Purposes: The purposes of this study are to compare macular perimetric sensitivities for conventional size III, frequency-doubling, and Gabor stimuli in terms of Weber contrast and to provide a theoretical interpretation of the results.
Methods: Twenty-two patients with glaucoma performed four perimetric tests: a conventional Swedish Interactive Threshold Algorithm (SITA) 10-2 test with Goldmann size III stimuli, two frequency-doubling tests (FDT 10-2, FDT Macula) with counterphase-modulated grating stimuli, and a laboratory-designed test with Gabor stimuli. Perimetric sensitivities were converted to the reciprocal of Weber contrast and sensitivities from different tests were compared using the Bland-Altman method. Effects of ganglion cell loss on perimetric sensitivities were then simulated with a two-stage neural model.
Results: The average perimetric loss was similar for all stimuli until advanced stages of ganglion cell loss, in which perimetric loss tended to be greater for size III stimuli than for frequency-doubling and Gabor stimuli. Comparison of the experimental data and model simulation suggests that, in the macula, linear relations between ganglion cell loss and perimetric sensitivity loss hold for all three stimuli.
Conclusions: Linear relations between perimetric loss and ganglion cell loss for all three stimuli can account for the similarity in perimetric loss until advanced stages. The results do not support the hypothesis that redundancy for frequency-doubling stimuli is lower than redundancy for size III stimuli.
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http://dx.doi.org/10.1097/01.opx.0000225103.18087.5d | DOI Listing |
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Indiana University, Indianapolis, IN, United States.
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Department of Medicine 1, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, 91052 Erlangen, Germany.
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Institute of High Pressure Physics, Polish Academy of Sciences, Warsaw 01-142, Poland.
Ultrasmall micro-light-emitting diodes (μLEDs), sized below 10 μm, are indispensable to create the next-generation augmented and virtual reality (AR/VR) devices. Their high brightness and low power consumption could not only enhance the user experience by providing vivid and lifelike visuals but also extend device longevity. However, a notable challenge emerges: a decrease in efficiency with a reduced size.
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View Article and Find Full Text PDFJ R Stat Soc Ser A Stat Soc
January 2025
Biostatistics, University of Michigan, 1415 Washington Heights, Michigan 48109, USA.
Model integration refers to the process of incorporating a fitted historical model into the estimation of a current study to increase statistical efficiency. Integration can be challenging when the current model includes new covariates, leading to potential model misspecification. We present and evaluate seven existing and novel model integration techniques, which employ both likelihood constraints and Bayesian informative priors.
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