使CT.

Keisuke Usui1,2, Sae Kamiyama3, Akihiro Arita3

  • 1Department of Radiological Technology, Faculty of Health Science, Juntendo University, 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan. k-usui@juntendo.ac.jp.

Scientific reports
|February 16, 2024
PubMed
概括

条件生成对抗网络 (CGAN) 通过减少工件来提高稀疏视图计算机断层扫描 (CT) 图像质量. 与自动编码器和U-Net模型相比,这种方法提供了更好的CT值恢复和图像相似性.