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Python Visual Field simulation. For latest development, please see zest-multi branch: https://github.com/constructor-s/PyVF/tree/zest-multi. Please contact us for any questions.

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PyVF

Python Visual Field simulation

work in progress

Purpose

The current goal is to create a robust framework for testing visual field testing strategies and implementation of popular known strategies. This can then facilitate development of new strategies.

During this process, visual field analysis functions will be integrated. The goal is that portion can be used separately for visual field analysis.

Currently there is no active plan to interface with commercial perimeters for real subject testing. See OPI - Open Perimetry Interface.

Usage

Requirements

See requirements.txt. Latest version of Python (3.8) installed using an Anaconda environment using packages from conda-forge channel is recommended.

Without installation

git clone https://github.com/constructor-s/PyVF.git
cd PyVF

With installation

git clone https://github.com/constructor-s/PyVF.git
cd PyVF
pip install . # or pip install git+https://github.com/constructor-s/PyVF.git

Simulation example

This performs a simulation of testing a range of true thresholds of a perfect responder, with a range of starting thresholds, using a 4-2 double staircase algorithm, on a single location.

python sim_ds_single_perfect.py

This performs a simulation of a set of visual fields (minimal example to be added)

python sim_field.py

Parsing example

Summarize Zeiss FORUM DICOM exports into CSV table:

python dcm_summarize.py --input path/to/data/*.dcm --output output.csv

Select References

  1. OPI - Open Perimetry Interface Turpin A, Artes PH, McKendrick AM. The Open Perimetry Interface: an enabling tool for clinical visual psychophysics. J Vis. 2012;12(11):22. Published 2012 Jan 1. doi:10.1167/12.11.22
  2. R visualFields package Marín-Franch I & Swanson WH. The visualFields package: A tool for analysis and visualization of visual fields. Journal of Vision, 2013, 13(4):10, 1-12
  3. Turpin, A., McKendrick, A. M., Johnson, C. A., & Vingrys, A. J. (2003). Properties of Perimetric Threshold Estimates from Full Threshold, ZEST, and SITA-like Strategies, as Determined by Computer Simulation. Investigative Ophthalmology and Visual Science, 44(11), 4787–4795. https://doi.org/10.1167/iovs.03-0023
  4. Heijl, A., Lindgren, G., & Olsson, J. (1987). Normal Variability of Static Perimetric Threshold Values Across the Central Visual Field. Archives of Ophthalmology, 105(11), 1544–1549. https://doi.org/10.1001/archopht.1987.01060110090039
  5. Hoehn, R., Häckel, S., Kucur, S., Iliev, M. E., Abegg, M., & Sznitman, R. (2019). Evaluation of Sequentially Optimized Reconstruction Strategy in visual field testing in normal subjects and glaucoma patients. Investigative Ophthalmology & Visual Science, 60(9), 2477.

Author

Bill Shi at Vision and Eye Movements Lab, University of Toronto

License

GNU GPLv3

About

Python Visual Field simulation. For latest development, please see zest-multi branch: https://github.com/constructor-s/PyVF/tree/zest-multi. Please contact us for any questions.

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