Variable precision registration via wavelets: Optimal spatial scales for inter-subject registration of functional MRI

Suckling, John; Long, Chris; Triantafyllou, Christina; Brammer, Michael; Bullmore, Edward T.

doi:10.1016/j.neuroimage.2005.11.032

Cited by 12 publications

(15 citation statements)

References 44 publications

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“…Some of the most important high-dimensional parametric models include: 1) FFD models with regular grid of control points, typically based on B-spline basis functions [51], [203], [214]- [222] or radial basis functions [57], [60], [77], [223]- [225]; 2) elastic-body spline warping models [226] such as thin plate spline (TPS) warping models [227]- [229] mainly used as interpolators for point set matching; 3) local affine transformations [166], [205], [206], [230]- [232]; 4) wavelet-mediated deformations [233]. A parametric particle method based on vector field formulation has also been developed [234].…”

Section: B Volume Registrationmentioning

confidence: 99%

“…Intensity-based correspondences are based on voxel intensity similarity measures which are either information-theory-based measures such as MI [50], [52], [59], [212], [223], [240], [246]; NMI [51], [216], [220], [221]; and KLD [55], [239], [247]; or based on likelihood functions of voxel intensities [215], [248] or voxel intensity differences computed as local or global sum of square differences (SSD) [58], [77], [149], [197], [233], [249]; mean square differences (MSD), or weighted MSD [49], [196], [202], [204], [225], [234], [250].…”

Section: B Volume Registrationmentioning

confidence: 99%

“…Instead, various quantitative measures have been used in individual studies. Cross-validation through the use of similarity measures other than those utilized in each registration technique is one of the basic evaluation methods [215], [219], [220], [223], [233], [251]. Other measures based on average brain [197], [196], [246], [252], [267]- [269], tissue overlap [204], [206], [225], [235], [240], [241], [256], [263], [270], and sulcus distance [208], [217], [225], [255], [262], [267] have been used in the literature.…”

Section: Validationmentioning

confidence: 99%

“…In determining correspondences between MRI images, the feature detection algorithm in [258] has shown to perform similarly to experts even for complex cortical structures. Qualitative validation of the registration results has also been carried out through visual inspection [45], [62], [197], [205], [207], [208], [210], [219], [227], [229], [230], [234], [236], [246], [249], [250], [252], [261], [266], matching of detected landmarks and segmentations, and more practically through the postanalysis and interpretation of the loci of activation maps [77], [188]- [190], [195], [233], [248], [268]. In some articles such observations and analysis have been quantified using empirical measures.…”

Section: Validationmentioning

confidence: 99%

“…In another study [268], the and values of statistical parametric mapping have been compared across the results obtained from three different spatial normalization techniques. The sensitivity of detected activation maps has been analyzed in [233]. The precision of functional localization has been analyzed through the use of the volumetric Talairach transformation and two surface-based registration techniques [188].…”

Section: Validationmentioning

confidence: 99%

See 4 more Smart Citations

Brain Functional Localization: A Survey of Image Registration Techniques

Gholipour

Kehtarnavaz

Briggs

et al. 2007

IEEE Trans. Med. Imaging

227

127

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Abstract-Functional localization is a concept which involves the application of a sequence of geometrical and statistical image processing operations in order to define the location of brain activity or to produce functional/parametric maps with respect to the brain structure or anatomy. Considering that functional brain images do not normally convey detailed structural information and, thus, do not present an anatomically specific localization of functional activity, various image registration techniques are introduced in the literature for the purpose of mapping functional activity into an anatomical image or a brain atlas. The problems addressed by these techniques differ depending on the application and the type of analysis, i.e., single-subject versus group analysis. Functional to anatomical brain image registration is the core part of functional localization in most applications and is accompanied by intersubject and subject-to-atlas registration for group analysis studies. Cortical surface registration and automatic brain labeling are some of the other tools towards establishing a fully automatic functional localization procedure. While several previous survey papers have reviewed and classified general-purpose medical image registration techniques, this paper provides an overview of brain functional localization along with a survey and classification of the image registration techniques related to this problem.Index Terms-Brain functional localization, fMRI image processing, functional imaging, survey of image registration techniques.

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Section: B Volume Registrationmentioning

confidence: 99%

Section: B Volume Registrationmentioning

confidence: 99%

Section: Validationmentioning

confidence: 99%

Section: Validationmentioning

confidence: 99%

Section: Validationmentioning

confidence: 99%

See 3 more Smart Citations

Brain Functional Localization: A Survey of Image Registration Techniques

Gholipour

Kehtarnavaz

Briggs

et al. 2007

IEEE Trans. Med. Imaging

227

127

View full text Add to dashboard Cite

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The relationship between regional and inter‐regional functional connectivity deficits in schizophrenia

Zalesky

Fornito

Egan

et al. 2011

Human Brain Mapping

100

107

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While schizophrenia is frequently characterized as a disorder of disturbed functional connectivity, the causes and pathophysiological origins of such disturbances remain unclear. The aim of this study was to better elucidate the mechanistic causes of abnormal functional connectivity in schizophrenia, measured as the extent of temporal correlation between endogenous fluctuations recorded at anatomically discrete brain regions during resting-state functional MRI. An approach was developed to perform whole-brain connectivity mapping at the resolution of individual pairs of voxels, without the need for arbitrary parcellation of the cerebrum. Between-group connectivity reductions in 12 people diagnosed with schizophrenia and 15 age-, IQ-, and gender-matched healthy volunteers were localized to a distributed network including frontoparietal and occipitoparietal connections. The gray-matter regions comprising this disturbed network showed evidence of local reductions in both intra-regional homogeneity (29%-33% reduction) and signal power (40%-60% reduction). The extent to which inter-regional correlation was reduced between a pair of gray matter regions was found to be strongly correlated with the extent of local decoherence evident within the gray matter regions per se. This suggests measurement of aberrant functional connectivity in schizophrenia is both a measurement of altered coupling between regions as well as a measurement of local decoherence within regions.

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Are power calculations useful? A multicentre neuroimaging study

Suckling

Henty

Ecker

et al. 2014

Human Brain Mapping

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There are now many reports of imaging experiments with small cohorts of typical participants that precede large-scale, often multicentre studies of psychiatric and neurological disorders. Data from these calibration experiments are sufficient to make estimates of statistical power and predictions of sample size and minimum observable effect sizes. In this technical note, we suggest how previously reported voxel-based power calculations can support decision making in the design, execution and analysis of cross-sectional multicentre imaging studies. The choice of MRI acquisition sequence, distribution of recruitment across acquisition centres, and changes to the registration method applied during data analysis are considered as examples. The consequences of modification are explored in quantitative terms by assessing the impact on sample size for a fixed effect size and detectable effect size for a fixed sample size. The calibration experiment dataset used for illustration was a precursor to the now complete Medical Research Council Autism Imaging Multicentre Study (MRC-AIMS). Validation of the voxel-based power calculations is made by comparing the predicted values from the calibration experiment with those observed in MRC-AIMS. The effect of non-linear mappings during image registration to a standard stereotactic space on the prediction is explored with reference to the amount of local deformation. In summary, power calculations offer a validated, quantitative means of making informed choices on important factors that influence the outcome of studies that consume significant resources.

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Variable precision registration via wavelets: Optimal spatial scales for inter-subject registration of functional MRI

Cited by 12 publications

References 44 publications

Brain Functional Localization: A Survey of Image Registration Techniques

Brain Functional Localization: A Survey of Image Registration Techniques

The relationship between regional and inter‐regional functional connectivity deficits in schizophrenia

Are power calculations useful? A multicentre neuroimaging study

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