{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T06:08:36Z","timestamp":1778220516159,"version":"3.51.4"},"reference-count":62,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2333209"],"award-info":[{"award-number":["U2333209"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019014","name":"Chengdu Municipal Science and Technology Program","doi-asserted-by":"publisher","award":["2024-YF05-01588-SN"],"award-info":[{"award-number":["2024-YF05-01588-SN"]}],"id":[{"id":"10.13039\/501100019014","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018554","name":"Science and Technology Program of Gansu Province","doi-asserted-by":"publisher","award":["24JRRA996"],"award-info":[{"award-number":["24JRRA996"]}],"id":[{"id":"10.13039\/501100018554","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004912","name":"Sichuan University","doi-asserted-by":"publisher","award":["2023CDZG-8"],"award-info":[{"award-number":["2023CDZG-8"]}],"id":[{"id":"10.13039\/501100004912","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1016\/j.neucom.2025.131776","type":"journal-article","created":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:15:31Z","timestamp":1760145331000},"page":"131776","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":7,"special_numbering":"C","title":["A lightweight dual path Kolmogorov-Arnold convolution network for medical optical image segmentation"],"prefix":"10.1016","volume":"659","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3928-2569","authenticated-orcid":false,"given":"Jun","family":"Yuan","sequence":"first","affiliation":[]},{"given":"Lijun","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Meirong","family":"He","sequence":"additional","affiliation":[]},{"given":"Changyu","family":"Luo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7620-3342","authenticated-orcid":false,"given":"Junran","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2025.131776_bib0005","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1016\/j.ins.2022.09.019","article-title":"H-Net: a dual-decoder enhanced FCNN for automated biomedical image diagnosis","volume":"613","author":"Zhou","year":"2022","journal-title":"inf. Sci."},{"issue":"6","key":"10.1016\/j.neucom.2025.131776_bib0010","doi-asserted-by":"crossref","first-page":"2886","DOI":"10.1109\/JBHI.2023.3259802","article-title":"ULFAC-Net: Ultra-lightweight fully asymmetric convolutional network for skin lesion segmentation","volume":"27","author":"Ma","year":"2023","journal-title":"IEEE J. Biomed. Health. Inf."},{"key":"10.1016\/j.neucom.2025.131776_bib0015","series-title":"Proc. of the International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"263","article-title":"PraNet: parallel reverse attention network for polyp segmentation","author":"Fan","year":"2020"},{"key":"10.1016\/j.neucom.2025.131776_bib0020","series-title":"PROC. of the International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"601","article-title":"SelfReg-UNet: self-regularized UNet for medical image segmentation","author":"Zhu","year":"2024"},{"key":"10.1016\/j.neucom.2025.131776_bib0025","series-title":"Proc. Of the International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"234","article-title":"U-Net: convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.neucom.2025.131776_bib0030","series-title":"Proceedings of the International Conference on Information Technology in Medicine and Education","first-page":"327","article-title":"Weighted Res-UNet for high-quality retina vessel segmentation","author":"Xiao","year":"2018"},{"key":"10.1016\/j.neucom.2025.131776_bib0035","series-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BRAINLES 2018","article-title":"Automatic brain structures segmentation using deep residual dilated U-net","author":"Li","year":"2019"},{"key":"10.1016\/j.neucom.2025.131776_bib0040","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1007\/s10278-024-00981-7","article-title":"From CNN to transformer: a review of medical image segmentation models","volume":"37","author":"Yao","year":"2024","journal-title":"J. Digit. Imaging. Inform. Med."