The Experts below are selected from a list of 86889 Experts worldwide ranked by ideXlab platform
Christian Gaser - One of the best experts on this subject based on the ideXlab platform.
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Structural MRI: Morphometry
Neuroeconomics, 2016Co-Authors: Christian GaserAbstract:Human brains are characterised by considerable intersubject anatomical variability, which is of interest in both clinical practice and research. Computational Morphometry of magnetic resonance images has emerged as the method of choice for studying macroscopic changes in brain structure. Magnetic resonance imaging not only allows the acquisition of images of the entire brain in vivo but also the tracking of changes over time using repeated measurements, while computational Morphometry enables the automated analysis of subtle changes in brain structure. In this section, several voxel-based morphometric methods for the automated analysis of brain images are presented. In the first part, some basic principles and techniques are introduced, while deformation- and voxel-based Morphometry are discussed in the second part.
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magnetic resonance based Morphometry a window into structural plasticity of the brain
Current Opinion in Neurology, 2006Co-Authors: Christian GaserAbstract:PURPOSE OF REVIEW: In contrast to traditional anatomical and pathological methods, magnetic resonance Morphometry of the brain allows the in-vivo study of temporal changes in brain morphology and the correlation of brain morphology with brain function. Magnetic resonance Morphometry has thereby recently emerged as one of the most promising fields in clinical neuroscience. This review covers the last 3 years, which have witnessed remarkable progress in this alluring new field. RECENT FINDINGS: Next to the detection of structural differences in grey and white matter in a number of brain diseases, a very important recent finding of magnetic resonance-based Morphometry is the discovery of the brain's ability to alter its shape within weeks, reflecting structural adaptation to physical and mental activity. Consequently, magnetic resonance Morphometry promises to be a powerful method to study disease states of the brain and to track the effects of novel therapies. SUMMARY: Despite these fascinating prospects, the results of morphometric studies are still dependent on the properties of the individual magnetic resonance scanner, which renders pooling of data almost impossible. It is also not known what the structural plasticity is based on at the histological or cellular level. Once these obstacles are overcome, magnetic resonance-based Morphometry will become a powerful method for multicenter and therapeutic trials of several brain diseases.
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Magnetic resonance-based Morphometry: a window into structural plasticity of the brain.
Current opinion in neurology, 2006Co-Authors: Arne May, Christian GaserAbstract:Purpose of reviewIn contrast to traditional anatomical and pathological methods, magnetic resonance Morphometry of the brain allows the in-vivo study of temporal changes in brain morphology and the correlation of brain morphology with brain function. Magnetic resonance Morphometry has thereby recent
Karl J Friston - One of the best experts on this subject based on the ideXlab platform.
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voxel based Morphometry
Reference Module in Neuroscience and Biobehavioral Psychology#R##N#Encyclopedia of Neuroscience, 2009Co-Authors: John Ashburner, Karl J FristonAbstract:At its simplest, voxel-based Morphometry (VBM) involves a voxelwise comparison of regional gray matter ‘density’ between two groups of subjects. Density here refers to the relative amount of gray matter and should not be confused with cell packing density (number of cells per unit volume of neuropil). The procedure is relatively straightforward and involves spatially normalizing and segmenting high-resolution magnetic resonance images into the same stereotaxic space. These gray matter segments are then smoothed to a spatial scale at which differences are expressed (usually approximately 8 mm). Voxelwise parametric statistical tests are performed, which compare the smoothed gray matter images from the groups using statistical parametric mapping. Corrections for multiple comparisons are generally made using the theory of random fields.
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voxel based Morphometry
In: Statistical Parametric Mapping: The Analysis of Functional Brain Images. (pp. 92-98). (2007), 2007Co-Authors: John Ashburner, Karl J FristonAbstract:At its simplest, voxel-based Morphometry (VBM) involves a voxel-wise comparison of regional grey-matter ‘density’ between two groups of subjects. The procedure is relatively straightforward, and involves spatially normalizing and segmenting high-resolution magnetic resonance (MR) images into the same stereotaxic space. These grey-matter segments are then smoothed to a spatial scale at which differences are expressed (usually about 12 mm). Voxel-wise parametric statistical tests are performed, which compare the smoothed grey-matter images from the groups using statistical parametric mapping. Corrections for multiple comparisons are generally made using the theory of random fields.
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Why voxel-based Morphometry should be used.
NeuroImage, 2001Co-Authors: John Ashburner, Karl J FristonAbstract:Thisarticle has been written in response to Dr. Fred L. Bookstein's article entitled ‘“Voxel-Based Morphometry” Should Not Be Used with Imperfectly Registered Images’ in this issue of NeuroImage. We will address three main issues: (i) Dr. Bookstein appears to have misunderstood the objective of voxel-based Morphometry (VBM) and the nature of the continuum we referred to. (ii) We agree with him when he states that findings from VBM can pertain to systematic registration errors during spatial normalization. (iii) His argument about voxelwise tests on smooth data holds in the absence of error variance, but is of no consequence when using actual data. We first review the tenets of VBM, paying particular attention to the relationship between VBM and tensor-based Morphometry. The last two sections of this response deal with the specific concerns raised by Dr. Bookstein.
Clare E Mackay - One of the best experts on this subject based on the ideXlab platform.
