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

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

Pancreatic ductal adenocarcinoma (PDAC) presents a critical global health challenge, and early detection is crucial for improving the 5-year survival rate. Recent medical imaging and computational algorithm advances offer potential solutions for early diagnosis. Deep learning, particularly in the fo...

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Bibliographic Details
Main Authors: Yu Shi, Hannah Tang, Michael J. Baine, Michael A. Hollingsworth, Huijing Du, Dandan Zheng, Chi Zhang, Hongfeng Yu
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Cancers
Subjects:
pancreatic cancer
generative adversarial network
3D volume synthesis
clinical tumor
medical imaging
Online Access:https://www.mdpi.com/2072-6694/15/23/5496

Internet

https://www.mdpi.com/2072-6694/15/23/5496

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