},{"key":"10.1016\/j.neucom.2025.131776_bib0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2024.103280","article-title":"TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers","volume":"97","author":"Chen","year":"2024","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.neucom.2025.131776_bib0050","series-title":"Proceedings of the European Conference on Computer Vision","first-page":"205","article-title":"Swin-UNet: UNet-like pure transformer for medical image segmentation","author":"Cao","year":"2022"},{"key":"10.1016\/j.neucom.2025.131776_bib0055","doi-asserted-by":"crossref","first-page":"3731","DOI":"10.1049\/ipr2.13219","article-title":"Skin cancer identification utilizing deep learning: a survey","volume":"18","author":"Meedeniya","year":"2024","journal-title":"IET Image Process"},{"key":"10.1016\/j.neucom.2025.131776_bib0060","author":"Bodner"},{"key":"10.1016\/j.neucom.2025.131776_bib0065","series-title":"Proceedings of the 38th International Conference on Machine Learning","first-page":"11863","article-title":"SimAM: a simple, parameter-free attention module for convolutional neural networks","author":"Yang","year":"2021"},{"key":"10.1016\/j.neucom.2025.131776_bib0070","series-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support","first-page":"3","article-title":"UNET++: A Nested U-Net Architecture for Medical Image Segmentation","author":"Zhou","year":"2018"},{"key":"10.1016\/j.neucom.2025.131776_bib0075","series-title":"Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"1055","article-title":"UNet3+ a full-scale connected UNet for medical image segmentation","author":"Huang","year":"2020"},{"key":"10.1016\/j.neucom.2025.131776_bib0080","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/electronics13040680","article-title":"Melanoma skin cancer identification with explainability utilizing mask guided technique","volume":"13","author":"Gamage","year":"2024","journal-title":"Electronics"},{"key":"10.1016\/j.neucom.2025.131776_bib0085","series-title":"2023 3rd International Conference on Advanced Research in Computing (ICARC)","first-page":"30","article-title":"Melanoma skin cancer classification with explainability","author":"Gamage","year":"2023"},{"key":"10.1016\/j.neucom.2025.131776_bib0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.108284","article-title":"Sparse dynamic volume TransUNet with multi-level edge fusion for brain tumor segmentation","volume":"172","author":"Zhu","year":"2024","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.neucom.2025.131776_bib0095","first-page":"1","article-title":"Visually stabilized mamba U-Shaped network with strong inductive bias for 3-D brain tumor segmentation","volume":"74","author":"Zhu","year":"2025","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.neucom.2025.131776_bib0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110553","article-title":"Brain tumor segmentation in MRI with multi-modality spatial information enhancement and boundary shape correction","volume":"153","author":"Zhu","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2025.131776_bib0105","series-title":"Proceedings of the European Conference on Computer Vision","first-page":"801","article-title":"Encoder-decoder with atrous separable convolution for semantic image segmentation","author":"Chen","year":"2018"},{"key":"10.1016\/j.neucom.2025.131776_bib0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2023.102805","article-title":"Self-supervised anomaly detection, staging and segmentation for retinal images","volume":"87","author":"Li","year":"2023","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.neucom.2025.131776_bib0115","series-title":"The Thirteenth International Conference on Learning Representations","article-title":"KAN: Kolmogorov\u2013Arnold networks","author":"Liu","year":"2025"},{"key":"10.1016\/j.neucom.2025.131776_bib0120","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"4652","article-title":"U-KAN makes strong backbone for medical image segmentation and generation.","author":"Li","year":"2025"},{"key":"10.1016\/j.neucom.2025.131776_bib0125","author":"Zhang"},{"key":"10.1016\/j.neucom.2025.131776_bib0130","doi-asserted-by":"crossref","first-page":"80508","DOI":"10.1109\/ACCESS.2025.3562387","article-title":"Kans-unet model and its application in image patch-shaped detection","volume":"13","author":"Li","year":"2025","journal-title":"IEEE Access"},{"key":"10.1016\/j.neucom.2025.131776_bib0135","author":"Wu"},{"key":"10.1016\/j.neucom.2025.131776_bib0140","first-page":"1","article-title":"Dual-path attention compensation U-Net for stroke lesion segmentation, comput","author":"Hui","year":"2021","journal-title":"Intell. Neurosci."