Abstract
We propose a new method to improve T 1 mapping with respect to the popular DESPOT1 algorithm. A distance function is defined to model the distance between the pure signal and the measurements in presence of noise. We use a constrained gradient descent optimization algorithm to iteratively find the optimal values of T 1 and M 0. The method is applied to MR images acquired with 2 gradient echo sequences and different flip angles. The performance of T 1 mapping is evaluated both on phantom and on in vivo experiments.
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Cao, F., Commowick, O., Bannier, E., Ferré, JC., Edan, G., Barillot, C. (2012). MRI Estimation of T 1 Relaxation Time Using a Constrained Optimization Algorithm. In: Yap, PT., Liu, T., Shen, D., Westin, CF., Shen, L. (eds) Multimodal Brain Image Analysis. MBIA 2012. Lecture Notes in Computer Science, vol 7509. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33530-3_18
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DOI: https://doi.org/10.1007/978-3-642-33530-3_18
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