Cargando…
Phase-Resolved Optical Coherence Elastography: An Insight into Tissue Displacement Estimation
Robust methods to compute tissue displacements in optical coherence elastography (OCE) data are paramount, as they play a significant role in the accuracy of tissue elastic properties estimation. In this study, the accuracy of different phase estimators was evaluated on simulated OCE data, where the...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10142248/ https://www.ncbi.nlm.nih.gov/pubmed/37112314 http://dx.doi.org/10.3390/s23083974 |
Sumario: | Robust methods to compute tissue displacements in optical coherence elastography (OCE) data are paramount, as they play a significant role in the accuracy of tissue elastic properties estimation. In this study, the accuracy of different phase estimators was evaluated on simulated OCE data, where the displacements can be accurately set, and on real data. Displacement ([Formula: see text]) estimates were computed from (i) the original interferogram data [Formula: see text] and two phase-invariant mathematical manipulations of the interferogram: (ii) its first-order derivative ([Formula: see text]) and (iii) its integral ([Formula: see text]). We observed a dependence of the phase difference estimation accuracy on the initial depth location of the scatterer and the magnitude of the tissue displacement. However, by combining the three phase-difference estimates ([Formula: see text] , the error in phase difference estimation could be minimized. By using [Formula: see text] , the median root-mean-square error associated with displacement prediction in simulated OCE data was reduced by 85% and 70% in data with and without noise, respectively, in relation to the traditional estimate. Furthermore, a modest improvement in the minimum detectable displacement in real OCE data was also observed, particularly in data with low signal-to-noise ratios. The feasibility of using [Formula: see text] to estimate agarose phantoms’ Young’s modulus is illustrated. |
---|