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Jun 1, 2021 � Aiming at the segmentation and sensitivity detection of retinal nerve fiber layer (RNFL) in glaucoma, this paper mainly studies it based on high-level semantic�...
In this algorithm, random forest classifier is used to find the boundary of single pixel width between layers of retina, and 12 features are used to train�...
In this algorithm, random forest classifier is used to find the boundary of single pixel width between layers of retina, and 12 features are used to train�...
Results: The sensitivities of the RNFL thickness deviation map ranged between 95.0% and 97.5%. There were significant differences in specificity between a map�...
Missing: Semantic Fusion Algorithm.
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What is a nerve fiber layer analysis?
Aiming at the segmentation and sensitivity detection of retinal nerve fiber layer (RNFL) in glaucoma, this paper mainly studies it based on high-level semantic�...
Purpose: To provide an update on the role of optic nerve head and peripapillary retinal nerve fiber layer imaging in monitoring glaucoma progression.
We conducted a comprehensive review on artificial intelligence-enabled glaucoma detection frameworks that produce and use segmented fundus images.
This chapter has been studying automated schemes for detection of nerve fiber layer defects and analysis of optic disc deformation, two major signs of�...
This work proposes an offline Computer-Aided Diagnosis (CAD) system for glaucoma diagnosis using retinal fundus images.
Jul 16, 2023 � They reported that the average RNFL thickness sensitivity using RTVue OCT was 0.66, and the average specificity was 0.95. They also found that�...
Missing: Level Fusion