{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T03:38:21Z","timestamp":1777088301416,"version":"3.51.4"},"reference-count":176,"publisher":"Tech Science Press","issue":"3","license":[{"start":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T00:00:00Z","timestamp":1754179200000},"content-version":"vor","delay-in-days":214,"URL":"https:\/\/doi.org\/10.32604\/TSP-CROSSMARKPOLICY"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.063726","type":"journal-article","created":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T07:24:21Z","timestamp":1753169061000},"page":"4259-4297","update-policy":"https:\/\/doi.org\/10.32604\/tsp-crossmarkpolicy","source":"Crossref","is-referenced-by-count":6,"title":["Transformers for Multi-Modal Image Analysis in Healthcare"],"prefix":"10.32604","volume":"84","author":[{"given":"Sameera V Mohd","family":"Sagheer","sequence":"first","affiliation":[]},{"given":"Meghana","family":"K H","sequence":"additional","affiliation":[]},{"given":"P M","family":"Ameer","sequence":"additional","affiliation":[]},{"given":"Muneer","family":"Parayangat","sequence":"additional","affiliation":[]},{"given":"Mohamed","family":"Abbas","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.cpet.2009.03.002","article-title":"The clinical role of fusion imaging using PET, CT, and MR imaging","volume":"3","author":"Zaidi","year":"2008","journal-title":"PET Clinics"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1038\/s41746-024-01248-9","article-title":"Effects of artificial intelligence implementation on efficiency in medical imaging-a systematic literature review and meta-analysis","volume":"7","author":"Wenderott","year":"2024","journal-title":"npj Digit Med"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"e41470","DOI":"10.1097\/MD.0000000000041470","article-title":"Reducing the workload of medical diagnosis through artificial intelligence: a narrative review","volume":"104","author":"Jeong","year":"2025","journal-title":"Medicine"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"100146","DOI":"10.1016\/j.cmpbup.2024.100146","article-title":"AI in diagnostic imaging: Revolutionising accuracy and efficiency","volume":"5","author":"Khalifa","year":"2024","journal-title":"Comput Methods Programs Biomed Update"},{"key":"ref5","first-page":"2319","article-title":"Emerging trends in AI-powered medical imaging: enhancing diagnostic accuracy and treatment decisions","volume":"13","author":"Oyeniyi","year":"2024","journal-title":"IJERSTE"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.3390\/diagnostics11081384","article-title":"Transmed: transformers advance multi-modal medical image classification","volume":"11","author":"Dai","year":"2021","journal-title":"Diagnostics"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"1273253","DOI":"10.3389\/fpubh.2023.1273253","article-title":"Medical image analysis using deep learning algorithms","volume":"11","author":"Li","year":"2023","journal-title":"Front Public Health"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"4430","DOI":"10.1109\/TMI.2024.3425533","article-title":"Counterfactual Causal-effect intervention for interpretable medical visual question answering","volume":"43","author":"Cai","year":"2024","journal-title":"IEEE T Med Imaging"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"4804","DOI":"10.1097\/JS9.0000000000001466","article-title":"Clot removAl with or without decompRessive craniectomy under ICP monitoring for supratentorial IntraCerebral Hemorrhage (CARICH): a randomized controlled trial","volume":"110","author":"Zhang","year":"2024","journal-title":"International Journal of Surgery"},{"key":"ref10","first-page":"6283","article-title":"SLNL: a novel method for gene selection and phenotype classification","volume":"37","author":"Huang","year":"2022","journal-title":"Int J Surg"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"0061","DOI":"10.34133\/cbsystems.0061","article-title":"Analysis of rowing force of the water strider middle leg by direct measurement using a bio-appropriating probe and by indirect measurement using image analysis","volume":"4","author":"Uesugi","year":"2023","journal-title":"Cyborg Bionic Syst"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"0102","DOI":"10.34133\/cbsystems.0102","article-title":"Merge-and-split graph convolutional network for skeleton-based interaction recognition","volume":"5","author":"Wang","year":"2024","journal-title":"Cyborg Bionic Syst"},{"key":"ref13","first-page":"1","article-title":"In situ magnetic field compensation method for optically pumped magnetometers under three-axis nonorthogonality","volume":"73","author":"Long","year":"2024","journal-title":"IEEE T Instrum Meas"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1007\/s40120-021-00279-8","article-title":"Hematoma evacuation via image-guided para-corticospinal tract approach in patients with spontaneous intracerebral hemorrhage","volume":"10","author":"Zhang","year":"2021","journal-title":"Neurolo Therapy"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"230212","DOI":"10.29026\/oea.2024.230212","article-title":"Large-field objective lens for multi-wavelength microscopy at mesoscale and submicron resolution","volume":"7","author":"Xu","year":"2024","journal-title":"Opto-Electron Adv"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"2454","DOI":"10.1109\/TBME.2024.3376603","article-title":"A complete scheme for multi-character classification using EEG signals from speech imagery","volume":"71","author":"Pan","year":"2024","journal-title":"IEEE T Bio-med Eng"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1109\/THMS.2024.3407875","article-title":"Reconstructing visual stimulus representation from eeg signals based on deep visual representation model","volume":"54","author":"Pan","year":"2024","journal-title":"IEEE T Hum-Mach Syst"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"0093","DOI":"10.34133\/cbsystems.0093","article-title":"Hybrid