Suhyung Park1, Jaeseok Park1
1Department of Brain and Cognitive Engineering, Korea University, Seoul, Korea, Republic of
Recently, several imaging techniques for combination of compressed sensing (CS) and parallel imaging (PI) have shown the possibility that can reduce total acquisition time and improve temporal and spatial resolution. Among them, approach proposed by Sung et al., which separated reconstruction methods in k-space, showed improved image quality compared to other methods. However, this method was vulnerable to image-degrading artifacts due to signal discontinuity occurring in boundary not only between high frequency sub-sections in k-space but also between CS and PI reconstruction data. In this work, we propose improved high frequency CS and new reconstruction method optimally synthesizing CS and PI data.