Skeleton Segmentation on Bone Scintigraphy for BSI Computation
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Region Definition
2.3. Neural Network Architectures
2.4. Image Pre-Processing
2.5. Evaluations
3. Results
3.1. 10-Fold Cross-Validation
3.2. 10-Fold Cross-Validation with Data Augmentation
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
References
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Hyperparameters | Mask R-CNN | Double U-Net | DeeplabV3 Plus |
---|---|---|---|
Learning Rate | 0.005 | 0.0005 | 0.0005 |
Batch Size | 4 | 4 | 4 |
Epochs | 100 | 200 | 200 |
Category | Mask R-CNN | Double U-Net | DeeplabV3 Plus | |||
---|---|---|---|---|---|---|
Precision | Sensitivity | Precision | Sensitivity | Precision | Sensitivity | |
Skull | 97.22 | 94.43 | 96.05 | 96.13 | 95.34 | 95.91 |
Spine | 93.90 | 88.62 | 91.16 | 91.30 | 89.94 | 89.79 |
Chest | 95.33 | 93.58 | 94.83 | 94.52 | 93.61 | 93.87 |
AR_humerus | 91.82 | 84.80 | 89.65 | 90.18 | 87.42 | 87.88 |
AL_humerus | 92.46 | 85.30 | 89.76 | 90.12 | 87.94 | 89.02 |
PR_humerus | 91.72 | 84.41 | 88.68 | 89.55 | 85.77 | 87.25 |
PL_humerus | 89.94 | 82.01 | 87.89 | 88.78 | 87.50 | 83.64 |
Pelvis | 92.32 | 88.26 | 90.76 | 90.83 | 90.99 | 87.84 |
Femurs | 88.40 | 81.75 | 86.08 | 84.85 | 85.59 | 82.60 |
Kidney | 86.13 | 79.23 | 82.45 | 82.73 | 80.15 | 81.87 |
Average | 91.93 | 86.24 | 89.73 | 89.90 | 88.43 | 87.97 |
Average (w/o kidney) | 92.57 | 87.02 | 90.54 | 90.70 | 89.34 | 88.64 |
Category | Mask_R-CNN | Double U-Net | DeeplabV3 Plus | |||
---|---|---|---|---|---|---|
Precision | Sensitivity | Precision | Sensitivity | Precision | Sensitivity | |
Skull | 97.24 | 94.23 | 96.18 | 95.88 | 95.91 | 93.24 |
Spine | 93.20 | 88.61 | 91.15 | 90.68 | 90.56 | 87.76 |
Chest | 95.17 | 93.48 | 94.10 | 94.32 | 92.78 | 93.40 |
AR_humerus | 89.67 | 80.23 | 87.21 | 86.01 | 85.88 | 81.90 |
AL_humerus | 89.07 | 81.20 | 86.44 | 84.97 | 87.15 | 80.26 |
PR_humerus | 89.65 | 82.10 | 87.58 | 86.46 | 85.41 | 83.66 |
PL_humerus | 88.28 | 80.08 | 87.34 | 86.39 | 86.62 | 81.92 |
Pelvis | 92.22 | 88.27 | 90.86 | 90.24 | 91.34 | 87.54 |
Femurs | 89.95 | 81.39 | 87.05 | 84.83 | 88.06 | 81.71 |
Kidney | 87.21 | 80.71 | 84.37 | 83.74 | 83.91 | 77.59 |
Average | 91.17 | 85.03 | 89.23 | 88.35 | 88.76 | 84.90 |
Average (w/o Kidney) | 91.61 | 85.51 | 89.77 | 88.86 | 89.30 | 85.71 |
Database | Mask_R-CNN | Double U-Net | DeeplabV3 Plus | ||||||
---|---|---|---|---|---|---|---|---|---|
Pre. | Sen. | F1-Score | Pre. | Sen. | F1-Score | Pre. | Sen. | F1-Score | |
Prostate cancer | 92.57 | 87.02 | 89.71 | 90.54 | 90.70 | 90.62 | 89.34 | 88.64 | 88.99 |
Breast cancer | 91.61 | 85.51 | 88.45 | 89.77 | 88.86 | 89.31 | 89.30 | 85.71 | 87.47 |
Hyperparameters | Double U-Net |
---|---|
Learning Rate | 0.0005 |
Batch Size | 4 |
Epochs | 20 |
Fold Number | Prostate | Breast | ||
---|---|---|---|---|
Precision | Sensitivity | Precision | Sensitivity | |
1 | 86.67 | 96.05 | 83.95 | 94.84 |
2 | 87.01 | 94.92 | 86.18 | 95.26 |
3 | 91.22 | 91.33 | 81.14 | 96.05 |
4 | 93.01 | 91.37 | 81.87 | 96.32 |
5 | 85.69 | 94.85 | 84.35 | 96.18 |
6 | 94.18 | 89.28 | 96.23 | 76.73 |
7 | 96.10 | 86.81 | 95.64 | 85.26 |
8 | 93.43 | 88.31 | 95.37 | 84.49 |
9 | 92.99 | 87.74 | 95.57 | 85.51 |
10 | 93.89 | 88.12 | 94.97 | 89.19 |
Average | 91.42 | 90.88 | 89.53 | 89.98 |
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Yu, P.-N.; Lai, Y.-C.; Chen, Y.-Y.; Cheng, D.-C. Skeleton Segmentation on Bone Scintigraphy for BSI Computation. Diagnostics 2023, 13, 2302. https://doi.org/10.3390/diagnostics13132302
Yu P-N, Lai Y-C, Chen Y-Y, Cheng D-C. Skeleton Segmentation on Bone Scintigraphy for BSI Computation. Diagnostics. 2023; 13(13):2302. https://doi.org/10.3390/diagnostics13132302
Chicago/Turabian StyleYu, Po-Nien, Yung-Chi Lai, Yi-You Chen, and Da-Chuan Cheng. 2023. "Skeleton Segmentation on Bone Scintigraphy for BSI Computation" Diagnostics 13, no. 13: 2302. https://doi.org/10.3390/diagnostics13132302
APA StyleYu, P.-N., Lai, Y.-C., Chen, Y.-Y., & Cheng, D.-C. (2023). Skeleton Segmentation on Bone Scintigraphy for BSI Computation. Diagnostics, 13(13), 2302. https://doi.org/10.3390/diagnostics13132302