Highly undersampled peripheral Time-of-Flight magnetic resonance angiography: optimized data acquisition and iterative image reconstruction
The aim of this study was to investigate the acceleration of peripheral Time-of-Flight magnetic resonance angiography using Compressed Sensing and parallel magnetic resonance imaging (MRI) while preserving image quality and vascular contrast.
Materials and methods
An analytical sampling pattern is proposed that combines aspects of parallel MRI and Compressed Sensing. It is used in combination with a dedicated Split Bregman algorithm. This approach is compared with current state-of-the-art patterns and reconstruction algorithms.
The acquisition time was reduced from 30 to 2.5 min in a study using ten volunteer data sets, while showing improved sharpness, better contrast and higher accuracy compared to state-of-the-art techniques.
This study showed the benefits of the proposed dedicated analytical sampling pattern and Split Bregman algorithm for optimizing the Compressed Sensing reconstruction of highly accelerated peripheral Time-of-Flight data.
KeywordsIterative reconstruction Non-contrast-enhanced MRA Peripheral angiography Compressed Sensing
- 9.Aelterman J, Luong H, Goossens B, Pizurica A, Philips W (2010) COMPASS: a joint framework for parallel imaging and compressive sensing in MRI. In: Proceedings of the IEEE international conference on image processing (ICIP 2010), Hong Kong, China, Sept 26–29 2010, pp 1653–1656Google Scholar
- 10.Facchinei F, Pang J (2003) Finite-dimensional variational inequalities and complementarity problems, vol I and II. Springer, BerlinGoogle Scholar
- 11.Lustig M, Alley M, Vasanawala S, Donoho DL, Pauly JM (2009) L1SPIR-iT: autocalibrating parallel imaging compressed sensing. In: Proceedings of the annual meeting ISMRM, Honolulu, USA, April 18–24 2009, p 334Google Scholar
- 12.Osher R, Fatemi E (1992) Nonlinear total variation based noise removal algorithms. Phys D 60(1–2):259–268Google Scholar
- 19.Hutter J, Grimm R, Forman C, Hornegger J, Schmitt P (2012) Vessel adapted regularization for iterative reconstruction in MR angiography. In: Pipe J (ed) Proceedings of the 21st annual meeting of the ISMRM. Melbourne, Australia, May 5–11, 2012Google Scholar