Adaptive filtering of optical coherent tomography fringe data with ensemble empirical mode decomposition

Gangjun Liu, Jun Zhang, Lingfeng Yu, Zhongping Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Empirical mode decomposition (EMD) is a new adaptive data analysis method in which the analyzed data is decomposed into a limited number of intrinsic mode functions (IMFs) through a sifting process. One problem with EMD is mode mixing, which has been solved by Wu et al using ensemble EMD (EEMD). In this paper, we applied the EEMD method to data acquired from optical coherence tomography (OCT) to improve the image quality. First, the original OCT fringe data is converted from linear wavelength to linear frequency through a calibration process. Second, the calibrated data is decomposed into different IMFs by EEMD. Third, the physical meaning of different IMFs was analyzed. Fourth, IMFs that represented noise were removed from the calibrated fringe data. The noise removed fringe data was then Fourier transformed to get depth information. EEMD was found to be able to separate different frequency noise into different IMFs. The signal to noise ratio of OCT image was improved by removing the IMFs that represent noise from the acquired fringe data.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7554
DOIs
StatePublished - 2010
Externally publishedYes
EventOptical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XIV - San Francisco, CA, United States
Duration: Jan 25 2010Jan 27 2010

Other

OtherOptical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XIV
CountryUnited States
CitySan Francisco, CA
Period1/25/101/27/10

Fingerprint

Optical Tomography
Adaptive filtering
Tomography
Noise
Optical Coherence Tomography
tomography
Decomposition
decomposition
Optical tomography
Signal-To-Noise Ratio
Calibration
Image quality
Signal to noise ratio
Wavelength
signal to noise ratios

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Liu, G., Zhang, J., Yu, L., & Chen, Z. (2010). Adaptive filtering of optical coherent tomography fringe data with ensemble empirical mode decomposition. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 7554). [75542U] https://doi.org/10.1117/12.841189

Adaptive filtering of optical coherent tomography fringe data with ensemble empirical mode decomposition. / Liu, Gangjun; Zhang, Jun; Yu, Lingfeng; Chen, Zhongping.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7554 2010. 75542U.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Liu, G, Zhang, J, Yu, L & Chen, Z 2010, Adaptive filtering of optical coherent tomography fringe data with ensemble empirical mode decomposition. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 7554, 75542U, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XIV, San Francisco, CA, United States, 1/25/10. https://doi.org/10.1117/12.841189
Liu G, Zhang J, Yu L, Chen Z. Adaptive filtering of optical coherent tomography fringe data with ensemble empirical mode decomposition. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7554. 2010. 75542U https://doi.org/10.1117/12.841189
Liu, Gangjun ; Zhang, Jun ; Yu, Lingfeng ; Chen, Zhongping. / Adaptive filtering of optical coherent tomography fringe data with ensemble empirical mode decomposition. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7554 2010.
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