{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T16:42:53Z","timestamp":1784738573422,"version":"3.55.0"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Phys Eng Sci Med"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1007\/s13246-025-01692-1","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T12:53:15Z","timestamp":1767617595000},"page":"617-630","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Diabetic foot ulcer classification using an enhanced coordinate attention integrated ConvNext model"],"prefix":"10.1007","volume":"49","author":[{"given":"L.","family":"Jani Anbarasi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R","family":"Neeraja","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Geetha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R.","family":"Vidhya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6873-6469","authenticated-orcid":false,"given":"Vinayakumar","family":"Ravi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"D","family":"Dhanya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,5]]},"reference":[{"issue":"7","key":"1692_CR1","first-page":"1899","volume":"59","author":"JD Santilli","year":"1999","unstructured":"Santilli JD, Santilli SM (1999) Chronic critical limb ischemia: diagnosis, treatment and prognosis. Am Family Phys 59(7):1899\u20131908","journal-title":"Am Family Phys"},{"issue":"1","key":"1692_CR2","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/0741-5214(92)90417-7","volume":"16","author":"M Albers","year":"1992","unstructured":"Albers M, Fratezi AC, De Luccia N (1992) Assessment of quality of life of patients with severe ischemia as a result of infrainguinal arterial occlusive disease. J Vasc Surg 16(1):54\u201359","journal-title":"J Vasc Surg"},{"issue":"12","key":"1692_CR3","doi-asserted-by":"publisher","first-page":"e132","DOI":"10.1093\/cid\/cis346","volume":"54","author":"BA Lipsky","year":"2012","unstructured":"Lipsky BA, Berendt AR, Cornia PB, Pile JC, Peters EJ, Armstrong DG et al (2012) 2012 infectious diseases society of America clinical practice guideline for the diagnosis and treatment of diabetic foot infections. Clin Infect Dis 54(12):e132\u2013e173","journal-title":"Clin Infect Dis"},{"issue":"6","key":"1692_CR4","doi-asserted-by":"publisher","first-page":"528","DOI":"10.1016\/S1067-2516(96)80125-6","volume":"35","author":"LA Lavery","year":"1996","unstructured":"Lavery LA, Armstrong DG, Harkless LB (1996) Classification of diabetic foot wounds. J Foot Ankle Surg 35(6):528\u2013531","journal-title":"J Foot Ankle Surg"},{"issue":"1","key":"1692_CR5","doi-asserted-by":"publisher","first-page":"163","DOI":"10.3928\/0147-7447-19870101-28","volume":"10","author":"FW Wagner","year":"1987","unstructured":"Wagner FW (1987) The diabetic foot. Orthopedics 10(1):163\u2013172","journal-title":"Orthopedics"},{"issue":"5","key":"1692_CR6","doi-asserted-by":"publisher","first-page":"9","DOI":"10.2337\/dc07-2367","volume":"31","author":"P Ince","year":"2008","unstructured":"Ince P, Abbas ZG, Lutale JK, Basit A, Ali SM, Chohan F, Morbach S et al (2008) Use of the Sinbad classification system and score in comparing outcome of foot ulcer management on three continents. Diabetes Care 31(5):9","journal-title":"Diabetes Care"},{"issue":"5","key":"1692_CR7","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1109\/TETCI.2018.2866254","volume":"4","author":"M Goyal","year":"2018","unstructured":"Goyal M et al (2018) Dfunet: convolutional neural networks for diabetic foot ulcer classification. IEEE Trans Emerg Top Comput Intell 4(5):728\u2013739","journal-title":"IEEE Trans Emerg Top Comput Intell"},{"key":"1692_CR8","doi-asserted-by":"publisher","first-page":"228586","DOI":"10.1109\/ACCESS.2020.3045732","volume":"8","author":"J Amin","year":"2020","unstructured":"Amin J et al (2020) An integrated design for classification and localization of diabetic foot ulcer based on CNN and YOLOv2-DFU models. IEEE Access 8:228586\u2013228597","journal-title":"IEEE Access"},{"key":"1692_CR9","first-page":"76","volume-title":"Classification of infection and ischemia in diabetic foot ulcers using Vgg architectures. Diabetic foot ulcers grand challenge","author":"O G\u00fcley","year":"2021","unstructured":"G\u00fcley O, Pati S, Bakas S (2021) Classification of infection and ischemia in diabetic foot ulcers using Vgg architectures. Diabetic