Breast Acoustic Parameter Reconstruction Method Based on Capacitive Micromachined Ultrasonic Transducer Array
Abstract
:1. Introduction
2. Model Creation
3. Algorithm Formulation
3.1. Sound Speed Inversion Algorithm
Algorithm 1 Sound Speed Inversion |
1. . |
2. For each source m,
|
3. using (6) and (7). |
4. for a prescribed threshold ε, stop. Otherwise, go to step 2. |
3.2. Attenuation Coefficient Inversion Algorithm
Algorithm 2 Attenuation Coefficient Inversion |
Input: projection data (amplitude attenuation) , angle , angle of the interval between sampling rays . |
1. . |
2. to generate and convolute the projection data to obtain . |
3. Loop the coordinate of each pixel to be reconstructed in the main cycle, and loop from 0 to 360° in a sub-cycle, representing different angles between the central ray and the axis. |
4. between the central ray and the line segment, connecting the point with the emission source, which corresponds to the central ray, calculated using the geometric relationship, and judge the positive and negative values corresponding to the central ray. |
5. by to obtain the sampling index at this angle. If it is a decimal, it means that the point is in the middle of two projection rays and that interpolation was performed. |
6. between the pixels and the emission source. |
7. Interpolate linearly, and accumulate the projection data after filtering. |
. |
8. End the sub-cycle and obtain the parameter value at that point through the cumulative sum. |
9. End the main cycle and obtain the parameter values of each point of the image through the cumulative sum. |
Output: Image of breast tissue attenuation coefficient. |
4. Experimental Results
4.1. Numerical Experiments
4.2. Breast Model Experiments
5. Summary and Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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ROI Number | Tissue Type | Size (mm) | Attenuation Coefficient (dB/MHz/cm) | Sound Speed (m/s) |
---|---|---|---|---|
1 | Fat | r = 40 | 0.2 | 1470 |
2 | Gland | r = 28 | 0.36 | 1480 |
3 | Tumor | a = 15, b = 7.5 | 0.48 | 1560 |
4 | Tumor | r = 3 | 0.48 | 1560 |
5 | Fibroma | r = 6 | 0.21 | 1540 |
6 | Cyst | r = 4.5 | 0.064 | 1510 |
7 | Calcification | r = 1 | 0.5 | 1506 |
ROI Number | Mean Value (m/s) | FBP | Expected Value (m/s) | Bias (%) |
---|---|---|---|---|
Time-Reversal | ||||
1 | 1467.31 | 1470 | 0.18 | |
1471.34 | 0.10 | |||
2 | 1483.18 | 1480 | 0.21 | |
1481.47 | 0.10 | |||
3 | 1555.56 | 1560 | 0.35 | |
1557.72 | 0.15 | |||
4 | 1555.49 | 1560 | 0.33 | |
1558.26 | 0.13 | |||
5 | 1544.57 | 1540 | 0.29 | |
1541.21 | 0.078 | |||
6 | 1505.12 | 1510 | 0.34 | |
1511.89 | 0.12 | |||
7 | 1501.36 | 1506 | 0.29 | |
1504.49 | 0.10 |
ROI Number | Mean Value (m/s) | Time-Reversal | Expected Value (m/s) | Bias (%) |
---|---|---|---|---|
FBP | ||||
1 | 0.226 | 0.2 | 0.13 | |
0.194 | 0.03 | |||
2 | 0.335 | 0.36 | 0.07 | |
0.353 | 0.02 | |||
3 | 0.456 | 0.48 | 0.05 | |
0.478 | 0.004 | |||
4 | 0.516 | 0.48 | 0.071 | |
0.481 | 0.002 | |||
5 | 0.236 | 0.21 | 0.12 | |
0.217 | 0.03 | |||
6 | 0.037 | 0.064 | 0.42 | |
0.062 | 0.03 | |||
7 | 0.39 | 0.5 | 0.22 | |
0.48 | 0.04 |
ROI | Mean Value (m/s) | FBP | Expected Value (m/s) | Bias (%) |
---|---|---|---|---|
Time-Reversal | ||||
Mass | 1474.5 | 1491 | 1.11 | |
1483.3 | 0.52 |
ROI | Mean Value (m/s) | Time-Reversal | Expected Value (m/s) | Bias (%) |
FBP | ||||
Mass | 0.081 | 0.094 | 13.83 | |
0.089 | 5.32 |
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Pei, Y.; Zhang, G.; Zhang, Y.; Zhang, W. Breast Acoustic Parameter Reconstruction Method Based on Capacitive Micromachined Ultrasonic Transducer Array. Micromachines 2021, 12, 963. https://doi.org/10.3390/mi12080963
Pei Y, Zhang G, Zhang Y, Zhang W. Breast Acoustic Parameter Reconstruction Method Based on Capacitive Micromachined Ultrasonic Transducer Array. Micromachines. 2021; 12(8):963. https://doi.org/10.3390/mi12080963
Chicago/Turabian StylePei, Yu, Guojun Zhang, Yu Zhang, and Wendong Zhang. 2021. "Breast Acoustic Parameter Reconstruction Method Based on Capacitive Micromachined Ultrasonic Transducer Array" Micromachines 12, no. 8: 963. https://doi.org/10.3390/mi12080963