directed hypergraph learning and forecasting of skeleton-based human poses","volume":"5","author":"Cui","year":"2024","journal-title":"Cyborg Bionic Syst"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"22786","DOI":"10.1038\/s41598-024-74186-x","article-title":"Retinal fundus image super-resolution based on generative adversarial network guided with vascular structure prior","volume":"14","author":"Jia","year":"2024","journal-title":"Sci Report"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"33378","DOI":"10.1364\/OE.530764","article-title":"Enhancing the sensitivity of spin-exchange relaxation-free magnetometers using phase-modulated pump light with external Gaussian noise","volume":"32","author":"Ma","year":"2024","journal-title":"Optics Express"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1109\/TBC.2022.3231101","article-title":"Perception-oriented U-shaped transformer network for 360-degree no-reference image quality assessment","volume":"69","author":"Zhou","year":"2023","journal-title":"IEEE T Broadcast"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"1280","DOI":"10.1109\/TR.2023.3336330","article-title":"LI-EMRSQL: linking information enhanced Text2SQL parsing on complex electronic medical records","volume":"73","author":"Li","year":"2024","journal-title":"IEEE T Reliab"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"1277123","DOI":"10.3389\/fcvm.2024.1277123","article-title":"A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme","volume":"11","author":"Bing","year":"2024","journal-title":"Front Cardiovasc Med"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"10965","DOI":"10.1109\/TMM.2024.3428349","article-title":"CenterFormer: a novel cluster center enhanced transformer for unconstrained dental plaque segmentation","volume":"26","author":"Song","year":"2024","journal-title":"IEEE T Multimed"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"245023","DOI":"10.1088\/1361-6560\/ad0a5a","article-title":"Deep learning for fast super-resolution ultrasound microvessel imaging","volume":"68","author":"Luan","year":"2023","journal-title":"Physic Med Biology"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"205002","DOI":"10.1088\/1361-6560\/acf98f","article-title":"Deep learning for fast denoising filtering in ultrasound localization microscopy","volume":"68","author":"Yu","year":"2023","journal-title":"Physic Med Biology"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1186\/s12984-024-01497-5","article-title":"Detecting muscle fatigue among community-dwelling senior adults with shape features of the probability density function of sEMG","volume":"21","author":"Ou","year":"2024","journal-title":"J NeuroEng Rehabil"},{"key":"ref28","series-title":"2021 3rd International Conference on Signal Processing and Communication (ICPSC)","first-page":"603","article-title":"Deep learning techniques on text classification using Natural language processing (NLP) in social healthcare network: a comprehensive survey","author":"Lavanya","year":"2021 May 13\u201314"},{"key":"ref29","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, et al. An image is worth 16x16 words: transformers for image recognition at scale. arXiv:2010.11929. 2020."},{"key":"ref30","unstructured":"Lahoud J, Cao J, Khan FS, Cholakkal H, Anwer RM, Khan S, et al. 3D vision with transformers: a survey. arXiv:2208.04309. 2022."},{"key":"ref31","unstructured":"Pereira GA, Hussain M. A review of transformer-based models for computer vision tasks: capturing global context and spatial relationships. arXiv:2408.15178. 2024."},{"key":"ref32","doi-asserted-by":"crossref","first-page":"2313","DOI":"10.3390\/math12152313","article-title":"Transformative noise reduction: leveraging a transformer-based deep network for medical image denoising","volume":"12","author":"Naqvi","year":"2024","journal-title":"Mathematics"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12885-017-3800-9","article-title":"Concordance of FDG PET\/CT metabolic tumour volume versus DW-MRI functional tumour volume with T2-weighted anatomical tumour volume in cervical cancer","volume":"17","author":"Lai","year":"2017","journal-title":"BMC Cancer"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"e59505","DOI":"10.2196\/59505","article-title":"Multimodal large language models in health care: applications, challenges, and future outlook","volume":"26","author":"AlSaad","year":"2024","journal-title":"J Med Internet Res"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"18949","DOI":"10.1109\/JSEN.2023.3297109","article-title":"Optically pumped magnetometers recent advances and applications in biomagnetism: a review","volume":"23","author":"Zhao","year":"2023","journal-title":"IEEE Sens J"},{"key":"ref36","unstructured":"Nerella S, Bandyopadhyay S, Zhang J, Contreras M, Siegel S, Bumin A, et al. Transformers in healthcare: a survey. arXiv:2307.00067. 2023."},{"key":"ref37","doi-asserted-by":"crossref","first-page":"102900","DOI":"10.1016\/j.artmed.2024.102900","article-title":"Transformers and large language models in healthcare: a review","volume":"154","author":"Nerella","year":"2024","journal-title":"Artif Intell Med"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"e49724","DOI":"10.2196\/49724","article-title":"Task-specific transformer-based language models in health care: scoping review","volume":"12","author":"Cho","year":"2024","journal-title":"JMIR Med Inform"},{"key":"ref39","doi-asserted-by":"crossref","first-page":"e2298","DOI":"10.7717\/peerj-cs.2298","article-title":"Advancing healthcare through multimodal data fusion: a comprehensive review of techniques and applications","volume":"10","author":"Teoh","year":"2024","journal-title":"PeerJ Comput Sci"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"354","DOI":"10.3390\/jpm14040354","article-title":"A comprehensive evaluation of AI-assisted diagnostic tools in ENT medicine: insights and perspectives from healthcare professionals","volume":"14","author":"Alshehri","year":"2024","journal-title":"J Pers Med"},{"key":"ref41","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1109\/RBME.2023.3297604","article-title":"Vision transformers for computational histopathology","volume":"17","author":"Xu","year":"2023","journal-title":"IEEE Rev Biomed Eng"},{"key":"ref42","unstructured":"Eghbali N, Bagher-Ebadian H, Alhanai T, Ghassemi MM. GLoG-CSUnet: enhancing vision transformers with adaptable radiomic features for medical image segmentation. arXiv:2501.02788. 