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

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...

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Main Authors: Qolamreza R. Razlighi, Nasser Kehtarnavaz
Format: Article
Language:English
Published: IEEE 2014-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Online Access:https://ieeexplore.ieee.org/document/6708450/
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spelling doaj-3db1d5def2834f5db755efb298b5e7822021-03-29T18:38:11ZengIEEEIEEE Journal of Translational Engineering in Health and Medicine2168-23722014-01-012273410.1109/JTEHM.2014.22992806708450Spatial Mutual Information as Similarity Measure for 3-D Brain Image RegistrationQolamreza R. Razlighi0Nasser Kehtarnavaz1Department of Biomedical Engineering and Neurology, Columbia University, New York, NY, USADepartment of Electrical Engineering, University of Texas at Dallas, Richardson, TX, USAInformation 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.https://ieeexplore.ieee.org/document/6708450/Spatial mutual informationspatially dependent similarity measuresbrain image registrationspatial entropy
collection DOAJ
language English
format Article
sources DOAJ
author Qolamreza R. Razlighi
Nasser Kehtarnavaz
spellingShingle Qolamreza R. Razlighi
Nasser Kehtarnavaz
Spatial Mutual Information as Similarity Measure for 3-D Brain Image Registration
IEEE Journal of Translational Engineering in Health and Medicine
Spatial mutual information
spatially dependent similarity measures
brain image registration
spatial entropy
author_facet Qolamreza R. Razlighi
Nasser Kehtarnavaz
author_sort Qolamreza R. Razlighi
title Spatial Mutual Information as Similarity Measure for 3-D Brain Image Registration
title_short Spatial Mutual Information as Similarity Measure for 3-D Brain Image Registration
title_full Spatial Mutual Information as Similarity Measure for 3-D Brain Image Registration
title_fullStr Spatial Mutual Information as Similarity Measure for 3-D Brain Image Registration
title_full_unstemmed Spatial Mutual Information as Similarity Measure for 3-D Brain Image Registration
title_sort spatial mutual information as similarity measure for 3-d brain image registration
publisher IEEE
series IEEE Journal of Translational Engineering in Health and Medicine
issn 2168-2372
publishDate 2014-01-01
description 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.
topic Spatial mutual information
spatially dependent similarity measures
brain image registration
spatial entropy
url https://ieeexplore.ieee.org/document/6708450/
work_keys_str_mv AT qolamrezarrazlighi spatialmutualinformationassimilaritymeasurefor3dbrainimageregistration
AT nasserkehtarnavaz spatialmutualinformationassimilaritymeasurefor3dbrainimageregistration
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