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Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2017.2786271
Abstract: This paper presents a supervised feature learning method to learn discriminative and compact descriptors for drusen segmentation from retinal images. This method combines generalized low rank approximation of matrices with supervised manifold regularization to learn…
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Keywords:
feature learning;
drusen segmentation;
supervised feature;
segmentation retinal ... See more keywords
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Published in 2021 at "Biomedical optics express"
DOI: 10.1364/boe.438948
Abstract: [This corrects the article on p. 4713 in vol. 12.].
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Keywords:
weakly supervised;
anomaly segmentation;
erratum weakly;
segmentation retinal ... See more keywords
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Published in 2022 at "Biomedical optics express"
DOI: 10.1364/boe.458004
Abstract: Optical coherence tomography angiography(OCTA) is an advanced noninvasive vascular imaging technique that has important implications in many vision-related diseases. The automatic segmentation of retinal vessels in OCTA is understudied, and the existing segmentation methods require…
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Keywords:
consistency semi;
segmentation retinal;
supervision;
segmentation ... See more keywords
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Published in 2020 at "Applied Sciences"
DOI: 10.3390/app10113777
Abstract: Diabetes can induce diseases including diabetic retinopathy, cataracts, glaucoma, etc. The blindness caused by these diseases is irreversible. Early analysis of retinal fundus images, including optic disc and optic cup detection and retinal blood vessel…
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Keywords:
retinal fundus;
segmentation;
segmentation retinal;
fundus image ... See more keywords
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Published in 2022 at "Biomedicines"
DOI: 10.3390/biomedicines10061269
Abstract: Diabetic macular edema (DME) is a highly common cause of vision loss in patients with diabetes. Optical coherence tomography (OCT) is crucial in classifying DME and tracking the results of DME treatment. The presence of…
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Keywords:
visual acuity;
segmentation retinal;
segmentation;
fluid ... See more keywords