# Image Quality Assessment for Digital Volume Correlation-Based Optical Coherence Elastography

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## Abstract

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## 1. Introduction

^{®}(LaVision, Ypsilanti, MI, USA) software-based OCE. Speckle tracking-based OCE shows a great application prospect in biological tissue elastic imaging, such as skin, blood vessels, cornea, etc. [11,12,13]. However, the analysis and evaluation of the measurement accuracy are lacking. Applying the correlation algorithms directly without considering the quality of the OCT images during deformation may induce serious artifacts to the results.

## 2. Materials and Methods

#### 2.1. DVC-Based OCE

#### 2.2. Quality Assessment of 3D OCT Images for DVC Calculation

#### 2.2.1. Mean Attenuation Intensity (MAI)

#### 2.2.2. Breadth and Dispersion of the Gray Level Distribution

#### 2.2.3. Image Evaluation Index Based on OCT-DVC

#### 2.3. Mean Bias Error

## 3. Results

#### 3.1. Verification Experiment of Reference Arm Adjustment

#### 3.2. Verification Experiment of Phantoms with Different Scatterers

_{2}, Shanghai Macklin Biochemical Co., Ltd., Shanghai, China) were imaged. The preparation process of the silica gel sample is briefly as follows, type AB liquid silica gel is mixed in a ratio of 1:1 and TiO

_{2}particles are added as a scattering agent. After being fully stirred, the mixture is poured into a Petri dish. Air bubbles are removed in a vacuum chamber. Four types of phantoms were made with TiO

_{2}particles. Scatterer parameters and OCT images with the histograms of the phantoms are shown in Figure 9. It shows the phantom without particles had the lowest FWHM and the largest peak. The content decrease for particles of the same size will reduce FWHM, and the corresponding peak will increase. This means that the sharper gray level distribution may have less useful information. Larger-sized particles increase FWHM and peak.

#### 3.3. The Criteria Evaluation in Deformation Measurement of Pork Sample

_{zz}field along the z direction are shown in Figure 11c,e. The mean bias errors of the displacements and strain of 81 points in different parts along the z direction are plotted in Figure 11d,f. The mean bias errors increase when it drops to about 4 at part IV. CMGG of Part Ⅵ is the lowest, and the mean bias errors of this part are the largest.

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 1.**Schematic diagram of OCE system. FS, fiber splitter. FC, fiber coupler. BPD, balanced photodetector. L, lens. C, circulator.

**Figure 2.**Features of 3D OCT image: (

**a**) the 3D image reconstructed by the OCE system; (

**b**) the gray level distribution at the positions of 100, 200 and 300 voxels in the axial depth; (

**c**) A-Scan image in a cross-section; (

**d**) the gray level distribution at the horizontal depth of 150, 300 and 450 voxels; (

**e**) A-Scan image on an axial section.

**Figure 3.**Diagram of finding the displacement by matching the 3D images before and after deformation by DVC.

**Figure 4.**The principle of the value range of MAI: ${\mathit{f}}_{\mathit{a}}\mathbf{\left(}\mathit{x}\mathbf{,}\mathit{y}\mathbf{,}\mathit{z}\mathbf{\right)}$ is the schematic diagram of maximum OCT signal attenuation, ${\mathit{f}}_{\mathit{b}}\mathbf{\left(}\mathit{x}\mathbf{,}\mathit{y}\mathbf{,}\mathit{z}\mathbf{\right)}$ is the schematic diagram of minimum OCT signal attenuation.

**Figure 5.**The principle of GDB: ${\mathit{f}}_{\mathit{a}}\mathbf{\left(}\mathit{x}\mathbf{,}\mathit{y}\mathbf{,}\mathit{z}\mathbf{\right)},{\mathit{f}}_{\mathit{b}}\mathbf{\left(}\mathit{x}\mathbf{,}\mathit{y}\mathbf{,}\mathit{z}\mathbf{\right)}\mathrm{and}{\mathit{f}}_{\mathit{c}}\mathbf{\left(}\mathit{x}\mathbf{,}\mathit{y}\mathbf{,}\mathit{z}\mathbf{\right)}$ are the schematic diagram corresponding to ${\mathit{\delta}}_{\mathit{GDB}}$ 20, 16, 11.31.

**Figure 6.**The principle of GDD: ${\mathit{f}}_{\mathit{a}}\mathbf{\left(}\mathit{x}\mathbf{,}\mathit{y}\mathbf{,}\mathit{z}\mathbf{\right)},{\mathit{f}}_{\mathit{b}}\mathbf{\left(}\mathit{x}\mathbf{,}\mathit{y}\mathbf{,}\mathit{z}\mathbf{\right)}\mathrm{and}{\mathit{f}}_{\mathit{c}}\mathbf{\left(}\mathit{x}\mathbf{,}\mathit{y}\mathbf{,}\mathit{z}\mathbf{\right)}$ are the schematic diagram corresponding to ${\mathit{\delta}}_{\mathit{GDD}}$ 127.50, 75.00, 37.44.

**Figure 7.**OCT images (

**A**–

**D**) with different reference arm light intensities (95.71 μW, 41.33 μW, 13.01 μW, 2.91 μW) and the corresponding histograms.

**Figure 8.**The influence of different reference arm laser intensities based on CMGG. (

**a**) Mean bias errors of imposed displacement in X direction. (

**b**) Mean bias errors of imposed displacement in depth direction. (

**c**) Evaluation index of OCT image under different reference arm laser intensities.

**Figure 9.**Three-dimensional OCT images of silica gel phantoms with different sizes and mass fractions of scatterers and their corresponding histograms of phantoms. S1: 1 μm(0.5%), S2: 20 nm(0.5%), S3: 20 nm(0.05%), S4: No scatterer.

**Figure 10.**The verification result is based on CMGG. (

**a**) Mean bias errors of imposed displacement in X direction. (

**b**) Mean bias errors of imposed displacement in depth direction. (

**c**) Evaluation index of OCT image with different contents of scatterers.

**Figure 11.**The criteria evaluation in deformation measurement. (

**a**) Three-dimensional OCT image of a piece of pork. (

**b**) CMGG in different areas. (

**c**) The displacement w field along the z direction. (

**d**) The mean bias errors of the displacements of 81 points in different parts along the z direction. (

**e**) the strain ε

_{zz}field along the z direction. (

**f**) The mean bias errors of the strains of 81 points in different parts along the z direction.

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**MDPI and ACS Style**

Lin, X.; Chen, J.; Hu, Y.; Feng, X.; Wang, H.; Liu, H.; Sun, C. Image Quality Assessment for Digital Volume Correlation-Based Optical Coherence Elastography. *Photonics* **2022**, *9*, 573.
https://doi.org/10.3390/photonics9080573

**AMA Style**

Lin X, Chen J, Hu Y, Feng X, Wang H, Liu H, Sun C. Image Quality Assessment for Digital Volume Correlation-Based Optical Coherence Elastography. *Photonics*. 2022; 9(8):573.
https://doi.org/10.3390/photonics9080573

**Chicago/Turabian Style**

Lin, Xianglong, Jinlong Chen, Yongzheng Hu, Xiaowei Feng, Haosen Wang, Haofei Liu, and Cuiru Sun. 2022. "Image Quality Assessment for Digital Volume Correlation-Based Optical Coherence Elastography" *Photonics* 9, no. 8: 573.
https://doi.org/10.3390/photonics9080573