Name
Abstract | ||
|---|---|---|
In medical imaging, comparing and retrieving objects is non-trivial because of the high variability in shape and appearance. Such variety leads to poor performance of retrieval algorithms only based on local or global descriptors (shape, color, texture). In this article, we propose a context-based framework for medical image retrieval on the grounds of a global object context based on the mutual positions of local descriptors. This characterization is incorporated into a fast non-rigid registration process to provide invariance against elastic transformations. We apply our method to a complex domain of images—retrieval of intravascular ultrasound images according to vessel morphology. Final results are very encouraging. � 2005 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.patrec.2004.12.007 | Pattern Recognition Letters |
Keywords | Field | DocType |
context-based framework,registration,global object context,local descriptors,contextual information,fast non-rigid registration process,global descriptors,elastic body,retrieval,final result,medical imaging,medical image retrieval,ivus,elastic transformation,elastic matching,complex domain,image retrieval | Elastic matching,Computer vision,Automatic image annotation,Pattern recognition,Invariant (physics),Computer science,Image texture,Medical imaging,Image retrieval,Artificial intelligence,Image registration,Visual Word | Journal |
Volume | Issue | ISSN |
26 | 11 | Pattern Recognition Letters |
Citations | PageRank | References |
5 | 0.54 | 14 |
Authors | ||
2 | ||