CITATION.cff

cff-version: 1.2.0
message: If you use this software, please cite both the software and the paper (see preferred-citation).
authors:
  - family-names: Ankenbrand
    given-names: "Markus J"
    orcid: 0000-0002-6620-807X
    affiliation: "Chair for Cellular and Molecular Imaging, Comprehensive Heart Failure Center, University Hospital Würzburg, Germany"
    email: markus.ankenbrand@uni-wuerzburg.de
  - family-names: Shainberg
    given-names: Liliia
    affiliation: "Chair for Cellular and Molecular Imaging, Comprehensive Heart Failure Center, University Hospital Würzburg, Germany"
  - family-names: Hock
    given-names: Michael
    affiliation: "Chair for Cellular and Molecular Imaging, Comprehensive Heart Failure Center, University Hospital Würzburg, Germany"
  - family-names: Lohr
    given-names: David
    orcid: 0000-0002-6509-3776
    affiliation: "Chair for Cellular and Molecular Imaging, Comprehensive Heart Failure Center, University Hospital Würzburg, Germany"
  - family-names: Schreiber
    given-names: "Laura M"
    orcid: 0000-0002-8827-1838
    affiliation: "Chair for Cellular and Molecular Imaging, Comprehensive Heart Failure Center, University Hospital Würzburg, Germany"
title: misas
version: 0.0.4
doi: 10.5281/zenodo.4438133
date-released: 2021-01-14
repository-code: https://github.com/chfc-cmi/misas
keywords:
  - Deep Learning
  - Neural Networks
  - Cardiac Magnetic Resonance
  - Sensitivity Analysis
  - Transformations
  - Augmentation
  - Segmentation
license: MIT
url: https://chfc-cmi.github.io/misas/
preferred-citation:
  type: article
  scope: Cite this paper if you used misas in your research
  authors:
    - family-names: Ankenbrand
      given-names: Markus J
    - family-names: Shainberg
      given-names: Liliia
    - family-names: Hock
      given-names: Michael
    - family-names: Lohr
      given-names: David
    - family-names: Schreiber
      given-names: Laura M
  title: "Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI"
  year: 2021
  journal: BMC Medical Imaging
  volume: 21
  issue: 27
  doi: 10.1186/s12880-021-00551-1
  url: https://bmcmedimaging.biomedcentral.com/articles/10.1186/s12880-021-00551-1