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Schroedinger Eigenmaps for the Analysis of Bio-Medical Data

Computational Engineering, Finance, and Science 2017-09-04 v2 Data Analysis, Statistics and Probability Medical Physics Quantitative Methods
Authors: Wojciech Czaja , Martin Ehler
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Abstract

We introduce Schroedinger Eigenmaps, a new semi-supervised manifold learning and recovery technique. This method is based on an implementation of graph Schroedinger operators with appropriately constructed barrier potentials as carriers of labeled information. We use our approach for the analysis of standard bio-medical datasets and new multispectral retinal images.

Keywords

medical image analysis

Cite

@article{arxiv.1102.4086,
  title  = {Schroedinger Eigenmaps for the Analysis of Bio-Medical Data},
  author = {Wojciech Czaja and Martin Ehler},
  journal= {arXiv preprint arXiv:1102.4086},
  year   = {2017}
}

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