Adaptive Tissue Cluster Tracking on Quantitative MRI for Fully Automatic Brain Segmentation on Young Children
Marcel Warntjes1,2, Suraj Serai3, James Leach3, and Blaise Jones3
1Center for Medical Imaging Science and Visualization, Linköping, Sweden, 2SyntheticMR AB, Linköping, Sweden, 3Department of radiology, Cincinnati, OH, United States
Brain
tissue properties change rapidly during the first few years of life. This poses
a problem for brain segmentation algorithms since adult tissue definitions for
white matter and grey matter do not apply for young children. An automatic
tissue cluster tracking algorithm was developed to determine WM and GM cluster
positions in a 3-dimensional search-space of quantitative R1 relaxation rate,
R2 relaxation rate and proton density. These positions are then used to segment
the brain, independent of age.
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