{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:34:17Z","timestamp":1757619257228,"version":"3.44.0"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T00:00:00Z","timestamp":1753056000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T00:00:00Z","timestamp":1753056000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Discov Artif Intell"],"DOI":"10.1007\/s44163-025-00446-y","type":"journal-article","created":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T09:23:00Z","timestamp":1753089780000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Edge-aware multisensor brain image fusion via guided filtering in Laplacian domain"],"prefix":"10.1007","volume":"5","author":[{"given":"Shweta","family":"Sharma","sequence":"first","affiliation":[]},{"given":"Shalli","family":"Rani","sequence":"additional","affiliation":[]},{"given":"Ayush","family":"Dogra","sequence":"additional","affiliation":[]},{"given":"Mohammed Wasim","family":"Bhatt","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,21]]},"reference":[{"issue":"8","key":"446_CR1","doi-asserted-by":"publisher","first-page":"101733","DOI":"10.1016\/j.jksuci.2023.101733","volume":"35","author":"SU Khan","year":"2023","unstructured":"Khan SU, Khan MA, Azhar M, Khan F, Lee Y, Javed M. Multimodal medical image fusion towards future research: a review. J King Saud Univ Comput Inf Sci. 2023;35(8):101733.","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"446_CR2","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1016\/j.inffus.2022.10.017","volume":"91","author":"T Zhou","year":"2023","unstructured":"Zhou T, Li Q, Lu H, Cheng Q, Zhang X. Gan review: models and medical image fusion applications. Inf Fusion. 2023;91:134\u201348.","journal-title":"Inf Fusion"},{"key":"446_CR3","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. Multi-modal medical image fusion by laplacian pyramid and adaptive sparse representation. Comput Biol Med. 2020;123:103823.","journal-title":"Comput Biol Med"},{"key":"446_CR4","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. Multi-modal medical image fusion based on two-scale image decomposition and sparse representation. Biomed Signal Process Control. 2020;57:101810.","journal-title":"Biomed Signal Process Control"},{"key":"446_CR5","doi-asserted-by":"publisher","first-page":"5134","DOI":"10.1109\/TIP.2022.3193288","volume":"31","author":"W Tang","year":"2022","unstructured":"Tang W, He F, Liu Y, Duan Y. Matr: multimodal medical image fusion via multiscale adaptive transformer. IEEE Trans Image Process. 2022;31:5134\u201349.","journal-title":"IEEE Trans Image Process"},{"issue":"4","key":"446_CR6","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1007\/s11517-020-02136-6","volume":"58","author":"SP Yadav","year":"2020","unstructured":"Yadav SP, Yadav S. Image fusion using hybrid methods in multimodality medical images. Med Biol Eng Comput. 2020;58(4):669\u201387.","journal-title":"Med Biol Eng Comput"},{"key":"446_CR7","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. A review on multimodal medical image fusion: compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics. Comput Biol Med. 2022;144:105253.","journal-title":"Comput Biol Med"},{"key":"446_CR8","doi-asserted-by":"crossref","unstructured":"Kumar V, Joshi K, Kanti P, Reshi JS, Rawat G, Kumar A. Brain tumor diagnosis using image fusion and deep learning. In: 2023 international conference on sustainable computing and data communication systems (ICSCDS). IEEE; 2023. pp. 1658\u20131662.","DOI":"10.1109\/ICSCDS56580.2023.10104937"},{"key":"446_CR9","doi-asserted-by":"crossref","unstructured":"Liu Y, Chen X, Cheng J, Peng H. A medical image fusion method based on convolutional neural networks. In: 2017 20th international conference on information fusion (Fusion). IEEE; 2017. pp. 1\u20137.","DOI":"10.23919\/ICIF.2017.8009769"},{"key":"446_CR10","doi-asserted-by":"publisher","first-page":"108942","DOI":"10.1109\/ACCESS.2021.3101639","volume":"9","author":"Q Li","year":"2021","unstructured":"Li Q, Han G, Liu P, Yang H, Wu J, Liu D. An infrared and visible image fusion method guided by saliency and gradient information. IEEE Access. 