Glaucoma detection and evaluation through pattern recognition in standard automated perimetry data

2009 ◽  
Vol 247 (11) ◽  
pp. 1517-1530 ◽  
Author(s):  
Dariusz Wroblewski ◽  
Brian A. Francis ◽  
Vikas Chopra ◽  
A. Shahem Kawji ◽  
Peter Quiros ◽  
...  
2009 ◽  
Vol 53 (5) ◽  
pp. 482-485
Author(s):  
Yoon Pyo Nam ◽  
Seong Bae Park ◽  
Sung Yong Kang ◽  
Kyung Rim Sung ◽  
Michael S. Kook

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexandru Lavric ◽  
Valentin Popa ◽  
Hidenori Takahashi ◽  
Rossen M. Hazarbassanov ◽  
Siamak Yousefi

AbstractThe main goal of this study is to identify the association between corneal shape, elevation, and thickness parameters and visual field damage using machine learning. A total of 676 eyes from 568 patients from the Jichi Medical University in Japan were included in this study. Corneal topography, pachymetry, and elevation images were obtained using anterior segment optical coherence tomography (OCT) and visual field tests were collected using standard automated perimetry with 24-2 Swedish Interactive Threshold Algorithm. The association between corneal structural parameters and visual field damage was investigated using machine learning and evaluated through tenfold cross-validation of the area under the receiver operating characteristic curves (AUC). The average mean deviation was − 8.0 dB and the average central corneal thickness (CCT) was 513.1 µm. Using ensemble machine learning bagged trees classifiers, we detected visual field abnormality from corneal parameters with an AUC of 0.83. Using a tree-based machine learning classifier, we detected four visual field severity levels from corneal parameters with an AUC of 0.74. Although CCT and corneal hysteresis have long been accepted as predictors of glaucoma development and future visual field loss, corneal shape and elevation parameters may also predict glaucoma-induced visual functional loss.


2012 ◽  
Vol 4 (2) ◽  
pp. 236-241
Author(s):  
S Ganekal

Objective: To compare the macular ganglion cell complex (GCC) with peripapillary retinal fiber layer (RNFL) thickness map in glaucoma suspects and patients. Subjects and methods: Forty participants (20 glaucoma suspects and 20 glaucoma patients) were enrolled. Macular GCC and RNFL thickness maps were performed in both eyes of each participant in the same visit. The sensitivity and specificity of a color code less than 5% (red or yellow) for glaucoma diagnosis were calculated. Standard Automated Perimetry was performed with the Octopus 3.1.1 Dynamic 24-2 program. Statistics: The statistical analysis was performed with the SPSS 10.1 (SPSS Inc. Chicago, IL, EUA). Results were expressed as mean ± standard deviation and a p value of 0.05 or less was considered significant. Results: Provide absolute numbers of these findings with their units of measurement. There was a statistically significant difference in average RNFL thickness (p=0.004), superior RNFL thickness (p=0.006), inferior RNFL thickness (p=0.0005) and average GCC (p=0.03) between the suspects and glaucoma patients. There was no difference in optic disc area (p=0.35) and vertical cup/disc ratio (p=0.234) in both groups. While 38% eyes had an abnormal GCC and 13% had an abnormal RNFL thickness in the glaucoma suspect group, 98% had an abnormal GCC and 90% had an abnormal RNFL thickness in the glaucoma group.Conclusion: The ability to diagnose glaucoma with macular GCC thickness is comparable to that with peripapillary RNFL thickness. Macular GCC thickness measurements may be a good alternative or a complementary measurement to RNFL thickness assessment in the clinical evaluation of glaucoma.DOI: http://dx.doi.org/10.3126/nepjoph.v4i2.6538 Nepal J Ophthalmol 2012; 4 (2): 236-241 


PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0207517 ◽  
Author(s):  
Kazunori Hirasawa ◽  
Kaoru Kobayashi ◽  
Asuka Shibamoto ◽  
Houmi Tobari ◽  
Yuki Fukuda ◽  
...  

Author(s):  
George Shafranov

Standard automated perimetry is a standard method of measuring peripheral visual function. Automated static perimetry gained wide acceptance among clinicians due to the test’s high reproducibility and standardization and ability to store, exchange, and statistically analyze digital data. Advances in the computerized visual field assessment have contributed to our understanding of the role that field of vision plays in clinical evaluation and management of patients. The Humphrey Visual Field Analyzer/HFA II-i is the most commonly used automated perimeter in the United States, and the examples in this chapter have been obtained with this instrument. Aubert and Förster in the 1860s developed the arc perimeter, which led to the mapping of peripheral neurologic visual field abnormalities and advanced glaucomatous field defects. Analysis of the central visual field was not seen as clinically important by most clinicians until 1889, when Bjerrum described a detected arcuate paracentral scotoma. Later, Traquair further contributed to kinetic perimetry on the tangent screen. In 1893, Groenouw proposed the term “isopter” for lines with the same sensitivity on a perimetry chart. Rønne further developed kinetic isopter perimetry in 1909 and described the nasal step in glaucoma. Although the first bowl perimeter was introduced in 1872 by Scherk, due to problems with achieving even illumination on the screen, it did not become popular. The version of the bowl perimeter introduced by Goldmann in 1945 became widely accepted and is a significant contribution to clinical perimetry. The Goldmann perimeter incorporated a projected stimulus on an illuminated bowl, with standardization of background illumination as well as size and intensity of the stimulus, and allowed effective use of both static and kinetic techniques. For these reasons, the Goldmann instrument has remained the clinical standard throughout the world until widespread acceptance of automated perimetry. Harms and Aulhorn later designed the Tübingen perimeter with a bowl-type screen exclusively for the measurement of static threshold fields, using stationary test objects with variable light intensity. While excellent threshold measurements were possible with this instrument, the time and effort involved in such measurements prevented this perimeter from becoming widely used.


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