Oliver Maier1, Markus Bödenler1,2, Rudolf Stollberger1,3, Mary-Joan MacLeod4, Lionel M Broche5, and Hermann Scharfetter1
1Graz University of Technology, Graz, Austria, 2Institute of eHealth, University of Applied Sciences FH JOANNEUM, Graz, Austria, 3BioTechMed Graz, Graz, Austria, 4Acute Stroke Unit, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, 5Aberdeen Biomedical Imaging Centre, Univeresity of Aberdeen, Aberdeen, United Kingdom
1Graz University of Technology, Graz, Austria, 2Institute of eHealth, University of Applied Sciences FH JOANNEUM, Graz, Austria, 3BioTechMed Graz, Graz, Austria, 4Acute Stroke Unit, Aberdeen Royal Infirmary, Aberdeen, United Kingdom, 5Aberdeen Biomedical Imaging Centre, Univeresity of Aberdeen, Aberdeen, United Kingdom
FFC
imaging suffers from poor SNR and long scan times due to the lower
field strengths used (0.2 T - 50 µT), impairing clinical utility. Model-based
reconstruction can overcome this drawbacks, giving a huge reduction in noise and reveals previously
unseen details in low field T1 maps of FFC data.
Figure
3: Comparison of T1 maps obtained with standard fitting
(top) and the proposed method (bottom) for all three evolution
fields. One can clearly see the lesion in the low field T1
maps. The proposed method is able to reduce noise in all T1
maps and enables a clear distinction of the lesion.
Figure
2: Reference T1 maps (top) and reconstruction results for
simple non-linear least squares fitting (standard, bottom left)
compared with the proposed model-based reconstruction and fitting
algorithm (bottom right).