{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T21:07:57Z","timestamp":1780088877954,"version":"3.54.0"},"reference-count":38,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005374","name":"Nanjing University of Posts and Telecommunications","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005374","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013058","name":"Jiangsu Provincial Key Research and Development Program","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013058","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.bspc.2026.110631","type":"journal-article","created":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T16:34:57Z","timestamp":1778862897000},"page":"110631","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["Condition-refined score-based diffusion model with perceptual loss for limited-angle CBCT reconstruction"],"prefix":"10.1016","volume":"123","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7739-5018","authenticated-orcid":false,"given":"Zhengyuan","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyi","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shipeng","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianling","family":"Lyu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4857-9878","authenticated-orcid":false,"given":"Dianlin","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.bspc.2026.110631_b0005","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1118\/1.3036112","article-title":"\u201cIterative image reconstruction for CBCT using edge-preserving prior,\u201d (in eng)","volume":"36","author":"Wang","year":"2009","journal-title":"Med. Phys."},{"issue":"2","key":"10.1016\/j.bspc.2026.110631_b0010","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1109\/TRPMS.2023.3316349","article-title":"A review of deep learning CT reconstruction from incomplete projection data","volume":"8","author":"Wang","year":"2024","journal-title":"IEEE Trans. Radiat. Plasma Med. Sci."},{"issue":"12","key":"10.1016\/j.bspc.2026.110631_b0015","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.3938\/jkps.64.1907","article-title":"Dental cone-beam CT reconstruction from limited-angle view data based on compressed-sensing (CS) theory for fast, low-dose X-ray imaging","volume":"64","author":"Je","year":"2014","journal-title":"J. Korean Phys. Soc."},{"key":"10.1016\/j.bspc.2026.110631_b0020","doi-asserted-by":"crossref","unstructured":"Z. Zhang, X. Han, J. Bian, J. J. Manak, E. Y. Sidky, and X. Pan, \u201cInitial experience in image reconstruction from limited-angle C-arm CBCT data,\u201d in 2011 IEEE Nuclear Science Symposium Conference Record, 2011, pp. 3977-3979.","DOI":"10.1109\/NSSMIC.2011.6153756"},{"issue":"7","key":"10.1016\/j.bspc.2026.110631_b0025","doi-asserted-by":"crossref","first-page":"1772","DOI":"10.1364\/JOSAA.25.001772","article-title":"\u201cAccurate image reconstruction from few-view and limited-angle data in diffraction tomography,\u201d (in eng)","volume":"25","author":"LaRoque","year":"2008","journal-title":"J. Opt. Soc. Am. A Opt. Image Sci. Vis."},{"issue":"17","key":"10.1016\/j.bspc.2026.110631_b0030","doi-asserted-by":"crossref","first-page":"5535","DOI":"10.1088\/0031-9155\/56\/17\/006","article-title":"\u201cEffects of the penalty on the penalized weighted least-squares image reconstruction for low-dose CBCT,\u201d (in eng)","volume":"56","author":"Ouyang","year":"2011","journal-title":"Phys. Med. Biol."},{"issue":"20","key":"10.1016\/j.bspc.2026.110631_b0035","doi-asserted-by":"crossref","first-page":"7300","DOI":"10.1088\/0031-9155\/61\/20\/7300","article-title":"Optimization-based image reconstruction with artifact reduction in C-arm CBCT","volume":"61","author":"Xia","year":"2016","journal-title":"Phys. Med. Biol."},{"issue":"9","key":"10.1016\/j.bspc.2026.110631_b0040","doi-asserted-by":"crossref","first-page":"4509","DOI":"10.1109\/TIP.2017.2713099","article-title":"Deep convolutional neural network for inverse problems in imaging","volume":"26","author":"Jin","year":"2017","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.bspc.2026.110631_b0045","first-page":"1","article-title":"SEA-net: structure-enhanced attention network for limited-angle CBCT reconstruction of clinical projection data","volume":"72","author":"Hu","year":"2023","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"7","key":"10.1016\/j.bspc.2026.110631_b0050","doi-asserted-by":"crossref","first-page":"1778","DOI":"10.1109\/TMI.2022.3148110","article-title":"DIOR: deep iterative optimization-based residual-learning for limited-angle CT reconstruction","volume":"41","author":"Hu","year":"2022","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110631_b0055","series-title":"Machine Learning for Medical Image Reconstruction","first-page":"101","article-title":"Data consistent artifact reduction for limited angle tomography with deep learning prior","author":"Huang","year":"2019"},{"issue":"12","key":"10.1016\/j.bspc.2026.110631_b0060","doi-asserted-by":"crossref","first-page":"e855","DOI":"10.1002\/mp.13631","article-title":"\u201cOne network to solve all ROIs: deep learning CT for any ROI using differentiated backprojection,\u201d (in eng)","volume":"46","author":"Han","year":"2019","journal-title":"Med. Phys."},{"issue":"5","key":"10.1016\/j.bspc.2026.110631_b0065","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1109\/TRPMS.2023.3242662","article-title":"CROSS: cross-domain residual-optimization-based structure strengthening reconstruction for limited-angle CT","volume":"7","author":"Hu","year":"2023","journal-title":"IEEE Trans. Radiat. Plasma Med. Sci."},{"key":"10.1016\/j.bspc.2026.110631_b0070","unstructured":"J. Ho, A. Jain, and P. Abbeel, \u201cDenoising Diffusion Probabilistic Models,\u201d in Advances in Neural Information Processing Systems, 2020, vol. 33, pp. 6840-6851: Curran Associates, Inc., 2020\/\/\/."},{"key":"10.1016\/j.bspc.2026.110631_b0075","doi-asserted-by":"crossref","unstructured":"Z. Han et al., \u201cContrastive Diffusion Model withAuxiliary Guidance forCoarse-to-Fine PET Reconstruction,\u201d in Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2023, Cham, 2023, pp. 239-249: Springer Nature Switzerland.","DOI":"10.1007\/978-3-031-43999-5_23"},{"key":"10.1016\/j.bspc.2026.110631_b0080","doi-asserted-by":"crossref","unstructured":"J. Liu et al., \u201cDOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction,\u201d in 2023 IEEE\/CVF International Conference on Computer Vision (ICCV), 2023, pp. 10464\u201310474.","DOI":"10.1109\/ICCV51070.2023.00963"},{"key":"10.1016\/j.bspc.2026.110631_b0085","unstructured":"Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, and B. Poole, \u201cScore-Based Generative Modeling through Stochastic Differential Equations,\u201d in International Conference on Learning Representations, 2020."},{"key":"10.1016\/j.bspc.2026.110631_b0090","unstructured":"Y. Song, L. Shen, L. Xing, and S. Ermon, \u201cSolving Inverse Problems in Medical Imaging with Score-Based Generative Models,\u201d in International Conference on Learning Representations, 2021."},{"key":"10.1016\/j.bspc.2026.110631_b0095","first-page":"1","article-title":"Wavelet-inspired Multi-channel Score-based Model for Limited-angle CT Reconstruction","author":"Zhang","year":"2024","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110631_b0100","unstructured":"A. Kendall and Y. Gal, \u201cWhat uncertainties do we need in bayesian deep learning for computer vision?,\u201d vol. 30, 2017."},{"issue":"6","key":"10.1016\/j.bspc.2026.110631_b0105","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1364\/JOSAA.1.000612","article-title":"Practical cone-beam algorithm","volume":"1","author":"Feldkamp","year":"1984","journal-title":"J. Opt. Soc. Am. A"},{"key":"10.1016\/j.bspc.2026.110631_b0110","doi-asserted-by":"crossref","unstructured":"J. Johnson, A. Alahi, and L. Fei-Fei, \u201cPerceptual Losses for Real-Time Style Transfer and Super-Resolution,\u201d in Computer Vision \u2013 ECCV 2016, Cham, 2016, pp. 694-711: Springer International Publishing.","DOI":"10.1007\/978-3-319-46475-6_43"},{"issue":"7","key":"10.1016\/j.bspc.2026.110631_b0115","doi-asserted-by":"crossref","first-page":"2289","DOI":"10.1109\/TMI.2020.2968472","article-title":"SACNN: self-attention convolutional neural network for low-dose CT denoising with self-supervised perceptual loss network","volume":"39","author":"Li","year":"2020","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"2","key":"10.1016\/j.bspc.2026.110631_b0120","article-title":"A selective kernel-based cycle-consistent generative adversarial network for unpaired low-dose CT denoising","volume":"5","author":"Tan","year":"2022","journal-title":"Precis. Clin. Med."