2021;9:108942\u201358.","journal-title":"IEEE Access"},{"key":"446_CR11","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.inffus.2014.09.004","volume":"24","author":"Y Liu","year":"2015","unstructured":"Liu Y, Liu S, Wang Z. A general framework for image fusion based on multi-scale transform and sparse representation. Inf Fusion. 2015;24:147\u201364.","journal-title":"Inf Fusion"},{"key":"446_CR12","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1016\/j.neucom.2016.07.039","volume":"216","author":"H Yin","year":"2016","unstructured":"Yin H, Li Y, Chai Y, Liu Z, Zhu Z. A novel sparse-representation-based multi-focus image fusion approach. Neurocomputing. 2016;216:216\u201329.","journal-title":"Neurocomputing"},{"issue":"5","key":"446_CR13","doi-asserted-by":"publisher","first-page":"057006","DOI":"10.1117\/1.OE.52.5.057006","volume":"52","author":"Q Zhang","year":"2013","unstructured":"Zhang Q, Fu Y, Li H, Zou J. Dictionary learning method for joint sparse representation-based image fusion. Opt Eng. 2013;52(5):057006\u2013057006.","journal-title":"Opt Eng"},{"key":"446_CR14","doi-asserted-by":"publisher","first-page":"112001","DOI":"10.1016\/j.optlastec.2024.112001","volume":"181","author":"Y Jie","year":"2025","unstructured":"Jie Y, Li X, Tan T, Yang L, Wang M. Multi-modality image fusion using fuzzy set theory and compensation dictionary learning. Opt Laser Technol. 2025;181:112001.","journal-title":"Opt Laser Technol"},{"issue":"1","key":"446_CR15","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s11517-022-02697-8","volume":"61","author":"SI Ibrahim","year":"2023","unstructured":"Ibrahim SI, Makhlouf M, El-Tawel GS. Multimodal medical image fusion algorithm based on pulse coupled neural networks and nonsubsampled contourlet transform. Med Biol Eng Comput. 2023;61(1):155\u201377.","journal-title":"Med Biol Eng Comput"},{"key":"446_CR16","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. A phase congruency and local laplacian energy based multi-modality medical image fusion method in NSCT domain. IEEE Access. 2019;7:20811\u201324.","journal-title":"IEEE Access"},{"issue":"9","key":"446_CR17","doi-asserted-by":"publisher","first-page":"6880","DOI":"10.1109\/TIM.2020.2975405","volume":"69","author":"X Li","year":"2020","unstructured":"Li X, Guo X, Han P, Wang X, Li H, Luo T. Laplacian redecomposition for multimodal medical image fusion. IEEE Trans Instrum Meas. 2020;69(9):6880\u201390.","journal-title":"IEEE Trans Instrum Meas"},{"key":"446_CR18","doi-asserted-by":"publisher","first-page":"1125","DOI":"10.1007\/s11760-012-0361-x","volume":"7","author":"B Shreyamsha Kumar","year":"2013","unstructured":"Shreyamsha Kumar B. Multifocus and multispectral image fusion based on pixel significance using discrete cosine harmonic wavelet transform. Signal Image Video Process. 2013;7:1125\u201343.","journal-title":"Signal Image Video Process"},{"key":"446_CR19","unstructured":"Al-Wassai FA, Kalyankar N, Al-Zuky AA. The IHS transformations based image fusion. arXiv preprint arXiv:1107.4396 (2011)."},{"issue":"7","key":"446_CR20","doi-asserted-by":"publisher","first-page":"1831","DOI":"10.1109\/TIP.2007.896687","volume":"16","author":"S Zheng","year":"2007","unstructured":"Zheng S, Shi W-Z, Liu J, Zhu G-X, Tian J-W. Multisource image fusion method using support value transform. IEEE Trans Image Process. 