{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T18:15:33Z","timestamp":1743012933501,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031440120"},{"type":"electronic","value":"9783031440137"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-44013-7_8","type":"book-chapter","created":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T23:02:39Z","timestamp":1694818959000},"page":"72-81","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Utilizing Meta Pseudo Labels for\u00a0Semantic Segmentation of\u00a0Targeted Optic Nerve Features"],"prefix":"10.1007","author":[{"given":"Ashelyn","family":"Mann","sequence":"first","affiliation":[]},{"given":"Adam","family":"Hedberg-Buenz","sequence":"additional","affiliation":[]},{"given":"Michael G.","family":"Anderson","sequence":"additional","affiliation":[]},{"given":"Mona K.","family":"Garvin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,16]]},"reference":[{"issue":"3","key":"8_CR1","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.tjem.2018.08.001","volume":"18","author":"H Akoglu","year":"2018","unstructured":"Akoglu, H.: User\u2019s guide to correlation coefficients. Turkish J. Emergency Med. 18(3), 91\u201393 (2018)","journal-title":"Turkish J. Emergency Med."},{"key":"8_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1741-7007-4-20","volume":"4","author":"MG Anderson","year":"2006","unstructured":"Anderson, M.G., et al.: Genetic context determines susceptibility to intraocular pressure elevation in a mouse pigmentary glaucoma. BMC Biol. 4, 1\u201311 (2006)","journal-title":"BMC Biol."},{"key":"8_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1007\/978-3-030-32245-8_11","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019","author":"J Bertels","year":"2019","unstructured":"Bertels, J., et al.: Optimizing the Dice score and Jaccard index for medical image segmentation: theory and practice. In: Shen, D., et al. (eds.) MICCAI 2019. LNCS, vol. 11765, pp. 92\u2013100. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32245-8_11"},{"issue":"14","key":"8_CR4","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1167\/tvst.10.14.22","volume":"10","author":"W Deng","year":"2021","unstructured":"Deng, W., et al.: AxonDeep: automated optic nerve axon segmentation in mice with deep learning. Transl. Vision Sci. Technol. 10(14), 22\u201322 (2021)","journal-title":"Transl. Vision Sci. Technol."},{"issue":"3","key":"8_CR5","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1167\/tvst.12.3.9","volume":"12","author":"V Goyal","year":"2023","unstructured":"Goyal, V., et al.: AxoNet 2.0: a deep learning-based tool for morphometric analysis of retinal ganglion cell axons. Transl. Vision Sci. Technol. 12(3), 9\u20139 (2023)","journal-title":"Transl. Vision Sci. Technol."},{"issue":"7553","key":"8_CR6","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"issue":"5","key":"8_CR7","doi-asserted-by":"publisher","first-page":"2679","DOI":"10.1167\/iovs.10-5993","volume":"52","author":"M Mao","year":"2011","unstructured":"Mao, M., Hedberg-Buenz, A., Koehn, D., John, S.W., Anderson, M.G.: Anterior segment dysgenesis and early-onset glaucoma in nee mice with mutation of Sh3pxd2b. Invest. Ophthalmol. Visual Sci. 52(5), 2679\u20132688 (2011)","journal-title":"Invest. Ophthalmol. Visual Sci."},{"key":"8_CR8","doi-asserted-by":"crossref","unstructured":"Pham, H., Dai, Z., Xie, Q., Le, Q.V.: Meta pseudo labels. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11557\u201311568 (2021)","DOI":"10.1109\/CVPR46437.2021.01139"},{"issue":"6","key":"8_CR9","doi-asserted-by":"publisher","first-page":"2951","DOI":"10.1167\/iovs.11-9274","volume":"53","author":"J Reynaud","year":"2012","unstructured":"Reynaud, J.: Automated quantification of optic nerve axons in primate glaucomatous and normal eyes\u2014method and comparison to semi-automated manual quantification. Investi. Ophthalmol. Visual Sci. 53(6), 2951\u20132959 (2012)","journal-title":"Investi. Ophthalmol. Visual Sci."},{"issue":"1","key":"8_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-020-64898-1","volume":"10","author":"MD Ritch","year":"2020","unstructured":"Ritch, M.D., et al.: AxoNet: a deep learning-based tool to count retinal ganglion cell axons. Sci. Rep. 10(1), 1\u201313 (2020)","journal-title":"Sci. Rep."},{"key":"8_CR11","doi-asserted-by":"crossref","unstructured":"Wang, Y., Zhang, J., Kan, M., Shan, S., Chen, X.: Self-supervised equivariant attention mechanism for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12275\u201312284 (2020)","DOI":"10.1109\/CVPR42600.2020.01229"},{"issue":"1","key":"8_CR12","doi-asserted-by":"publisher","first-page":"26559","DOI":"10.1038\/srep26559","volume":"6","author":"K Zarei","year":"2016","unstructured":"Zarei, K., et al.: Automated axon counting in rodent optic nerve sections with AxonJ. Sci. Rep. 6(1), 26559 (2016)","journal-title":"Sci. Rep."}],"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\/978-3-031-44013-7_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T23:12:16Z","timestamp":1695078736000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-44013-7_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031440120","9783031440137"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-44013-7_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"16 September 2023","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":"Vancouver, BC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"omia2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/view\/omiax\/","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 System","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"27","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":"16","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":"59% - 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)"}}]}}