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Table 1. Classes of Morphometric Methods. While not an exhaustive list, this table describes some key methods for analyzing MRI data. Each of these methods can be used to identify group differences in brain structure. [Abbreviations. VBM: voxel based morphometry; DBM: deformation based morphometry; TBM: tensor based morphometry]. Method Principle Methods Papers

in Automated Analysis Of
by Structural Mri Data, Paul Thompson Phd, Judith L. Rapoport Md, Tyrone D. Cannon Phd, Arthur W. Toga Phd, Stephen Lawrie, Eve C. Johnstone, Daniel Weinberger, Paul M. Thompson, Judith L. Rapoport, Tyrone D. Cannon, Arthur W. Toga
"... In PAGE 3: ... We describe the mathematical concepts underlying several common approaches, including voxel-based morphometry, deformation morphometry, and tensor-based morphometry, as well as shape modeling, and traditional volumetrics (see Fig. 1; Table1 summarizes these concepts).... In PAGE 25: ...ig. 1. Taxonomy of Methods for Analyzing MRI Data. This schematic illustrates six major types of analysis of structural images, showing some of the data used in each case (see Table1 for the key concepts underlying each method). Voxel based morphometry (VBM; top left panels) compares anatomy voxel by voxel to find voxels (shown here in blue) where the tissue classification (gray, white matter, CSF) depends on diagnosis or other factors.... ..."

Table 3: Coarse-to-fine multiscale tensor-based motion estimation

in A Coarse To Fine Multiscale Approach For Linear Least Squares Optical Flow Estimation
by F. Lauze, P. Kornprobst, E. Mémin
Cited by 1

Table 1. Classification Accuracy for Brain Maps and Stimuli

in Abstract Partially Distributed Representations of Objects and Faces in Ventral Temporal Cortex
by Alice J. O’toole, Fang Jiang, Hervé Abdi, James V. Haxby
"... In PAGE 3: ... Thus, the measure assesses the separability of the 2 classes of scans by combining classification success on both categories of objects simultaneously. Brain Scan Discriminability by Category The moderate to high classification accuracy for all pos- sible pairs of object categories ( Table1 ) replicates the performance levels reported previously for these data using a correlation-based classification algorithm with individual category identification measures (Haxby et al., 2001).... In PAGE 3: ..., 2001), houses and faces were discriminated most accurately. The range of d0 we found for category pair discriminations indicates sufficient variation to make use of the confusability matrix in Table1 as a standard for evaluating an analogously derived computational as- sessment of object category structure. The PC displayed in Figure 1 achieved a high degree of separation between face and house brain maps (d0 = 3.... In PAGE 6: ... This assumption was met for this stimulus set, as the objects were sufficiently aligned to achieve highly accurate classification without these transformations. The results of the simulation indicated that the ob- ject categories used in the fMRI experiment, like the brain scan categories, are highly, although not homo- geneously, discriminable (see Table1 ). As was seen for the brain-map discriminations, faces and houses were the categories discriminated most accurately.... In PAGE 6: ..., 2001) included images of objects taken from different view- points (Figure 2). As seen in Table1 , the algorithm Figure 2. Example chair stimuli from neuroimaging experiment and simulations show the range of view variations in the data set.... ..."

Table 1 Diffusion Coefficients of Water in Human Brain (31023 mm2/s)*

in Diffusion Tensor Imaging: Concepts and Applications
by Hughes Chabriat, et al.

Table 2 Overview of morphometry cell nuclei descriptors used in the study Morphometry

in Summary
by Dimitris K. Tasoulis A, Panagiota Spyridonos C, Nicos G. Pavlidis A, Vassilis P. Plagianakos A, Panagiota Ravazoula D, Georgios Nikiforidis C, Michael N. Vrahatis A 2006

Table 4. Results of Voxel-Based Morphometry

in Functional and Structural Alterations of the Intraparietal Sulcus in a Developmental Dyscalculia of Genetic Origin
by Nicolas Molko, Arnaud Cachia, Denis Rivière, Jean-françois Mangin, Marie Bru, Denis Le Bihan, Laurent Cohen, Stanislas Dehaene Inserm U, Unité De Neuro-activation Fonctionnelle, Service Hospitalier, Frédéric Joliot, Service De Neurologie, Hôpital Pitié-salpétrière
"... In PAGE 7: ... fMRI revealed a functional correlate We also analyzed our data for differences in voxel-by- voxel gray matter density. The result of this analysis is of the arithmetic impairment: there was an insufficient recruitment of the right intraparietal sulcus as a function summarized in Table4 . After restriction ofthe analysis to the parietal lobe, only a small and marginally significant of number size.... ..."

Table 4. Longitudinal eigenvalues, Stabilator trimmed case

in Cg/Stability Map for the Reference H Cycle 3 Supersonic Transport Concept Along the High Speed Research Baseline Mission Profile
by Daniel Giesy And, Daniel P. Giesy, David M. Christhilf
"... In PAGE 34: ...1204 -1.2215 Table4 (continued). Longitudinal eigenvalues, Stabilator trimmed case... ..."

Table 4. Longitudinal eigenvalues, Stabilator trimmed case

in Cg/Stability Map for the Reference H Cycle 3 Supersonic Transport Concept Along the High Speed Research Baseline Mission Profile
by Daniel Giesy And, High Speed, Mission Profile, Daniel P. Giesy, David M. Christhilf
"... In PAGE 34: ...1204 -1.2215 Table4 (continued). Longitudinal eigenvalues, Stabilator trimmed case... ..."

Table 2 The RMS of the standard deviations of the homogenous areas for the original and filtered MRI datasets used in our experiments Heart Brain Whole body MRCP

in MRI diffusion-based filtering: A note on performance characterisation
by Ovidiu Ghita, Kevin Robinson, Michael Lynch, Paul F. Whelan 2004

TABLE 1. Changes in Brain and Lesion Volumes Shown by Magnetic Resonance Imaging (MRI) Scans Taken 4 Years Apart in a Patient With Possible Vascular Dementia

in unknown title
by unknown authors
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