Retesting Visual Fields: Utilizing Prior Information to Decrease Test–Retest Variability in Glaucoma
Author:
Affiliation:
1. From the School of Computer Science and Information Technology, RMIT University, Melbourne, Australia; and the
2. Department of Optometry and Vision Sciences, University of Melbourne, Carlton, Victoria, Australia.
Publisher
Association for Research in Vision and Ophthalmology (ARVO)
Subject
General Medicine
Cited by 34 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Rapid campimetry - a novel robust kinetic approach for visual field screening in glaucoma;Frontiers in Medicine;2024-08-02
2. VF-Mask-Net: A Visual Field Noise Reduction Method Using Neural Networks;Electronics;2024-02-04
3. Deep Learning Estimation of 10-2 Visual Field Map Based on Macular Optical Coherence Tomography Angiography Measurements;American Journal of Ophthalmology;2024-01
4. Multiple (frontloaded) visual field tests increase identification of very slow mean deviation progression in glaucoma;Canadian Journal of Ophthalmology;2023-08
5. Suprathreshold Approaches to Mapping the Visual Field in Advanced Glaucoma;Translational Vision Science & Technology;2023-06-28
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