/ima.22778","volume":"32","author":"PH Dinh","year":"2022","unstructured":"Dinh PH, Giang NL (2022) A new medical image enhancement algorithm using adaptive parameters. Int J Imaging Syst Technol 32(6):2198\u20132218. https:\/\/doi.org\/10.1002\/ima.22778","journal-title":"Int J Imaging Syst Technol"},{"key":"9294_CR72","doi-asserted-by":"publisher","DOI":"10.1007\/s11220-023-00411-y","author":"PH Dinh","year":"2023","unstructured":"Dinh PH (2023) A novel approach based on marine predators algorithm for medical image enhancement. Sens Imaging. https:\/\/doi.org\/10.1007\/s11220-023-00411-y","journal-title":"Sens Imaging"},{"issue":"3","key":"9294_CR73","doi-asserted-by":"publisher","first-page":"1001","DOI":"10.1007\/s11045-022-00829-9","volume":"33","author":"PH Dinh","year":"2022","unstructured":"Dinh PH (2022) A novel approach using structure tensor for medical image fusion. Multidimens Syst Signal Process 33(3):1001\u20131021. https:\/\/doi.org\/10.1007\/s11045-022-00829-9","journal-title":"Multidimens Syst Signal Process"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-09294-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-09294-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-09294-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T10:17:13Z","timestamp":1707733033000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-09294-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,12]]},"references-count":73,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,3]]}},"alternative-id":["9294"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-09294-2","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,12]]},"assertion":[{"value":"16 March 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 December 2023","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 that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}