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Abstract #1427

Flexible convex optimization with non-smooth regularizations for accelerated MRI reconstructions

Renjie He1, Ruobing He2, Guobing Li1, Nan Liu1, Renkuan Zhai1, Ding Yu1, Qi Liu1, Jian Xu1, and Weiguo Zhang1

1United-Imaging Healthcare America, Houston, TX, United States, 2Indiana University School of Medicine, Fort Wayne, IN, United States

Convex optimization with non-smooth regularizers has recently gained increased interest as it has shown excellent performance and the ability to facilitate most of reconstruction problems in MR convincible. While there are many approaches towards its fulfillment, a flexible yet easy and comprehensive to realize method is always beneficial. One of the algorithms is proposed in this abstract. and we demonstrate that this algorithm can be easily adapted to many reconstruction problems in MRI with accelerated performance.

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