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 language | English (US) |
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Pages | 3990-3995 |
Number of pages | 6 |
State | Published - Dec 1 1994 |
Event | Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA Duration: Jun 27 1994 → Jun 29 1994 |
Other
Other | Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) |
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City | Orlando, FL, USA |
Period | 6/27/94 → 6/29/94 |
ASJC Scopus subject areas
- Software