Comparison of PDE-based nonlinear diffusion approaches for image enhancement and denoising in optical coherence tomography

Harry M. Salinas, Delia Cabrera DeBuc

Research output: Contribution to journalArticle

134 Citations (Scopus)

Abstract

A comparison between two nonlinear diffusion methods for denoising OCT images is performed. Specifically, we compare and contrast the performance of the traditional nonlinear Perona-Malik filter with a complex diffusion filter that has been recently introduced by Gilboa et al., The complex diffusion approach based on the generalization of the nonlinear scale space to the complex domain by combining the diffusion and the free Schrödinger equation is evaluated on synthetic images and also on representative OCT images at various noise levels. The performance improvement over the traditional nonlinear Perona-Malik filter is quantified in terms of noise suppression, image structural preservation and visual quality. An average signal-to-noise ratio (SNR) improvement of about 2.5 times and an average contrast to noise ratio (CNR) improvement of 49% was obtained while mean structure similarity (MSSIM) was practically not degraded after denoising. The nonlinear complex diffusion filtering can be applied with success to many OCT imaging applications. In summary, the numerical values of the image quality metrics along with the qualitative analysis results indicated the good feature preservation performance of the complex diffusion process, as desired for better diagnosis in medical imaging processing.

Original languageEnglish (US)
Pages (from-to)761-771
Number of pages11
JournalIEEE Transactions on Medical Imaging
Volume26
Issue number6
DOIs
StatePublished - Jun 2007

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Image Enhancement
Image denoising
Image enhancement
Optical tomography
Optical Coherence Tomography
Noise
Medical imaging
Signal-To-Noise Ratio
Diagnostic Imaging
Image quality
Signal to noise ratio
Imaging techniques
Processing

Keywords

  • Complex diffusion filter
  • Image enhancement
  • Optical coherence tomography
  • Segmentation
  • Speckle noise

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

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title = "Comparison of PDE-based nonlinear diffusion approaches for image enhancement and denoising in optical coherence tomography",
abstract = "A comparison between two nonlinear diffusion methods for denoising OCT images is performed. Specifically, we compare and contrast the performance of the traditional nonlinear Perona-Malik filter with a complex diffusion filter that has been recently introduced by Gilboa et al., The complex diffusion approach based on the generalization of the nonlinear scale space to the complex domain by combining the diffusion and the free Schr{\"o}dinger equation is evaluated on synthetic images and also on representative OCT images at various noise levels. The performance improvement over the traditional nonlinear Perona-Malik filter is quantified in terms of noise suppression, image structural preservation and visual quality. An average signal-to-noise ratio (SNR) improvement of about 2.5 times and an average contrast to noise ratio (CNR) improvement of 49{\%} was obtained while mean structure similarity (MSSIM) was practically not degraded after denoising. The nonlinear complex diffusion filtering can be applied with success to many OCT imaging applications. In summary, the numerical values of the image quality metrics along with the qualitative analysis results indicated the good feature preservation performance of the complex diffusion process, as desired for better diagnosis in medical imaging processing.",
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