Isotropic multichannel total variation framework for joint reconstruction of multicontrast parallel MRI
This work addresses the challenge of improving image quality and reducing scan times in multicontrast parallel MRI, potentially enhancing patient comfort, though it appears incremental as it builds on existing total variation and compressed sensing techniques.
The authors tackled the problem of combining multicontrast, multicoil, and compressed sensing in MRI reconstruction by introducing an isotropic multicontrast total variation regularizer, which outperformed state-of-the-art methods in preserving rotation-invariance, suppressing noise and artifacts, and preventing intercontrast leakage at aggressive undersampling rates.
Purpose: To develop a synergistic image reconstruction framework that exploits multicontrast (MC), multicoil, and compressed sensing (CS) redundancies in magnetic resonance imaging (MRI). Approach: CS, MC acquisition, and parallel imaging (PI) have been individually well developed, but the combination of the three has not been equally well studied, much less the potential benefits of isotropy within such a setting. Inspired by total variation theory, we introduce an isotropic MC image regularizer and attain its full potential by integrating it into compressed MC multicoil MRI. A convex optimization problem is posed to model the new variational framework and a first-order algorithm is developed to solve the problem. Results: It turns out that the proposed isotropic regularizer outperforms many of the state-of-the-art reconstruction methods not only in terms of rotation-invariance preservation of symmetrical features, but also in suppressing noise or streaking artifacts, which are normally encountered in PI methods at aggressive undersampling rates. Moreover, the new framework significantly prevents intercontrast leakage of contrast-specific details, which seems to be a difficult situation to handle for some variational and low-rank MC reconstruction approaches. Conclusions: The new framework is a viable option for image reconstruction in fast protocols of MC parallel MRI, potentially reducing patient discomfort in otherwise long and time-consuming scans.