},{"key":"10.1016\/j.bspc.2026.110631_b0125","doi-asserted-by":"crossref","unstructured":"M. Green, E. M. Marom, and A. Mayer, \u201cPerceptual Transformer Loss for the Neural Denoising of Ultra-Low Dose CT,\u201d in 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024, pp. 1-5.","DOI":"10.1109\/ISBI56570.2024.10635771"},{"issue":"6","key":"10.1016\/j.bspc.2026.110631_b0130","doi-asserted-by":"crossref","first-page":"1348","DOI":"10.1109\/TMI.2018.2827462","article-title":"Low-dose CT image denoising using a generative adversarial network with wasserstein distance and perceptual loss","volume":"37","author":"Yang","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"7","key":"10.1016\/j.bspc.2026.110631_b0135","doi-asserted-by":"crossref","first-page":"2119","DOI":"10.1088\/0031-9155\/58\/7\/2119","article-title":"\u201cA limited-angle CT reconstruction method based on anisotropic TV minimization,\u201d (in eng)","volume":"58","author":"Chen","year":"2013","journal-title":"Phys. Med. Biol."},{"issue":"20","key":"10.1016\/j.bspc.2026.110631_b0140","doi-asserted-by":"crossref","first-page":"7300","DOI":"10.1088\/0031-9155\/61\/20\/7300","article-title":"\u201cOptimization-based image reconstruction with artifact reduction in C-arm CBCT,\u201d (in eng)","volume":"61","author":"Xia","year":"2016","journal-title":"Phys. Med. Biol."},{"key":"10.1016\/j.bspc.2026.110631_b0145","unstructured":"Z. Gui et al., 3D Computed Laminography Based on Prior Images and Total Variation, IEEE Trans. Nucl. Sci., vol. PP, pp. 1-1, 03\/01 2023."},{"key":"10.1016\/j.bspc.2026.110631_b0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2023.114057","article-title":"Industrial computed tomography for three-dimensional cultural relic model reconstruction based on L1-\u03b1L2+TV norm minimization","volume":"225","author":"Zhang","year":"2024","journal-title":"Measurement"},{"key":"10.1016\/j.bspc.2026.110631_b0155","unstructured":"H. Chung, S. Lee, and J. C. Ye, \u201cDecomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems,\u201d in The Twelfth International Conference on Learning Representations, 2024."},{"key":"10.1016\/j.bspc.2026.110631_b0160","unstructured":"H. Kim and K. Champley, \u201cDifferentiable Forward Projector for X-ray Computed Tomography,\u201d in ICML 2023 Workshop on Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators, 2023."},{"key":"10.1016\/j.bspc.2026.110631_b0165","doi-asserted-by":"crossref","unstructured":"O. Ronneberger, P. Fischer, and T. Brox, \u201cU-Net: Convolutional Networks for Biomedical Image Segmentation,\u201d in Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015, Cham, 2015, pp. 234-241: Springer International Publishing.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"10.1016\/j.bspc.2026.110631_b0170","doi-asserted-by":"crossref","unstructured":"Y. Dong, Y. Liu, H. Zhang, S. Chen, and Y. Qiao, \u201cFD-GAN: Generative Adversarial Networks with Fusion-Discriminator for Single Image Dehazing,\u201d Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 07, pp. 10729-10736, 04\/03 2020.","DOI":"10.1609\/aaai.v34i07.6701"},{"key":"10.1016\/j.bspc.2026.110631_b0175","unstructured":"J. Song, C. Meng, and S. J. a. p. a. Ermon, \u201cDenoising diffusion implicit models,\u201d 2020."},{"key":"10.1016\/j.bspc.2026.110631_b0180","doi-asserted-by":"crossref","unstructured":"X. Ma, G. Fang, and X. Wang, \u201cDeepcache: Accelerating diffusion models for free,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 15762-15772.","DOI":"10.1109\/CVPR52733.2024.01492"},{"key":"10.1016\/j.bspc.2026.110631_b0185","first-page":"1","article-title":"Time-reversion fast-sampling score-based model for limited-angle CT reconstruction","author":"Wang","year":"2024","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110631_b0190","unstructured":"Q. Zhang, M. Tao, and Y. J. a. p. a. Chen, \u201cgddim: Generalized denoising diffusion implicit models,\u201d 2022."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426011857?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426011857?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T20:16:27Z","timestamp":1780085787000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426011857"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":38,"alternative-id":["S1746809426011857"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110631","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Condition-refined score-based diffusion model with perceptual loss for limited-angle CBCT reconstruction","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110631","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110631"}}