Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging

Jan-Hinrich Nölke, Tim Adler, Janek Gröhl, Thomas Kirchner, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Lena Maier-Hein. Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging. In Christoph Palm, Thomas M. Deserno, Heinz Handels, Andreas Maier 0001, Klaus H. Maier-Hein, Thomas Tolxdorff, editors, Bildverarbeitung für die Medizin 2021 - Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021. Informatik Aktuell, pages 330-335, Springer, 2021. [doi]

@inproceedings{NolkeAGKARKM21,
  title = {Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging},
  author = {Jan-Hinrich Nölke and Tim Adler and Janek Gröhl and Thomas Kirchner and Lynton Ardizzone and Carsten Rother and Ullrich Köthe and Lena Maier-Hein},
  year = {2021},
  doi = {10.1007/978-3-658-33198-6_80},
  url = {https://doi.org/10.1007/978-3-658-33198-6_80},
  researchr = {https://researchr.org/publication/NolkeAGKARKM21},
  cites = {0},
  citedby = {0},
  pages = {330-335},
  booktitle = {Bildverarbeitung für die Medizin 2021 - Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021},
  editor = {Christoph Palm and Thomas M. Deserno and Heinz Handels and Andreas Maier 0001 and Klaus H. Maier-Hein and Thomas Tolxdorff},
  series = {Informatik Aktuell},
  publisher = {Springer},
  isbn = {978-3-658-33198-6},
}