Andrew G. Scoggins

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Image labeling and parcellation (i.e., assigning structure to a collection of voxels) are critical tasks for the assessment of volumetric and morphometric features in medical imaging data. The process of image labeling is inherently error prone as images are corrupted by noise and artifacts. Even expert interpretations are subject to subjectivity and the(More)
Labeling or parcellation of structures of interest on magnetic resonance imaging (MRI) is essential in quantifying and characterizing correlation with numerous clinically relevant conditions. The use of statistical methods using automated methods or complete data sets from several different raters have been proposed to simultaneously estimate both rater(More)
Labels that identify specific anatomical and functional structures within medical images are essential to the characterization of the relationship between structure and function in many scientific and clinical studies. Automated methods that allow for high throughput have not yet been developed for all anatomical targets or validated for exceptional(More)
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