乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,6]],"date-time":"2024-07-06T16:08:07Z","timestamp":1720282087397},"reference-count":62,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP23KJ0118"],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","clinicalkey.es","clinicalkey.com.au","clinicalkey.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Methods and Programs in Biomedicine"],"published-print":{"date-parts":[[2024,3]]},"DOI":"10.1016\/j.cmpb.2023.108000","type":"journal-article","created":{"date-parts":[[2024,1,3]],"date-time":"2024-01-03T18:51:38Z","timestamp":1704307898000},"page":"108000","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Learn from orientation prior for radiograph super-resolution: Orientation operator transformer"],"prefix":"10.1016","volume":"245","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-3114-9206","authenticated-orcid":false,"given":"Yongsong","family":"Huang","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0001-5205-0542","authenticated-orcid":false,"given":"Tomo","family":"Miyazaki","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-4514-2016","authenticated-orcid":false,"given":"Xiaofeng","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Kaiyuan","family":"Jiang","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2011-8105","authenticated-orcid":false,"given":"Zhengmi","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Shinichiro","family":"Omachi","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.cmpb.2023.108000_br0010","first-page":"173","article-title":"Orthopedic imaging: a practical approach","volume":"29","author":"Vives","year":"2006","journal-title":"J. Spinal Cord Med."},{"key":"10.1016\/j.cmpb.2023.108000_br0020","doi-asserted-by":"crossref","DOI":"10.1155\/2013\/213234","article-title":"Age-related changes in trabecular and cortical bone microstructure","author":"Chen","year":"2013","journal-title":"Int. J. Endocrinol."},{"key":"10.1016\/j.cmpb.2023.108000_br0030","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1007\/s10439-006-9239-9","article-title":"Vertebral osteoporosis and trabecular bone quality","volume":"35","author":"Mc Donnell","year":"2007","journal-title":"Ann. Biomed. Eng."},{"key":"10.1016\/j.cmpb.2023.108000_br0040","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.neuroimage.2014.10.005","article-title":"Accelerated longitudinal cortical thinning in adolescence","volume":"104","author":"Zhou","year":"2015","journal-title":"NeuroImage"},{"key":"10.1016\/j.cmpb.2023.108000_br0050","doi-asserted-by":"crossref","first-page":"658","DOI":"10.1016\/S0012-3692(15)32498-3","article-title":"The radiology of emergency medicine","volume":"123","author":"Turlington","year":"2003","journal-title":"Chest"},{"key":"10.1016\/j.cmpb.2023.108000_br0060","doi-asserted-by":"crossref","first-page":"1328","DOI":"10.1016\/j.joca.2022.07.005","article-title":"Biglycan neo-epitope (bgn262), a novel biomarker for screening early changes in equine osteoarthritic subchondral bone","volume":"30","author":"Adepu","year":"2022","journal-title":"Osteoarthr. Cartil."},{"key":"10.1016\/j.cmpb.2023.108000_br0070","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1093\/stmcls\/sxad012","article-title":"Inflammation-mediated aberrant glucose metabolism in subchondral bone induces osteoarthritis","volume":"41","author":"Ying","year":"2023","journal-title":"Stem Cells"},{"key":"10.1016\/j.cmpb.2023.108000_br0080","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.nuclcard.2007.01.006","article-title":"Pharmacologic stress myocardial perfusion imaging: a practical approach","volume":"14","author":"Miyamoto","year":"2007","journal-title":"J. Nucl. Cardiol."},{"key":"10.1016\/j.cmpb.2023.108000_br0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.intimp.2022.109095","article-title":"Advance in bone destruction participated by jak\/stat in rheumatoid arthritis and therapeutic effect of jak\/stat inhibitors","volume":"111","author":"Hu","year":"2022","journal-title":"Int. Immunopharmacol."},{"key":"10.1016\/j.cmpb.2023.108000_br0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.colsurfb.2022.112826","article-title":"Dual targeted zeolitic imidazolate framework nanoparticles for treating metastatic breast cancer and inhibiting bone destruction","volume":"219","author":"Shen","year":"2022","journal-title":"Colloids Surf. B, Biointerfaces"},{"key":"10.1016\/j.cmpb.2023.108000_br0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2023.107591","article-title":"Multivariable-incorporating super-resolution residual network for transcranial focused ultrasound simulation","volume":"237","author":"Shin","year":"2023","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2023.108000_br0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2022.106995","article-title":"Improved generative adversarial network for retinal image super-resolution","volume":"225","author":"Qiu","year":"2022","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2023.108000_br0130","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2022.107313","article-title":"Feedback attention network for cardiac magnetic resonance imaging super-resolution","volume":"231","author":"Zhu","year":"2023","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2023.108000_br0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2023.102694","article-title":"Source-free domain adaptive segmentation with class-balanced complementary self-training","volume":"146","author":"Huang","year":"2023","journal-title":"Artif. Intell. Med."