{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T09:18:34Z","timestamp":1785403114884,"version":"3.56.0"},"reference-count":33,"publisher":"Optica Publishing Group","issue":"5","license":[{"start":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T00:00:00Z","timestamp":1680480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR-OA"},{"start":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T00:00:00Z","timestamp":1680480000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of\n\t\t\t\t\t\tChina","doi-asserted-by":"publisher","award":["82171016"],"award-info":[{"award-number":["82171016"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Biomed. Opt. Express"],"published-print":{"date-parts":[[2023,5,1]]},"abstract":"<jats:p>The tear fluid reservoir (TFR) under the sclera lens is a unique\n\t\t\t\t\tcharacteristic providing optical neutralization of any aberrations\n\t\t\t\t\tfrom corneal irregularities. Anterior segment optical coherence\n\t\t\t\t\ttomography (AS-OCT) has become an important imaging modality for\n\t\t\t\t\tsclera lens fitting and visual rehabilitation therapy in both\n\t\t\t\t\toptometry and ophthalmology. Herein, we aimed to investigate whether\n\t\t\t\t\tdeep learning can be used to segment the TFR from healthy and\n\t\t\t\t\tkeratoconus eyes, with irregular corneal surfaces, in OCT images.\n\t\t\t\t\tUsing AS-OCT, a dataset of 31850 images from 52 healthy and 46\n\t\t\t\t\tkeratoconus eyes, during sclera lens wear, was obtained and labeled\n\t\t\t\t\twith our previously developed algorithm of semi-automatic\n\t\t\t\t\tsegmentation. A custom-improved U-shape network architecture with a\n\t\t\t\t\tfull-range multi-scale feature-enhanced module (FMFE-Unet) was\n\t\t\t\t\tdesigned and trained. A hybrid loss function was designed to focus\n\t\t\t\t\ttraining on the TFR, to tackle the class imbalance problem. The\n\t\t\t\t\texperiments on our database showed an IoU, precision, specificity, and\n\t\t\t\t\trecall of 0.9426, 0.9678, 0.9965, and 0.9731, respectively.\n\t\t\t\t\tFurthermore, FMFE-Unet was found to outperform the other two\n\t\t\t\t\tstate-of-the-art methods and ablation models, suggesting its strength\n\t\t\t\t\tin segmenting the TFR under the sclera lens depicted on OCT images.\n\t\t\t\t\tThe application of deep learning for TFR segmentation in OCT images\n\t\t\t\t\tprovides a powerful tool to assess changes in the dynamic tear film\n\t\t\t\t\tunder the sclera lens, improving the efficiency and accuracy of lens\n\t\t\t\t\tfitting, and thus supporting the promotion of sclera lenses in\n\t\t\t\t\tclinical practice.<\/jats:p>","DOI":"10.1364\/boe.480247","type":"journal-article","created":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T04:00:08Z","timestamp":1675656008000},"page":"1848","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Deep learning segmentation of the tear fluid reservoir under the sclera lens in optical coherence tomography images"],"prefix":"10.1364","volume":"14","author":[{"given":"Yuheng","family":"Zhou","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangqing","family":"Lin","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangle","family":"Yu","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Cao","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongling","family":"Cheng","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ce","family":"Shi","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Jiang","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hebei","family":"Gao","sequence":"additional","affiliation":[{"name":"Wenzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fan","family":"Lu","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Wenzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meixiao","family":"Shen","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00rd5t069","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Wenzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2023,4,3]]},"reference":[{"key":"boe-14-5-1848-R1","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.clae.2017.07.002","volume":"41","author":"Vincent","year":"2018","journal-title":"Cont Lens 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