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Recurrent Self Fusion: Iterative Denoising for Consistent Retinal OCT Segmentation.

Shuwen Wei1, Yihao Liu1, Zhangxing Bian1

  • 1Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.

Ophthalmic Medical Image Analysis : 10Th International Workshop, OMIA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. OMIA (Workshop) (10Th : 2023 : Vancouver, B.C. ; Online)
|February 6, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a recurrent self fusion (RSF) algorithm to standardize retinal layer thickness measurements from different optical coherence tomography (OCT) devices. The RSF algorithm improves segmentation consistency for better disease monitoring.

Keywords:
DenoiseOptical coherence tomographySegmentation

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Optical coherence tomography (OCT) is crucial for retinal imaging in ophthalmology.
  • Inconsistent retinal layer thickness measurements across different OCT devices hinder data comparison and longitudinal studies.
  • Standardization is needed for reliable OCT data analysis.

Purpose of the Study:

  • To introduce and validate a recurrent self fusion (RSF) algorithm for harmonizing OCT retinal layer thickness measurements.
  • To improve the consistency and reliability of OCT image analysis for disease detection and monitoring.
  • To address discrepancies in measurements between Spectralis and Cirrus OCT devices.

Main Methods:

  • Development of a recurrent self fusion (RSF) algorithm based on self fusion methodology.
  • Iterative denoising of retinal OCT images using the RSF algorithm.
  • Application of a deep learning-based segmentation algorithm for downstream analysis.
  • Validation using a large dataset of paired OCT scans from Spectralis and Cirrus devices.

Main Results:

  • The RSF algorithm effectively reduces speckle contrast in OCT images.
  • Enhanced consistency in retinal OCT segmentation was achieved.
  • The algorithm demonstrated improved data comparability across different OCT devices.
  • RSF algorithm shows potential for more accurate disease monitoring.

Conclusions:

  • The recurrent self fusion (RSF) algorithm offers a robust solution for standardizing OCT measurements.
  • This method enhances the reliability of retinal imaging analysis in ophthalmology.
  • RSF facilitates more accurate longitudinal monitoring of retinal and neurological diseases.