A multi-view approach to consensus clustering in multi-modal MRI

C. Andrés Méndez, Gloria Menegaz, Paul Summers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It has been shown that the combination of multi-modal MRI images can improve the discrimination of diseased tissue. The fusion of dissimilar imaging data for classification and segmentation purposes however, is not a trivial task, as there is an inherent difference in information domains, dimensionality and scales. This work proposes a multi-view consensus clustering methodology for the integration of multi-modal MR images into a unified segmentation of tumoral lesions for heterogeneity assessment. Using a variety of metrics and distance functions this multi-view imaging approach calculates multiple vectorial dissimilarity-spaces for each MRI modality and makes use of cluster ensembles to combine a set of un-supervised base segmentations into an unified partition of the voxel-based data. The methodology is demonstrated in application to DCE-MRI and DTI-MR, for which a manifold learning step is implemented in order to account for the geometric constrains of the high dimensional diffusion information.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6627-6631
Number of pages5
ISBN (Print)9781479928927
DOIs
Publication statusPublished - 2014
Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: May 4 2014May 9 2014

Other

Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
CountryItaly
CityFlorence
Period5/4/145/9/14

Keywords

  • Classification
  • Cluster Ensembles
  • Clustering
  • DCE-MRI
  • DTI-MR
  • Segmentation

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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  • Cite this

    Méndez, C. A., Menegaz, G., & Summers, P. (2014). A multi-view approach to consensus clustering in multi-modal MRI. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 6627-6631). [6854882] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2014.6854882