Interactive ultrasound image retrieval using magnitude frequency spectrum

Abstract

An efficient algorithm is proposed for interactive ultrasound image retrieval using magnitude frequency spectrum (MFS). The interactive retrieval is especially intended to be useful for training an intern to diagnose with ultrasound images. In the retrieval process, information on which are relevant to a query image among object images retrieved in the previous iteration is fed back by user interaction. In order to improve discrimination between a query image and each of object images in a database (DB) by using the MFS, which is powerful for ultrasound image retrieval, we incorporate feature vector normalization and root filtering in feature extraction. To effectively integrate the feedback information, we use a feedback scheme based on Rocchio equation, where the feature of a query image is replaced with the weighted average of the feature of a query image and those of object images. Experimental results for real ultrasound images show that while yielding a precision of about 75% at a recall of about 8% in the initial retrieval, the interactive procedure yields a great performance improvement, that is, a precision of about 95% in the third iteration.