CBIR of Spine X-ray Images On Inter-vertebral Disc Space and Shape Profiles Using Feature Ranking and Voting Consensus.
Lee DJ, Antani S, Chang Y, Long LR, Christensen P, Jeronimo J
Data & Knowledge Engineering, Special Issue on Knowledge Discovery in Medicine. 2009.
Abstract:
Very limited research is published in the literature that applies content-based image retrieval (CBIR) techniques to retrieval of digitized spine X-ray images that combines inter-vertebral disc space and vertebral shape profiles. This paper describes a novel technique for retrieving vertebra pairs that exhibit a specified disc space narrowing (DSN) and inter-vertebral disc shape. DSN is characterized using spatial and geometrical features between two adjacent vertebrae. In order to obtain the best retrieval result, all selected features are ranked and assigned a weight to indicate their importance in the computation of the final similarity measure. Using a two phase algorithm, initial retrieval results are clustered and used to construct a voting committee to retrieve vertebra pairs with the highest DSN similarity. The overall retrieval accuracy is validated by a radiologist and proves that selected features combined with voting consensus are effective for DSN-based spine X-ray image retrieval.
Lee DJ, Antani S, Chang Y, Long LR, Christensen P, Jeronimo J. CBIR of Spine X-ray Images On Inter-vertebral Disc Space and Shape Profiles Using Feature Ranking and Voting Consensus.
Data & Knowledge Engineering, Special Issue on Knowledge Discovery in Medicine. 2009.