Document Detail


Bilateral filtering of diffusion tensor magnetic resonance images.
MedLine Citation:
PMID:  17926929     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We extend the well-known scalar image bilateral filtering technique to diffusion tensor magnetic resonance images (DTMRI). The scalar version of bilateral image filtering is extended to perform edge-preserving smoothing of DT field data. The bilateral DT filtering is performed in the Log-Euclidean framework which guarantees valid output tensors. Smoothing is achieved by weighted averaging of neighboring tensors. Analogous to bilateral filtering of scalar images, the weights are chosen to be inversely proportional to two distance measures: The geometrical Euclidean distance between the spatial locations of tensors and the dissimilarity of tensors. We describe the noniterative DT smoothing equation in closed form and show how interpolation of DT data is treated as a special case of bilateral filtering where only spatial distance is used. We evaluate different recent DT tensor dissimilarity metrics including the Log-Euclidean, the similarity-invariant Log-Euclidean, the square root of the J-divergence, and the distance scaled mutual diffusion coefficient. We present qualitative and quantitative smoothing and interpolation results and show their effect on segmentation, for both synthetic DT field data, as well as real cardiac and brain DTMRI data.
Authors:
Ghassan Hamarneh; Judith Hradsky
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  IEEE transactions on image processing : a publication of the IEEE Signal Processing Society     Volume:  16     ISSN:  1057-7149     ISO Abbreviation:  IEEE Trans Image Process     Publication Date:  2007 Oct 
Date Detail:
Created Date:  2007-10-11     Completed Date:  2007-11-13     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9886191     Medline TA:  IEEE Trans Image Process     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2463-75     Citation Subset:  IM    
Affiliation:
Medical Image Analysis Lab, School of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Brain Mapping / methods*
Diffusion Magnetic Resonance Imaging / methods*
Humans
Image Enhancement / methods*
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Reproducibility of Results
Sensitivity and Specificity

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


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