2025."},{"key":"ref43","unstructured":"Famiglini L. Enhancing the explainability and reliability of AI support for informed healthcare decisions [Ph.D. thesis]. Milano, Italy: Universit\u00e0 degli Studi di Milano Bicocca; 2025."},{"key":"ref44","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1002\/9781394278695.ch14","author":"Rashid","year":"2025","journal-title":"AI in disease detection: advancements and applications"},{"key":"ref45","doi-asserted-by":"crossref","unstructured":"Maambo M. Assisted artificial intelligence medical diagnosis system for heart disease [master thesis]. Lusaka, Zambia: The University of Zambia; 2023.","DOI":"10.33260\/zictjournal.v6i1.123"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"102762","DOI":"10.1016\/j.media.2023.102762","article-title":"Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives","volume":"85","author":"Li","year":"2023","journal-title":"Med Image Anal"},{"key":"ref47","doi-asserted-by":"crossref","first-page":"11039","DOI":"10.1007\/s00521-025-11081-0","article-title":"The paradigm of digital health: aI applications and transformative trends","volume":"37","author":"Rashid","year":"2025","journal-title":"Neural Comput Appl"},{"key":"ref48","first-page":"62","article-title":"The transformative role of artificial intelligence in the healthcare industry: a comprehensive analysis","volume":"6","author":"Salehi","year":"2024","journal-title":"Asian J Res Med Med Sci"},{"key":"ref49","doi-asserted-by":"crossref","first-page":"1","DOI":"10.16925\/2357-6014.2024.02.07","article-title":"A comprehensive review on ai-driven healthcare transformation","volume":"20","author":"Balakrishna","year":"2024","journal-title":"Ing Solidar"},{"key":"ref50","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.neucom.2015.07.160","article-title":"An overview of multi-modal medical image fusion","volume":"215","author":"Du","year":"2016","journal-title":"Neurocomputing"},{"key":"ref51","first-page":"1","article-title":"Detail enhanced feature-level medical image fusion in decorrelating decomposition domain","volume":"70","author":"Singh","year":"2020","journal-title":"IEEE Trans Instrum Meas"},{"key":"ref52","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/978-981-15-4867-3_4","author":"Xiao","year":"2020","journal-title":"Image fusion"},{"key":"ref53","doi-asserted-by":"crossref","first-page":"108036","DOI":"10.1016\/j.sigpro.2021.108036","article-title":"Multimodal medical image fusion review: theoretical background and recent advances","volume":"183","author":"Hermessi","year":"2021","journal-title":"Signal Process"},{"key":"ref54","doi-asserted-by":"crossref","first-page":"42821","DOI":"10.1007\/s11042-022-13482-y","article-title":"Multi-layer, multi-modal medical image intelligent fusion","volume":"81","author":"Nair","year":"2022","journal-title":"Multimedia Tools Appl"},{"key":"ref55","doi-asserted-by":"crossref","first-page":"101733","DOI":"10.1016\/j.jksuci.2023.101733","article-title":"Multimodal medical image fusion towards future research: a review","volume":"35","author":"Khan","year":"2023","journal-title":"J King Saud Univ\u2014Comput Inf Sci"},{"key":"ref56","series-title":"2017 International Conference on Inventive Computing and Informatics (ICICI)","first-page":"198","article-title":"A study on brain tumor segmentation using convolution neural network","author":"Parihar","year":"2017 Nov 23\u201324"},{"key":"ref57","series-title":"Medical Image Computing and Computer Assisted Intervention-MICCAI 2021: 24th International Conference","first-page":"14","article-title":"Transfuse: Fusing transformers and cnns for medical image segmentation","author":"Zhang","year":"2021 Sep 27\u2013Oct 1"},{"key":"ref58","doi-asserted-by":"crossref","first-page":"104791","DOI":"10.1016\/j.bspc.2023.104791","article-title":"Transformers in medical image segmentation: a review","volume":"84","author":"Xiao","year":"2023","journal-title":"Biomed Signal Process Control"},{"key":"ref59","unstructured":"Khan A, Rauf Z, Khan AR, Rathore S, Khan SH, Shah NS, et al. A recent survey of vision transformers for medical image segmentation. arXiv:2312.00634. 2023."},{"key":"ref60","doi-asserted-by":"crossref","first-page":"3420","DOI":"10.3390\/s23073420","article-title":"High-resolution Swin transformer for automatic medical image segmentation","volume":"23","author":"Wei","year":"2023","journal-title":"Sensors"},{"key":"ref61","doi-asserted-by":"crossref","first-page":"105331","DOI":"10.1016\/j.bspc.2023.105331","article-title":"Hybrid CNN-Transformer model for medical image segmentation with pyramid convolution and multi-layer perceptron","volume":"86","author":"Liu","year":"2023","journal-title":"Biomed Signal Process Control"},{"key":"ref62","unstructured":"Ma J, Li F, Wang B. U-mamba: enhancing long-range dependency for biomedical image segmentation. arXiv:2401.04722. 2024."