Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the
Biochimica et biophysica acta, 1863(1), 56-63 (2015-10-04)
Hyperspectral imaging uses spectral and spatial image information for target detection and classification. In this work hyperspectral autofluorescence imaging was applied to patient olfactory neurosphere-derived cells, a cell model of a human metabolic disease MELAS (mitochondrial myopathy, encephalomyopathy, lactic acidosis
Physics in medicine and biology, 60(14), 5543-5556 (2015-07-03)
In the context of investigating the potential of low-dose PET imaging for screening applications, we developed methods to assess small lesion detectability as a function of the number of counts in the scan. We present here our methods and preliminary
Quarterly journal of experimental psychology (2006), 68(8), 1623-1642 (2015-02-20)
Subjective ratings for age of acquisition, concreteness, affective valence, and many other variables are an important element of psycholinguistic research. However, even for well-studied languages, ratings usually cover just a small part of the vocabulary. A possible solution involves using
Class prediction models have been shown to have varying performances in clinical gene expression datasets. Previous evaluation studies, mostly done in the field of cancer, showed that the accuracy of class prediction models differs from dataset to dataset and depends
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