Multimodal ct image synthesis using unsupervised deep generative adversarial networks for stroke lesion segmentation

HIGHLIGHTS

• who: Suzhe Wang and collaborators from the College of Information and Computer, Taiyuan University of Technology, Taiyuan, China have published the research work: Multimodal CT Image Synthesis Using Unsupervised Deep Generative Adversarial Networks for Stroke Lesion Segmentation, in the Journal: Electronics 2022, 2612 of /2022/
• what: The authors proposed a GAN-based data enhancement architecture for CT ischemic stroke lesion segmentation. The authors develop an image augmentation architecture that is capable of synthesizing CT images and automatic learning translation from CT to its perfusion domains. The authors compare the generation quality to assess the effectiveness . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.