TY - GEN
T1 - Quantitative susceptibility map reconstruction via a total generalized variation regularization
AU - Yanez, Felipe
AU - Fan, Audrey
AU - Bilgic, Berkin
AU - Milovic, Carlos
AU - Adalsteinsson, Elfar
AU - Irarrazaval, Pablo
PY - 2013
Y1 - 2013
N2 - Quantitative susceptibility mapping (QSM) is a last decade new concept which allows to determine the magnetic susceptibility distribution of tissue in-vivo. Nowadays it has several applications such as venous blood oxygenation and iron concentration quantification. To reconstruct high quality maps, a regularized scheme must be used to solve this ill-posed problem, due to the dipole kernel under sampling k-space. A widely used regularization penalty is Total Variation (TV), however, we can find stair casing artifacts in reconstructions due to the assumption that images are piecewise constant, not always true in MRI. In this sense, we propose a less restrictive functional, to avoid this problem and to improve QSM quality. A second order Total Generalized Variation (TGV) does not assume piecewise constancy in the images and is equivalent to TV in terms of edge preservation and noise removal. This work describes how TGV penalty addresses an increase in imaging efficiency in magnetic susceptibility maps from numerical phantom and in-vivo data. Currently, we report higher specificity with the proposed regularization. Moreover, the robustness of TGV suggest that is a possible alternative to tissue susceptibility mapping.
AB - Quantitative susceptibility mapping (QSM) is a last decade new concept which allows to determine the magnetic susceptibility distribution of tissue in-vivo. Nowadays it has several applications such as venous blood oxygenation and iron concentration quantification. To reconstruct high quality maps, a regularized scheme must be used to solve this ill-posed problem, due to the dipole kernel under sampling k-space. A widely used regularization penalty is Total Variation (TV), however, we can find stair casing artifacts in reconstructions due to the assumption that images are piecewise constant, not always true in MRI. In this sense, we propose a less restrictive functional, to avoid this problem and to improve QSM quality. A second order Total Generalized Variation (TGV) does not assume piecewise constancy in the images and is equivalent to TV in terms of edge preservation and noise removal. This work describes how TGV penalty addresses an increase in imaging efficiency in magnetic susceptibility maps from numerical phantom and in-vivo data. Currently, we report higher specificity with the proposed regularization. Moreover, the robustness of TGV suggest that is a possible alternative to tissue susceptibility mapping.
KW - Brain
KW - Quantitative susceptibility mapping
KW - Total Generalized Variation
UR - http://www.scopus.com/inward/record.url?scp=84885213121&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84885213121&partnerID=8YFLogxK
U2 - 10.1109/PRNI.2013.59
DO - 10.1109/PRNI.2013.59
M3 - Conference contribution
AN - SCOPUS:84885213121
SN - 9780769550619
T3 - Proceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013
SP - 203
EP - 206
BT - Proceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013
T2 - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013
Y2 - 22 June 2013 through 24 June 2013
ER -