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Phase-Resolved Optical Coherence Elastography: An Insight into Tissue Displacement Estimation.

Ana Batista1,2, Pedro Serranho1,3, Mário J Santos4

  • 1Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal.

Sensors (Basel, Switzerland)
|April 28, 2023
PubMed
Summary
This summary is machine-generated.

Accurate tissue displacement estimation in optical coherence elastography (OCE) is crucial. Combining multiple phase difference estimates (Δdav) significantly reduces displacement prediction errors in OCE data, improving elastic property accuracy.

Keywords:
Young’s modulusdisplacement estimationoptical coherence elastographyphase-resolved OCE

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Area of Science:

  • Biomedical Engineering
  • Optical Physics
  • Medical Imaging

Background:

  • Accurate estimation of tissue displacements is critical for reliable elastic properties determination in optical coherence elastography (OCE).
  • Existing phase estimation methods can be sensitive to scatterer depth and displacement magnitude, impacting accuracy.
  • Developing robust displacement estimation techniques is essential for advancing OCE applications.

Purpose of the Study:

  • To evaluate the accuracy of different phase estimators for computing tissue displacements in OCE data.
  • To investigate methods for minimizing phase difference estimation errors.
  • To assess the impact of improved displacement estimation on elastic property determination.

Main Methods:

  • Displacement estimates were computed from original interferogram data (Δφori) and its first-order derivative (Δφd) and integral (Δφint).
  • Accuracy was evaluated using simulated OCE data with known displacements and real OCE data.
  • A combined phase-difference estimate (Δdav) was developed by integrating the three methods.

Main Results:

  • Phase difference estimation accuracy depended on scatterer depth and displacement magnitude.
  • The combined estimate (Δdav) minimized phase difference errors.
  • Median root-mean-square error in displacement prediction was reduced by up to 85% in simulated data.
  • A modest improvement in minimum detectable displacement was observed in real OCE data, especially with low signal-to-noise ratios.

Conclusions:

  • Combining multiple phase difference estimates (Δdav) significantly enhances the accuracy of tissue displacement computation in OCE.
  • This improved method reduces prediction errors and shows potential for more accurate elastic property estimation, including Young's modulus.
  • The Δdav approach offers a more robust solution for OCE data analysis, particularly in challenging low signal-to-noise conditions.