Efficient evaluation of radial queries using the target tree.
We propose a novel indexing structure, called the target tree, which is designed to answer a new type of spatial query, called the radial query. A radial query finds all objects in the spatial data set that intersect with line segments emanating from a single target point. Many biomedical applications use radial queries, including neurosurgical planning. A target tree uses a regular hierarchical decomposition of space using wedge shapes that emanate from the target point. We compare the target tree with the R*-tree and quadtree, and show that the target tree is significantly faster than these methods.
Department of Electrical and Computer Science, University of Michigan, Ann Arbor, MI 48105, USA. mmorse@eecs.umich.edu
Michael
M
Morse
Jignesh M
JM
Patel
William I
WI
Grosky
D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D003201:Computers; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D016247:Information Storage and Retrieval; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D009493:Neurosurgery / Q000379:methods; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*