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Automated Classification of Inherited Retinal Diseases in Optical Coherence Tomography Images Using Few-shot Learning

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收录情况： ◇ SCIE ◇ CSCD-C ◇ 卓越：梯队期刊

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机构： [1]Department of Ophthalmology,Beijing Tongren Eye Center,Beijing Tongren Hospital,Capital Medical University,Beijing Key Laboratory of Ophthalmology and Visual Sciences,Beijing 100730,China [2]Department of Computer Science, Rutgers, The State University of New Jersey, New Brunswick 08901, USA [3]Department of Computer Science and Engineering, University at Buffalo, Buffalo 14260, USA [4]Beijing Institute of Ophthalmology,Beijing Tongren Hospital,Capital Medical University,Beijing Ophthalmology and Visual Science Key Laboratory,Beijing 100730,China

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关键词： Few-shot learning Student-teacher learning Knowledge distillation Transfer learning Optical coherence tomography Retinal degeneration Inherited retinal diseases

摘要：

To develop a few-shot learning (FSL) approach for classifying optical coherence tomography (OCT) images in patients with inherited retinal disorders (IRDs).In this study, an FSL model based on a student-teacher learning framework was designed to classify images. 2,317 images from 189 participants were included. Of these, 1,126 images revealed IRDs, 533 were normal samples, and 658 were control samples.The FSL model achieved a total accuracy of 0.974-0.983, total sensitivity of 0.934-0.957, total specificity of 0.984-0.990, and total F1 score of 0.935-0.957, which were superior to the total accuracy of the baseline model of 0.943-0.954, total sensitivity of 0.866-0.886, total specificity of 0.962-0.971, and total F1 score of 0.859-0.885. The performance of most subclassifications also exhibited advantages. Moreover, the FSL model had a higher area under curves (AUC) of the receiver operating characteristic (ROC) curves in most subclassifications.This study demonstrates the effective use of the FSL model for the classification of OCT images from patients with IRDs, normal, and control participants with a smaller volume of data. The general principle and similar network architectures can also be applied to other retinal diseases with a low prevalence.Copyright © 2023 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

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出版当年[2022]版：

大类 | 3 区医学

小类 | 3 区环境科学 3 区公共卫生、环境卫生与职业卫生

最新[2023]版：

大类 | 3 区医学

小类 | 4 区环境科学 4 区公共卫生、环境卫生与职业卫生

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出版当年[2021]版：

Q3 ENVIRONMENTAL SCIENCES Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

最新[2023]版：

Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Q2 ENVIRONMENTAL SCIENCES

影响因子： 3 最新[2023版] 3.1 最新五年平均 2.831 出版当年[2021版] 3.367 出版当年五年平均 3.118 出版前一年[2020版] 3.5 出版后一年[2022版]

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第一作者机构： [1]Department of Ophthalmology,Beijing Tongren Eye Center,Beijing Tongren Hospital,Capital Medical University,Beijing Key Laboratory of Ophthalmology and Visual Sciences,Beijing 100730,China

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