Abstract
Original language  English 

Qualification  Doctor of Philosophy 
Awarding Institution 

Supervisors/Advisors 

Award date  20 Oct 2009 
Place of Publication  San Antonio 
Publisher  
Publication status  Published  2009 
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Obstacleavoiding similarity metrics and shortestpath problems. / Cook IV, A.F.
San Antonio : University of Texas at San Antonio, 2009. 120 p.Research output: Thesis › Phd Thesis 4 Research NOT TU/e / Graduation NOT TU/e)
TY  THES
T1  Obstacleavoiding similarity metrics and shortestpath problems
AU  Cook IV, A.F.
PY  2009
Y1  2009
N2  Similarity metrics are functions that measure the similarity of geometric objects. The motivation for studying similarity metrics is that these functions are essential building blocks for areas such as computer vision, robotics, medical imaging, and drug design. Although similarity metrics are traditionally computed in environments without obstacles, we use shortest paths to compute similarity metrics in simple polygons, in polygons with polygonal holes, and on polyhedral surfaces. We measure the length of a path either by Euclidean distance or by the number of turns on the path. We also compute shortest paths that steer a medical needle through a sequence of treatment points in the plane. This technique could be used in biopsy procedures to take multiple tissue samples with a single puncture of the skin. Such an algorithm could also be applied to brachytherapy procedures that implant radioactive pellets at many cancerous locations. Computing shortest paths for medical needles is a challenging problem because medical needles cut through tissue along circular arcs and have a limited ability to turn. Although optimal substructure can fail, we compute globally optimal paths with a wavefront propagation technique.
AB  Similarity metrics are functions that measure the similarity of geometric objects. The motivation for studying similarity metrics is that these functions are essential building blocks for areas such as computer vision, robotics, medical imaging, and drug design. Although similarity metrics are traditionally computed in environments without obstacles, we use shortest paths to compute similarity metrics in simple polygons, in polygons with polygonal holes, and on polyhedral surfaces. We measure the length of a path either by Euclidean distance or by the number of turns on the path. We also compute shortest paths that steer a medical needle through a sequence of treatment points in the plane. This technique could be used in biopsy procedures to take multiple tissue samples with a single puncture of the skin. Such an algorithm could also be applied to brachytherapy procedures that implant radioactive pellets at many cancerous locations. Computing shortest paths for medical needles is a challenging problem because medical needles cut through tissue along circular arcs and have a limited ability to turn. Although optimal substructure can fail, we compute globally optimal paths with a wavefront propagation technique.
M3  Phd Thesis 4 Research NOT TU/e / Graduation NOT TU/e)
PB  University of Texas at San Antonio
CY  San Antonio
ER 