Temporal Consistency Objectives Regularize the Learning of Disentangled Representations

@article{Valvano2019TemporalCO,
  title={Temporal Consistency Objectives Regularize the Learning of Disentangled Representations},
  author={Gabriele Valvano and Agisilaos Chartsias and Andrea Leo and Sotirios A. Tsaftaris},
  journal={ArXiv},
  year={2019},
  volume={abs/1908.11330}
}
There has been an increasing focus in learning interpretable feature representations, particularly in applications such as medical image analysis that require explainability, whilst relying less on annotated data (since annotations can be tedious and costly. [...] Key Method This forces the anatomical decomposition to be consistent with the temporal cardiac contraction in cine MRI and to have semantic meaning with less need for annotations. We demonstrate that using this regularization, we achieve competitive…Expand
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