Structural adaptive segmentation for statistical parametric mapping
نویسندگان
چکیده
منابع مشابه
Structural adaptive segmentation for statistical parametric mapping
Functional Magnetic Resonance Imaging inherently involves noisy measurements and a severe multiple test problem. Smoothing is usually used to reduce the effective number of multiple comparisons and to locally integrate the signal and hence increase the signal-to-noise ratio. Here, we provide a new structural adaptive segmentation algorithm (AS) that naturally combines the signal detection with ...
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1. INTRODUCTION This chapter is about making regionally specific inferences in neuroimaging. These inferences may be about differences expressed when comparing one group of subjects to another or, within subjects, over a sequence of observations. They may pertain to structural differences (e.g. in voxel-based morphometry-Ashburner and Friston 2000) or neurophysiological indices of brain functio...
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چکیده ندارد.
15 صفحه اولWSPM: Wavelet-based statistical parametric mapping
Recently, we have introduced an integrated framework that combines wavelet-based processing with statistical testing in the spatial domain. In this paper, we propose two important enhancements of the framework. First, we revisit the underlying paradigm; i.e., that the effect of the wavelet processing can be considered as an adaptive denoising step to "improve" the parameter map, followed by a s...
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ژورنال
عنوان ژورنال: NeuroImage
سال: 2010
ISSN: 1053-8119
DOI: 10.1016/j.neuroimage.2010.04.241