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Abstract #4535

Noise Reduction and Uncertainty Estimation for the Variable Flip Angle T1 Method with Automatic Selection of Regularization Parameters

Anders Garpebring1, Max Hellström1, Mikael Bylund1, and Tommy Löfstedt1

1Radiation Sciences, Umeå University, Umeå, Sweden

The purpose of this work was to develop a method that simultaneously reduces and estimates the uncertainty in the T1 maps obtained with the VFA method while also avoiding the need for any manual tuning of regularization parameters. A Markov Chain Monte Carlo-based algorithm was implemented and evaluated on real and synthetic data. The results show that the method can be used to reduce both noise and noise-induced bias and simultaneously give information about the uncertainty in the estimates.

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