2007;16(7):1831\u20139.","journal-title":"IEEE Trans Image Process"},{"issue":"3","key":"446_CR21","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1006\/gmip.1995.1022","volume":"57","author":"H Li","year":"1995","unstructured":"Li H, Manjunath B, Mitra SK. Multisensor image fusion using the wavelet transform. Graph Models Image Process. 1995;57(3):235\u201345.","journal-title":"Graph Models Image Process"},{"issue":"8","key":"446_CR22","doi-asserted-by":"publisher","first-page":"1215","DOI":"10.3390\/e25081215","volume":"25","author":"R Kurban","year":"2023","unstructured":"Kurban R. Gaussian of differences: a simple and efficient general image fusion method. Entropy. 2023;25(8):1215.","journal-title":"Entropy"},{"key":"446_CR23","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.infrared.2016.01.009","volume":"76","author":"DP Bavirisetti","year":"2016","unstructured":"Bavirisetti DP, Dhuli R. Two-scale image fusion of visible and infrared images using saliency detection. Infrared Phys Technol. 2016;76:52\u201364.","journal-title":"Infrared Phys Technol"},{"issue":"7","key":"446_CR24","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. Image fusion with guided filtering. IEEE Trans Image Process. 2013;22(7):2864\u201375.","journal-title":"IEEE Trans Image Process"},{"issue":"3","key":"446_CR25","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1002\/ima.22228","volume":"27","author":"DP Bavirisetti","year":"2017","unstructured":"Bavirisetti DP, Kollu V, Gang X, Dhuli R. Fusion of MRI and CT images using guided image filter and image statistics. Int J Imaging Syst Technol. 2017;27(3):227\u201337.","journal-title":"Int J Imaging Syst Technol"},{"key":"446_CR26","doi-asserted-by":"publisher","first-page":"104740","DOI":"10.1016\/j.bspc.2023.104740","volume":"84","author":"P-H Dinh","year":"2023","unstructured":"Dinh P-H. Medical image fusion based on enhanced three-layer image decomposition and chameleon swarm algorithm. Biomed Signal Process Control. 2023;84:104740.","journal-title":"Biomed Signal Process Control"},{"issue":"2","key":"446_CR27","first-page":"2905","volume":"74","author":"W El-Shafai","year":"2023","unstructured":"El-Shafai W, El-Hag N, Sedik A, Elbanby G, Abd El-Samie F, Soliman NF, AlEisa HN, Abdel Samea M. An efficient medical image deep fusion model based on convolutional neural networks. Comput Mater Contin. 2023;74(2):2905\u201325.","journal-title":"Comput Mater Contin"},{"key":"446_CR28","doi-asserted-by":"crossref","unstructured":"Li J, Liu J, Zhou S, Zhang Q, Kasabov NK. Gesenet: a general semantic-guided network with couple mask ensemble for medical image fusion. IEEE Trans Neural Netw Learn Syst (2023).","DOI":"10.1109\/TNNLS.2023.3293274"},{"issue":"2","key":"446_CR29","doi-asserted-by":"publisher","first-page":"79","DOI":"10.21608\/mjeer.2021.195522","volume":"30","author":"F El-Sayed","year":"2021","unstructured":"El-Sayed F, El-Shafai W, Elsayed Taha T, et al. Efficient fusion of medical images based on CNN. Menoufia J Electron Eng Res. 2021;30(2):79\u201383.","journal-title":"Menoufia J Electron Eng Res"},{"issue":"8","key":"446_CR30","doi-asserted-by":"publisher","first-page":"2169","DOI":"10.3390\/s20082169","volume":"20","author":"K Wang","year":"2020","unstructured":"Wang K, Zheng M, Wei H, Qi G, Li Y. Multi-modality medical image fusion using convolutional neural network and contrast pyramid. Sensors. 