},{"key":"ref63","doi-asserted-by":"crossref","first-page":"638","DOI":"10.1109\/TMI.2018.2868977","article-title":"Learning cross-modality representations from multi-modal images","volume":"38","author":"van Tulder","year":"2018","journal-title":"IEEE Trans Med Imaging"},{"key":"ref64","first-page":"439","volume":"10953","author":"Yu","year":"2019","journal-title":"Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging"},{"key":"ref65","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1007\/978-3-031-18576-2_2","author":"Patel","year":"2022","journal-title":"MICCAI Workshop on Deep Generative Models"},{"key":"ref66","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.imed.2022.07.002","article-title":"Transformers in medical image analysis","volume":"3","author":"He","year":"2023","journal-title":"Intell Med"},{"key":"ref67","doi-asserted-by":"crossref","first-page":"e38","DOI":"10.1002\/mef2.38","article-title":"Recent advances of transformers in medical image analysis: a comprehensive review","volume":"2","author":"Xia","year":"2023","journal-title":"MedComm-Future Med"},{"key":"ref68","doi-asserted-by":"crossref","first-page":"1398","DOI":"10.1109\/JBHI.2023.3348436","article-title":"Is attention all you need in medical image analysis? A review","volume":"28","author":"Papanastasiou","year":"2023","journal-title":"IEEE J Biomed Health Inform"},{"key":"ref69","first-page":"3680","article-title":"Systematic review of hybrid vision transformer architectures for radiological image analysis","volume":"13","author":"Kim","year":"2024","journal-title":"medRxiv"},{"key":"ref70","series-title":"2024 International Conference on Emerging Smart Computing and Informatics (ESCI)","first-page":"1","article-title":"Exploring hand gesture recognition techniques for enhanced control of bionic hands","author":"Yadav","year":"2024 Mar 5\u20137"},{"key":"ref71","first-page":"1","article-title":"Survey on deep multi-modal data analytics: collaboration, rivalry, and fusion","volume":"17","author":"Wang","year":"2021","journal-title":"ACM Trans Multimed Comput Commun Appl (TOMM)"},{"key":"ref72","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1162\/neco_a_01273","article-title":"A survey on deep learning for multimodal data fusion","volume":"32","author":"Gao","year":"2020","journal-title":"Neural Comput"},{"key":"ref73","doi-asserted-by":"crossref","first-page":"102536","DOI":"10.1016\/j.inffus.2024.102536","article-title":"Deep learning based multimodal biomedical data fusion: an overview and comparative review","volume":"112","author":"Duan","year":"2024","journal-title":"Inf Fusion"},{"key":"ref74","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1038\/s41568-021-00408-3","article-title":"Harnessing multimodal data integration to advance precision oncology","volume":"22","author":"Boehm","year":"2022","journal-title":"Nat Rev Cancer"},{"key":"ref75","doi-asserted-by":"crossref","first-page":"113","DOI":"10.3390\/biomedinformatics4010008","article-title":"Interpretable medical imagery diagnosis with self-attentive transformers: a review of explainable AI for health care","volume":"4","author":"Lai","year":"2024","journal-title":"BioMedInformatics"},{"key":"ref76","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1007\/s10278-013-9619-2","article-title":"Content-based medical image retrieval: a survey of applications to multidimensional and multimodality data","volume":"26","author":"Kumar","year":"2013","journal-title":"J Digit Imaging"},{"key":"ref77","doi-asserted-by":"crossref","first-page":"99540","DOI":"10.1109\/ACCESS.2019.2929365","article-title":"Going deep in medical image analysis: concepts, methods, challenges, and future directions","volume":"7","author":"Altaf","year":"2019","journal-title":"IEEE Access"},{"key":"ref78","doi-asserted-by":"crossref","first-page":"110905","DOI":"10.1109\/ACCESS.2024.3439439","article-title":"Weighted fusion transformer for dual PET\/CT head and neck tumor segmentation","volume":"12","author":"Mahdi","year":"2024","journal-title":"IEEE Access"},{"key":"ref79","doi-asserted-by":"crossref","unstructured":"Rane N. Transformers for medical image analysis: applications, challenges, and future scope. 2023 Nov 2. doi:10.2139\/ssrn.4622241.","DOI":"10.2139\/ssrn.4622241"},{"key":"ref80","doi-asserted-by":"crossref","first-page":"102802","DOI":"10.1016\/j.media.2023.102802","article-title":"Transformers in medical imaging: a survey","volume":"88","author":"Shamshad","year":"2023","journal-title":"Med Image Anal"},{"key":"ref81","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.jksuci.2017.12.007","article-title":"Implications of big data analytics in developing healthcare frameworks\u2014a review","volume":"31","author":"Palanisamy","year":"2019","journal-title":"J King Saud Univ-Comput Inform Sci"},{"key":"ref82","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.bdr.2016.05.002","article-title":"Towards a comprehensive data analytics framework for smart healthcare services","volume":"4","author":"Sakr","year":"2016","journal-title":"Big Data Res"},{"key":"ref83","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4471-7320-5","author":"Toennies","year":"2017","journal-title":"Guide to medical image analysis"},{"key":"ref84","doi-asserted-by":"crossref","first-page":"111810","DOI":"10.1016\/j.knosys.2024.111810","article-title":"GaitFormer: leveraging dual-stream spatial-temporal Vision Transformer via a single low-cost RGB camera for clinical gait analysis","volume":"295","author":"Li","year":"2024","journal-title":"Knowl Based Syst"},{"key":"ref85","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"107","article-title":"mmformer: multimodal medical transformer for incomplete multimodal learning of brain tumor segmentation","author":"Zhang","year":"2022"},{"key":"ref86","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1109\/JBHI.2023.3326151","article-title":"MFTrans: modality-masked fusion transformer for incomplete multi-modality brain tumor segmentation","volume":"28","author":"Shi","year":"2023","journal-title":"IEEE J Biomed Health Inform"},{"key":"ref87","first-page":"1144","author":"Karimijafarbigloo","year":"2024","journal-title":"Medical Imaging with Deep Learning"},{"key":"ref88","series-title":"Proceedings of the 6th ACM\/SPEC International Conference on Performance Engineering","first-page":"145","article-title":"Enhancing performance prediction robustness by combining analytical modeling and machine learning","author":"Didona","year":"2015 