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Micro X-ray computed tomography (μCT) is a promising technique, not only to visualise juveniles inside the bursae, but also to keep the sample intact and make the dataset of the scan available for future reference.
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The parametric search proposed in [16] requires a large number of datasets from the scan region to generate accurate estimates.
Analysis was performed with full experimental datasets of the five scans and with smoothed data and reduced TACs, respectively, as described under the 'Methods' section.
To build the atlas, we combined a dataset of 39 scans with already existing manual delineations of the whole brainstem and a dataset of 10 scans in which the brainstem structures were manually labeled with a protocol that was specifically designed for this study.
Datasets were analyzed in pairs, and the person responsible for segmenting each scan (AL) was blinded to the participants ID number and the timepoint of the scan.
Confirm the results of the scan.
The approach feasibility is demonstrated by using a training dataset of computer tomography scans from British subjects aged 25 106 years (75 male and 34 female).
Haxby dataset contains the fMRI scans of 6 subjects.
The dataset consists of subjects scanned at two time points and at each time point the DTI acquisition consists of two back-to-back repeats in the same scanning session.
The resulting maps show brain regions where activity across subjects was reliably correlated with a seed-voxel's time course while subjects performed the Vigilance Task scanning run, a dataset that was independent of the Fact Encoding Task scanning runs.
Quantitative evaluation is performed on a publicly available dataset of 82 patient CT scans using 4-fold cross-validation (CV).
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