2026-04-27T21:28:25Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/560142025-02-20T07:49:53Zcom_10324_23459com_10324_954com_10324_894col_10324_23460
UVaDOC
author
Jimenez García, Jorge
author
Romero Oraa, Roberto
author
García Gadañón, María
author
López Gálvez, María Isabel
author
Hornero Sánchez, Roberto
2022-10-19T11:54:09Z
2022-10-19T11:54:09Z
2019
Entropy, 2019, vol. 21, n. 3, 311
1099-4300
https://uvadoc.uva.es/handle/10324/56014
10.3390/e21030311
Diabetic retinopathy (DR) is one of the most common causes of visual loss in developed countries. Computer-aided diagnosis systems aimed at detecting DR can reduce the workload of ophthalmologists in screening programs. Nevertheless, a large number of retinal images cannot be analyzed by physicians and automatic methods due to poor quality. Automatic retinal image quality assessment (RIQA) is needed before image analysis. The purpose of this study was to combine novel generic quality features to develop a RIQA method. Several features were calculated from retinal images to achieve this goal. Features derived from the spatial and spectral entropy-based quality (SSEQ) and the natural images quality evaluator (NIQE) methods were extracted. They were combined with novel sharpness and luminosity measures based on the continuous wavelet transform (CWT) and the hue saturation value (HSV) color model, respectively. A subset of non-redundant features was selected using the fast correlation-based filter (FCBF) method. Subsequently, a multilayer perceptron (MLP) neural network was used to obtain the quality of images from the selected features. Classification results achieved 91.46% accuracy, 92.04% sensitivity, and 87.92% specificity. Results suggest that the proposed RIQA method could be applied in a more general computer-aided diagnosis system aimed at detecting a variety of retinal pathologies such as DR and age-related macular degeneration.
eng
Atribución 4.0 Internacional
Combination of global features for the automatic quality assessment of retinal images
info:eu-repo/semantics/article
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https://uvadoc.uva.es/bitstream/10324/56014/1/Combination-global-features.pdf
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Combination-global-features.pdf