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阿德莱德Adelaide代写Essay:核磁共振成像
2020-01-10 13:18

阿德莱德Adelaide代写Essay:核磁共振成像
The role of magnetic resonance imaging (MRI) in assessing brain architecture has become increasingly popular among neuroscientists studying the complex nature of the brain. This non-invasive tool has enabled the in-vivo investigation of spatially varying patterns that occur over time as a function of normal development and aging as well as in the perturbation of this trajectory in the presence of disease. The multi-modal nature of MRI has allowed for the assessment of brain morphology, connectivity, and function and the precision of this technology has only increased with time. Moreover, the association of these measurements with genetic and cognitive indices has propelled our understanding of the synergistic interplay between brain structure and function. Among these implementations lies structural MRI, a modality that allows for the quantification of density, volume, and thickness of grey and white matter within the brain. These macroscopic anatomical changes are thought to be an outcome of the microscopic changes occurring at the neuronal and synaptic level ultimately shedding light on the biological processes driving a disease or function (Tardif et al., 2016). Voxel based morphometry, a technique that utilizes structural MRI, has been instrumental in comparing local gray matter concentrations between different groups of interest .Voxel-based morphometry(VBM) involves a number of steps in order to ensure that regional differences between groups are initially comparable in their spatial location. The methodological steps described below have been described at length in Ashburner et al., 2000. To summarize, the first step of the pipeline involves pre-processing the images so that they are realigned and normalized to a standard template space where all resulting images will occupy the same 3D coordinates. This is performed by estimating the optimum 12-parameter affine transformations where images are scaled, rotated, translated, or sheared accordingly. Prior knowledge of variability in brain size is used to constrain maximum estimates. A second step is taken to account for global nonlinear shape differences by implementing a linear combination of smooth spatial basis functions and then by calculating the coefficients of the functions that minimize the difference between the template and the subject image while maximizing the smoothness of the deformations.
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