CBIR of spine X-ray images on inter-vertebral disc space and shape profiles using feature ranking and voting consensus

Authors:
Dah-Jye Lee;Sameer Antani;Yuchou Chang;Kent Gledhill;L. Rodney Long;Paul Christensen
Affiliations:
Department of Electrical and Computer Eng., Brigham Young University, Provo, UT, United States;National Library of Medicine, National Institutes of Health, Bethesda, MD, United States;Department of Electrical and Computer Eng., Brigham Young University, Provo, UT, United States;Utah Valley Regional Medical Center, Provo, UT, United States;National Library of Medicine, National Institutes of Health, Bethesda, MD, United States;Department of Electrical and Computer Eng., Brigham Young University, Provo, UT, United States
Venue:
Data & Knowledge Engineering
Year:
2009

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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.