2012
DOI: 10.1097/rlu.0b013e3182443b2d
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Voxel-Based Quantitative Analysis of Brain Images From 18F-FDG PET With a Block-Matching Algorithm for Spatial Normalization

Abstract: Results obtained with the BM normalization of brain FDG PET appear more precise and robust than with SPM normalization, especially in cases of numerous or extended abnormalities.

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Cited by 9 publications
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“…SPM requires spatial normalization to align all images to a standard anatomic model (the template), but this may lead to image distortion and artifacts, especially in cases of marked brain abnormalities. Person et al [18 ]aimed to assess a block-matching normalization algorithm in which most transformations are not directly computed on the overall brain volume but through small blocks, a principle that is likely to minimize artifacts.…”
Section: Discussionmentioning
confidence: 99%
“…SPM requires spatial normalization to align all images to a standard anatomic model (the template), but this may lead to image distortion and artifacts, especially in cases of marked brain abnormalities. Person et al [18 ]aimed to assess a block-matching normalization algorithm in which most transformations are not directly computed on the overall brain volume but through small blocks, a principle that is likely to minimize artifacts.…”
Section: Discussionmentioning
confidence: 99%