An intelligent speckle reduction algorithm for optical coherence tomography images

Saba Adabi, Silvia Conforto, Anne Clayton, Adrian G. Podoleanu, Ali Hojjat, Mohammad R.N. Avanaki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

33 Scopus citations

Abstract

Optical Coherence Tomography (OCT) offers three dimensional images of tissue microstructures. Although OCT imaging offers a promising high resolution method, due to the low coherent light source used in the configuration of OCT, OCT images suffers from an artefact called, speckle. Speckle deteriorates the image quality and effects image analysis algorithm such as segmentation and pattern recognition. We present a novel and intelligent speckle reduction algorithm to reduce speckle based on an ensemble framework of Multi-Layer Perceptron (MLP) neural networks. We tested the algorithm on images of retina obtained from a spectrometerbased Fourier-domain OCT system operating at 890 nm, and observed considerable improvement in the signal-to-noise ratio and contrast of the images.

Original languageEnglish
Title of host publicationPHOTOPTICS 2016 - Proceedings of the 4th International Conference on Photonics, Optics and Laser Technology
EditorsPaulo A. Ribeiro, Maria Raposo
PublisherSciTePress
Pages40-45
Number of pages6
ISBN (Electronic)9789897581748
DOIs
StatePublished - 2016
Externally publishedYes
Event4th International Conference on Photonics, Optics and Laser Technology, PHOTOPTICS 2016 - Rome, Italy
Duration: 27 Feb 201629 Feb 2016

Publication series

NamePHOTOPTICS 2016 - Proceedings of the 4th International Conference on Photonics, Optics and Laser Technology

Conference

Conference4th International Conference on Photonics, Optics and Laser Technology, PHOTOPTICS 2016
Country/TerritoryItaly
CityRome
Period27/02/1629/02/16

Keywords

  • Artificial Neural Network (ANN)
  • Multi-Layer Perceptron (MLP)
  • Optical Coherence Tomography
  • Speckle Noise Reduction

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