{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:37:05Z","timestamp":1772822225815,"version":"3.50.1"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030329556","type":"print"},{"value":"9783030329563","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-32956-3_2","type":"book-chapter","created":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T23:04:04Z","timestamp":1570662244000},"page":"9-17","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Structure-Aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image"],"prefix":"10.1007","author":[{"given":"Yan","family":"Guo","sequence":"first","affiliation":[]},{"given":"Kang","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Suhui","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Yue","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Peng","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Guotong","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Chuanfeng","family":"Lv","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Lv","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,8]]},"reference":[{"key":"2_CR1","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1097\/ICU.0b013e32835f8bf8","volume":"24","author":"N Adhi","year":"2013","unstructured":"Adhi, N., Duker, J.S.: Optical coherence tomography-current and future applications. Curr. Opin. Ophthalmol. 24, 213\u2013221 (2013)","journal-title":"Curr. Opin. Ophthalmol."},{"issue":"6","key":"2_CR2","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1109\/TMI.2006.887375","volume":"26","author":"HM Salinas","year":"2007","unstructured":"Salinas, H.M., Fern\u00e1ndez, D.C.: Comparison of PDE-Based nonlinear diffusion ap-proaches for image enhancement and denoising in optical coherence tomography. IEEE Trans. Med. Imaging 26(6), 761\u2013771 (2007)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"3","key":"2_CR3","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1364\/BOE.3.000572","volume":"3","author":"MA Mayer","year":"2012","unstructured":"Mayer, M.A., Borsdorf, A., Wagner, M., et al.: Wavelet denoising of multiframe optical coherence tomography data. Biomed. Opt. Express 3(3), 572\u2013589 (2012)","journal-title":"Biomed. Opt. Express"},{"issue":"13","key":"2_CR4","doi-asserted-by":"publisher","first-page":"D43","DOI":"10.1364\/AO.54.000D43","volume":"54","author":"J Aum","year":"2015","unstructured":"Aum, J., Kim, J.H., Jeong, J.: Effective speckle noise suppression in optical coherence tomography images using nonlocal means denoising filter with double Gaussian aniso-tropic kernels. Appl. Opt. 54(13), D43\u2013D50 (2015)","journal-title":"Appl. Opt."},{"key":"2_CR5","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1016\/j.optcom.2012.10.053","volume":"291","author":"B Chong","year":"2013","unstructured":"Chong, B., Zhu, Y.: Speckle reduction in optical coherence tomography images of human finger skin by wavelet modified BM3D filter. Opt. Commun. 291, 461\u2013469 (2013)","journal-title":"Opt. Commun."},{"issue":"9","key":"2_CR6","doi-asserted-by":"publisher","first-page":"3903","DOI":"10.1364\/BOE.8.003903","volume":"8","author":"M Li","year":"2017","unstructured":"Li, M., Idoughi, R., Choudhury, B., et al.: Statistical model for OCT image denoising. Biomed. Opt. Express 8(9), 3903\u20133917 (2017)","journal-title":"Biomed. Opt. Express"},{"key":"2_CR7","doi-asserted-by":"crossref","unstructured":"Devalla, S.K., Subramanian, G., Pham, T.H., et al.: A deep learning approach to denoise optical coherence tomography images of the optic nerve head. arXiv preprint arXiv:1809.10589 (2018)","DOI":"10.1038\/s41598-019-51062-7"},{"issue":"11","key":"2_CR8","doi-asserted-by":"publisher","first-page":"5129","DOI":"10.1364\/BOE.9.005129","volume":"9","author":"Y Ma","year":"2018","unstructured":"Ma, Y., Chen, X., Zhu, W., et al.: Speckle noise reduction in optical coherence tomography images based on edge-sensitive cGAN. Biomed. Opt. Express 9(11), 5129\u20135146 (2018)","journal-title":"Biomed. Opt. Express"},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.Y., Zhou, T., et al.: Image-to-image translation with conditional adversarial networks. In: Computer Vision and Pattern Recognition (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Zhu, J.Y., Park, T., Isola, P., et al.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: International Conference on Computer Vision (2017)","DOI":"10.1109\/ICCV.2017.244"},{"key":"2_CR11","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., et al.: Generative adversarial networks. In: Advances in Neural Information Processing Systems, Montreal (2014)"},{"issue":"4","key":"2_CR12","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"2_CR13","doi-asserted-by":"publisher","first-page":"1042","DOI":"10.1109\/TMI.2014.2374354","volume":"34","author":"R Kafieh","year":"2015","unstructured":"Kafieh, R., Rabbani, H., Selesnick, I.: Three dimensional data-driven multi scale atomic representation of optical coherence tomography. IEEE Trans. Med. Imag. 34(5), 1042\u20131062 (2015)","journal-title":"IEEE Trans. Med. Imag."}],"container-title":["Lecture Notes in Computer Science","Ophthalmic Medical Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32956-3_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:13:43Z","timestamp":1728519223000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-32956-3_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030329556","9783030329563"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32956-3_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"8 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"OMIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Ophthalmic Medical Image Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"omia2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/view\/mwomia2019\/home","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"cmt","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"22","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"61% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}