Automated malarial retinopathy detection using transfer learning and multi-camera retinal images

IF 5.3 2区医学 Q1 ENGINEERING, BIOMEDICAL

Biocybernetics and Biomedical Engineering Pub Date : 2023-01-01 DOI:10.1016/j.bbe.2022.12.003

Aswathy Rajendra Kurup , Jeff Wigdahl , Jeremy Benson , Manel Martínez-Ramón , Peter Solíz , Vinayak Joshi

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引用次数: 1

Abstract

Cerebral malaria (CM) is a fatal syndrome found commonly in children less than 5 years old in Sub-saharan Africa and Asia. The retinal signs associated with CM are known as malarial retinopathy (MR), and they include highly specific retinal lesions such as whitening and hemorrhages. Detecting these lesions allows the detection of CM with high specificity. Up to 23% of CM, patients are over-diagnosed due to the presence of clinical symptoms also related to pneumonia, meningitis, or others. Therefore, patients go untreated for these pathologies, resulting in death or neurological disability. It is essential to have a low-cost and high-specificity diagnostic technique for CM detection, for which We developed a method based on transfer learning (TL). Models pre-trained with TL select the good quality retinal images, which are fed into another TL model to detect CM. This approach shows a 96% specificity with low-cost retinal cameras.

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使用迁移学习和多摄像头视网膜图像自动检测疟疾视网膜病变

脑疟疾（CM）是一种常见于5岁以下儿童的致命综合征 撒哈拉以南非洲和亚洲的岁。与CM相关的视网膜体征被称为疟疾视网膜病变（MR），包括高度特异性的视网膜病变，如白化和出血。检测这些病变可以以高特异性检测CM。高达23%的CM患者由于存在与肺炎、脑膜炎或其他相关的临床症状而被过度诊断。因此，患者因这些疾病得不到治疗，导致死亡或神经系统残疾。有一种低成本、高特异性的CM检测诊断技术是至关重要的，为此我们开发了一种基于迁移学习（TL）的方法。用TL预训练的模型选择高质量的视网膜图像，将其输入另一个TL模型以检测CM。这种方法在低成本的视网膜相机中显示出96%的特异性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biocybernetics and Biomedical Engineering ENGINEERING, BIOMEDICAL-

CiteScore

16.50

自引率

6.20%

发文量

审稿时长

38 days

期刊介绍： Biocybernetics and Biomedical Engineering is a quarterly journal, founded in 1981, devoted to publishing the results of original, innovative and creative research investigations in the field of Biocybernetics and biomedical engineering, which bridges mathematical, physical, chemical and engineering methods and technology to analyse physiological processes in living organisms as well as to develop methods, devices and systems used in biology and medicine, mainly in medical diagnosis, monitoring systems and therapy. The Journal''s mission is to advance scientific discovery into new or improved standards of care, and promotion a wide-ranging exchange between science and its application to humans.