Abstract
The efficacy and efficiency of decision-making based on visualization of reductive decompositions of time series image data were addressed. Three classes of decomposition were evaluated: interactive dynamic, fixed dynamic, and static. Performance was enhanced by tailoring data visualization to the requirements of the problem-solving system.
| Original language | English |
|---|---|
| Pages (from-to) | 134-144 |
| Number of pages | 11 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 3298 |
| DOIs | |
| State | Published - 1998 |
| Externally published | Yes |
| Event | Visual Data Exploration and Analysis V - San Jose, CA, United States Duration: 26 Jan 1998 → 27 Jan 1998 |
Keywords
- Decision-making
- Decomposition
- Medical-diagnostics
- Time-series
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