Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Acquisition
2.2. Image Reconstruction
2.3. Denoising Convolutional Neural Network (DCNN)
2.4. Quantitative Evaluation
2.5. Qualitative Evaluation by Expert Body Radiologist
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Score | Overall Image Quality | Rectum Margin and Rectal Wall Layers Demarcation | Noise Suppression | Image Sharpness |
---|---|---|---|---|
1 | Nondiagnostic/poor | No visualization or inability to trace structures clearly | Significant noise that hampers diagnostic capability of readers | Nondiagnostic, blurred, hampering diagnostic capability |
2 | Fair | Fair demarcation | Substantial noise with significant image quality degradation | Substantially blurred, not hampering diagnostic capability but low image quality |
3 | Good | Nearly complete and clear demarcation | Moderate noise | Mild blur with mild image quality degradation |
4 | Excellent | Complete and clear demarcation | Minimal noise without image quality degradation | Minimal or no blur |
Loss Function | PSNR Denoised | PSNR Noisy | SSIM Denoised | SSIM Noisy |
---|---|---|---|---|
L1 | 84.13 ± 4.6 | 80.29 ± 5.1 | 0.89 ± 0.03 | 0.85 ± 0.1 |
L2 | 82.63 ± 5.2 | 0.90 ± 0.07 | ||
Joint L1–L2 | 84.33 ± 5.1 | 0.94 ± 0.03 |
Image Quality | Rectum Margin and Rectal Wall Layers Demarcation | Noise Suppression | Image Sharpness | |
---|---|---|---|---|
Reader 1 | ||||
Noisy, NEX = 1 | 2 ± 1 | 2 ± 1 | 2 ± 1 | 2.5 ± 0.5 |
Noisy, NEX = 2 | 2 ± 0.5 | 2 ± 0.5 | 2 ± 1 | 3 ± 0.5 |
Noisy, NEX = 4 | 2 ± 0.5 | 2 ± 0.5 | 2 ± 0.5 | 2 ± 0.5 |
Denoised NEX = 1 | 2.5 ± 0.6 | 2 ± 0.6 | 3 ± 1 | 2.5 ± 0.5 |
Denoised NEX = 2 | 2.5 ± 0.6 | 2 ± 0.1 | 3.5 ± 1 | 3 ± 0.5 |
Denoised NEX = 4 | 3 ± 0.6 | 3 ± 0.5 | 4 ± 0.5 | 3 ± 1 |
Target | 3 ± 1 | 3 ± 1 | 3 ± 0.8 | 3 ± 1 |
Reader 2 | ||||
Noisy, NEX = 1 | 2 ± 0.6 | 2 ± 0.7 | 2 ± 1 | 2 ± 0.5 |
Noisy, NEX = 2 | 2 ± 0.5 | 2 ± 0.5 | 2.5 ± 0.5 | 2 ± 0.5 |
Noisy, NEX = 4 | 2 ± 0.5 | 2 ± 0.5 | 2.5 ± 0.5 | 2 ± 0.5 |
Denoised NEX = 1 | 2 ± 0.5 | 2 ± 0.5 | 3 ± 1 | 3 ± 0.5 |
Denoised NEX = 2 | 3 ± 0.5 | 3 ± 0.5 | 4 ± 0.5 | 3 ± 0 |
Denoised NEX = 4 | 3 ± 0.5 | 3 ± 0.5 | 4 ± 0.5 | 3 ± 0.5 |
Target | 2 ± 0.5 | 2 ± 0.5 | 3 ± 0.5 | 2.5 ± 0.5 |
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Mohammadi, M.; Kaye, E.A.; Alus, O.; Kee, Y.; Golia Pernicka, J.S.; El Homsi, M.; Petkovska, I.; Otazo, R. Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network. Bioengineering 2023, 10, 359. https://doi.org/10.3390/bioengineering10030359
Mohammadi M, Kaye EA, Alus O, Kee Y, Golia Pernicka JS, El Homsi M, Petkovska I, Otazo R. Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network. Bioengineering. 2023; 10(3):359. https://doi.org/10.3390/bioengineering10030359
Chicago/Turabian StyleMohammadi, Mohaddese, Elena A. Kaye, Or Alus, Youngwook Kee, Jennifer S. Golia Pernicka, Maria El Homsi, Iva Petkovska, and Ricardo Otazo. 2023. "Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network" Bioengineering 10, no. 3: 359. https://doi.org/10.3390/bioengineering10030359
APA StyleMohammadi, M., Kaye, E. A., Alus, O., Kee, Y., Golia Pernicka, J. S., El Homsi, M., Petkovska, I., & Otazo, R. (2023). Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network. Bioengineering, 10(3), 359. https://doi.org/10.3390/bioengineering10030359