Jan 28\u2013Feb 4"},{"key":"ref89","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1038\/s42256-022-00516-1","article-title":"Advances, challenges and opportunities in creating data for trustworthy AI","volume":"4","author":"Liang","year":"2022","journal-title":"Nat Mach Intell"},{"key":"ref90","first-page":"167","author":"Abdollahi","year":"2020","journal-title":"Data augmentation in training deep learning models for medical image analysis. Deep learners and deep learner descriptors for medical applications"},{"key":"ref91","doi-asserted-by":"crossref","first-page":"219","DOI":"10.3390\/bioengineering11030219","article-title":"A comprehensive review on synergy of multi-modal data and ai technologies in medical diagnosis","volume":"11","author":"Xu","year":"2024","journal-title":"Bioengineering"},{"key":"ref92","doi-asserted-by":"crossref","first-page":"1392807","DOI":"10.3389\/fbioe.2024.1392807","article-title":"Recent deep learning-based brain tumor segmentation models using multi-modality magnetic resonance imaging: a prospective survey","volume":"12","author":"Abidin","year":"2024","journal-title":"Front Bioeng Biotechnol"},{"key":"ref93","first-page":"93","article-title":"Deep learning attention mechanism in medical image analysis: basics and beyonds","volume":"2","author":"Li","year":"2023","journal-title":"Int J Netw Dyn Intell"},{"key":"ref94","doi-asserted-by":"crossref","unstructured":"Khanal B, Shrestha P, Amgain S, Khanal B, Bhattarai B, Linte CA. Investigating the robustness of vision transformers against label noise in medical image classification. arXiv:2402.16734. 2024.","DOI":"10.1109\/EMBC53108.2024.10782929"},{"key":"ref95","unstructured":"Xu L, Sun H, Ni Z, Li H, Zhang S. MedViLaM: a multimodal large language model with advanced generalizability and explainability for medical data understanding and generation. arXiv:2409.19684. 2024."},{"key":"ref96","doi-asserted-by":"crossref","first-page":"34","DOI":"10.70589\/JRTCSE.2024.1.6","article-title":"Enhancing real-world robustness in AI: challenges and solutions","volume":"12","author":"Roy","year":"2024","journal-title":"J Recent Trends Comput Sci Eng (JRTCSE)"},{"key":"ref97","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1167\/tvst.9.2.45","article-title":"Current challenges and barriers to real-world artificial intelligence adoption for the healthcare system, provider, and the patient","volume":"9","author":"Singh","year":"2020","journal-title":"Transl Vis Sci Technol"},{"key":"ref98","doi-asserted-by":"crossref","first-page":"102308","DOI":"10.1016\/j.compmedimag.2023.102308","article-title":"Multi-modal medical Transformers: a meta-analysis for medical image segmentation in oncology","volume":"110","author":"Andrade-Miranda","year":"2023","journal-title":"Comput Med Imaging Graph"},{"key":"ref99","doi-asserted-by":"crossref","first-page":"109228","DOI":"10.1016\/j.patcog.2022.109228","article-title":"An effective CNN and Transformer complementary network for medical image segmentation","volume":"136","author":"Yuan","year":"2023","journal-title":"Pattern Recognit"},{"key":"ref100","doi-asserted-by":"crossref","first-page":"113233","DOI":"10.1016\/j.knosys.2025.113233","article-title":"DCSSGA-UNet: biomedical image segmentation with DenseNet channel spatial and semantic guidance attention","volume":"314","author":"Hussain","year":"2025","journal-title":"Knowl Based Syst"},{"key":"ref101","doi-asserted-by":"crossref","first-page":"105605","DOI":"10.1016\/j.bspc.2023.105605","article-title":"HTC-Net: a hybrid CNN-transformer framework for medical image segmentation","volume":"88","author":"Tang","year":"2024","journal-title":"Biomed Signal Process Control"},{"key":"ref102","doi-asserted-by":"crossref","first-page":"1034","DOI":"10.3390\/bioengineering11101034","article-title":"Advances in medical image segmentation: a comprehensive review of traditional, deep learning and hybrid approaches","volume":"11","author":"Xu","year":"2024","journal-title":"Bioengineering"},{"key":"ref103","doi-asserted-by":"crossref","first-page":"267","DOI":"10.51537\/chaos.1326790","article-title":"Unveiling the complexity of medical imaging through deep learning approaches","volume":"5","author":"Rasool","year":"2023","journal-title":"Chaos Theory Applicati"},{"key":"ref104","doi-asserted-by":"crossref","first-page":"105253","DOI":"10.1016\/j.compbiomed.2022.105253","article-title":"A review on multimodal medical image fusion: compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics","volume":"144","author":"Azam","year":"2022","journal-title":"Comput Biol Med"},{"key":"ref105","series-title":"Proceedings of the 2021 International Conference on Multimedia Retrieval","first-page":"456","article-title":"Cross-modal self-attention with multi-task pre-training for medical visual question answering","author":"Gong","year":"2021 Nov 16\u201319"},{"key":"ref106","article-title":"Research on tumor detection and classification model based on self-attention mechanism","author":"Huang","year":"2024","journal-title":"IEEE Access"},{"key":"ref107","doi-asserted-by":"crossref","first-page":"109583","DOI":"10.1016\/j.engappai.2024.109583","article-title":"Cross-attention interaction learning network for multi-model image fusion via transformer","volume":"139","author":"Wang","year":"2025","journal-title":"Eng Appl Artif Intell"},{"key":"ref108","first-page":"471","article-title":"Foundation models in medical imaging: revolutionizing diagnostic accuracy and efficiency","volume":"4","author":"Prabhod","year":"2024","journal-title":"J Artif Intell Res Appl"},{"key":"ref109","doi-asserted-by":"crossref","first-page":"9375","DOI":"10.1109\/ACCESS.2017.2788044","article-title":"Deep learning applications in medical image analysis","volume":"6","author":"Ker","year":"2017","journal-title":"IEEE Access"},{"key":"ref110","first-page":"323","author":"Razzak","year":"2017","journal-title":"Classification in BioApps: Automation of