AAI_2025_Capstone_Chronicles_Combined
Born, J., Beymer, D., Rajan, D., Coy, A., Mukherjee, V. V., Manica, M., Prasanna, P., Ballah,
D., Guindy, M., Shaham, D., Shah, P. L., Karteris, E., Robertus, J. L., Gabrani, M., &
Rosen-Zvi, M. (2021). On the role of artificial intelligence in medical imaging of
COVID-19. Patterns , 2(6), 100269. https://doi.org/10.1016/j.patter.2021.100269
Che Azemin, M. Z., Mohd Tamrin, M. I., Hilmi, M. R., & Mohd Kamal, K. (2024). Assessing the
Efficacy of StyleGAN 3 in Generating Realistic Medical Images with Limited Data
Availability. In Proceedings of the 2024 13th International Conference on Software
and Computer Applications (pp. 192–197). ACM.
https://doi.org/10.1145/3651781.3651810
DCGAN tutorial — PyTorch tutorials 2.6.0+cu124 documentation. (2024, January 19).
PyTorch. https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html
Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C.,
Corrado, G., Thrun, S., & Dean, J. (2019). A guide to deep learning in healthcare.
Nature Medicine , 25(1), 24–29. https://doi.org/10.1038/s41591-018-0316-z
Fetty, L., Bylund, M., Kuess, P., Heilemann, G., Nyholm, T., Georg, D., & Löfstedt, T. (2020).
Latent space manipulation for high-resolution medical image synthesis via the
StyleGAN. Zeitschrift für Medizinische Physik , 30(4), 305–314.
https://doi.org/10.1016/j.zemedi.2020.05.001
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