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.