An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net)
Abstract
:1. Introduction
2. Related Work
3. Materials and Methods
3.1. Study Subjects and Data Acquisition
3.2. Pre-Processing
3.3. Architecture of ICPIU-Net
3.3.1. Anatomical Network
3.3.2. Pathological Network
3D U-Net Architecture
Network Implementation
Shape Reconstruction
Class Constraint
3.4. Post-Processing
4. Results and Discussion
4.1. Evaluation Metrics
4.2. Results Analysis and Extensive Discussions
5. Conclusions
6. Code Availability
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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EMIDEC Dataset (n = 150) | Healthy Cases | Pathological Cases | |
---|---|---|---|
Infarcted Cases | Infarcted + MVO (a Subclass of MI) Cases | ||
Training dataset (n = 100) | 33 | 27 | 40 |
Testing dataset (n = 50) | 17 | 22 | 11 |
Targets | Metrics | 5-Fold Cross-Validation | ||||||
---|---|---|---|---|---|---|---|---|
Fold 0 | Fold 1 | Fold 2 | Fold 3 | Fold 4 | Average | Standard Deviation | ||
Myocardium | DSC (%) | 95.38 | 95.07 | 95.21 | 95.35 | 95.59 | 95.32 | 0.17 |
AVD (mm) | 232.74 | 290.61 | 225.42 | 229.14 | 203.49 | 236.28 | 29.01 | |
HD (mm) | 4.02 | 4.78 | 3.87 | 3.61 | 3.46 | 3.95 | 0.44 | |
MI | DSC (%) | 77.05 | 79.45 | 78.73 | 78.92 | 77.34 | 78.30 | 0.75 |
AVD (mm) | 283.31 | 267.26 | 190.34 | 156.53 | 271.25 | 233.74 | 50.65 | |
AVDR (%) | 4.01 | 4.20 | 3.18 | 2.03 | 4.53 | 3.39 | 0.77 | |
MVO | DSC (%) | 76.54 | 79.15 | 79.92 | 75.51 | 78.03 | 77.83 | 1.62 |
AVD (mm) | 34.18 | 26.80 | 45.10 | 49.19 | 46.68 | 40.39 | 8.51 | |
AVDR (%) | 0.62 | 0.61 | 0.69 | 0.74 | 0.76 | 0.68 | 0.10 |
Targets | Metrics | Methods | ||
---|---|---|---|---|
Huellebrand et al. [44] | Zhang [47] | Proposed (ICPIU-Net) | ||
Myocardium | DSC (%) | 81.00 | 94.40 | 95.32 |
AVD (mm) | 13655.55 | 6474.38 | 236.28 | |
HD (mm) | 16.72 | 17.21 | 3.95 | |
MI | DSC (%) | 36.08 | 72.08 | 78.30 |
AVD (mm) | 8980.5 | 4179.5 | 233.74 | |
AVDR (%) | 7.07 | 3.41 | 3.39 | |
MVO | DSC (%) | 54.15 | 71.01 | 77.83 |
AVD (mm) | 1501.73 | 918.69 | 40.39 | |
AVDR (%) | 1.08 | 0.69 | 0.68 |
Methods | Structures | ||||||||
---|---|---|---|---|---|---|---|---|---|
Myocardium | MI | MVO | |||||||
DSC (%) | AVD (mm) | HD (mm) | DSC (%) | AVD (mm) | AVDR (%) | DSC (%) | AVD (mm) | AVDR (%) | |
Feng et al. [42] | 83.56 | 15,187.48 | 33.77 | 54.68 | 3970.73 | 2.89 | 72.22 | 883.42 | 0.53 |
Huellebrand et al. [44] | 84.08 | 10,874.47 | 18.3 | 37.87 | 6166.01 | 4.93 | 52.25 | 953.47 | 0.64 |
Yang et al. [46] | 85.53 | 16,539.52 | 13.23 | 62.79 | 5343.69 | 4.37 | 60.99 | 1851.52 | 1.69 |
Zhang [47] | 87.86 | 9258.24 | 13.01 | 71.24 | 3117.88 | 2.38 | 78.51 | 634.69 | 0.38 |
Camarasa et al. [41] | 75.74 | 17,108.13 | 25.44 | 30.79 | 4868.56 | 3.64 | 60.52 | 867.86 | 0.52 |
Zhou et al. [48] | 82.46 | 13,292.68 | 83.42 | 37.77 | 6104.99 | 4.71 | 51.98 | 879.99 | 0.54 |
Girum et al. [43] | 80.26 | 11,807.68 | 51.48 | 34.00 | 11,521.71 | 8.58 | 78.00 | 891.13 | 0.51 |
Proposed (ICPIU-Net) | 87.65 | 8863.41 | 13.10 | 73.36 | 2693.84 | 1.95 | 81.31 | 511.25 | 0.32 |
Methods | Structures | ||||||||
---|---|---|---|---|---|---|---|---|---|
Myocardium | MI | MVO | |||||||
DSC (%) | AVD (mm) | HD (mm) | DSC (%) | AVD (mm) | AVDR (%) | DSC (%) | AVD (mm) | AVDR (%) | |
Without IC and CC | 87.77 | 9381.77 | 13.07 | 65.05 | 3096.54 | 2.39 | 78.82 | 553.56 | 0.34 |
Without CC | 87.74 | 9201.04 | 13.09 | 71.71 | 2830.32 | 2.15 | 80.99 | 538.60 | 0.34 |
Proposed (ICPIU-Net) | 87.65 | 8863.41 | 13.10 | 73.36 | 2693.84 | 1.95 | 81.31 | 511.25 | 0.32 |
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Brahim, K.; Arega, T.W.; Boucher, A.; Bricq, S.; Sakly, A.; Meriaudeau, F. An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net). Sensors 2022, 22, 2084. https://doi.org/10.3390/s22062084
Brahim K, Arega TW, Boucher A, Bricq S, Sakly A, Meriaudeau F. An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net). Sensors. 2022; 22(6):2084. https://doi.org/10.3390/s22062084
Chicago/Turabian StyleBrahim, Khawla, Tewodros Weldebirhan Arega, Arnaud Boucher, Stephanie Bricq, Anis Sakly, and Fabrice Meriaudeau. 2022. "An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net)" Sensors 22, no. 6: 2084. https://doi.org/10.3390/s22062084