City Research Online

Registration of Ultrasound Images Using an Information-Theoretic Feature Detector

Wang, Z., Slabaugh, G.G., Unal, G.B. and Fang, T. (2007). Registration of Ultrasound Images Using an Information-Theoretic Feature Detector. In: 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. (pp. 736-739). IEEE. ISBN 1-4244-0672-2

Abstract

In this paper, we present a new method for ultrasound image registration. For each image to be registered, our method first applies an ultrasound-specific information-theoretic feature detector, which is based on statistical modeling of speckle and provides a feature image that robustly delineates important edges in the image. These feature images are then registered using differential equations, the solution of which provides a locally optimal transformation that brings the images into alignment. We describe our method and present experimental results demonstrating its effectiveness, particularly for low contrast, speckled images. Furthermore, we compare our method to standard gradient-based techniques, which we show are more susceptible to misregistration.

Publication Type: Book Section
Additional Information: © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Image registration, information theory, biomedical image processing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
URI: http://openaccess.city.ac.uk/id/eprint/6114
[img]
Preview
PDF - Accepted Version
Download (680kB) | Preview

Export

Downloads

Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login