loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Igor Yanovsky 1 ; Stanley Osher 1 ; Paul M. Thompson 2 and Alex D. Leow 2

Affiliations: 1 University of California, United States ; 2 Laboratory of Neuro Imaging, UCLA School of Medicine, United States

ISBN: 978-972-8865-73-3

Keyword(s): Nonlinear image registration, information theory, mutual information, log-unbiased deformation, biomedical imaging.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Image Registration ; Medical Image Analysis

Abstract: In the past decade, information theory has been studied extensively in medical imaging. In particular, image matching by maximizing mutual information has been shown to yield good results in multi-modal image registration. However, there has been few rigorous studies to date that investigate the statistical aspect of the resulting deformation fields. Different regularization techniques have been proposed, sometimes generating deformations very different from one another. In this paper, we apply information theory to quantifying the magnitude of deformations. We examine the statistical distributions of Jacobian maps in the logarithmic space, and develop a new framework for constructing log-unbiased image registration methods. The proposed framework yields both theoretically and intuitively correct deformation maps, and is compatible with large-deformation models. In the results section, we tested the proposed method using pairs of synthetic binary images, two-dimensional serial MRI ima ges, and three-dimensional serial MRI volumes. We compared our results to those computed using the viscous fluid registration method, and demonstrated that the proposed method is advantageous when recovering voxel-wise local tissue change. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.229.126.29

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Yanovsky I.; Osher S.; M. Thompson P.; D. Leow A. and (2007). LOG-UNBIASED LARGE-DEFORMATION IMAGE REGISTRATION.In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 978-972-8865-73-3, pages 272-279. DOI: 10.5220/0002048202720279

@conference{visapp07,
author={Igor Yanovsky and Stanley Osher and Paul {M. Thompson} and Alex {D. Leow}},
title={LOG-UNBIASED LARGE-DEFORMATION IMAGE REGISTRATION},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2007},
pages={272-279},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002048202720279},
isbn={978-972-8865-73-3},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - LOG-UNBIASED LARGE-DEFORMATION IMAGE REGISTRATION
SN - 978-972-8865-73-3
AU - Yanovsky, I.
AU - Osher, S.
AU - M. Thompson, P.
AU - D. Leow, A.
PY - 2007
SP - 272
EP - 279
DO - 10.5220/0002048202720279

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.