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Multi-atlas segmentation is an effective approach for automatically labeling objects of interest in biomedical images. In this approach, multiple expert-segmented example images, called atlases, are registered to a target image, and deformed atlas segmentations are combined using label fusion. Among the proposed label fusion strategies, weighted voting with(More)
We present and evaluate a new method for automatically labeling the subfields of the hippocampal formation in focal 0.4 × 0.5 × 2.0mm(3) resolution T2-weighted magnetic resonance images that can be acquired in the routine clinical setting with under 5 min scan time. The method combines multi-atlas segmentation, similarity-weighted voting, and a novel(More)
The median (MR) and dorsal raphe (DR) nuclei contain the majority of the 5-hydroxytryptamine (5-HT, serotonin) neurons that project to limbic forebrain regions, are important in regulating homeostatic functions and are implicated in the etiology and treatment of mood disorders and schizophrenia. The primary synaptic inputs within and to the raphe are(More)
Recently, there has been a growing effort to analyze the morphometry of hippocampal subfields using both in vivo and postmortem magnetic resonance imaging (MRI). However, given that boundaries between subregions of the hippocampal formation (HF) are conventionally defined on the basis of microscopic features that often lack discernible signature in MRI,(More)
We propose a simple strategy to improve automatic medical image segmentation. The key idea is that without deep understanding of a segmentation method, we can still improve its performance by directly calibrating its results with respect to manual segmentation. We formulate the calibration process as a bias correction problem, which is addressed by machine(More)
UNLABELLED Newborn neurons enter an extended maturation stage, during which they acquire excitability characteristics crucial for development of presynaptic and postsynaptic connectivity. In contrast to earlier specification programs, little is known about the regulatory mechanisms that control neuronal maturation. The Pet-1 ETS (E26(More)
We develop a semi-automatic technique for segmentation of hippocampal subfields in T2-weighted in vivo brain MRI. The technique takes the binary segmentation of the whole hip-pocampus as input, and automatically labels the subfields inside the hippocampus segmentation. Shape priors for the hip-pocampal subfields are generated from shape-based normal-ization(More)
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