| Predicting the future direction of cell movement with convolutional neural networks S Nishimoto, Y Tokuoka, TG Yamada, NF Hiroi, A Funahashi PloS one 14 (9), e0221245, 2019 | 6 | 2019 |
| Convolutional neural network-based instance segmentation algorithm to acquire quantitative criteria of early mouse development Y Tokuoka, TG Yamada, NF Hiroi, TJ Kobayashi, K Yamagata, ... BioRxiv, 324186, 2018 | 6 | 2018 |
| 3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis Y Tokuoka, TG Yamada, D Mashiko, Z Ikeda, NF Hiroi, TJ Kobayashi, ... NPJ systems biology and applications 6 (1), 1-12, 2020 | 2 | 2020 |
| An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation Y Tokuoka, S Suzuki, Y Sugawara Proceedings of the 2019 6th International Conference on Biomedical and …, 2019 | 1 | 2019 |
| Deep learning for non-invasive determination of the differentiation status of human neuronal cells by using phase-contrast photomicrographs M Ooka, Y Tokuoka, S Nishimoto, NF Hiroi, TG Yamada, A Funahashi Applied Sciences 9 (24), 5503, 2019 | 1 | 2019 |
| Direct Cell Counting Using Macro-Scale Smartphone Images of Cell Aggregates C Imashiro, Y Tokuoka, K Kikuhara, TG Yamada, K Takemura, ... IEEE Access 8, 170033-170043, 2020 | | 2020 |
