A feasibility study for compressed sensing combined phase contrast MR angiography reconstruction

Dong-Hoon Lee; Cheol-Pyo Hong; Man-Woo Lee; Bong-Soo Han

doi:10.1117/12.911788

24 February 2012 A feasibility study for compressed sensing combined phase contrast MR angiography reconstruction

Dong-Hoon Lee, Cheol-Pyo Hong, Man-Woo Lee, Bong-Soo Han

Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83144O (2012) https://doi.org/10.1117/12.911788
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Phase contrast magnetic resonance angiography (PC MRA) is a technique for flow velocity measurement and vessels visualization, simultaneously. The PC MRA takes long scan time because each flow encoding gradients which are composed bipolar gradient type need to reconstruct the angiography image. Moreover, it takes more image acquisition time when we use the PC MRA at the low-tesla MRI system. In this study, we studied and evaluation of feasibility for CS MRI reconstruction combined PC MRA which data acquired by low-tesla MRI system. We used non-linear reconstruction algorithm which named Bregman iteration for CS image reconstruction and validate the usefulness of CS combined PC MRA reconstruction technique. The results of CS reconstructed PC MRA images provide similar level of image quality between fully sampled reconstruction data and sparse sampled reconstruction using CS technique. Although our results used half of sampling ratio and do not used specification hardware device or performance which are improving the temporal resolution of MR image acquisition such as parallel imaging reconstruction using phased array coil or non-cartesian trajectory, we think that CS combined PC MRA technique will be helpful to increase the temporal resolution and at low-tesla MRI system.

Citation Download Citation

Dong-Hoon Lee, Cheol-Pyo Hong, Man-Woo Lee, and Bong-Soo Han "A feasibility study for compressed sensing combined phase contrast MR angiography reconstruction", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83144O (24 February 2012); https://doi.org/10.1117/12.911788

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