{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:15:29Z","timestamp":1772262929351,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2018,6,20]],"date-time":"2018-06-20T00:00:00Z","timestamp":1529452800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61671272"],"award-info":[{"award-number":["61671272"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Opening Project of Guangdong Province Key Laboratory of Big Data Analysis and Processing","award":["201803"],"award-info":[{"award-number":["201803"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>We present an automatic method based on transfer learning for the identification of dry age-related macular degeneration (AMD) and diabetic macular edema (DME) from retinal optical coherence tomography (OCT) images. The algorithm aims to improve the classification performance of retinal OCT images and shorten the training time. Firstly, we remove the last several layers from the pre-trained Inception V3 model and regard the remaining part as a fixed feature extractor. Then, the features are used as input of a convolutional neural network (CNN) designed to learn the feature space shifts. The experimental results on two different retinal OCT images datasets demonstrate the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/a11060088","type":"journal-article","created":{"date-parts":[[2018,6,20]],"date-time":"2018-06-20T10:41:24Z","timestamp":1529491284000},"page":"88","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Efficient Deep Learning-Based Automated Pathology Identification in Retinal Optical Coherence Tomography Images"],"prefix":"10.3390","volume":"11","author":[{"given":"Qingge","family":"Ji","sequence":"first","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, 132 East Waihuan Road, Guangzhou Higher Education Mega Center, Guangzhou 510006, China"},{"name":"Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjie","family":"He","sequence":"additional","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, 132 East Waihuan Road, Guangzhou Higher Education Mega Center, Guangzhou 510006, China"},{"name":"Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, 132 East Waihuan Road, Guangzhou Higher Education Mega Center, Guangzhou 510006, China"},{"name":"Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yankui","family":"Sun","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou 510006, China"},{"name":"Department of Computer Science and Technology, Tsinghua University, 30 Shuangqing Road, Haidian District, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.1126\/science.1957169","article-title":"Optical coherence tomography","volume":"254","author":"Huang","year":"1991","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1016\/j.preteyeres.2008.03.002","article-title":"Combinations of techniques in imaging the retina with high resolution","volume":"27","author":"Podoleanu","year":"2008","journal-title":"Prog. 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