Multi-parameter medical image visualization with self-organizing maps

Research output: Contribution to conferencePaper

1 Scopus citations

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, a useful complement to projection-pursuit or other linear techniques, and 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)
Pages3990-3995
Number of pages6
StatePublished - Dec 1 1994
EventProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA
Duration: Jun 27 1994Jun 29 1994

Other

OtherProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
CityOrlando, FL, USA
Period6/27/946/29/94

ASJC Scopus subject areas

  • Software

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    Manduca, A. (1994). Multi-parameter medical image visualization with self-organizing maps. 3990-3995. Paper presented at Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7), Orlando, FL, USA, .