Speckle reduction in optical coherence tomography by matrix completion using bilateral random projection

Jun Cheng, Lixin Duan, Damon Wing Kee Wong, Masahiro Akiba, Jiang Liu

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

11 Citations (Scopus)

Abstract

Speckle noise is problematic in optical coherence tomography (OCT) and often obscures the structure details. In this paper, we propose a new method to reduce speckle noise from multiply scanned OCT slices. The proposed method registers the OCT scans using a global alignment followed by a local alignment based on global and local motion estimation. Then low rank matrix completion using bilateral random projection is utilized to estimate the noise and recover the clean image. Experimental results show that the proposed method archives average contrast to noise ratio 14.90, better than 13.78 by the state-of-the-art method used in current OCT machines. The technology can be embedded into current OCT machines to enhance the image quality.

Original languageEnglish
Title of host publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages186-189
Number of pages4
ISBN (Electronic)9781424479290
DOIs
Publication statusPublished - 2 Nov 2014
Externally publishedYes
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: 26 Aug 201430 Aug 2014

Publication series

Name2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Conference

Conference2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Country/TerritoryUnited States
CityChicago
Period26/08/1430/08/14

Keywords

  • Speckle noise
  • bilateral random projection
  • low rank
  • matrix completion

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Biomedical Engineering
  • General Medicine

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