Document Detail


CPOL: complex phase order likelihood as a similarity measure for MR-CT registration.
MedLine Citation:
PMID:  19892585     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
A novel similarity measure for registering magnetic resonance (MR) and computed tomography (CT) images has been designed and built. MR-CT registration methods often rely on the statistical intensity relationship between the images. The proposed similarity measure instead depends on the statistical relationship between the complex phase order between the images. By utilizing the complex phase order likelihood (CPOL) as a similarity measure, structural relationships instead of intensity relationships are explicitly used. This approach can be advantageous for MR-CT registration, where the intensities of the CT imagery have highly complex and nonlinear relationships with the intensities of corresponding MR imagery but simpler linear structural relationships. This new similarity measure has been tested on real MR-CT 3D volumes and has been evaluated based on fiducial registration error to determine alignment accuracy. Quantitative results show that CPOL is capable of achieving comparable alignment accuracy when compared to normalized mutual information, while being more robust to imaging artifacts such as noise.
Authors:
Alexander Wong; David A Clausi; Paul Fieguth
Related Documents :
22013145 - Paediatric multiple sclerosis: examining utility of the mcdonald 2010 criteria.
21748695 - Mr evaluation of retroperitoneal fibrosis.
22033035 - Analysis of the management of occult fractures of the scaphoid through early magnetic r...
16148705 - Three-dimensional computed tomography angiography of the internal carotid artery for pr...
11733325 - Blood volume of gliomas determined by double-echo dynamic perfusion-weighted mr imaging...
21231135 - Dynamics of magnetic charges in artificial spin ice.
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2009-10-20
Journal Detail:
Title:  Medical image analysis     Volume:  14     ISSN:  1361-8423     ISO Abbreviation:  Med Image Anal     Publication Date:  2010 Feb 
Date Detail:
Created Date:  2009-11-30     Completed Date:  2010-02-22     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9713490     Medline TA:  Med Image Anal     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  50-7     Citation Subset:  IM    
Affiliation:
Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada N2L 3G1. a28wong@engmail.uwaterloo.ca
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence
Brain / pathology*,  radiography*
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Likelihood Functions
Magnetic Resonance Imaging / methods*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique*
Tomography, X-Ray Computed / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Bone morphogenetic proteins in orthopaedic surgery.
Next Document:  Language: the perspective from organismal biology.