To Align Multimodal Lumbar Spine Images via Bending Energy Constrained Normalized Mutual Information.
To align multimodal images is important for information fusion, clinical diagnosis, treatment planning, and delivery, while few methods have been dedicated to matching computerized tomography (CT) and magnetic resonance (MR) images of lumbar spine. This study proposes a coarse-to-fine registration f...
| Publicado en: | BioMed Research International pp. 1 - 12 |
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| Autores principales: | , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
7/11/2020
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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=144527724&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 144527724 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 7/11/2020 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 144527724 144527724 144527724 10.1155/2020/5615371 144527724 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: To Align Multimodal Lumbar Spine Images via Bending Energy Constrained Normalized Mutual Information. aug: au: Wu, Shibin He, Pin Yu, Shaode Zhou, Shoujun Xia, Jun Xie, Yaoqin affil: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China sug: subj: Tomography, X-Ray Computed Magnetic Resonance Imaging Lumbar Vertebrae Anatomy and Histology Lumbar Vertebrae Radiography Human Conceptual Framework Experimental Studies Blood Vessels Anatomy and Histology Spinal Diseases Diagnosis Spinal Diseases Therapy Blood Vessels Radiography ab: To align multimodal images is important for information fusion, clinical diagnosis, treatment planning, and delivery, while few methods have been dedicated to matching computerized tomography (CT) and magnetic resonance (MR) images of lumbar spine. This study proposes a coarse-to-fine registration framework to address this issue. Firstly, a pair of CT-MR images are rigidly aligned for global positioning. Then, a bending energy term is penalized into the normalized mutual information for the local deformation of soft tissues. In the end, the framework is validated on 40 pairs of CT-MR images from our in-house collection and 15 image pairs from the SpineWeb database. Experimental results show high overlapping ratio (in-house collection, vertebrae 0.97 ± 0.02 , blood vessel 0.88 ± 0.07 ; SpineWeb, vertebrae 0.95 ± 0.03 , blood vessel 0.93 ± 0.10) and low target registration error (in-house collection, ≤ 2.00 ± 0.62 mm ; SpineWeb, ≤ 2.37 ± 0.76 mm) are achieved. The proposed framework concerns both the incompressibility of bone structures and the nonrigid deformation of soft tissues. It enables accurate CT-MR registration of lumbar spine images and facilitates image fusion, spine disease diagnosis, and interventional treatment delivery. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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