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 language | English (US) |
---|---|
Pages | 593-598 |
Number of pages | 6 |
State | Published - Dec 1 1994 |
Event | Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) - St. Louis, MO, USA Duration: Nov 13 1994 → Nov 16 1994 |
Other
Other | Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) |
---|---|
City | St. Louis, MO, USA |
Period | 11/13/94 → 11/16/94 |
ASJC Scopus subject areas
- Engineering(all)