Deep Learning Classifies Low- and High-Grade Glioma Patients with High Accuracy, Sensitivity, and Specificity Based on Their Brain White Matter Networks Derived from Diffusion Tensor Imaging
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Acquisition
2.2. Imaging Protocol
2.3. Data Processing
2.3.1. Diffusion Tensor Image Processing
2.3.2. Deep Neural Network Model to Classify LGG and HGG
2.3.3. Deep Neural Network Architecture for Connectivity Matrix as Images
2.3.4. Deep Neural Network Architecture Considering the Connectivity Matrix as a Matrix
3. Results
3.1. Performance of the DNN Model on Connectivity Matrix as Image
3.2. Performance of the DNN Model on the Connectivity Matrix as it is
3.3. GRAD-CAM Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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PREDICTED | |||
---|---|---|---|
ACTUAL | GROUP | LGG | HGG |
LGG | 54 | 1 | |
HGG | 1 | 54 |
Group | TP | TN | FP | FN | Precision | Recall | Specificity | F1-Score |
---|---|---|---|---|---|---|---|---|
LGG | 54 | 54 | 1 | 1 | 0.9818 | 0.9818 | 0.9818 | 0.9818 |
HGG | 54 | 54 | 1 | 1 | 0.9818 | 0.9818 | 0.9818 | 0.9818 |
PREDICTED | |||
---|---|---|---|
ACTUAL | GROUP | LGG | HGG |
LGG | 55 | 0 | |
HGG | 1 | 54 |
Group | TP | TN | FP | FN | Precision | Recall | Specificity | F1-score |
---|---|---|---|---|---|---|---|---|
LGG | 55 | 54 | 1 | 0 | 0.9821 | 1 | 0.9818 | 0.9909 |
HGG | 54 | 55 | 0 | 1 | 1 | 0.9818 | 1 | 0.9908 |
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Vidyadharan, S.; Prabhakar Rao, B.V.V.S.N.; Perumal, Y.; Chandrasekharan, K.; Rajagopalan, V. Deep Learning Classifies Low- and High-Grade Glioma Patients with High Accuracy, Sensitivity, and Specificity Based on Their Brain White Matter Networks Derived from Diffusion Tensor Imaging. Diagnostics 2022, 12, 3216. https://doi.org/10.3390/diagnostics12123216
Vidyadharan S, Prabhakar Rao BVVSN, Perumal Y, Chandrasekharan K, Rajagopalan V. Deep Learning Classifies Low- and High-Grade Glioma Patients with High Accuracy, Sensitivity, and Specificity Based on Their Brain White Matter Networks Derived from Diffusion Tensor Imaging. Diagnostics. 2022; 12(12):3216. https://doi.org/10.3390/diagnostics12123216
Chicago/Turabian StyleVidyadharan, Sreejith, Budhiraju Veera Venkata Satya Naga Prabhakar Rao, Yogeeswari Perumal, Kesavadas Chandrasekharan, and Venkateswaran Rajagopalan. 2022. "Deep Learning Classifies Low- and High-Grade Glioma Patients with High Accuracy, Sensitivity, and Specificity Based on Their Brain White Matter Networks Derived from Diffusion Tensor Imaging" Diagnostics 12, no. 12: 3216. https://doi.org/10.3390/diagnostics12123216