Classification of Skin Cancer Using Novel Hyperspectral Imaging Engineering via YOLOv5
Abstract
:1. Introduction
2. Methods
2.1. Data Preprocessing
2.2. YOLOv5 Model
3. Results
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Skin Disease | Results of the RGB Model | ||||
---|---|---|---|---|---|
True | |||||
BCC | SCC | SK | Background FP | ||
Predicted | BCC | 133 | 7 | 8 | 45 |
SCC | 6 | 66 | 0 | 27 | |
SK | 6 | 1 | 102 | 54 | |
Background FN | 23 | 16 | 16 | ||
Skin Disease | Result of HSI Model | ||||
True | |||||
BCC | SCC | SK | Background FP | ||
Predicted | BCC | 102 | 4 | 19 | 74 |
SCC | 17 | 72 | 0 | 10 | |
SK | 6 | 0 | 100 | 55 | |
Background FN | 43 | 14 | 7 |
RGB Model | Precision | Recall | Specificity | F1-Score | Accuracy |
---|---|---|---|---|---|
All | 0.888 | 0.758 | 0.798 | 0.818 | 0.792 |
BCC | 0.899 | 0.747 | 0.791 | 0.816 | |
SCC | 0.812 | 0.722 | 0.833 | 0.764 | |
SK | 0.954 | 0.805 | 0.71 | 0.873 | |
HSI Model | Precision | Recall | Specificity | F1-score | Accuracy |
All | 0.8 | 0.726 | 0.786 | 0.761 | 0.787 |
BCC | 0.813 | 0.624 | 0.716 | 0.706 | |
SCC | 0.746 | 0.794 | 0.878 | 0.769 | |
SK | 0.841 | 0.76 | 0.764 | 0.798 |
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Huang, H.-Y.; Hsiao, Y.-P.; Mukundan, A.; Tsao, Y.-M.; Chang, W.-Y.; Wang, H.-C. Classification of Skin Cancer Using Novel Hyperspectral Imaging Engineering via YOLOv5. J. Clin. Med. 2023, 12, 1134. https://doi.org/10.3390/jcm12031134
Huang H-Y, Hsiao Y-P, Mukundan A, Tsao Y-M, Chang W-Y, Wang H-C. Classification of Skin Cancer Using Novel Hyperspectral Imaging Engineering via YOLOv5. Journal of Clinical Medicine. 2023; 12(3):1134. https://doi.org/10.3390/jcm12031134
Chicago/Turabian StyleHuang, Hung-Yi, Yu-Ping Hsiao, Arvind Mukundan, Yu-Ming Tsao, Wen-Yen Chang, and Hsiang-Chen Wang. 2023. "Classification of Skin Cancer Using Novel Hyperspectral Imaging Engineering via YOLOv5" Journal of Clinical Medicine 12, no. 3: 1134. https://doi.org/10.3390/jcm12031134