Spatial Mutual Information as Similarity Measure for 3-D Brain Image Registration.

TitleSpatial Mutual Information as Similarity Measure for 3-D Brain Image Registration.
Publication TypeJournal Article
Year of Publication2014
AuthorsRazlighi QR, Kehtarnavaz N
JournalIEEE J Transl Eng Health Med
Volume2
Date Published2014 Jan 09
ISSN2168-2372
Abstract

Information theoretic-based similarity measures, in particular mutual information, are widely used for intermodal/intersubject 3-D brain image registration. However, conventional mutual information does not consider spatial dependency between adjacent voxels in images, thus reducing its efficacy as a similarity measure in image registration. This paper first presents a review of the existing attempts to incorporate spatial dependency into the computation of mutual information (MI). Then, a recently introduced spatially dependent similarity measure, named spatial MI, is extended to 3-D brain image registration. This extension also eliminates its artifact for translational misregistration. Finally, the effectiveness of the proposed 3-D spatial MI as a similarity measure is compared with three existing MI measures by applying controlled levels of noise degradation to 3-D simulated brain images.

DOI10.1109/JTEHM.2014.2299280
Alternate JournalIEEE J Transl Eng Health Med
PubMed ID24851197
PubMed Central IDPMC4025931
Grant ListK01 AG044467 / AG / NIA NIH HHS / United States
R01 AG026158 / AG / NIA NIH HHS / United States
T32 AG000261 / AG / NIA NIH HHS / United States
Z01 AG000261 / / Intramural NIH HHS / United States
Related Institute: 
Brain Health Imaging Institute (BHII)

Weill Cornell Medicine
Department of Radiology
525 East 68th Street New York, NY 10065