A multidimensional data visualization and clustering method: Consensus similarity mapping

Vishwa S. Parekh, Michael Jacobs

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

Abstract

Multiparametric Magnetic Resonance Imaging (MRI) produces large amounts of high dimensional data for radiologists to read. Currently, radiologists integrate multiparametric MRI data visually to identify meaningful structures within the data. In this paper, we present a novel visualization and clustering technique called «Consensus Similarity Mapping (CSM)» for integration of multidimensional radiological data. The CSM algorithm computes an ensemble of stable clustering results obtained from multiple runs of the k-means algorithm. The CSM algorithm uses a unique method called cluster stability index (CSI) to identify the stable clustering configurations required to create the k-means ensemble. The CSM algorithm transforms the stable clustering ensemble into a matrix of pairwise similarities, which, uncovers the intrinsic classes within the high dimensional input data. We demonstrate the performance of CSM on well-known synthetic datasets as well as multiparametric magnetic resonance imaging (MRI) data.

Original languageEnglish (US)
Title of host publication2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings
PublisherIEEE Computer Society
Pages420-423
Number of pages4
Volume2016-June
ISBN (Electronic)9781479923502
DOIs
StatePublished - Jun 15 2016
Event2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Prague, Czech Republic
Duration: Apr 13 2016Apr 16 2016

Other

Other2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
CountryCzech Republic
CityPrague
Period4/13/164/16/16

Keywords

  • clustering
  • evidence accumulation
  • multiparametric MRI
  • nonlinear dimensionality reduction
  • segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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