{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:46:26Z","timestamp":1743122786574,"version":"3.40.3"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030013639"},{"type":"electronic","value":"9783030013646"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01364-6_11","type":"book-chapter","created":{"date-parts":[[2018,10,16]],"date-time":"2018-10-16T05:41:20Z","timestamp":1539668480000},"page":"95-104","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["An Efficient and Comprehensive Labeling Tool for Large-Scale Annotation of Fundus Images"],"prefix":"10.1007","author":[{"given":"Jaemin","family":"Son","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sangkeun","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang Jun","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyu-Hwan","family":"Jung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,10,17]]},"reference":[{"key":"11_CR1","unstructured":"Indian diabetic retinopathy image dataset (IDRiD). \n                      https:\/\/idrid.grand-challenge.org\n                      \n                    . Accessed 29 May 2018"},{"key":"11_CR2","unstructured":"Kaggle diabetic retinopathy detection competition. \n                      https:\/\/www.kaggle.com\/c\/diabetic-retinopathy-detection\n                      \n                    . Accessed 29 May 2018"},{"issue":"3","key":"11_CR3","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.artmed.2008.04.005","volume":"43","author":"EJ Carmona","year":"2008","unstructured":"Carmona, E.J., Rinc\u00f3n, M., Garc\u00eda-Feijo\u00f3, J., Mart\u00ednez-de-la Casa, J.M.: Identification of the optic nerve head with genetic algorithms. Artif. Intell. Med. 43(3), 243\u2013259 (2008)","journal-title":"Artif. Intell. Med."},{"issue":"2","key":"11_CR4","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1016\/j.irbm.2013.01.010","volume":"34","author":"E Decenci\u00e8re","year":"2013","unstructured":"Decenci\u00e8re, E., et al.: Teleophta: machine learning and image processing methods for teleophthalmology. IRBM 34(2), 196\u2013203 (2013)","journal-title":"IRBM"},{"issue":"3","key":"11_CR5","doi-asserted-by":"publisher","first-page":"231","DOI":"10.5566\/ias.1155","volume":"33","author":"E Decenci\u00e8re","year":"2014","unstructured":"Decenci\u00e8re, E., et al.: Feedback on a publicly distributed image database: the Messidor database. Image Anal. Stereol. 33(3), 231\u2013234 (2014)","journal-title":"Image Anal. Stereol."},{"issue":"5","key":"11_CR6","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1177\/112067210401400505","volume":"14","author":"M Detry-Morel","year":"2004","unstructured":"Detry-Morel, M., Zeyen, T., Kestelyn, P., Collignon, J., Goethals, M., Belgian Glaucoma Society: Screening for glaucoma in a general population with the non-mydriatic fundus camera and the frequency doubling perimeter. Eur. J. Ophthalmol. 14(5), 387\u2013393 (2004)","journal-title":"Eur. J. Ophthalmol."},{"issue":"7","key":"11_CR7","doi-asserted-by":"publisher","first-page":"962","DOI":"10.1016\/j.ophtha.2017.02.008","volume":"124","author":"R Gargeya","year":"2017","unstructured":"Gargeya, R., Leng, T.: Automated identification of diabetic retinopathy using deep learning. Ophthalmology 124(7), 962\u2013969 (2017)","journal-title":"Ophthalmology"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"ETDRS Group, et al.: Grading diabetic retinopathy from stereoscopic color fundus photographsan extension of the modified airlie house classification: ETDRS report number 10. Ophthalmology 98(5), 786\u2013806 (1991)","DOI":"10.1016\/S0161-6420(13)38012-9"},{"issue":"22","key":"11_CR9","doi-asserted-by":"publisher","first-page":"2402","DOI":"10.1001\/jama.2016.17216","volume":"316","author":"V Gulshan","year":"2016","unstructured":"Gulshan, V., et al.: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 316(22), 2402\u20132410 (2016)","journal-title":"JAMA"},{"issue":"4","key":"11_CR10","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1001\/archopht.122.4.552","volume":"122","author":"JH Kempen","year":"2004","unstructured":"Kempen, J.H., et al.: The prevalence of diabetic retinopathy among adults in the United States. Arch. Ophthalmol. (Chicago, Ill.: 1960) 122(4), 552\u2013563 (2004)","journal-title":"Arch. Ophthalmol. (Chicago, Ill.: 1960)"},{"issue":"2","key":"11_CR11","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1016\/S0002-9394(02)01522-2","volume":"134","author":"DY Lin","year":"2002","unstructured":"Lin, D.Y., Blumenkranz, M.S., Brothers, R.J., Grosvenor, D.M.: The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography1. Am. J. Ophthalmol. 134(2), 204\u2013213 (2002)","journal-title":"Am. J. Ophthalmol."},{"key":"11_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). \n                      https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"issue":"22","key":"11_CR13","doi-asserted-by":"publisher","first-page":"2211","DOI":"10.1001\/jama.2017.18152","volume":"318","author":"DSW Ting","year":"2017","unstructured":"Ting, D.S.W., et al.: Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. JAMA 318(22), 2211\u20132223 (2017)","journal-title":"JAMA"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Park, S.J., Shin, J.Y., Kim, S., Son, J., Jung, K.H., Park, K.H.: A novel fundus image reading tool for efficient generation of a multi-dimensional categorical image database for machine learning algorithm training. J. Korean Med. Sci. 33(43) (2018)","DOI":"10.3346\/jkms.2018.33.e239"}],"container-title":["Lecture Notes in Computer Science","Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01364-6_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T04:57:40Z","timestamp":1558328260000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-01364-6_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030013639","9783030013646"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01364-6_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"17 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"LABELS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Granada","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"labels2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/labels.tue-image.nl\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}