Medical image collection indexing: shape-based retrieval using KD-trees.
The capacity to retrieve images containing objects with shapes similar to a query shape is desirable in medical image databases. We propose a similarity measure and an indexing mechanism for non-rigid comparison of shape which adds this capability to image databases. The (dis-)similarity measure is based on the observations that: (1) the geometry of the same organ in different subjects is not related by a strictly rigid transformation; and (2) the orientation of the organ plays a key role in comparing shape. We propose a similarity measure that computes a non-rigid mapping between curves and uses this mapping to compare oriented shape. We also show how KD-trees can index curves so that retrieval with our similarity measure is efficient. Experiments with real-world data from a database of magnetic resonance images are provided.
Robinson
G P
GP
Department of Diagnostic Radiology, Yale University, New Haven, CT 06520, USA.
Tagare
H D
HD
Duncan
J S
JS
Jaffe
C C
CC
D000043:Abstracting and Indexing; D003663:Decision Trees; D007091:Image Processing, Computer-Assisted; D016247:Information Storage and Retrieval; D008279:Magnetic Resonance Imaging; D011873:Radiology Information Systems