Temporal and Locational Values of Images Affecting the Deep Learning of Cancer Stem Cell Morphology
Abstract
:1. Introduction
2. Materials and Methods
2.1. Cell Culture
2.2. Microscopy
2.3. Image Processing and AI
2.4. Statistical Analysis
3. Results
3.1. Image Acquisition of Cultured CSC and Deep Learning
3.2. Versatility of Application of AI to Datasets Other Than the Training Dataset
3.3. CSC Object Recognized by Deep Learning
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
References
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Transfer-Learning Model | Class * | Precision | Recall | F-Measure |
---|---|---|---|---|
ResNet50 | 0 | 0.888 | 0.950 | 0.918 |
1 | 0.946 | 0.880 | 0.912 | |
VGG16 | 0 | 0.862 | 0.940 | 0.900 |
1 | 0.934 | 0.850 | 0.890 |
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Hanai, Y.; Ishihata, H.; Zhang, Z.; Maruyama, R.; Kasai, T.; Kameda, H.; Sugiyama, T. Temporal and Locational Values of Images Affecting the Deep Learning of Cancer Stem Cell Morphology. Biomedicines 2022, 10, 941. https://doi.org/10.3390/biomedicines10050941
Hanai Y, Ishihata H, Zhang Z, Maruyama R, Kasai T, Kameda H, Sugiyama T. Temporal and Locational Values of Images Affecting the Deep Learning of Cancer Stem Cell Morphology. Biomedicines. 2022; 10(5):941. https://doi.org/10.3390/biomedicines10050941
Chicago/Turabian StyleHanai, Yumi, Hiroaki Ishihata, Zaijun Zhang, Ryuto Maruyama, Tomonari Kasai, Hiroyuki Kameda, and Tomoyasu Sugiyama. 2022. "Temporal and Locational Values of Images Affecting the Deep Learning of Cancer Stem Cell Morphology" Biomedicines 10, no. 5: 941. https://doi.org/10.3390/biomedicines10050941