},{"key":"10.1016\/j.cmpb.2023.108000_br0150","doi-asserted-by":"crossref","first-page":"3365","DOI":"10.1109\/TPAMI.2020.2982166","article-title":"Deep learning for image super-resolution: a survey","volume":"43","author":"Wang","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.cmpb.2023.108000_br0160","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/MSP.2003.1203207","article-title":"Super-resolution image reconstruction: a technical overview","volume":"20","author":"Park","year":"2003","journal-title":"IEEE Signal Process. Mag."},{"key":"10.1016\/j.cmpb.2023.108000_br0170","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.inffus.2021.09.005","article-title":"Real-world single image super-resolution: a brief review","volume":"79","author":"Chen","year":"2022","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.cmpb.2023.108000_br0180","author":"Huang"},{"key":"10.1016\/j.cmpb.2023.108000_br0190","series-title":"Computer Vision\u2013ECCV 2014: 13th European Conference","first-page":"184","article-title":"Learning a deep convolutional network for image super-resolution","volume":"vol. 13","author":"Dong","year":"2014"},{"key":"10.1016\/j.cmpb.2023.108000_br0200","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"1646","article-title":"Accurate image super-resolution using very deep convolutional networks","author":"Kim","year":"2016"},{"key":"10.1016\/j.cmpb.2023.108000_br0210","doi-asserted-by":"crossref","first-page":"1070","DOI":"10.1109\/LSP.2021.3080219","article-title":"Difference value network for image super-resolution","volume":"28","author":"Jiang","year":"2021","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.cmpb.2023.108000_br0220","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"286","article-title":"Image super-resolution using very deep residual channel attention networks","author":"Zhang","year":"2018"},{"key":"10.1016\/j.cmpb.2023.108000_br0230","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"2694","article-title":"Overnet: lightweight multi-scale super-resolution with overscaling network","author":"Behjati","year":"2021"},{"key":"10.1016\/j.cmpb.2023.108000_br0240","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1145\/3422622","article-title":"Generative adversarial networks","volume":"63","author":"Goodfellow","year":"2020","journal-title":"Commun. ACM"},{"key":"10.1016\/j.cmpb.2023.108000_br0250","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"4681","article-title":"Photo-realistic single image super-resolution using a generative adversarial network","author":"Ledig","year":"2017"},{"key":"10.1016\/j.cmpb.2023.108000_br0260","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1109\/LSP.2021.3077801","article-title":"Infrared image super-resolution via transfer learning and psrgan","volume":"28","author":"Huang","year":"2021","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.cmpb.2023.108000_br0270","series-title":"Proceedings of the European on Conference on Computer Vision (ECCV) Workshops","article-title":"Esrgan: enhanced super-resolution generative adversarial networks","author":"Wang","year":"2018"},{"key":"10.1016\/j.cmpb.2023.108000_br0280","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"1905","article-title":"Real-esrgan: training real-world blind super-resolution with pure synthetic data","author":"Wang","year":"2021"},{"key":"10.1016\/j.cmpb.2023.108000_br0290","article-title":"Improved training of wasserstein gans","volume":"30","author":"Gulrajani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.cmpb.2023.108000_br0300","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5791","article-title":"Learning texture transformer network for image super-resolution","author":"Yang","year":"2020"},{"key":"10.1016\/j.cmpb.2023.108000_br0310","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"457","article-title":"Transformer for single image super-resolution","author":"Lu","year":"2022"},{"key":"10.1016\/j.cmpb.2023.108000_br0320","author":"Gao"},{"key":"10.1016\/j.cmpb.2023.108000_br0330","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2023.107590","article-title":"Medical image super-resolution reconstruction algorithms based on deep learning: a survey","author":"Qiu","year":"2023","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2023.108000_br0340","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2022.106707","article-title":"Dual u-net residual networks for cardiac magnetic resonance images super-resolution","volume":"218","author":"Qiu","year":"2022","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2023.108000_br0350","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2021.106330","article-title":"Residual dense network for medical magnetic resonance images super-resolution","volume":"209","author":"Zhu","year":"2021","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2023.108000_br0360","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1109\/TPAMI.2015.2439281","article-title":"Image super-resolution using deep convolutional networks","volume":"38","author":"Dong","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.cmpb.2023.108000_br0370","series-title":"PRICAI 2021: Trends in Artificial Intelligence: 18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021","first-page":"461","article-title":"Infrared image super-resolution via heterogeneous convolutional wgan","author":"Huang","year":"2021"},{"key":"10.1016\/j.cmpb.2023.108000_br0380","author":"Huang"},{"key":"10.1016\/j.cmpb.2023.108000_br0390","author":"Han"},{"key":"10.1016\/j.cmpb.2023.108000_br0400","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.cmpb.2023.108000_br0410","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.109038","article-title":"Single image super-resolution based on progressive fusion of orientation-aware features","volume":"133","author":"He","year":"2023","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.cmpb.2023.108000_br0420","series-title":"International Conference on Information Processing in Medical Imaging","first-page":"730","article-title":"Rethinking boundary detection in deep learning models for medical image segmentation","author":"Lin","year":"2023"},{"key":"10.1016\/j.cmpb.2023.108000_br0430","doi-asserted-by":"crossref","first-page":"355","DOI":"10.3390\/electronics12020355","article-title":"Mulvernet: nucleus segmentation and classification of pathology images using the hover-net and multiple filter units","volume":"12","author":"Vo","year":"2023","journal-title":"Electron."