Order Article Reprints

Shi Y, Tang H, Baine MJ, Hollingsworth MA, Du H, Zheng D, Zhang C, Yu H. 3DGAUnet: 3D Generative Adversarial Networks with a 3D U-Net Based Generator to Achieve the Accurate and Effective Synthesis of Clinical Tumor Image Data for Pancreatic Cancer. Cancers. 2023; 15(23):5496. https://doi.org/10.3390/cancers15235496

Shi, Yu, Hannah Tang, Michael J. Baine, Michael A. Hollingsworth, Huijing Du, Dandan Zheng, Chi Zhang, and Hongfeng Yu. 2023. "3DGAUnet: 3D Generative Adversarial Networks with a 3D U-Net Based Generator to Achieve the Accurate and Effective Synthesis of Clinical Tumor Image Data for Pancreatic Cancer" Cancers 15, no. 23: 5496. https://doi.org/10.3390/cancers15235496

Shi, Y., Tang, H., Baine, M. J., Hollingsworth, M. A., Du, H., Zheng, D., Zhang, C., & Yu, H. (2023). 3DGAUnet: 3D Generative Adversarial Networks with a 3D U-Net Based Generator to Achieve the Accurate and Effective Synthesis of Clinical Tumor Image Data for Pancreatic Cancer. Cancers, 15(23), 5496. https://doi.org/10.3390/cancers15235496