{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T13:30:07Z","timestamp":1793626207178,"version":"4.5.1"},"reference-count":28,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Medical Image Analysis"],"published-print":{"date-parts":[[2027,1]]},"DOI":"10.1016\/j.media.2026.104305","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T16:18:59Z","timestamp":1790180339000},"page":"104305","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Med-REDUCE: Representation transfer and efficiency under resolution constraints"],"prefix":"10.1016","volume":"115","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4660-1560","authenticated-orcid":false,"given":"Vasiliki","family":"Bikia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2891-937X","authenticated-orcid":false,"given":"Sonnet","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aikaterini","family":"Skrika","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7426-2068","authenticated-orcid":false,"given":"Ryan","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4404-4828","authenticated-orcid":false,"given":"Aaron","family":"Fanous","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roxana","family":"Daneshjou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.media.2026.104305_b1","series-title":"Robust and efficient medical imaging with self-supervision","author":"Azizi","year":"2022"},{"key":"10.1016\/j.media.2026.104305_b2","series-title":"FlexiViT: One model for all patch sizes","author":"Beyer","year":"2023"},{"key":"10.1016\/j.media.2026.104305_b3","doi-asserted-by":"crossref","unstructured":"Caron, M., Touvron, H., Misra, I., J\u00e9gou, H., Mairal, J., Bojanowski, P., Joulin, A., 2021. Emerging Properties in Self-Supervised Vision Transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV). pp. 9650\u20139660.","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"10.1016\/j.media.2026.104305_b4","doi-asserted-by":"crossref","DOI":"10.1038\/s41591-024-02857-3","article-title":"Towards a general-purpose foundation model for computational pathology","author":"Chen","year":"2024","journal-title":"Nature Med."},{"key":"10.1016\/j.media.2026.104305_b5","series-title":"Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC)","author":"Codella","year":"2018"},{"key":"10.1016\/j.media.2026.104305_b6","series-title":"Patch n\u2019 pack: NaViT, a vision transformer for any aspect ratio and resolution","author":"Dehghani","year":"2023"},{"key":"10.1016\/j.media.2026.104305_b7","series-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2021"},{"key":"10.1016\/j.media.2026.104305_b8","series-title":"HDKD: Hybrid data-efficient knowledge distillation network for medical image classification","author":"EL-Assiouti","year":"2025"},{"key":"10.1016\/j.media.2026.104305_b9","series-title":"Look one and more: Distilling hybrid order relational knowledge for cross-resolution image recognition","author":"Ge","year":"2024"},{"key":"10.1016\/j.media.2026.104305_b10","series-title":"Cross-domain knowledge distillation for low-resolution human pose estimation","author":"Gu","year":"2024"},{"key":"10.1016\/j.media.2026.104305_b11","series-title":"Masked autoencoders are scalable vision learners","author":"He","year":"2021"},{"key":"10.1016\/j.media.2026.104305_b12","unstructured":"Hendrycks, D., Dietterich, T., 2019. Benchmarking Neural Network Robustness to Common Corruptions and Perturbations, cs.LG arXiv:1903.12261."},{"key":"10.1016\/j.media.2026.104305_b13","series-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"10.1016\/j.media.2026.104305_b14","series-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017"},{"key":"10.1016\/j.media.2026.104305_b15","doi-asserted-by":"crossref","unstructured":"Irvin, J., Rajpurkar, P., Ko, M., Yu, Y., Ciurea-Ilcus, S., Chute, C., Marklund, H., Haghgoo, B., Ball, R., Shpanskaya, K., et al., 2019. CheXpert: A large chest radiograph dataset with uncertainty labels and expert comparison. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 33, pp. 590\u2013597.","DOI":"10.1609\/aaai.v33i01.3301590"},{"key":"10.1016\/j.media.2026.104305_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111664","article-title":"RSKD: Enhanced medical image segmentation via multi-layer, rank-sensitive knowledge distillation in vision transformer models","volume":"293","author":"Liang","year":"2024","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.media.2026.104305_b17","series-title":"Towards a visual-language foundation model for computational pathology","author":"Lu","year":"2023"},{"key":"10.1016\/j.media.2026.104305_b18","series-title":"DINOv2: Learning robust visual features without supervision","author":"Oquab","year":"2024"},{"key":"10.1016\/j.media.2026.104305_b19","series-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021"},{"key":"10.1016\/j.media.2026.104305_b20","series-title":"FitNets: Hints for thin deep nets","author":"Romero","year":"2015"},{"key":"10.1016\/j.media.2026.104305_b21","series-title":"DINOv3","author":"Sim\u00e9oni","year":"2025"},{"issue":"12","key":"10.1016\/j.media.2026.104305_b22","doi-asserted-by":"crossref","first-page":"1399","DOI":"10.1038\/s41551-022-00936-9","article-title":"Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning","volume":"6","author":"Tiu","year":"2022","journal-title":"Nat. Biomed. Eng."},{"key":"10.1016\/j.media.2026.104305_b23","series-title":"Training data-efficient image transformers & distillation through attention","author":"Touvron","year":"2021"},{"key":"10.1016\/j.media.2026.104305_b24","series-title":"Fixing the train-test resolution discrepancy","author":"Touvron","year":"2019"},{"key":"10.1016\/j.media.2026.104305_b25","series-title":"TinyViT: Fast pretraining distillation for small vision transformers","author":"Wu","year":"2022"},{"key":"10.1016\/j.media.2026.104305_b26","first-page":"1","article-title":"A multimodal vision foundation model for clinical dermatology","author":"Yan","year":"2025","journal-title":"Nature Med."},{"issue":"4","key":"10.1016\/j.media.2026.104305_b27","doi-asserted-by":"crossref","first-page":"2374","DOI":"10.1109\/TCSVT.2023.3310042","article-title":"Low-resolution object recognition with cross-resolution relational contrastive distillation","volume":"34","author":"Zhang","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.media.2026.104305_b28","series-title":"Biomedclip: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs","author":"Zhang","year":"2023"}],"container-title":["Medical Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841526003749?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841526003749?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T12:54:24Z","timestamp":1793624064000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1361841526003749"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,1]]},"references-count":28,"alternative-id":["S1361841526003749"],"URL":"https:\/\/doi.org\/10.1016\/j.media.2026.104305","relation":{},"ISSN":["1361-8415"],"issn-type":[{"value":"1361-8415","type":"print"}],"subject":[],"published":{"date-parts":[[2027,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Med-REDUCE: Representation transfer and efficiency under resolution constraints","name":"articletitle","label":"Article Title"},{"value":"Medical Image Analysis","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.media.2026.104305","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104305"}}