Dual-force ISOMAP: a new relevance feedback method for medical image retrieval.

ABSTRACT: With great potential for assisting radiological image interpretation and decision making, content-based image retrieval in the medical domain has become a hot topic in recent years. Many methods to enhance the performance of content-based medical image retrieval have been proposed, among which the relevance feedback (RF) scheme is one of the most promising. Given user feedback information, RF algorithms interactively learn a user's preferences to bridge the "semantic gap" between low-level computerized visual features and high-level human semantic perception and thus improve retrieval performance. However, most existing RF algorithms perform in the original high-dimensional feature space and ignore the manifold structure of the low-level visual features of images. In this paper, we propose

SUBMITTER: Shen H 

PROVIDER: S-EPMC3877227 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature