Keywords: MR-Guided Focused Ultrasound, MR-Guided Interventions, MR-ARFI, image reconstruction, compressed sensing.
Motivation: Magnetic resonance acoustic radiation force imaging (MR-ARFI) is a promising tool for ultrasound localization in MR-guided ultrasound applications. To ensure image quality, repetitive ultrasound sonication is required and may cause inevitable neurological effects and energy deposition.
Goal(s): We aim to develop a reconstruction algorithm for highly under-sampled MR-ARFI.
Approach: The reconstruction is formulated by a constrained minimization problem regulated by the spatial sparsity of displacement image and data consistencies between ARFI images with opposite displacement encodings.
Results: Experimental results of retrospective and prospective under-sampling show that the proposed method is well-performed in terms of reconstruction error at acceleration rate as high as 10.
Impact: The proposed method can be exploited to achieve fast MR-ARFI at high under-sampling rate to reduce the ultrasound deposition and shorten the scanning time, which is crucial for the safety concern of ARFI application in human study.
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