{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T20:53:59Z","timestamp":1792270439150,"version":"4.4.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,3,27]],"date-time":"2020-03-27T00:00:00Z","timestamp":1585267200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,3,27]],"date-time":"2020-03-27T00:00:00Z","timestamp":1585267200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This study was performed to estimate choroidal thickness by fundus photography, based on image processing and deep learning. Colour fundus photography and central choroidal thickness examinations were performed in 200 normal eyes and 200 eyes with central serous chorioretinopathy (CSC). Choroidal thickness under the fovea was measured using optical coherence tomography images. The adaptive binarisation method was used to delineate choroidal vessels within colour fundus photographs. Correlation coefficients were calculated between the choroidal vascular density (defined as the choroidal vasculature appearance index of the binarisation image) and choroidal thickness. The correlations between choroidal vasculature appearance index and choroidal thickness were \u22120.60 for normal eyes (p\u2009&lt;\u20090.01) and \u22120.46 for eyes with CSC (p\u2009&lt;\u20090.01). A deep convolutional neural network model was independently created and trained with augmented training data by K-Fold Cross Validation (K\u2009=\u20095). The correlation coefficients between the value predicted from the colour image and the true choroidal thickness were 0.68 for normal eyes (p\u2009&lt;\u20090.01) and 0.48 for eyes with CSC (p\u2009&lt;\u20090.01). Thus, choroidal thickness could be estimated from colour fundus photographs in both normal eyes and eyes with CSC, using imaging analysis and deep learning.<\/jats:p>","DOI":"10.1038\/s41598-020-62347-7","type":"journal-article","created":{"date-parts":[[2020,3,27]],"date-time":"2020-03-27T11:03:21Z","timestamp":1585307001000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Choroidal thickness estimation from colour fundus photographs by adaptive binarisation and deep learning, according to central serous chorioretinopathy status"],"prefix":"10.1038","volume":"10","author":[{"given":"Yuki","family":"Komuku","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atsuya","family":"Ide","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hisashi","family":"Fukuyama","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroki","family":"Masumoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hitoshi","family":"Tabuchi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takeshi","family":"Okadome","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fumi","family":"Gomi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,3,27]]},"reference":[{"key":"62347_CR1","doi-asserted-by":"publisher","first-page":"1469","DOI":"10.1097\/IAE.0b013e3181be0a83","volume":"29","author":"Y Iamura","year":"2009","unstructured":"Iamura, Y. et al. Enhanced depth imaging optical coherence tomography of the choroid in central serous chorioretinopathy. Retina 29, 1469\u20131473 (2009).","journal-title":"Retina"},{"key":"62347_CR2","doi-asserted-by":"publisher","first-page":"1666","DOI":"10.1016\/j.ophtha.2012.02.021","volume":"119","author":"P Jirarattanasopa","year":"2012","unstructured":"Jirarattanasopa, P. et al. Assessment of macular choroidal thickness by optical coherence tomography and angiographic changes in central serous chorioretinopathy. Ophthalmology 119, 1666\u201378 (2012).","journal-title":"Ophthalmology"},{"key":"62347_CR3","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1097\/IAE.0b013e318263d11f","volume":"33","author":"S Kuroda","year":"2013","unstructured":"Kuroda, S. et al. Choroidal thickness in central serous chorioretinopathy. Retina 33, 302\u20138 (2013).","journal-title":"Retina"},{"key":"62347_CR4","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1016\/j.ajo.2008.05.032","volume":"146","author":"RF Spaide","year":"2008","unstructured":"Spaide, R. F. et al. Enhanced depth imaging spectral-domain optical coherence tomography. Am. J. Ophthalmol. 