Decision Making"},{"key":"ref111","first-page":"1","article-title":"Attention-guided and noise-resistant learning for robust medical image segmentation","volume":"73","author":"Chen","year":"2024","journal-title":"IEEE Trans Instrum Meas"},{"key":"ref112","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1038\/s41551-022-00898-y","article-title":"Shifting machine learning for healthcare from development to deployment and from models to data","volume":"6","author":"Zhang","year":"2022","journal-title":"Nat Biomed Eng"},{"key":"ref113","doi-asserted-by":"crossref","first-page":"17979","DOI":"10.1007\/s00521-024-10353-5","article-title":"Vision transformers in domain adaptation and domain generalization: a study of robustness","volume":"36","author":"Alijani","year":"2024","journal-title":"Neural Comput Appl"},{"key":"ref114","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10916-024-02105-8","article-title":"Comparison of vision transformers and convolutional neural networks in medical image analysis: a systematic review","volume":"48","author":"Takahashi","year":"2024","journal-title":"J Med Syst"},{"key":"ref115","series-title":"ICMLCA 2021; 2nd International Conference on Machine Learning and Computer Application","first-page":"1","article-title":"Comparison of the potential between transformer and CNN in image classification","author":"Lu","year":"2021 Dec 17\u201319"},{"key":"ref116","doi-asserted-by":"crossref","first-page":"40290","DOI":"10.1109\/ACCESS.2024.3374108","article-title":"MAGRes-UNet: improved medical image segmentation through a deep learning paradigm of multi-attention gated residual U-Net","volume":"12","author":"Hussain","year":"2024","journal-title":"IEEE Access"},{"key":"ref117","unstructured":"Kilimci ZH, Yalcin M, Kucukmanisa A, Mishra AK. Heart disease detection using vision-based transformer models from ECG images. arXiv:2310.12630. 2023."},{"key":"ref118","doi-asserted-by":"crossref","DOI":"10.1049\/cit2.12293","article-title":"ECG-TransCovNet: a hybrid transformer model for accurate arrhythmia detection using electrocardiogram signals","author":"Shah","year":"2024","journal-title":"CAAI Trans Intell Technol"},{"key":"ref119","doi-asserted-by":"crossref","first-page":"105714","DOI":"10.1016\/j.bspc.2023.105714","article-title":"ECGTransForm: empowering adaptive ECG arrhythmia classification framework with bidirectional transformer","volume":"89","author":"El-Ghaish","year":"2024","journal-title":"Biomed Signal Process Control"},{"key":"ref120","series-title":"33rd British Machine Vision Conference","article-title":"Adversarial vision transformer for medical image semantic segmentation with limited annotations","author":"Wang","year":"2022 Nov 21\u201324"},{"key":"ref121","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/s11633-017-1053-3","article-title":"A survey on deep learning-based fine-grained object classification and semantic segmentation","volume":"14","author":"Zhao","year":"2017","journal-title":"Int J Automa Comput"},{"key":"ref122","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference","first-page":"762","article-title":"Self-supervision with superpixels: training few-shot medical image segmentation without annotation","author":"Ouyang","year":"2020 Aug 23\u201328"},{"key":"ref123","doi-asserted-by":"crossref","first-page":"21741","DOI":"10.1007\/s00521-022-07635-1","article-title":"Multi-modal medical image fusion based on densely-connected high-resolution CNN and hybrid transformer","volume":"34","author":"Zhou","year":"2022","journal-title":"Neural Comput Appl"},{"key":"ref124","unstructured":"Yang Q, Zhao Y, Cheng H. MMLF: multi-modal multi-class late fusion for object detection with uncertainty estimation. arXiv:2410.08739. 2024."},{"key":"ref125","series-title":"Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2021: 24th International Conference","first-page":"589","article-title":"Modality-aware mutual learning for multi-modal medical image segmentation","author":"Zhang","year":"2021 Sep 27\u2013Oct 1"},{"key":"ref126","series-title":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","first-page":"872","article-title":"Universal multi-modal deep network for classification and segmentation of medical images","author":"Harouni","year":"2018 Apr 4\u20137"},{"key":"ref127","series-title":"2021 IEEE International Conference on Image Processing (ICIP)","first-page":"299","article-title":"Liver tumor detection via a multi-scale intermediate multi-modal fusion network on MRI images","author":"Pan","year":"2021 Sep 19\u201322"},{"key":"ref128","doi-asserted-by":"crossref","first-page":"10817","DOI":"10.1007\/s11042-024-19313-6","article-title":"Denoising and segmentation in medical image analysis: a comprehensive review on machine learning and deep learning approaches","volume":"84","author":"Kumar","year":"2025","journal-title":"Multimed Tools Appl"},{"key":"ref129","first-page":"188","article-title":"Performance of quality metrics for compressed medical images through mean opinion score prediction","volume":"2","author":"Kumar","year":"2012","journal-title":"J Med Imaging Health Infor"},{"key":"ref130","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-030-33128-3_1","author":"Chan","year":"2020","journal-title":"Deep learning in medical image analysis: challenges and applications"},{"key":"ref131","series-title":"Medical Image Computing and Computer-Assisted Intervention-MICCAI 2016: 19th International Conference","first-page":"478","article-title":"Deep learning for multi-task medical image segmentation in multiple modalities","author":"Moeskops","year":"2016 Oct 17\u201321"},{"key":"ref132","doi-asserted-by":"crossref","first-page":"14263","DOI":"10.1038\/s41598-024-63446-5","article-title":"Hybrid transformer-CNN model for accurate prediction of peptide hemolytic potential","volume":"14","author":"Almotairi","year":"2024","journal-title":"Sci