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Article
Open AccessVisusmindernde Irispigmentepithelzysten
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Article
Image quality assessment of retinal fundus photographs for diabetic retinopathy in the machine learning era: a review
This study aimed to evaluate the image quality assessment (IQA) and quality criteria employed in publicly available datasets for diabetic retinopathy (DR). A literature search strategy was used to identify rel...
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Living Reference Work Entry In depth
Hirnnervenparesen
Hirnnervenparesen sind durch Hirnnervenläsionen bedingte okuläre Motilitätsstörungen. Sie sind von kortikalen Störungen der koordinierten Augenbeweglichkeit, sog. supranukleären Störungen, zu unterscheiden. Ke...
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Chapter and Conference Paper
Visual Explanations for the Detection of Diabetic Retinopathy from Retinal Fundus Images
In medical image classification tasks like the detection of diabetic retinopathy from retinal fundus images, it is highly desirable to get visual explanations for the decisions of black-box deep neural network...
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Chapter and Conference Paper
Interpretable Gender Classification from Retinal Fundus Images Using BagNets
Deep neural networks (DNNs) are able to predict a person’s gender from retinal fundus images with high accuracy, even though this task is usually considered hardly possible by ophthalmologists. Therefore, it h...