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regional deficits in brain volume in schizophrenia a meta analysis of voxel based Morphometry studies
American Journal of Psychiatry, 2005Co-Authors: Robyn A Honea, T J Crow, Dick Passingham, Clare E MackayAbstract:OBJECTIVE: Voxel-based Morphometry is a method for detecting group differences in the density or volume of brain matter. The authors reviewed the literature on use of voxel-based Morphometry in schizophrenia imaging research to examine the capabilities of this method for clearly identifying specific structural differences in patients with schizophrenia, compared with healthy subjects. The authors looked for consistently reported results of relative deficits in gray and white matter in schizophrenia and evaluated voxel-based Morphometry methods in order to propose a future strategy for using voxel-based Morphometry in schizophrenia research. METHOD: The authors reviewed all voxel-based Morphometry studies of schizophrenia that were published to May 2004 (15 studies). The studies included a total of 390 patients with a diagnosis of schizophrenia and 364 healthy volunteers. RESULTS: Gray and white matter deficits in patients with schizophrenia, relative to healthy comparison subjects, were reported in a tota...
Julien Cohen-adad - One of the best experts on this subject based on the ideXlab platform.
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Axons Morphometry in the human spinal cord.
NeuroImage, 2018Co-Authors: Tanguy Duval, Ariane Saliani, Harris Nami, Antonio Nanci, Nikola Stikov, Hugues Leblond, Julien Cohen-adadAbstract:Due to the technical challenges of large-scale microscopy and analysis, to date only limited knowledge has been made available about axon Morphometry (diameter, shape, myelin thickness, volume fraction), thereby limiting our understanding of neuronal microstructure and slowing down research on neurodegenerative pathologies. This study addresses this knowledge gap by establishing a state-of-the-art acquisition and analysis framework for mapping axon Morphometry, and providing the first comprehensive mapping of axon Morphometry in the human spinal cord. We dissected, fixed and stained a human spinal cord with osmium tetroxide, and used a scanning electron microscope to image the entirety of 23 axial slices, covering C1 to L5 spinal levels. An automatic method based on deep learning was then used to segment each axon and myelin sheath to produce maps of axon Morphometry. These maps were then registered to a standard spinal cord magnetic resonance imaging (MRI) template. Between 500,000 (lumbar) and 1 million (cervical) myelinated axons were segmented at each level of this human spinal cord. Morphometric features show a large disparity between tracts, but high right-left symmetry. Our results suggest a modality-based organization of the dorsal column in the human, as it has been observed in the rat. The generated axon Morphometry template is publicly available at https://osf.io/8k7jr/ and could be used as a reference for quantitative MRI studies. The proposed framework for axon Morphometry mapping could be extended to other parts of the central or peripheral nervous system that exhibit coherently-oriented axons.
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Axons Morphometry in the human spinal cord
2018Co-Authors: Tanguy Duval, Ariane Saliani, Harris Nami, Antonio Nanci, Nikola Stikov, Hugues Leblond, Julien Cohen-adadAbstract:Abstract Due to the technical challenges of large-scale microscopy and analysis, to date only limited knowledge has been made available about axon Morphometry (diameter, shape, myelin thickness, density), thereby limiting our understanding of neuronal microstructure and slowing down research on neurodegenerative pathologies. This study addresses this knowledge gap by establishing a state-of-the-art acquisition and analysis framework for mapping axon Morphometry, and providing the first comprehensive mapping of axon Morphometry in the human spinal cord. We dissected, fixed and stained a human spinal cord with osmium, and used a scanning electron microscope to image the entirety of 24 axial slices, covering C1 to L5 spinal levels. An automatic method based on deep learning was then used to segment each axon and myelin sheath which, producing maps of axon Morphometry. These maps were then registered to a standard spinal cord magnetic resonance imaging (MRI) template. Between 500,000 (lumbar) and 1 million (cervical) myelinated axons were segmented at each level of this human spinal cord. Morphometric features show a large disparity between tracts, but remarkable right-left symmetry. Results confirm the modality-based organization of the dorsal column in the human, as been observed in the rat. The generated axon Morphometry template is publicly available at https://osf.io/8k7jr/ and could be used as a reference for quantitative MRI studies. The proposed framework for axon Morphometry mapping could be extended to other parts of the central or peripheral nervous system.
Giuseppe Guglielmi - One of the best experts on this subject based on the ideXlab platform.
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Vertebral Morphometry.
Radiologic clinics of North America, 2010Co-Authors: Daniele Diacinti, Giuseppe GuglielmiAbstract:Visual semiquantitative (SQ) assessment of the radiographs by a trained and experienced observer is the "gold standard" method to detect vertebral fractures. Vertebral Morphometry is a quantitative method to identify osteoporotic vertebral fractures based on the measurement of vertebral heights. Vertebral Morphometry may be performed on conventional spinal radiographs (MRX: morphometric x-ray radiography) or on images obtained from dual x-ray absorptiometry (DXA) scans (MXA: morphometric x-ray absorptiometry). Vertebral fracture assessment (VFA) indicates the method for identification of the vertebral fractures using lateral spine views acquired by DXA, with low-dose exposition. For epidemiologic studies and clinical drug trials in osteoporosis research but also in clinical practice, the preferred method is radiographic SQ assessment., because an expert eye can better distinguish between true fractures and vertebral anomalies than can quantitative Morphometry. However, vertebral Morphometry, calculating the deformity of overall thoracic and lumbar spine, may supply useful data about the vertebral fracture risk. VFA performed during routine densitometry allows identification, by visual or morphometric methods, of most osteoporotic vertebral fractures, even those that are asymptomatic.