Rep"},{"key":"ref133","doi-asserted-by":"crossref","first-page":"8066","DOI":"10.1021\/acs.chemrev.0c00004","article-title":"Big-data science in porous materials: materials genomics and machine learning","volume":"120","author":"Jablonka","year":"2020","journal-title":"Chem Rev"},{"key":"ref134","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1038\/s41586-023-05905-z","article-title":"Computational approaches streamlining drug discovery","volume":"616","author":"Sadybekov","year":"2023","journal-title":"Nature"},{"key":"ref135","doi-asserted-by":"crossref","first-page":"6075","DOI":"10.3390\/s24186075","article-title":"DSC-Net: enhancing blind road semantic segmentation with visual sensor using a dual-branch swin-CNN architecture","volume":"24","author":"Yuan","year":"2024","journal-title":"Sensors"},{"key":"ref136","series-title":"International Conference on Machine Learning","first-page":"5156","article-title":"Transformers are RNNs: fast autoregressive transformers with linear attention","author":"Katharopoulos","year":"2020"},{"key":"ref137","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"325","article-title":"Operating critical machine learning models in resource constrained regimes","author":"Selvan","year":"2023"},{"key":"ref138","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1049\/cit2.12356","article-title":"Deep learning on medical image analysis","volume":"10","author":"Wang","year":"2025","journal-title":"CAAI Trans Intell Technol"},{"key":"ref139","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.techfore.2015.12.019","article-title":"Big data analytics: understanding its capabilities and potential benefits for healthcare organizations","volume":"126","author":"Wang","year":"2018","journal-title":"Technol Forecast Soc Change"},{"key":"ref140","doi-asserted-by":"crossref","first-page":"125","DOI":"10.3390\/healthcare12020125","article-title":"Transformative potential of AI in healthcare: definitions, applications, and navigating the ethical landscape and public perspectives","volume":"12","author":"Bekbolatova","year":"2024","journal-title":"Healthcare"},{"key":"ref141","unstructured":"Henry EU, Emebob O, Omonhinmin CA. Vision transformers in medical imaging: a review. arXiv:2211.10043. 2022."},{"key":"ref142","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"4981","article-title":"SegFormer3D: an efficient Transformer for 3D medical image segmentation","author":"Perera","year":"2024 Jun 16\u201322"},{"key":"ref143","first-page":"11079","article-title":"Recurrent memory transformer","volume":"35","author":"Bulatov","year":"2022","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref144","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3505244","article-title":"Transformers in vision: a survey","volume":"54","author":"Khan","year":"2022","journal-title":"ACM Comput Surv (CSUR)"},{"key":"ref145","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"10012","article-title":"Swin transformer: Hierarchical vision transformer using shifted windows","author":"Liu","year":"2021 Oct 11\u201317"},{"key":"ref146","unstructured":"Heidari M, Azad R, Kolahi SG, Arimond R, Niggemeier L, Sulaiman A, et al. Enhancing efficiency in vision transformer networks: design techniques and insights. arXiv:2403.19882. 2024."},{"key":"ref147","doi-asserted-by":"crossref","unstructured":"Hamlomo S, Atemkeng M, Brima Y, Nunhokee C, Baxter J. Advancing low-rank and local low-rank matrix approximation in medical imaging: a systematic literature review and future directions. arXiv:2402.14045. 2024.","DOI":"10.1007\/s00521-025-11055-2"},{"key":"ref148","series-title":"Proceedings of the 31st Annual International Conference on Computer Science and Software Engineering","first-page":"163","article-title":"Text classification on software requirements specifications using transformer models","author":"Kici","year":"2021 Nov 22\u201325"},{"key":"ref149","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"15793","article-title":"Learning imbalanced data with vision transformers","author":"Xu","year":"2023 Jun 17\u201324"},{"key":"ref150","doi-asserted-by":"crossref","first-page":"e232471","DOI":"10.1148\/radiol.232471","article-title":"Generating synthetic data for medical imaging","volume":"312","author":"Koetzier","year":"2024","journal-title":"Radiology"},{"key":"ref151","doi-asserted-by":"crossref","first-page":"12189","DOI":"10.1109\/ACCESS.2024.3354826","article-title":"Enhancing the quality and authenticity of synthetic mammogram images for improved breast cancer detection","volume":"12","author":"Shah","year":"2024","journal-title":"IEEE Access"},{"key":"ref152","doi-asserted-by":"crossref","first-page":"118454","DOI":"10.1109\/ACCESS.2022.3221138","article-title":"Transformers meet small datasets","volume":"10","author":"Shao","year":"2022","journal-title":"IEEE Access"},{"key":"ref153","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/s10916-024-02043-5","article-title":"Transformer models in healthcare: a survey and thematic analysis of potentials, shortcomings and risks","volume":"48","author":"Denecke","year":"2024","journal-title":"J Med Syst"},{"key":"ref154","first-page":"1","article-title":"Language Model Interpretability-explainable AI methods: exploring explainable AI methods for interpreting and explaining the decisions made by language models to enhance transparency and trustworthiness","volume":"2","author":"Maruthi","year":"2022","journal-title":"Australian J Mach Learn Res Appl"},{"key":"ref155","first-page":"168","article-title":"Enhancing transparency and understanding in AI decision-making processes","volume":"8","author":"Pillai","year":"2024","journal-title":"Iconic Res Eng J"},{"key":"ref156","doi-asserted-by":"crossref","first-page":"239","DOI":"10.3390\/jimaging10100239","article-title":"A survey on explainable artificial intelligence (xai) techniques for visualizing deep learning models in medical imaging","volume":"10","author":"Bhati","year":"2024","journal-title":"J Imaging"},{"key":"ref157","doi-asserted-by":"crossref","first-page":"110519","DOI":"10.1016\/j.engappai.2025.110519","article-title":"Enhancing histopathological image analysis: an explainable vision transformer approach with comprehensive interpretation methods and evaluation of explanation quality","volume":"149","author":"Mir","year":"2025","journal-title":"Eng Appl Artif Intell"},{"key":"ref158","doi-asserted-by":"crossref","unstructured":"Li S, Sui X, Luo X, Xu X, Liu Y, Goh R. Medical image segmentation using squeeze-and-expansion transformers. arXiv:2105.09511. 