Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Data and Preprocessing
2.2. Model Architecture and Training
2.3. Evaluation of Synthetic Images
2.4. Latent Code Lesion Classification
3. Results
3.1. Latent Code Manipulation
3.2. Evaluation of Synthetic Images
3.3. Latent Code Lesion Classification
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A—Statistical Analysis
Appendix B—Classifier Parameters
References
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Rater | Accuracy Experiment | Times s (std) Experiment 1 | Accuracy Experiment 2 | Times s (std) Experiment 2 |
---|---|---|---|---|
1 | 0.65 | 8.05 (4.71) | 0.425 | 5.03 (2.9) |
2 | 0.625 | 14.34 (13.53) | 0.575 | 7.84 (5.84) |
3 | 0.575 | 7.62 (13.99) | 0.6 | 4.01 (3.67) |
4 | 0.6 | 9.86 (6.65) | 0.6 | 6.21 (4.5) |
5 | 0.725 | 72.3 (216.61) | 0.65 | 15.29 (9.48) |
Ensemble | 0.7 | - | 0.65 | - |
Classifier | All Data | Normal | ||||||
---|---|---|---|---|---|---|---|---|
ACC | SE | SP | AUC | ACC | SE | SP | AUC | |
Linear SVM | 0.95 (0.02) | 0.94 (0.04) | 0.97 (0.01) | 0.96 (0.02) | 0.97 (0.02) | 0.95 (0.03) | 0.99 (0.02) | 0.97 (0.02) |
Random Forest | 0.87 (0.04) | 0.93 (0.04) | 0.80 (0.06) | 0.86 (0.04) | 0.91 (0.04) | 0.92 (0.06) | 0.89 (0.04) | 0.90 (0.04) |
MLP | 0.95 (0.03) | 0.93 (0.05) | 0.98 (0.03) | 0.95 (0.02) | 0.96 (0.02) | 0.93 (0.04) | 0.99 (0.02) | 0.96 (0.02) |
Naive Bayes | 0.84 (0.05) | 0.92 (0.05) | 0.76 (0.09) | 0.84 (0.05) | 0.88 (0.04) | 0.91 (0.06) | 0.84 (0.06) | 0.88 (0.04) |
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Kleesiek, J.; Kersjes, B.; Ueltzhöffer, K.; Murray, J.M.; Rother, C.; Köthe, U.; Schlemmer, H.-P. Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions. Cancers 2021, 13, 3108. https://doi.org/10.3390/cancers13133108
Kleesiek J, Kersjes B, Ueltzhöffer K, Murray JM, Rother C, Köthe U, Schlemmer H-P. Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions. Cancers. 2021; 13(13):3108. https://doi.org/10.3390/cancers13133108
Chicago/Turabian StyleKleesiek, Jens, Benedikt Kersjes, Kai Ueltzhöffer, Jacob M. Murray, Carsten Rother, Ullrich Köthe, and Heinz-Peter Schlemmer. 2021. "Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions" Cancers 13, no. 13: 3108. https://doi.org/10.3390/cancers13133108