foot ulcers grand challenge. Springer International Publishing, Cham, pp 76\u201389"},{"key":"1692_CR10","doi-asserted-by":"publisher","first-page":"105341","DOI":"10.1016\/j.bspc.2023.105341","volume":"86","author":"J Reyes-Lu\u00e9vano","year":"2023","unstructured":"Reyes-Lu\u00e9vano J et al (2023) DFU_VIRNet: A novel Visible-InfraRed CNN to improve diabetic foot ulcer classification and early detection of ulcer risk zones. Biomed Signal Process Control 86:105341","journal-title":"Biomed Signal Process Control"},{"key":"1692_CR11","doi-asserted-by":"publisher","first-page":"811028","DOI":"10.3389\/fbioe.2021.811028","volume":"9","author":"Y Xu","year":"2022","unstructured":"Xu Y et al (2022) Classification of diabetic foot ulcers using class knowledge banks. Front Bioeng Biotechnol 9:811028","journal-title":"Front Bioeng Biotechnol"},{"key":"1692_CR12","doi-asserted-by":"publisher","first-page":"127578","DOI":"10.1109\/ACCESS.2023.3332292","volume":"11","author":"S Nagaraju","year":"2023","unstructured":"Nagaraju S et al (2023) Automated diabetic foot ulcer detection and classification using deep learning. IEEE Access 11:127578\u2013127588","journal-title":"IEEE Access"},{"issue":"1","key":"1692_CR13","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1002\/ima.22598","volume":"32","author":"S Das","year":"2022","unstructured":"Das S, Kumar P, Roy, Arnab Kumar M (2022) Recognition of ischaemia and infection in diabetic foot ulcer: a deep convolutional neural network based approach. Int J Imaging Syst Technol 32(1):192\u2013208","journal-title":"Int J Imaging Syst Technol"},{"key":"1692_CR14","doi-asserted-by":"publisher","first-page":"105055","DOI":"10.1016\/j.compbiomed.2021.105055","volume":"140","author":"N Al-Garaawi","year":"2022","unstructured":"Al-Garaawi N et al (2022) Diabetic foot ulcer classification using mapped binary patterns and convolutional neural networks. Comput Biol Med 140:105055","journal-title":"Comput Biol Med"},{"issue":"21","key":"1692_CR15","doi-asserted-by":"publisher","first-page":"15655","DOI":"10.1007\/s11042-019-07820-w","volume":"79","author":"L Alzubaidi","year":"2020","unstructured":"Alzubaidi L et al (2020) DFU_QUTNet: diabetic foot ulcer classification using novel deep convolutional neural network. Multimedia Tools Appl 79(21):15655\u201315677","journal-title":"Multimedia Tools Appl"},{"key":"1692_CR16","doi-asserted-by":"crossref","unstructured":"H\u00fcsers J et al (2022) Automatic classification of diabetic foot ulcer images\u2013A transfer-learning approach to detect wound maceration. Informatics and technology in clinical care and public health. IOS, pp 301\u2013304","DOI":"10.3233\/SHTI210919"},{"key":"1692_CR17","volume-title":"Automatic classification of diabetic foot ulcers using computer vision techniques. International workshop on artificial intelligence and pattern recognition","author":"D L\u00f3pez-Cabrera Jos\u00e9","year":"2021","unstructured":"L\u00f3pez-Cabrera Jos\u00e9 D et al (2021) Automatic classification of diabetic foot ulcers using computer vision techniques. International workshop on artificial intelligence and pattern recognition. Cham: Springer"},{"key":"1692_CR18","doi-asserted-by":"crossref","unstructured":"Yap MH et al (2021) Analysis towards classification of infection and ischaemia of diabetic foot ulcers. In: 2021 IEEE EMBS international conference on biomedical and, informatics (BHI). IEEE","DOI":"10.1109\/BHI50953.2021.9508563"},{"key":"1692_CR19","doi-asserted-by":"publisher","first-page":"103616","DOI":"10.1016\/j.compbiomed.2020.103616","volume":"117","author":"M Goyal","year":"2020","unstructured":"Goyal M et al (2020) Recognition of ischaemia and infection in diabetic foot ulcers: dataset and techniques. Comput Biol Med 117:103616","journal-title":"Comput Biol Med"},{"key":"1692_CR20","doi-asserted-by":"crossref","unstructured":"Toofanee MS, Ally et al (2023) Dfu-siam a novel diabetic foot ulcer classification with deep learning. IEEE Access","DOI":"10.1109\/ACCESS.2023.3312531"},{"issue":"1","key":"1692_CR21","doi-asserted-by":"publisher","first-page":"36","DOI":"10.3390\/info14010036","volume":"14","author":"M Ahsan","year":"2023","unstructured":"Ahsan M et al (2023) A deep learning approach for diabetic foot ulcer classification and recognition. Information 14(1):36","journal-title":"Information"},{"issue":"3","key":"1692_CR22","first-page":"2001","volume":"16","author":"L