This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.
Browsing Institute for Systems Research Technical Reports by Subject "access methods"
We examine the problem of finding similar tumor shapes. Starting from a natural similarity function (the so-called ax morphological distance'), we showed how to lower-bound it and how to search for nearest neighbors in large collections of tumor- like shapes.
Specifically, we used state-of-the-art concepts from morphology, namely the attern spectrum' of a shape, to map each shape to a point in n-dimensional space. Following [19, 36], we organized the n-d points in an R-tree. We showed that the L (= max) norm in the n-d space lower-bounds the actual distance. This guarantees no false dismissals for range queries. In addition, we developed a nearest neighbor algorithm that also guarantees no false dismissals.
Finally, we implemented the method, and we tested it against a testbed of realistic tumor shapes, using an established tumor-growth model of Murray Eden . The experiments showed that our method is up to 27 times faster than straightforward sequential scanning.