TY - GEN
T1 - A hybrid total-variation minimization approach to compressed sensing
AU - Wang, Yong
AU - Liang, Dong
AU - Chang, Yuchou
AU - Ying, Leslie
PY - 2012
Y1 - 2012
N2 - Compressed sensing (CS) has been successfully applied to accelerate conventional magnetic resonance imaging (MRI) with Fourier encoding. Total variation (TV) is usually used as the regularization function for image reconstruction. However, it is know that such ℓ 1-based minimization algorithm needs more measurements than the ℓ 0-based ones. On the other hand, ℓ 0-based minimization is computational intractable and unstable. In this paper, we propose a hybrid total variation (HTV) which effectively integrates both ℓ 1-norm and ℓ 0-norm of the image gradient by introducing a threshold. The HTV minimization algorithm has the benefits of both the robustness of ℓ 1 and fewer measurements of ℓ 0. Simulations and in vivo experiments demonstrate the proposed method outperforms the conventional TV minimization algorithm.
AB - Compressed sensing (CS) has been successfully applied to accelerate conventional magnetic resonance imaging (MRI) with Fourier encoding. Total variation (TV) is usually used as the regularization function for image reconstruction. However, it is know that such ℓ 1-based minimization algorithm needs more measurements than the ℓ 0-based ones. On the other hand, ℓ 0-based minimization is computational intractable and unstable. In this paper, we propose a hybrid total variation (HTV) which effectively integrates both ℓ 1-norm and ℓ 0-norm of the image gradient by introducing a threshold. The HTV minimization algorithm has the benefits of both the robustness of ℓ 1 and fewer measurements of ℓ 0. Simulations and in vivo experiments demonstrate the proposed method outperforms the conventional TV minimization algorithm.
KW - Compressed sensing
KW - hybrid total variation
KW - image reconstruction
KW - magnetic resonance imaging
KW - total variation
UR - https://www.scopus.com/pages/publications/84864832401
U2 - 10.1109/ISBI.2012.6235487
DO - 10.1109/ISBI.2012.6235487
M3 - Conference contribution
AN - SCOPUS:84864832401
SN - 9781457718588
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 74
EP - 77
BT - 2012 9th IEEE International Symposium on Biomedical Imaging
T2 - 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012
Y2 - 2 May 2012 through 5 May 2012
ER -