},{"issue":"9","key":"10.1016\/j.neucom.2025.131776_bib0145","doi-asserted-by":"crossref","first-page":"4519","DOI":"10.1109\/JBHI.2022.3181462","article-title":"HMRNet: high and multi-resolution network with bidirectional feature calibration for brain structure segmentation in radiotherapy","volume":"26","author":"Fu","year":"2022","journal-title":"IEEE J. Biomed. Health. Inf."},{"key":"10.1016\/j.neucom.2025.131776_bib0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2024.103241","article-title":"I2U-Net: a dual-path U-Net with rich information interaction for medical image segmentation","volume":"97","author":"Dai","year":"2024","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.neucom.2025.131776_bib0155","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.107368","article-title":"A dual-branch network for ultrasound image segmentation","volume":"103","author":"Zhu","year":"2025","journal-title":"Biomed. Signal Process. Control"},{"key":"10.1016\/j.neucom.2025.131776_bib0160","series-title":"Proceedings of the IEEE International Conference on Computer Vision, ICCV","first-page":"406","article-title":"Bi-directional ConvLSTM U-Net with densely connected convolutions","author":"Azad","year":"2019"},{"issue":"10","key":"10.1016\/j.neucom.2025.131776_bib0165","doi-asserted-by":"crossref","first-page":"2281","DOI":"10.1109\/TMI.2019.2903562","article-title":"CE-Net: context encoder network for 2D medical image segmentation","volume":"38","author":"Gu","year":"2019","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"10","key":"10.1016\/j.neucom.2025.131776_bib0170","doi-asserted-by":"crossref","first-page":"3008","DOI":"10.1109\/TMI.2020.2983721","article-title":"CPFNet: context pyramid fusion network for medical image segmentation","volume":"39","author":"Feng","year":"2020","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.neucom.2025.131776_bib0175","series-title":"Proceedings of the International Conference on Learning Representations","article-title":"Differential transformer","author":"Ye","year":"2025"},{"key":"10.1016\/j.neucom.2025.131776_bib0180","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"13726","article-title":"Combating noisy labels by agreement: a joint training method with co-regularization","author":"Wei","year":"2020"},{"key":"10.1016\/j.neucom.2025.131776_bib0185","first-page":"4470","article-title":"Dual path networks","author":"Chen","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2025.131776_bib0190","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"2261","article-title":"Densely connected convolutional networks","author":"Huang","year":"2017"},{"key":"10.1016\/j.neucom.2025.131776_bib0195","first-page":"10627","article-title":"Recurrence along depth: deep convolutional neural networks with recurrent layer aggregation","volume":"34","author":"Zhao","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2025.131776_bib0200","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"3684","article-title":"DenseASPP for semantic segmentation in street scenes","author":"Yang","year":"2018"},{"key":"10.1016\/j.neucom.2025.131776_bib0205","author":"Oktay"},{"key":"10.1016\/j.neucom.2025.131776_bib0210","author":"Wang"},{"issue":"2","key":"10.1016\/j.neucom.2025.131776_bib0215","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","article-title":"nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation","volume":"18","author":"Isensee","year":"2021","journal-title":"Nat. Methods"},{"issue":"4","key":"10.1016\/j.neucom.2025.131776_bib0220","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1016\/j.jia.2022.09.004","article-title":"MRUNet: a two-stage segmentation model for small insect targets in complex environments","volume":"22","author":"Wang","year":"2023","journal-title":"J. Integr. Agric."},{"key":"10.1016\/j.neucom.2025.131776_bib0225","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.media.2019.01.012","article-title":"Attention gated networks: learning to leverage salient regions in medical images","volume":"53","author":"Schlemper","year":"2019","journal-title":"Med. Image Anal."