Wild, Derk Sven Gard; Kucur, Serife Seda; Sznitman, Raphael (2017). Spatial Entropy Pursuit for Fast and Accurate Perimetry Testing. Investigative ophthalmology & visual science, 58(9), pp. 3414-3424. Association for Research in Vision and Ophthalmology 10.1167/iovs.16-21144
|
Text
i1552-5783-58-9-3414.pdf - Published Version Available under License Creative Commons: Attribution-Noncommercial-No Derivative Works (CC-BY-NC-ND). Download (2MB) | Preview |
Purpose: To propose a static automated perimetry strategy that increases the speed of visual field (VF) evaluation while retaining threshold estimate accuracy.
Methods: We propose a novel algorithm, spatial entropy pursuit (SEP), which evaluates individual locations by using zippy estimation by sequential testing (ZEST) but additionally uses neighboring locations to estimate the sensitivity of related locations. We model the VF with a conditional random field (CRF) where each node represents a location estimate that depends on itself as well as its neighbors. Tested locations are randomly selected from a pool of locations and new locations are added such that they maximally reduce the uncertainty over the entire VF. When no location can further reduce the uncertainty significantly, remaining locations are estimated from the CRF directly.
Results: SEP was evaluated and compared to tendency-oriented strategy, ZEST, and the Dynamic Test Strategy by using computer simulations on a test set of 245 healthy and 172 glaucomatous VFs. For glaucomatous VFs, root-mean-square error (RMSE) of SEP was comparable to that of existing strategies (3.4 dB), whereas the number of stimulus presentations of SEP was up to 23% lower than that of other methods. For healthy VFs, SEP had an RMSE comparable to evaluated methods (3.1 dB) but required 55% fewer stimulus presentations.
Conclusions: When compared to existing methods, SEP showed improved performances, especially with respect to test speed. Thus, it represents an interesting alternative to existing strategies.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Medical Imaging Laboratory |
Graduate School: |
Graduate School for Cellular and Biomedical Sciences (GCB) |
UniBE Contributor: |
Wild, Derk Sven Gard, Kucur, Serife Seda, Sznitman, Raphael |
Subjects: |
500 Science > 570 Life sciences; biology 600 Technology > 610 Medicine & health 600 Technology > 620 Engineering |
ISSN: |
0146-0404 |
Publisher: |
Association for Research in Vision and Ophthalmology |
Language: |
English |
Submitter: |
Raphael Sznitman |
Date Deposited: |
24 Oct 2017 10:50 |
Last Modified: |
05 Dec 2022 15:06 |
Publisher DOI: |
10.1167/iovs.16-21144 |
PubMed ID: |
28692736 |
BORIS DOI: |
10.7892/boris.102085 |
URI: |
https://boris.unibe.ch/id/eprint/102085 |
Actions (login required)
 |
Edit item |