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Machine-Learned Assist for Boundary Contour Tracing

Stewart Crawford-Hines and Charles Anderson 
Department of Computer Science 
Colorado State University 
Fort Collins, CO 80523, USA
sgcraw@cs.colostate.eduanderson@cs.colostate.edu 
http://www.cs.colostate.edu/~sgcraw and http://www.cs.colostate.edu/~anderson 
Thomas McCracken  
Visible Productions 
116 North College Ave, Suite #7 
Fort Collins, CO 80523, USA
vip@visiblep.com 


Abstract
      To generate anatomical models from the Visible Human imagery, a key first step is to trace the tissues & organs of interest on each of many slices. This tracing has been, by and large, a manual task so far.  Our focus is to aid the human tracers by having a computer system learn the contour being traced, and then automatically trace through similar regions. We have integrated our research ideas into the production tracing systems of Visible Productions, and early results demonstrate a significant improvement in overall tracing speed, while potentially relieving human tracers of much of the monotony in their task.

Keywords: 3D anatomical models, contour tracing, edge detection.

 
Table of Contents
 
Full text index  
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References 
 
Acknowledgements
      This research is funded in part by CASI (Colorado Advanced Software Institute) and NSF (SBIR#9761590).  Our research software was integrated into the tracing software of Visible Productions, Inc. (of Fort Collins, CO); Dan Steward provided invaluable system assistance.  And, of course, thanks to NIH for making the Visible Human imagery widely available.
 
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