2020;20(8):2169.","journal-title":"Sensors"},{"issue":"7","key":"446_CR31","doi-asserted-by":"publisher","first-page":"827","DOI":"10.3390\/e23070827","volume":"23","author":"B Wei","year":"2021","unstructured":"Wei B, Feng X, Wang K, Gao B. The multi-focus-image-fusion method based on convolutional neural network and sparse representation. Entropy. 2021;23(7):827.","journal-title":"Entropy"},{"key":"446_CR32","doi-asserted-by":"crossref","unstructured":"Song X, Shen T, Li H, Wu X-J. D2-lrr: a dual-decomposed mdlatlrr approach for medical image fusion. In: 2023 international conference on machine vision, image processing and imaging technology (MVIPIT). IEEE; 2023. pp. 24\u201330.","DOI":"10.1109\/MVIPIT60427.2023.00010"},{"key":"446_CR33","doi-asserted-by":"crossref","unstructured":"Agrawal C, Yadav SK, Singh SP, Panigrahy C. A simplified parameter adaptive dcpcnn based medical image fusion. In: Proceedings of international conference on communication and artificial intelligence: ICCAI 2021. Springer; 2022. pp. 489\u2013501.","DOI":"10.1007\/978-981-19-0976-4_40"},{"key":"446_CR34","doi-asserted-by":"crossref","unstructured":"Jia Y, Rong C, Wu C, Yang Y. Research on the decomposition and fusion method for the infrared and visible images based on the guided image filtering and Gaussian filter. In: 2017 3rd IEEE international conference on computer and communications (ICCC). IEEE; 2017. pp. 1797\u20131802.","DOI":"10.1109\/CompComm.2017.8322849"},{"key":"446_CR35","doi-asserted-by":"publisher","first-page":"104020","DOI":"10.1016\/j.dsp.2023.104020","volume":"137","author":"S Singh","year":"2023","unstructured":"Singh S, Singh H, Bueno G, Deniz O, Singh S, Monga H, Hrisheekesha P, Pedraza A. A review of image fusion: methods, applications and performance metrics. Digit Signal Process. 2023;137:104020.","journal-title":"Digit Signal Process"},{"issue":"5","key":"446_CR36","doi-asserted-by":"publisher","first-page":"3645","DOI":"10.1007\/s11831-020-09518-x","volume":"28","author":"S Singh","year":"2021","unstructured":"Singh S, Mittal N, Singh H. Review of various image fusion algorithms and image fusion performance metric. Arch Comput Methods Eng. 2021;28(5):3645\u201359.","journal-title":"Arch Comput Methods Eng"},{"issue":"4","key":"446_CR37","first-page":"880","volume":"5","author":"H Kekre","year":"2013","unstructured":"Kekre H, Mishra D, Saboo R. Review on image fusion techniques and performance evaluation parameters. Int J Eng Sci Technol. 2013;5(4):880.","journal-title":"Int J Eng Sci Technol"},{"key":"446_CR38","unstructured":"Dawachyophel, Mydataset. https:\/\/github.com\/dawachyophel\/medical-fusion\/tree\/main\/MyDataset. Accessed 14 June 2025."},{"key":"446_CR39","unstructured":"Imagingscience, Fusion. https:\/\/github.com\/Imagingscience\/Image-Fusion-Image-Denoising-Image-Enhancement-\/commits?author=I. Accessed 14 June 2025."}],"container-title":["Discover Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44163-025-00446-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44163-025-00446-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44163-025-00446-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T16:31:27Z","timestamp":1757262687000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44163-025-00446-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,21]]},"references-count":39,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["446"],"URL":"https:\/\/doi.org\/10.1007\/s44163-025-00446-y","relation":{},"ISSN":["2731-0809"],"issn-type":[{"type":"electronic","value":"2731-0809"}],"subject":[],"published":{"date-parts":[[2025,7,21]]},"assertion":[{"value":"3 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publications"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Clinical trial number"}}],"article-number":"162"}}