Alzubaidi","year":"2021","unstructured":"Alzubaidi L, A. I. TH et al (2021) Comparison of hybrid convolutional neural networks models for diabetic foot ulcer classification. J Eng Sci Technol 16(3):2001\u20132017","journal-title":"J Eng Sci Technol"},{"key":"1692_CR23","doi-asserted-by":"crossref","unstructured":"Gupta S, Sharvan Kumar P (2021) Detection of Ischemia in DFU to acknowledge the wound status from a far-off location. In: 2021 International conference on smart generation computing, communication and networking (SMART GENCON). IEEE","DOI":"10.1109\/SMARTGENCON51891.2021.9645778"},{"key":"1692_CR24","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1109\/OJEMB.2022.3219725","volume":"3","author":"Z Liu","year":"2022","unstructured":"Liu Z, Josvin John, and, Agu E (2022) Diabetic foot ulcer ischemia and infection classification using Efficientnet deep learning models. IEEE Open J Eng Med Biol 3:189\u2013201","journal-title":"IEEE Open J Eng Med Biol"},{"key":"1692_CR25","first-page":"2349849","volume":"20221","author":"J Yogapriya","year":"2022","unstructured":"Yogapriya J et al (2022) Automated detection of infection in diabetic foot ulcer images using convolutional neural network. J Healthc Eng 20221:2349849","journal-title":"J Healthc Eng"},{"key":"1692_CR26","first-page":"1","volume-title":"Quantifying the effect of image similarity on diabetic foot ulcer classification. Diabetic foot ulcers grand challenge","author":"I Dipto","year":"2022","unstructured":"Dipto I, Chowdhury et al (2022) Quantifying the effect of image similarity on diabetic foot ulcer classification. Diabetic foot ulcers grand challenge. Springer International Publishing, Cham, pp 1\u201318"},{"issue":"2","key":"1692_CR27","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1016\/j.icte.2021.08.022","volume":"8","author":"S Das","year":"2022","unstructured":"Das S, Kumar P, Roy, Arnab Kumar Mishra (2022) DFU_SPNet: a stacked parallel convolution layers based CNN to improve diabetic foot ulcer classification. ICT Express 8(2):271\u2013275","journal-title":"ICT Express"},{"key":"1692_CR28","volume-title":"FCFNet: a network fusing color features and focal loss for diabetic foot ulcer image classification. In: International conference on neural information processing","author":"C Xie","year":"2022","unstructured":"Xie C (2022) FCFNet: a network fusing color features and focal loss for diabetic foot ulcer image classification. In: International conference on neural information processing. Springer, Singapore"},{"key":"1692_CR29","doi-asserted-by":"crossref","unstructured":"Niri R et al (2021) A superpixel-wise fully convolutional neural network approach for diabetic foot ulcer tissue classification. Pattern recognition. In: ICPR international workshops and challenges: virtual event, January 10\u201315, 2021, proceedings, part I. Springer","DOI":"10.1007\/978-3-030-68763-2_23"},{"key":"1692_CR30","doi-asserted-by":"crossref","unstructured":"Prabhu MS, Verma S (2021) A deep learning framework and its implementation for diabetic Foot ulcer classification. In: 2021 9th international conference on reliability, infocom technologies and optimization (trends and future directions) (ICRITO). IEEE","DOI":"10.1109\/ICRITO51393.2021.9596380"},{"key":"1692_CR31","first-page":"21","volume-title":"Convolutional nets versus vision transformers for diabetic foot ulcer classification. Diabetic foot ulcers grand challenge","author":"A Galdran","year":"2021","unstructured":"Galdran A, Carneiro G, Miguel A, Gonz\u00e1lez B (2021) Convolutional nets versus vision transformers for diabetic foot ulcer classification. Diabetic foot ulcers grand challenge. Springer, Cham, pp 21\u201329"},{"key":"1692_CR32","doi-asserted-by":"crossref","unstructured":"Shuvo Biswas R, Mostafiz BK, Paul FNU, Shariful (2023) DFU_MultiNet: a deep neural network approach for detecting diabetic foot ulcers through multi-scale feature fusion using the DFU dataset. Intell Based Med 8:100128","DOI":"10.1016\/j.ibmed.2023.100128"},{"issue":"7","key":"1692_CR33","doi-asserted-by":"publisher","first-page":"11723","DOI":"10.1109\/JSEN.2024.3361018","volume":"24","author":"H Luo","year":"2024","unstructured":"Luo H, Zhang X, Xu Y, Yu J, Ma X, Chen W-M (2024) A novel flexible multidimensional force platform for assessing regional plantar