High-Accuracy Digitization of Humphrey Visual Field Reports Using Convolutional Neural Networks.

Journal: Translational vision science & technology

PMID: 40323288

Abstract

PURPOSE: Glaucoma is a leading cause of irreversible blindness worldwide, necessitating precise visual field (VF) assessments for effective diagnosis and management. The ability to accurately digitize VF reports is critical for maximizing the utility of the data gathered from clinical evaluations.

Authors

Shian-Sen Shie

Department of Internal Medicine, Division of Infectious Diseases, Chang Gung Memorial Hostpital, Linkou Branch, Taoyuan Taiwan; and College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Wei-Wen Su

Department of Ophthalmology, Chansn Hospital, Zhongli, Taoyuan, Taiwan.

Keywords

Convolutional Neural Networks Glaucoma Humans Neural Networks, Computer Reproducibility of Results Visual Field Tests Visual Fields

External Resources

View on PubMed Access via DOI PubMed (40323288)

High-Accuracy Digitization of Humphrey Visual Field Reports Using Convolutional Neural Networks.

Abstract

Authors

Keywords

External Resources

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