DocumentCode :
2521439
Title :
A COMBINED FEATURE ENSEMBLE BASED MUTUAL INFORMATION SCHEME FOR ROBUST INTER-MODAL, INTER-PROTOCOL IMAGE REGISTRATION
Author :
Chappelow, Jonathan ; Madabhushi, Anant ; Rosen, Mark ; Tomaszeweski, John ; Feldman, Michael
Author_Institution :
Dept. of Biomed. Eng., Rutgers Univ., Piscataway, NJ
fYear :
2007
fDate :
12-15 April 2007
Firstpage :
644
Lastpage :
647
Abstract :
In this paper we present a new robust method for medical image registration called combined feature ensemble mutual information (COFEMI). While mutual information (MI) has become arguably the most popular similarity metric for image registration, intensity based MI schemes have been found wanting in inter-modal and interprotocol image registration, especially when (1) significant image differences across modalities (e.g. pathological and radiological studies) exist, and (2) when imaging artifacts have significantly altered the characteristics of one or both of the images to be registered. Intensity-based MI registration methods operate by maximization of MI between two images A and B. The COFEMI scheme extracts over 450 feature representations of image B that provide additional information about A not conveyed by image B alone and are more robust to the artifacts affecting original intensity image B. COFEMI registration operates by maximization of combined mutual information (CMI) of the image A with the feature ensemble associated with B. The combination of information from several feature images provides a more robust similarity metric compared to the use of a single feature image or the original intensity image alone. We also present a computer-assisted scheme for determining an optimal set of maximally informative features for use with our CMI formulation. We quantitatively and qualitatively demonstrate the improvement in registration accuracy by using our COFEMI scheme over the traditional intensity based-Mi scheme in registering (1) prostate whole mount histological sections with corresponding magnetic resonance imaging (MRI) slices; and (2) phantom brain T1 and T2 MRI studies, which were adversely affected by imaging artifacts
Keywords :
biological organs; biological tissues; biomedical MRI; feature extraction; image registration; medical image processing; phantoms; T1 MRI; T2 MRI; combined feature ensemble mutual information; computer-assisted scheme; feature extraction; histological sections; image differences; imaging artifacts; intensity based mutual information scheme; intensity image; intermodal image registration; interprotocol image registration; magnetic resonance imaging; medical image registration; phantom brain; prostate; registration accuracy; robust method; similarity metric; Biomedical engineering; Biomedical imaging; Brain; Image registration; Magnetic resonance imaging; Medical treatment; Mutual information; Pathology; Robustness; Ultrasonic imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
1-4244-0672-2
Electronic_ISBN :
1-4244-0672-2
Type :
conf
DOI :
10.1109/ISBI.2007.356934
Filename :
4193368
Link To Document :
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