A unified information-theoretic approach to groupwise non-rigid registration and model building.
about
A generative model for image segmentation based on label fusion3D pattern of brain abnormalities in Williams syndrome visualized using tensor-based morphometry.What Data to Co-register for Computing Atlases.The optimal template effect in hippocampus studies of diseased populationsImage-driven population analysis through mixture modeling.Automatic hippocampus segmentation of 7.0 Tesla MR images by combining multiple atlases and auto-context modelsThe SRI24 multichannel atlas of normal adult human brain structure.Morphological appearance manifolds for group-wise morphometric analysis.3D pattern of brain atrophy in HIV/AIDS visualized using tensor-based morphometryRobust estimation of group-wise cortical correspondence with an application to macaque and human neuroimaging studiesEncoding probabilistic brain atlases using Bayesian inference.3D pattern of brain abnormalities in Fragile X syndrome visualized using tensor-based morphometry.What is where and why it is important.3D characterization of brain atrophy in Alzheimer's disease and mild cognitive impairment using tensor-based morphometryRegistration of challenging pre-clinical brain imagesEffects of registration regularization and atlas sharpness on segmentation accuracy.Learning task-optimal registration cost functions for localizing cytoarchitecture and function in the cerebral cortexMapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer's disease, mild cognitive impairment and elderly controls.Implicit reference-based group-wise image registration and its application to structural and functional MRIMorphological appearance manifolds in computational anatomy: groupwise registration and morphological analysis.Comparing pairwise and simultaneous joint registrations of decorrelating interval exams using entropic graphs.From label fusion to correspondence fusion: a new approach to unbiased groupwise registrationA new statistically-constrained deformable registration framework for MR brain images.Generalized L2-divergence and its application to shape alignment.Feature-based alignment of volumetric multi-modal images.Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms.
P2860
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P2860
A unified information-theoretic approach to groupwise non-rigid registration and model building.
description
2005 nî lūn-bûn
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2005年の論文
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2005年学术文章
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2005年学术文章
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2005年学术文章
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2005年学术文章
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2005年学术文章
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2005年學術文章
@zh-hant
name
A unified information-theoreti ...... gistration and model building.
@en
A unified information-theoreti ...... gistration and model building.
@nl
type
label
A unified information-theoreti ...... gistration and model building.
@en
A unified information-theoreti ...... gistration and model building.
@nl
prefLabel
A unified information-theoreti ...... gistration and model building.
@en
A unified information-theoreti ...... gistration and model building.
@nl
P2093
P1476
A unified information-theoreti ...... gistration and model building.
@en
P2093
Carole J Twining
Chris J Taylor
Roy Schestowitz
Stephen Marsland
Tim Cootes
Vladimir Petrovic
P577
2005-01-01T00:00:00Z