Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Martin Bretzner

Martin Bretzner

Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels


Dec 13, 2021
Sungmin Hong, Anna K. Bonkhoff, Andrew Hoopes, Martin Bretzner, Markus D. Schirmer, Anne-Katrin Giese, Adrian V. Dalca, Polina Golland, Natalia S. Rost

Figure 1 for Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels
Figure 2 for Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels
Figure 3 for Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels
Figure 4 for Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images


Jul 20, 2021
Sungmin Hong, Razvan Marinescu, Adrian V. Dalca, Anna K. Bonkhoff, Martin Bretzner, Natalia S. Rost, Polina Golland

Figure 1 for 3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images
Figure 2 for 3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images
Figure 3 for 3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images
Figure 4 for 3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images
* 11 pages, 6 figures, 2 tables. Provisionally Accepted at DGM4MICCAI workshop in MICCAI 2021 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email