Subspace constrained T2 mapping uses PCA to reconstruct a few principal components instead of all the echo train images before T2 fitting. The temporal (contrast) subspace in these methods is estimated either from acquired training data or via training curves from a signal model. Typically, a single global PC basis is used for all the contrast signals. In this work we present a T2 mapping method based on non-local clustering of signal relaxation curves and tailor the PC bases for the curves in each cluster and compare it with the global PC basis approach.
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