pressure and shear stress under the foot during gait. IEEE Sens J 24(7):11723\u201311733. https:\/\/doi.org\/10.1109\/JSEN.2024.3361018","journal-title":"IEEE Sens J"},{"key":"1692_CR34","doi-asserted-by":"publisher","first-page":"55199","DOI":"10.1007\/s11042-023-17710-x","volume":"83","author":"AM Devi","year":"2024","unstructured":"Devi AM, Hepzibai T (2024) Diabetic foot ulcer classification of hybrid convolutional neural network on hyperspectral imaging. Multimed Tools Appl 83:55199\u201355218. https:\/\/doi.org\/10.1007\/s11042-023-17710-x","journal-title":"Multimed Tools Appl"},{"key":"1692_CR35","doi-asserted-by":"publisher","unstructured":"Schmalen PG, Meyer T (2024) Temperature sensing insoles for diabetic foot ulcer diagnostics. IEEE Sens Lett 8(7):1\u20134, Art no. 6006704. https:\/\/doi.org\/10.1109\/LSENS.2024.3407589","DOI":"10.1109\/LSENS.2024.3407589"},{"key":"1692_CR36","doi-asserted-by":"crossref","unstructured":"Liu Z, Mao H, Wu CY, Feichtenhofer C, Darrell T, Xie S (2022) A convnet for the 2020s. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 11976\u201311986","DOI":"10.1109\/CVPR52688.2022.01167"},{"key":"1692_CR37","doi-asserted-by":"crossref","unstructured":"Hou Q, Zhou D, Feng J (2021) Coordinate attention for efficient mobile network design. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 13713\u201313722","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"1692_CR38","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1692_CR39","doi-asserted-by":"crossref","unstructured":"Zhao H, Shi J, Qi X, Wang X, Jia J (2017) Pyramid scene parsing network. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2881\u20132890","DOI":"10.1109\/CVPR.2017.660"},{"key":"1692_CR40","unstructured":"https:\/\/www.kaggle.com\/datasets\/laithjj\/diabetic-foot-ulcer-dfu"},{"issue":"21","key":"1692_CR41","doi-asserted-by":"publisher","first-page":"15655","DOI":"10.1007\/s11042-019-07820-w","volume":"79","author":"L Alzubaidi","year":"2020","unstructured":"Alzubaidi L, Fadhel MA, Oleiwi SR, Al-Shamma O, Zhang J (2020) DFU_QUTNet: diabetic foot ulcer classification using novel deep convolutional neural network. Multimedia Tools Appl 79(21):15655\u201315677","journal-title":"Multimedia Tools Appl"},{"issue":"10","key":"1692_CR42","doi-asserted-by":"publisher","first-page":"13289","DOI":"10.1007\/s11042-021-10942-9","volume":"81","author":"L Alzubaidi","year":"2022","unstructured":"Alzubaidi L, Fadhel MA, Al-Shamma O, Zhang J, Santamar\u00eda J, Duan Y (2022) Robust application of new deep learning tools: an experimental study in medical imaging. Multimed Tools Appl 81(10):13289\u201313317","journal-title":"Multimed Tools Appl"},{"issue":"13","key":"1692_CR43","doi-asserted-by":"publisher","first-page":"4523","DOI":"10.3390\/app10134523","volume":"10","author":"L Alzubaidi","year":"2020","unstructured":"Alzubaidi L, Fadhel MA, Al-Shamma O, Zhang J, Santamar\u00eda J, Duan Y, Oleiwi R, S (2020) Towards a better understanding of transfer learning for medical imaging: a case study. Appl Sci 10(13):4523","journal-title":"Appl Sci"}],"container-title":["Physical and Engineering Sciences in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13246-025-01692-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13246-025-01692-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13246-025-01692-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T09:14:57Z","timestamp":1784193297000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13246-025-01692-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,5]]},"references-count":43,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["1692"],"URL":"https:\/\/doi.org\/10.1007\/s13246-025-01692-1","relation":{},"ISSN":["2662-4729","2662-4737"],"issn-type":[{"value":"2662-4729","type":"print"},{"value":"2662-4737","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,5]]},"assertion":[{"value":"21 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This study used a publicly available dataset obtained from Kaggle (Diabetic Foot Ulcer dataset). The data were fully anonymized prior to release, and no identifiable personal information was accessible to the authors. Therefore, ethical approval and informed consent were not required for this study.","order":1,"name":"Ethics","label":"Ethics approval","group":{"name":"EthicsHeading","label":"Declarations"}}]}}