},{"key":"10.1016\/j.cmpb.2023.108000_br0440","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2022.104199","article-title":"Attention augmented distance regression and classification network for nuclei instance segmentation and type classification in histology images","volume":"79","author":"Dogar","year":"2023","journal-title":"Biomed. Signal Process. Control"},{"key":"10.1016\/j.cmpb.2023.108000_br0450","series-title":"Computer Vision\u2013ECCV 2022: 17th European Conference","first-page":"146","article-title":"Stripformer: strip transformer for fast image deblurring","author":"Tsai","year":"2022"},{"key":"10.1016\/j.cmpb.2023.108000_br0460","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"769","article-title":"Learning a convolutional neural network for non-uniform motion blur removal","author":"Sun","year":"2015"},{"key":"10.1016\/j.cmpb.2023.108000_br0470","series-title":"International Conference on Information Processing in Medical Imaging","first-page":"360","article-title":"Vicinal feature statistics augmentation for federated 3d medical volume segmentation","author":"Huang","year":"2023"},{"key":"10.1016\/j.cmpb.2023.108000_br0480","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"2472","article-title":"Residual dense network for image super-resolution","author":"Zhang","year":"2018"},{"key":"10.1016\/j.cmpb.2023.108000_br0490","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"517","article-title":"Multi-scale residual network for image super-resolution","author":"Li","year":"2018"},{"key":"10.1016\/j.cmpb.2023.108000_br0500","series-title":"Proceedings of the IEEE International Conference on Computer Vision","first-page":"4799","article-title":"Image super-resolution using dense skip connections","author":"Tong","year":"2017"},{"key":"10.1016\/j.cmpb.2023.108000_br0510","series-title":"Computer Vision\u2013ECCV 2022: 17th European Conference","first-page":"649","article-title":"Efficient long-range attention network for image super-resolution","author":"Zhang","year":"2022"},{"key":"10.1016\/j.cmpb.2023.108000_br0520","series-title":"Machine Learning in Medical Imaging: 13th International Workshop, MLMI 2022, Held in Conjunction with MICCAI 2022","first-page":"43","article-title":"Rethinking degradation: radiograph super-resolution via aid-srgan","author":"Huang","year":"2022"},{"key":"10.1016\/j.cmpb.2023.108000_br0530","author":"Kingma"},{"key":"10.1016\/j.cmpb.2023.108000_br0540","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.cmpb.2023.108000_br0550","series-title":"Proceedings of the European Conference on Computer Vision (ECCV) Workshops","article-title":"The 2018 pirm challenge on perceptual image super-resolution","author":"Blau","year":"2018"},{"key":"10.1016\/j.cmpb.2023.108000_br0560","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","article-title":"Making a \u201ccompletely blind\u201d image quality analyzer","volume":"20","author":"Mittal","year":"2012","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.cmpb.2023.108000_br0570","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108997","article-title":"Single image super-resolution based on directional variance attention network","volume":"133","author":"Behjati","year":"2023","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.cmpb.2023.108000_br0580","author":"Sun"},{"key":"10.1016\/j.cmpb.2023.108000_br0590","author":"Sun"},{"key":"10.1016\/j.cmpb.2023.108000_br0600","series-title":"Computer Vision\u2013ECCV 2016: 14th European Conference","first-page":"391","article-title":"Accelerating the super-resolution convolutional neural network","volume":"vol. 14","author":"Dong","year":"2016"},{"key":"10.1016\/j.cmpb.2023.108000_br0610","first-page":"886","article-title":"Histograms of Oriented Gradients for Human Detection","volume":"vol. 1","author":"Dalal","year":"2005"},{"key":"10.1016\/j.cmpb.2023.108000_br0620","first-page":"1","article-title":"Generative adversarial networks with dual-domain u-net-based discriminators for low-dose ct denoising","volume":"71","author":"Huang","year":"2021","journal-title":"IEEE Trans. Instrum. Meas."}],"container-title":["Computer Methods and Programs in Biomedicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260723006661?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260723006661?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T16:54:27Z","timestamp":1705510467000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169260723006661"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3]]},"references-count":62,"alternative-id":["S0169260723006661"],"URL":"https:\/\/doi.org\/10.1016\/j.cmpb.2023.108000","relation":{},"ISSN":["0169-2607"],"issn-type":[{"value":"0169-2607","type":"print"}],"subject":[],"published":{"date-parts":[[2024,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Learn from orientation prior for radiograph super-resolution: Orientation operator transformer","name":"articletitle","label":"Article Title"},{"value":"Computer Methods and Programs in Biomedicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cmpb.2023.108000","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"108000"}}