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Longitudinal brain MRI analysis with uncertain registration

Abstract:

In this paper we propose a novel approach for incorporating measures of spatial uncertainty, which are derived from non-rigid registration, into spatially normalised statistics. Current approaches to spatially normalised statistical analysis use point-estimates of the registration parameters. This is limiting as the registration will rarely be completely accurate, and therefore data smoothing is often used to compensate for the uncertainty of the mapping. We derive localised measurements of s...

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Journal:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume:
6892 LNCS
Issue:
PART 2
Pages:
647-654
Publication date:
2011-01-01
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
URN:
uuid:9d9ea686-d144-4822-a67a-30f666d8742e
Source identifiers:
194653
Local pid:
pubs:194653
Language:
English

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