146, 496\u2013500 (2008).","journal-title":"Am. J. Ophthalmol."},{"key":"62347_CR5","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1016\/j.ajo.2008.12.008","volume":"147","author":"R Margolis","year":"2009","unstructured":"Margolis, R. & Spaide, R. F. A Pilot Study of dnhanced depth imaging optical coherence tomography of the choroid in normal eyes. Am. J. Ophthalmol. 147, 811\u2013815 (2009).","journal-title":"Am. J. Ophthalmol."},{"key":"62347_CR6","doi-asserted-by":"publisher","first-page":"4545","DOI":"10.1167\/iovs.07-1553","volume":"49","author":"DM de Bruin","year":"2008","unstructured":"de Bruin, D. M. et al. In vivo three-dimensional imaging of neovascular age-related macular degeneration using optical frequency domain imaging at 1050 nm. Invest. Ophthalmol. Vis. Sci. 49, 4545\u201352 (2008).","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"key":"62347_CR7","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1167\/iovs.08-2272","volume":"50","author":"Y Yasuno","year":"2009","unstructured":"Yasuno, Y. et al. Visualization of Sub-retinal Pigment Epithelium Morphologies of Exudative Macular Diseases by High-Penetration Optical Coherence Tomography. Investig. Opthalmology Vis. Sci. 50, 405 (2009).","journal-title":"Investig. Opthalmology Vis. Sci."},{"key":"62347_CR8","doi-asserted-by":"publisher","first-page":"7630","DOI":"10.1167\/iovs.13-13135","volume":"54","author":"Y Matsuo","year":"2013","unstructured":"Matsuo, Y. et al. Comparisons of Choroidal Thickness of Normal Eyes Obtained by Two Different Spectral-Domain OCT Instruments and One Swept-Source OCT Instrument. Investig. Opthalmology Vis. Sci. 54, 7630 (2013).","journal-title":"Investig. Opthalmology Vis. Sci."},{"key":"62347_CR9","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.ajo.2015.04.018","volume":"160","author":"E Harb","year":"2015","unstructured":"Harb, E. et al. Choroidal Thickness Profiles in Myopic Eyes of Young Adults in the Correction of Myopia Evaluation Trial Cohort. Am. J. Ophthalmol. 160, 62\u201371.e2 (2015).","journal-title":"Am. J. Ophthalmol."},{"key":"62347_CR10","doi-asserted-by":"publisher","first-page":"1901","DOI":"10.1016\/j.ophtha.2013.01.066","volume":"120","author":"LA Branchini","year":"2013","unstructured":"Branchini, L. A. et al. Analysis of choroidal morphologic features and vasculature in healthy eyes using spectral-domain optical coherence tomography. Ophthalmology 120, 1901\u20131908 (2013).","journal-title":"Ophthalmology"},{"key":"62347_CR11","doi-asserted-by":"publisher","first-page":"9555","DOI":"10.1167\/iovs.11-8076","volume":"52","author":"X Ding","year":"2011","unstructured":"Ding, X. et al. Choroidal thickness in healthy chinese subjects. Investig. Opthalmology Vis. Sci. 52, 9555 (2011).","journal-title":"Investig. Opthalmology Vis. Sci."},{"key":"62347_CR12","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1080\/09273948.2016.1184283","volume":"25","author":"N Ikeda","year":"2017","unstructured":"Ikeda, N. et al. Detection of asymptomatic choroiditis by fundus examination in Vogt\u2013Koyanagi\u2013Harada disease. Ocul. Immunol. Inflamm. 25, 830\u2013833 (2017).","journal-title":"Ocul. Immunol. Inflamm."},{"key":"62347_CR13","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1001\/archopht.1977.04450050139018","volume":"95","author":"FC Delori","year":"1977","unstructured":"Delori, F. C. et al. Monochromatic ophthalmoscopy and fundus photography. The normal fundus. Arch. Ophthalmol. (Chicago, Ill. 1960) 95, 861\u20138 (1977).","journal-title":"Arch. Ophthalmol. (Chicago, Ill. 1960)"},{"key":"62347_CR14","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/j.oret.2018.09.005","volume":"3","author":"N Kakiuchi","year":"2019","unstructured":"Kakiuchi, N. et al. Choroidal vasculature from ultra-widefield images without contrast dye and its application to Vogt-Koyanagi-Harada disease. Ophthalmol. Retin. 3, 161\u2013169 (2019).","journal-title":"Ophthalmol. Retin."