2021.","DOI":"10.24963\/ijcai.2021\/112"},{"key":"ref159","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.neucom.2019.07.065","article-title":"Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems","volume":"365","author":"Abiri","year":"2019","journal-title":"Neurocomputing"},{"key":"ref160","doi-asserted-by":"crossref","first-page":"93338","DOI":"10.1109\/ACCESS.2021.3092425","article-title":"Image de-noising with machine learning: a review","volume":"9","author":"Thakur","year":"2021","journal-title":"IEEE Access"},{"key":"ref161","doi-asserted-by":"crossref","first-page":"1859","DOI":"10.1007\/s10618-020-00706-8","article-title":"MIDIA: exploring denoising autoencoders for missing data imputation","volume":"34","author":"Ma","year":"2020","journal-title":"Data Min Knowl Discov"},{"key":"ref162","doi-asserted-by":"crossref","first-page":"837","DOI":"10.3390\/biomedinformatics4010047","article-title":"Generative pre-trained transformer-empowered healthcare conversations: current trends, challenges, and future directions in large language model-enabled medical chatbots","volume":"4","author":"Chow","year":"2024","journal-title":"BioMedInformatics"},{"key":"ref163","doi-asserted-by":"crossref","first-page":"1435","DOI":"10.1007\/s10278-021-00525-3","article-title":"AI integration in the clinical workflow","volume":"34","author":"Blezek","year":"2021","journal-title":"J Digit Imaging"},{"key":"ref164","unstructured":"Rahman AA, Agarwal P, Noumeir R, Jouvet P, Michalski V, Kahou SE. Empowering clinicians with medical decision Transformers: a framework for sepsis treatment. arXiv:2407.19380. 2024."},{"key":"ref165","unstructured":"Shokrollahi Y, Yarmohammadtoosky S, Nikahd MM, Dong P, Li X, Gu L. A comprehensive review of generative AI in healthcare. arXiv:2310.00795. 2023."},{"key":"ref166","unstructured":"Gao Y, Zhou M, Liu D, Yan Z, Zhang S, Metaxas DN. A data-scalable transformer for medical image segmentation: architecture, model efficiency, and benchmark. arXiv:2203.00131. 2022."},{"key":"ref167","series-title":"2024 3rd International Conference on Automation, Computing and Renewable Systems (ICACRS)","first-page":"1217","article-title":"Comparative analysis of vision Transformers and CNN-based models for enhanced brain tumor diagnosis","author":"Kocharekar","year":"2024 Dec 4\u20136"},{"key":"ref168","doi-asserted-by":"crossref","first-page":"31078","DOI":"10.1109\/ACCESS.2024.3367715","article-title":"Generative AI for transformative healthcare: a comprehensive study of emerging models, applications, case studies and limitations","volume":"12","author":"Sai","year":"2024","journal-title":"IEEE Access"},{"key":"ref169","doi-asserted-by":"crossref","first-page":"98909","DOI":"10.1109\/ACCESS.2022.3206449","article-title":"A survey on attention mechanisms for medical applications: are we moving toward better Algorithms?","volume":"10","author":"Gon\u00e7alves","year":"2022","journal-title":"IEEE Access"},{"key":"ref170","doi-asserted-by":"crossref","first-page":"1935","DOI":"10.1093\/jamia\/ocaa189","article-title":"Clinical concept extraction using transformers","volume":"27","author":"Yang","year":"2020","journal-title":"J Am Med Inform Assoc"},{"key":"ref171","doi-asserted-by":"crossref","first-page":"658","DOI":"10.1007\/s41666-024-00171-8","article-title":"Large language models in biomedical and health informatics: a review with bibliometric analysis","volume":"8","author":"Yu","year":"2024","journal-title":"J Healthcare Inform Res"},{"key":"ref172","doi-asserted-by":"crossref","unstructured":"Agarwal S, Peta SB. Balancing technology and privacy: securing patient data in healthcare under HIPAA regulations. TechRxiv. 2024.","DOI":"10.36227\/techrxiv.172710272.27746544\/v1"},{"key":"ref173","doi-asserted-by":"crossref","first-page":"675","DOI":"10.3390\/app14020675","article-title":"Balancing privacy and progress: a review of privacy challenges, systemic oversight, and patient perceptions in AI-driven healthcare","volume":"14","author":"Williamson","year":"2024","journal-title":"Appl Sci"},{"key":"ref174","doi-asserted-by":"crossref","first-page":"171","DOI":"10.4018\/979-8-3693-7630-0.ch007","author":"Almeida","year":"2025","journal-title":"Navigating Privacy, Innovation, and Patient Empowerment Through Ethical Healthcare Technology"},{"key":"ref175","doi-asserted-by":"crossref","first-page":"5134","DOI":"10.1109\/TIP.2022.3193288","article-title":"MATR: multimodal medical image fusion via multiscale adaptive transformer","volume":"31","author":"Tang","year":"2022","journal-title":"IEEE Trans Image Process"},{"key":"ref176","first-page":"1","article-title":"Multimodal fusion transformer for remote sensing image classification","volume":"61","author":"Roy","year":"2023","journal-title":"IEEE Trans Geosci Remote Sens"}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-84-3\/TSP_CMC_63726\/TSP_CMC_63726.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T05:45:20Z","timestamp":1776923120000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v84n3\/63129"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":176,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.063726","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2025-01-22","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-06-16","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-30","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}