Cervical spine image retrieval with semantic shape features

Abstract

The objective of the proposed approach is to narrow down the semantic gap between the query and retrieval primitives in a spine image retrieval system. The proposed retrieval technique is based on a geometric eight-point model to enable formation of semantic query. The geometric eight-point model is uniform for all vertebrae, not biased by human experts and thus free from ambiguity. The features are extracted after automatically locating contour points of eight-point geometric model of spine vertebra. Then, vertebra is represented in feature space using region-based shape features, indicative of pathology (at two anterior corners). The proposed retrieval scheme uses Euclidean distance as similarity measure in feature space. It yields better result than an existing whole shape-based matching method for retrieval of spine images that uses Procrustes metric, in term of accuracy and parsimony of model. The approach is simple and computationally efficient.