},{"key":"62347_CR15","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, 2402 (2016).","journal-title":"JAMA"},{"key":"62347_CR16","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-33013-w","volume":"8","author":"N Shibata","year":"2018","unstructured":"Shibata, N. et al. Development of a deep residual learning algorithm to screen for glaucoma from fundus photography. Sci. Rep. 8, 14665 (2018).","journal-title":"Sci. Rep."},{"key":"62347_CR17","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1016\/j.ophtha.2018.01.023","volume":"125","author":"Z Li","year":"2018","unstructured":"Li, Z. et al. Efficacy of a deep Learning system for detecting glaucomatous optic neuropathy based on color fundus photographs. Ophthalmology 125, 1199\u20131206 (2018).","journal-title":"Ophthalmology"},{"key":"62347_CR18","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1016\/j.oret.2016.12.009","volume":"1","author":"CS Lee","year":"2017","unstructured":"Lee, C. S. et al. Deep learning is effective for classifying normal versus age-related macular degeneration OCT images. Ophthalmol. Retin. 1, 322\u2013327 (2017).","journal-title":"Ophthalmol. Retin."},{"key":"62347_CR19","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.ajo.2016.03.040","volume":"166","author":"S Hirahara","year":"2016","unstructured":"Hirahara, S. et al. Densitometry of choroidal vessels in eyes with and without central serous chorioretinopathy by wide-field indocyanine green angiography. Am. J. Ophthalmol. 166, 103\u2013111 (2016).","journal-title":"Am. J. Ophthalmol."},{"key":"62347_CR20","doi-asserted-by":"publisher","first-page":"e0157190","DOI":"10.1371\/journal.pone.0157190","volume":"11","author":"S Sonoda","year":"2016","unstructured":"Sonoda, S. et al. Structural changes of inner and outer choroid in central serous chorioretinopathy determined by optical coherence tomography. PLoS One 11, e0157190 (2016).","journal-title":"PLoS One"},{"key":"62347_CR21","first-page":"145","volume":"27","author":"JJ Weiter","year":"1986","unstructured":"Weiter, J. J. et al. Retinal pigment epithelial lipofuscin and melanin and choroidal melanin in human eyes. Investig. Ophthalmol. Vis. Sci. 27, 145\u2013152 (1986).","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"62347_CR22","doi-asserted-by":"publisher","first-page":"2173","DOI":"10.1167\/iovs.09-4383","volume":"51","author":"Y Ikuno","year":"2010","unstructured":"Ikuno, Y. et al. Choroidal thickness in healthy Japanese subjects. Invest. Ophthalmol. Vis. Sci. 51, 2173\u20136 (2010).","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"key":"62347_CR23","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1016\/j.ajo.2008.12.008","volume":"147","author":"R Margolis","year":"2009","unstructured":"Margolis, R. & Spaide, R. F. A Pilot Study of enhanced depth imaging optical coherence tomography of the choroid in normal eyes. Am. J. Ophthalmol. 147, 811\u2013815 (2009).","journal-title":"Am. J. Ophthalmol."},{"key":"62347_CR24","unstructured":"Simonyan, K. & Zisserman, A. very deep convolutional networks for large-scale image recognition. (2014)."},{"key":"62347_CR25","unstructured":"Glorot, X. et al. Deep sparse rectifier neural networks. (2011)."},{"key":"62347_CR26","doi-asserted-by":"crossref","unstructured":"Selvaraju, R. R. et al. Grad-CAM: Visual explanations from deep networks via gradient-based localization. (2017).","DOI":"10.1109\/ICCV.2017.74"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-020-62347-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-020-62347-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-020-62347-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,6]],"date-time":"2022-12-06T09:04:21Z","timestamp":1670317461000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-020-62347-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,27]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["62347"],"URL":"https:\/\/doi.org\/10.1038\/s41598-020-62347-7","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,27]]},"assertion":[{"value":"17 September 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 March 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 March 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"5640"}}