MRI2MRI weights for transformations between T1-weighted and T2-weighted MRI images
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Xiao, Sa
Lee, Aaron
Rokem, Ariel
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Abstract
Different brain MRI contrasts represent different tissue properties and are sensitive to different artifacts. The relationship between different contrasts is therefore complex and nonlinear. We developed a deep convolutional network that learns the mapping between different MRI contrasts. Using a publicly available dataset, we demonstrate that this algorithm accurately transforms between T1- and T2-weighted images, proton density images, time-of-flight angiograms, and diffusion MRI images. We demonstrate that these transformed images can be used to improve spatial registration between MR images of different contrasts.
Description
These are the learned pytorch weights for these transformations
