A multi-view approach to multi-modal MRI cluster ensembles

Carlos Andrés Méndez; Paul Summers; Gloria Menegaz

doi:10.1117/12.2042327

21 March 2014 A multi-view approach to multi-modal MRI cluster ensembles

Carlos Andrés Méndez, Paul Summers, Gloria Menegaz

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 90341Q (2014) https://doi.org/10.1117/12.2042327
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

It has been shown that the combination of multi-modal MRI images improve the discrimination of diseased tissue. However the fusion of dissimilar imaging data for classification and segmentation purposes is not a trivial task, there is an inherent difference in information domains, dimensionality and scales. This work proposes a multiview 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 one of the MRI modalities and makes use of the concepts behind cluster ensembles to combine a set of base unsupervised segmentations into an unified partition of the voxel-based data. The methodology is specially designed for combining 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.

Citation Download Citation

Carlos Andrés Méndez, Paul Summers, and Gloria Menegaz "A multi-view approach to multi-modal MRI cluster ensembles", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90341Q (21 March 2014); https://doi.org/10.1117/12.2042327

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