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  1. Home
  3. Vis-oct Explorer: An Open-source Software For Visible-light Optical Coherence Tomography Data Processing.
  1. Home
  3. Vis-oct Explorer: An Open-source Software For Visible-light Optical Coherence Tomography Data Processing.

Related Experiment Video

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy (oSLO) and Optical Coherence Tomography (OCT)
12:22

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy (oSLO) and Optical Coherence Tomography (OCT)

Published on: August 4, 2018

Vis-OCT Explorer: an open-source software for visible-light optical coherence tomography data processing.

Weijia Fan1, Fengyuanshan Xu1, Roman Kuranov1,2

  • 1Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.

Biomedical Optics Express
|May 11, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

We created Vis-OCT Explorer, open-source software for high-resolution visible-light OCT imaging. This tool ensures reliable quantitative measurements for retinal imaging, aiding clinical studies.

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Area of Science:

  • Ophthalmology
  • Biomedical Imaging
  • Software Engineering

Background:

  • Visible-light optical coherence tomography (vis-OCT) offers superior retinal imaging resolution.
  • Clinical application of vis-OCT is hindered by the need for advanced post-processing techniques.
  • High-quality, dependable vis-OCT imaging requires specialized reconstruction and analysis methods.

Purpose of the Study:

  • To develop and validate Vis-OCT Explorer, an open-source Python software package for vis-OCT image reconstruction and post-processing.
  • To enhance the quality and reliability of vis-OCT images through advanced processing techniques.
  • To support standardization and multicenter clinical studies using vis-OCT data.

Main Methods:

  • Developed Vis-OCT Explorer, a modular Python package incorporating standard OCT processing steps.
  • Implemented dual-spectrometer balanced detection and STFT-based dispersion compensation optimization.
  • Utilized GPU acceleration for enhanced processing speed and efficiency.
  • Evaluated reconstruction performance using an intensity-based tissue contrast index and assessed measurement repeatability via ICC analysis.

    • Main Results:

    • Balanced detection significantly improved vis-OCT image quality.
    • Vis-OCT Explorer demonstrated good repeatability for retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thickness measurements (ICC > 0.8).
    • High cross-user repeatability was confirmed for both macula- and optic nerve head-centered images.

    Conclusions:

    • Vis-OCT Explorer provides high-quality image reconstruction for reliable quantitative measurements in vis-OCT.
    • The software facilitates dependable quantitative analysis, crucial for clinical ophthalmology.
    • This validated tool supports future multicenter vis-OCT studies and data standardization efforts.