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DPSF: a Novel Dual-Parametric Sigmoid Function for Optical Coherence Tomography Image Enhancement.

I P Okuwobi1, Z Ding2, J Wan2

  • 1School of Artificial Intelligence, Guilin University of Electronic Technology, #1 Jinji Road, Guilin, 541004, China. paulokuwobi@guet.edu.cn.

Medical & Biological Engineering & Computing
|March 2, 2022
PubMed
Summary

A new dual-parametric sigmoid function (DPSF) framework enhances optical coherence tomography (OCT) images by reducing speckle noise. This improves image contrast and clarity for better clinical interpretation and disease monitoring.

Keywords:
AnalysisImage enhancementImage processingOptical coherence tomographyRetinal diseasesSigmoid function

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Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Computer Vision

Background:

  • Speckle noise in optical coherence tomography (OCT) images significantly reduces contrast, obscuring boundaries of highly scattering structures.
  • This limitation hinders clinical applications, impeding disease monitoring, treatment assessment, and decision-making.
  • Existing methods struggle to effectively address speckle noise while preserving crucial image details.

Purpose of the Study:

  • To develop a fast and robust OCT image enhancement framework to overcome speckle noise limitations.
  • To improve the interpretability and perception of OCT images for clinical use.
  • To provide quantitative and qualitative information for clinicians and computer vision algorithms.

Main Methods:

  • A non-linear statistical parametric technique is employed, modeling OCT images using Gaussian distribution.
  • A novel dual-parametric sigmoid function (DPSF) is introduced to control image dynamic range and contrast.
  • Linear and non-linear normalization, followed by a mapping operation, are performed to achieve image enhancement.

Main Results:

  • The DPSF framework demonstrated superior performance across three OCT vendors (Cirrus, Spectralis, Topcon) compared to state-of-the-art methods.
  • High performance metrics including EME, PSNR, SSIM, and ρ were achieved, with low MSE values.
  • Quantitative results showed significant improvements in image quality, indicating enhanced interpretability.

Conclusions:

  • The proposed DPSF framework effectively reduces speckle noise and enhances OCT image quality.
  • The enhanced images provide improved interpretability and perception, benefiting clinical assessment and computer vision analysis.
  • This method offers a valuable tool for advancing the clinical utility of OCT imaging.