Distance transforms in multichannel MR image registration

Min Chen; Aaron Carass; John Bogovic; Pierre-Louis Bazin; Jerry L. Prince

doi:10.1117/12.878367

11 March 2011 Distance transforms in multi channel MR image registration

Min Chen, Aaron Carass, John Bogovic, Pierre-Louis Bazin, Jerry L. Prince

Author Affiliations +

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 79621D (2011) https://doi.org/10.1117/12.878367
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

Deformable registration techniques play vital roles in a variety of medical imaging tasks such as image fusion, segmentation, and post-operative surgery assessment. In recent years, mutual information has become one of the most widely used similarity metrics for medical image registration algorithms. Unfortunately, as a matching criteria, mutual information loses much of its effectiveness when there is poor statistical consistency and a lack of structure. This is especially true in areas of images where the intensity is homogeneous and information is sparse. Here we present a method designed to address this problem by integrating distance transforms of anatomical segmentations as part of a multi-channel mutual information framework within the registration algorithm. Our method was tested by registering real MR brain data and comparing the segmentation of the results against that of the target. Our analysis showed that by integrating distance transforms of the the white matter segmentation into the registration, the overall segmentation of the registration result was closer to the target than when the distance transform was not used.

Citation Download Citation

Min Chen, Aaron Carass, John Bogovic, Pierre-Louis Bazin, and Jerry L. Prince "Distance transforms in multi channel MR image registration", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79621D (11 March 2011); https://doi.org/10.1117/12.878367

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE