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Updated: Feb 22, 2026

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
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Collaborative SDOCT Segmentation and Analysis Software.

Yeyi Yun1, Aaron Carass1, Andrew Lang1

  • 1Department of Electrical and Computer Engineering, The Johns Hopkins University.

Proceedings of Spie--The International Society for Optical Engineering
|September 19, 2017
PubMed
Summary
This summary is machine-generated.

A new graphical user interface (GUI) tool allows researchers to visualize, segment, and analyze spectral domain optical coherence tomography (SDOCT) images. This unified platform aids in managing ocular disease research and longitudinal studies across different scanners and protocols.

Keywords:
SDOCTgraphical user interfaceretinavisualization

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Spectral domain optical coherence tomography (SDOCT) is crucial for diagnosing and managing ocular diseases.
  • Quantitative SDOCT measurements are vital for tracking disease progression in research.
  • A lack of unified tools hinders analysis of SDOCT data from diverse scanners and protocols, especially in longitudinal studies.

Purpose of the Study:

  • To present a novel graphical user interface (GUI) for SDOCT image analysis.
  • To enable visualization, segmentation, and analysis of SDOCT data from multiple scanner types.
  • To facilitate data collation from collaborative research sites.

Main Methods:

  • Development of a user-friendly GUI for SDOCT image processing.
  • Implementation of a segmentation method for retinal surfaces.
  • Integration of a normative database for retinal layer thickness comparison.
  • Functionality for manual correction of segmented surfaces.
  • Data import/export capabilities to an SQL database.

Main Results:

  • The GUI successfully visualizes and analyzes SDOCT images from two common scanners.
  • Retinal layer thicknesses can be segmented and compared against a normative database.
  • The tool allows for correction of segmentation errors and data export to an SQL database for multi-site data collation.

Conclusions:

  • The developed GUI provides a unified solution for SDOCT image analysis in research.
  • This tool enhances the management of longitudinal studies involving diverse SDOCT data.
  • It facilitates standardized data analysis and collaboration across research institutions.