Multivariate mathematical morphology for DCE-MRI image analysis in angiogenesis studies

@article{Noyel2019MultivariateMM,
  title={Multivariate mathematical morphology for DCE-MRI image analysis in angiogenesis studies},
  author={Guillaume Noyel and Jes{\'u}s Angulo and Dominique Jeulin and Daniel Balvay and Charles Andr{\'e} Cu{\'e}nod},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.12704}
}
We propose a new computer aided detection framework for tumours acquired on DCE-MRI (Dynamic Contrast Enhanced Magnetic Resonance Imaging) series on small animals. In this approach we consider DCE-MRI series as multivariate images. A full multivariate segmentation method based on dimensionality reduction, noise filtering, supervised classification and stochastic watershed is explained and tested on several data sets. The two main key-points introduced in this paper are noise reduction… Expand
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