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Related Concept Videos

Downsampling01:20

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
Upsampling01:22

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...

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Speckle reduction in optical coherence tomography images using digital filtering.

Aydogan Ozcan1, Alberto Bilenca, Adrien E Desjardins

  • 1Harvard Medical School, Massachusetts General Hospital, Boston 02114, USA.

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|August 31, 2007
PubMed
Summary

Digital filters significantly reduce speckle noise in optical coherence tomography (OCT) images, improving image quality and preserving details. These methods enhance signal-to-noise ratio, potentially reducing the need for multiple imaging angles.

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Biomedical Optics

Background:

  • Speckle noise is a common artifact in optical coherence tomography (OCT) images.
  • This noise degrades image quality and hinders accurate interpretation.
  • Effective speckle reduction is crucial for advancing OCT applications.

Purpose of the Study:

  • To evaluate the performance of various digital filters for speckle reduction in OCT images.
  • To compare the efficacy of these filters against incoherent angular compounding.
  • To identify filters that preserve image features while reducing noise.

Main Methods:

  • Application of shift-invariant, nonorthogonal wavelet-transform-based filters.
  • Implementation of enhanced Lee and adaptive Wiener filters.
  • Comparison with speckle reduction achieved through incoherent angular compounding.

Main Results:

  • Wavelet-transform-based, enhanced Lee, and adaptive Wiener filters significantly reduced speckle noise.
  • These filters increased the signal-to-noise ratio in OCT images.
  • Strong edges and image details were preserved effectively.
  • The digital filters showed comparable or superior speckle reduction to incoherent angular compounding.

Conclusions:

  • Digital filters, particularly wavelet-transform-based, enhanced Lee, and adaptive Wiener filters, offer effective speckle reduction for OCT.
  • These filters improve image quality and preserve essential structural information.
  • Utilizing these filters may decrease the number of angles required for incoherent angular compounding, optimizing acquisition time.