},{"issue":"7","key":"10.1016\/j.neucom.2025.131776_bib0230","doi-asserted-by":"crossref","first-page":"1597","DOI":"10.1109\/TMI.2018.2791488","article-title":"Joint optic disc and cup segmentation based on multi-label deep network and polar transformation","volume":"37","author":"Fu","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.neucom.2025.131776_bib0235","series-title":"Proc. Of the International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"36","article-title":"Medical transformer: gated axial-attention for medical image segmentation","author":"Valanarasu","year":"2021"},{"key":"10.1016\/j.neucom.2025.131776_bib0240","author":"Codella"},{"key":"10.1016\/j.neucom.2025.131776_bib0245","author":"Codella"},{"key":"10.1016\/j.neucom.2025.131776_bib0250","series-title":"Proceedings of the Multimedia Modeling","first-page":"451","article-title":"Kvasir-SEG: a segmented polyp dataset","author":"Jha","year":"2020"},{"key":"10.1016\/j.neucom.2025.131776_bib0255","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.compmedimag.2015.02.007","article-title":"WM-DOVA maps for accurate polyp highlighting in colonoscopy: validation vs. Saliency maps from physicians, comput","volume":"45","author":"Bernal","year":"2015","journal-title":"Med. Imaging Graphics"},{"key":"10.1016\/j.neucom.2025.131776_bib0260","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.media.2016.08.008","article-title":"Gland segmentation in colon histology images: the GLAS challenge contest","volume":"35","author":"Sirinukunwattana","year":"2017","journal-title":"Med. Image Anal."},{"issue":"7","key":"10.1016\/j.neucom.2025.131776_bib0265","doi-asserted-by":"crossref","first-page":"1550","DOI":"10.1109\/TMI.2017.2677499","article-title":"A dataset and a technique for generalized nuclear segmentation for computational pathology","volume":"36","author":"Kumar","year":"2017","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.neucom.2025.131776_bib0270","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11531","article-title":"ECA-Net: efficient channel attention for deep convolutional neural networks","author":"Wang","year":"2020"},{"key":"10.1016\/j.neucom.2025.131776_bib0275","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"7132","article-title":"Squeeze-and-excitation networks","author":"Hu","year":"2018"},{"key":"10.1016\/j.neucom.2025.131776_bib0280","series-title":"Proceedings of the European Conference on Computer Vision","first-page":"3","article-title":"CBAM: convolutional block attention module","author":"Woo","year":"2018"},{"key":"10.1016\/j.neucom.2025.131776_bib0285","article-title":"Channel prior convolutional attention for medical image segmentation, Comput","volume":"178","author":"Huang","year":"2024","journal-title":"Biol. Med."},{"key":"10.1016\/j.neucom.2025.131776_bib0290","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Rethinking transformer-based blind-spot network for self-supervised image denoising","author":"Li","year":"2025"},{"key":"10.1016\/j.neucom.2025.131776_bib0295","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2023.102863","article-title":"A survey on deep learning for skin lesion segmentation","volume":"88","author":"Mirikharaji","year":"2023","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.neucom.2025.131776_bib0300","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2025.103545","article-title":"LW-CTrans: a lightweight hybrid network of CNN and transformer for 3D medical image segmentation","volume":"102","author":"Kuang","year":"2025","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.neucom.2025.131776_bib0305","article-title":"Attention-guided hierarchical fusion U-Net for uncertainty-driven medical image segmentation","volume":"115","author":"Afsana","year":"2025","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.neucom.2025.131776_bib0310","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2024.103277","article-title":"EfficientQ: an efficient and accurate post-training neural network quantization method for medical image segmentation","volume":"97","author":"Zhang","year":"2024","journal-title":"Med. Image Anal."}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231225024488?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231225024488?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T01:02:08Z","timestamp":1773190928000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231225024488"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":62,"alternative-id":["S0925231225024488"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2025.131776","relation":{"has-preprint":[{"id-type":"doi","id":"10.36227\/techrxiv.174742688.89355979\/v1","asserted-by":"object"}]},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A lightweight dual path Kolmogorov-Arnold convolution network for medical optical image segmentation","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2025.131776","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 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":"131776"}}