Abstract #1804

Accelerated Real-Time MR Thermometry Using a New Compressed Sensing Framework of Nonlinear Filter and K-T FOCUSS

Feiyu Chen¹, Xiaoying Cai¹, Xinwei Shi¹, Shuo Chen², Enhao Gong³, Kui Ying², Shi Wang²

¹Department of Biomedical Engineering, Tsinghua University, Beijing, China; ²Department of Engineering Physics, Tsinghua University, Beijing, China; ³Electrical Engineering, Stanford University, Stanford, CA, United States

Phase information is significant in temperature mapping using proton resonance frequency shift (PRFS) method. Acceleration methods can be applied to reconstruction in order to shorten the imaging duration and accomplish real-time temperature mapping. A method to improve the accuracy of phase reconstruction in dynamic scans is proposed in our research. Compressed Sensing with nonlinear filters such as median filter and k-t FOCUSS are combined in our method. Phantom experiments have demonstrated that the proposed method is a promising tool for real-time temperature monitoring using PRFS method.