نتایج جستجو برای: voxel model
تعداد نتایج: 2115264 فیلتر نتایج به سال:
We develop a novel statistical model, called multiscale adaptive regression model (MARM), for spatial and adaptive analysis of neuroimaging data. The primary motivation and application of the proposed methodology is statistical analysis of imaging data on the two-dimensional (2D) surface or in the 3D volume for various neuroimaging studies. The existing voxel-wise approach has several major lim...
Neuroimaging datasets often have a very large number of voxels and a very small number of training cases, which means that overfitting of models for this data can become a very serious problem. Working with a set of fMRI images from a study on stroke recovery, we consider a classification task for which logistic regression performs poorly, even when L1or L2regularized. We show that much better ...
The acquisition of sub-sampled data from an array of receiver coils has become a common means of reducing data acquisition time in MRI. Of the various techniques used in parallel MRI, SENSitivity Encoding (SENSE) is one of the most common, making use of a complex-valued weighted least squares estimation to unfold the aliased images. It was recently shown in Bruce et al. [Magn. Reson. Imag. 29(2...
In this paper we investigate the advantages of using hexagonal grids in raster and volume graphics. In 2D, we present a hexagonal graphical model based on a hexagonal grid. In 3D, we introduce two honeycomb graphical models in which the voxels are hexagonal prisms, and we show that these are the only possible models under certain reasonable conditions. In the framework of the proposed models, w...
Two important tools for manipulating polygonal models are simplification and repair and we present voxel-based methods for performing both of these tasks. We describe a method for converting polygonal models to a volumetric representation in a way that handles models with holes, double walls, and intersecting parts. This allows us to perform polygon model repair simply by converting a model to ...
An unsupervised model-based strategy for bias field correction is proposed. We assume that information (in the sense of the information theory) in the corrupted image is greater than that in the uncorrupted one. The method exploits the fact that neighboring voxels are highly correlated to correct the bias field using a linear model.
When developing statistical models of normal brain perfusion, two questions are of crucial interest: How well does an atlas describe normality and how sensitive is it at detecting abnormalities? In this work we attempt to find partial responses to these questions by extensively experimenting with our local database of SPECT images of normal subjects, systematically synthesizing abnormalities an...
New techniques to measure 2-D and 3-D visibility over urban spaces are presented in this paper. The concept of ‘isovist’, i.e. the visible space from a vantage point, could help in providing a quantifiable basis for Kevin Lynch's urban analysis, as outlined in his book The Image of the City. We also expand on the concept of 3-D isovists and develop a new technique to calculate them on Digital E...
Due to phase imperfections, voxel time course measurements are complex valued. However, most fMRI studies measure activation using magnitude-only time courses. We show that magnitude-only analyses are equivalent to a complex fMRI activation model in which the phase is unrestricted, or allowed to dynamically change over time. This suggests that improvements to the magnitude-only model are possib...
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