Multi-parameter image visualization with self-organizing maps

Research output: Contribution to conferencePaper

Abstract

The effective display of multi-parameter medical image data sets is assuming increasing importance as more distinct imaging modalities are becoming available. For medical purposes, one desirable goal is to fuse such data sets into a single most informative gray-scale image without making rigid classification decisions. A visualization technique based on a non-linear projection onto a 1-D self-organizing map is described and examples are shown. The SOM visualization technique is fast, theoretically attractive, and has properties which complement those of projection-pursuit or other linear techniques. It may be of particular value in calling attention to specific regions in a multi-parameter image where the component images should be examined in detail.

Original languageEnglish (US)
Pages593-598
Number of pages6
StatePublished - Dec 1 1994
EventProceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) - St. Louis, MO, USA
Duration: Nov 13 1994Nov 16 1994

Other

OtherProceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94)
CitySt. Louis, MO, USA
Period11/13/9411/16/94

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Manduca, A. (1994). Multi-parameter image visualization with self-organizing maps. 593-598. Paper presented at Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94), St. Louis, MO, USA, .