Compresso: Efficient Compression of Segmentation Data for Connectomics

Brian Matejek, Daniel Haehn, Fritz Lekschas, Michael Mitzenmacher, Hanspeter Pfister. Compresso: Efficient Compression of Segmentation Data for Connectomics. In Maxime Descoteaux, Lena Maier-Hein, Alfred Franz, Pierre Jannin, D. Louis Collins, Simon Duchesne, editors, Medical Image Computing and Computer Assisted Intervention - MICCAI 2017 - 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part I. Volume 10433 of Lecture Notes in Computer Science, pages 781-788, Springer, 2017. [doi]

@inproceedings{MatejekHLMP17,
  title = {Compresso: Efficient Compression of Segmentation Data for Connectomics},
  author = {Brian Matejek and Daniel Haehn and Fritz Lekschas and Michael Mitzenmacher and Hanspeter Pfister},
  year = {2017},
  doi = {10.1007/978-3-319-66182-7_89},
  url = {https://doi.org/10.1007/978-3-319-66182-7_89},
  researchr = {https://researchr.org/publication/MatejekHLMP17},
  cites = {0},
  citedby = {0},
  pages = {781-788},
  booktitle = {Medical Image Computing and Computer Assisted Intervention - MICCAI 2017 - 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part I},
  editor = {Maxime Descoteaux and Lena Maier-Hein and Alfred Franz and Pierre Jannin and D. Louis Collins and Simon Duchesne},
  volume = {10433},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-66182-7},
}