Automatic deformable PET/MRI registration for preclinical studies based on B-splines and non-linear intensity transformation.
PET images deliver functional data, whereas MRI images provide anatomical information. Merging the complementary information from these two modalities is helpful in oncology. Alignment of PET/MRI images requires the use of multi-modal registration methods. Most of existing PET/MRI registration metho...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 9; pp. 1531 - 1540 |
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| Autores principales: | , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2018
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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=131278134&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 131278134 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2018 vid: 56 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 131278134 131278134 NLM29411247 10.1007/s11517-018-1797-0 NLM29411247 131278134 ppf: 1531 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automatic deformable PET/MRI registration for preclinical studies based on B-splines and non-linear intensity transformation. aug: au: Bricq, Stéphanie Kidane, Hiliwi Leake Zavala-Bojorquez, Jorge Oudot, Alexandra Vrigneaud, Jean-Marc Brunotte, François Walker, Paul Michael Cochet, Alexandre Lalande, Alain affil: Le2i FRE2005, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, Dijon, France sug: subj: Magnetic Resonance Imaging Chaos Theory Algorithms Tomography, Emission-Computed Animals Automation Kidney Mice Clinical Assessment Tools Scales ab: PET images deliver functional data, whereas MRI images provide anatomical information. Merging the complementary information from these two modalities is helpful in oncology. Alignment of PET/MRI images requires the use of multi-modal registration methods. Most of existing PET/MRI registration methods have been developed for humans and few works have been performed for small animal images. We proposed an automatic tool allowing PET/MRI registration for pre-clinical study based on a two-level hierarchical approach. First, we applied a non-linear intensity transformation to the PET volume to enhance. The global deformation is modeled by an affine transformation initialized by a principal component analysis. A free-form deformation based on B-splines is then used to describe local deformations. Normalized mutual information is used as voxel-based similarity measure. To validate our method, CT images acquired simultaneously with the PET on tumor-bearing mice were used. Results showed that the proposed algorithm outperformed affine and deformable registration techniques without PET intensity transformation with an average error of 0.72 ± 0.44 mm. The optimization time was reduced by 23% due to the introduction of robust initialization. In this paper, an automatic deformable PET-MRI registration algorithm for small animals is detailed and validated. Graphical abstract ᅟ. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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