2023
DOI: 10.3390/math11020257
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Assisting Glaucoma Screening Process Using Feature Excitation and Information Aggregation Techniques in Retinal Fundus Images

Abstract: The rapidly increasing trend of retinal diseases needs serious attention, worldwide. Glaucoma is a critical ophthalmic disease that can cause permanent vision impairment. Typically, ophthalmologists diagnose glaucoma using manual assessments which is an error-prone, subjective, and time-consuming approach. Therefore, the development of automated methods is crucial to strengthen and assist the existing diagnostic methods. In fundus imaging, optic cup (OC) and optic disc (OD) segmentation are widely accepted by … Show more

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Cited by 8 publications
(3 citation statements)
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“…The second step is training the generators for the total regions. After embedding the trained weights in the encoder into the corresponding generators, the random vector and AL difference were utilized to produce the modified feature vector as ( 6)- (7). During training, the region of the input images needs to be the previous or the next region that the label images belong to, because referencing the data in the nearest region is assumed to be more efficient in terms of generating the data.…”
Section: The Procedures Of the Data Augmentationmentioning
confidence: 99%
See 2 more Smart Citations
“…The second step is training the generators for the total regions. After embedding the trained weights in the encoder into the corresponding generators, the random vector and AL difference were utilized to produce the modified feature vector as ( 6)- (7). During training, the region of the input images needs to be the previous or the next region that the label images belong to, because referencing the data in the nearest region is assumed to be more efficient in terms of generating the data.…”
Section: The Procedures Of the Data Augmentationmentioning
confidence: 99%
“…Retinal image analysis involves detecting and segmenting biological components in retinal images or screening high-quality images. Fundus images, one of the most commonly used images in ophthalmology, show the retinal vessels, optic disc, and fovea; rapid and accurate identification of these components is important for achieving diagnosis automation and downstream tasks [7,8]. In addition, retinal disease classification and retinal pathology segmentation have attracted significant research attention for automating retinopathy diagnoses [9,10].…”
Section: Introductionmentioning
confidence: 99%
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