Title: Cervical spine image retrieval with semantic shape features

Authors: Pranati Das, Sudipta Mukhopadhyay

Addresses: Department of Electrical and Electronics Engineering, Indira Gandhi Institute of Technology, Sarang-759146, Orissa, India. ' Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur-721302, India

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.

Keywords: content-based image retrieval; CBIR; semantic query; feature extraction; shape representation; anterior osteophyte; cervical spine imaging; geometric modelling; feature space; computational vision; spinal images; spine vertebrae models; shape features.

DOI: 10.1504/IJCVR.2010.036077

International Journal of Computational Vision and Robotics, 2010 Vol.1 No.2, pp.136 - 146

Published online: 17 Oct 2010 *

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