Computer Vision And Pattern Analysis Laboratory Home Page  Home
People  People
Publications  Publications
Publications  Databases
Contact Information  Contact
Supported Research Projects  Supported Research Projects
Research Activites  Research Activites
Research Groups
SPIS - Signal Processing and Information Systems Lab.SPIS - Signal Processing and Information Systems Lab.
Medical Vision and Analysis Group  Medical Research Activities
Biometrics Research Group  Biometrics Research Group
SPIS - Signal Processing and Information Systems Lab.MISAM - Machine Intelligence for Speech Audio and Multimedia.
Knowledge Base
  Paper Library
Information-Theoretic Feature Detection and Its Application to Registration of Ultrasound Images
Authors: Zhe Wendy Wang, Greg Slabaugh, Gozde Unal, Tong Fang
Published in: IJICS - The International Journal of Intelligent Control and Systems
Publication year: 2008
Abstract: Abstract—Medical ultrasound image registration is an essential component in an increasing number of applications, and has therefore been the subject of many studies in the literature. These applications use either generic registration algorithms or pixel-to-pixel comparison based ultrasound-specific methods. Hence, they are not well suited for the case of speckled images resulting from different realizations of a random process. To better handle the speckle, this work proposes an information-theoretic feature detector-based registration approach. Using speckle modeling based on the distributions of Rayleigh or normalized Fisher-Tippett, a speckle-specific information-theoretic feature detector is constructed and applied to provide feature images. Those feature images are then registered using differential equations, whose solution provides a transformation to bring the images into alignment. Compared to standard gradient-based techniques, the experimental results demonstrate the effectiveness of the proposed method, particularly for low contrast ultrasound images. It can be readily applied in the healthcare industry.
  download full paper

Home Back