MR image reconstruction via guided filter.
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 smoo...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 4; pp. 635 - 649 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Apr2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=128549165&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 128549165 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2018 vid: 56 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 128549165 128549165 NLM28840445 10.1007/s11517-017-1709-8 NLM28840445 128549165 ppf: 635 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: MR image reconstruction via guided filter. aug: au: Huang, Heyan Yang, Hang Wang, Kang affil: School of Sciences, Changchun University, 130012, Changchun, China sug: subj: Magnetic Resonance Imaging Methods Image Processing, Computer Assisted Methods Brain Algorithms Leg Ferrans and Powers Quality of Life Index ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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