| Literature DB >> 28840445 |
Heyan Huang1, Hang Yang2, Kang Wang3.
Abstract
Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.Keywords: Compressive sensing; Guided filter; Image reconstruction; Magnetic resonance imaging
Mesh:
Year: 2017 PMID: 28840445 DOI: 10.1007/s11517-017-1709-8
Source DB: PubMed Journal: Med Biol Eng Comput ISSN: 0140-0118 Impact factor: 2.602