Influence of Acquisition Time on MR Image Quality Estimated with Nonparametric Measures Based on Texture Features.
Correlation of parametrized image texture features (ITF) analyses conducted in different regions of interest (ROIs) overcomes limitations and reliably reflects image quality. The aim of this study is to propose a nonparametrical method and classify the quality of a magnetic resonance (MR) image that...
| Publicado en: | BioMed Research International pp. 1 - 11 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
11/20/2019
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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=139756259&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139756259 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 11/20/2019 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 139756259 139756259 139756259 10.1155/2019/3706581 139756259 ppf: 1 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Influence of Acquisition Time on MR Image Quality Estimated with Nonparametric Measures Based on Texture Features. aug: au: Obuchowicz, Rafał Piórkowski, Adam Urbanik, Andrzej Strzelecki, Michał affil: Department of Diagnostic Imaging, Jagiellonian University Medical College, Kraków 31-501, Poland sug: subj: Image Enhancement Magnetic Resonance Imaging Methods Diagnosis, Musculoskeletal Methods Human Nonparametric Statistics Male Female Lumbar Vertebrae Analysis Cervical Vertebrae Analysis Knee Shoulder Wrist Femur Analysis Spine Analysis Connective Tissue Analysis Tendons Analysis Muscle, Skeletal Analysis Male Female ab: Correlation of parametrized image texture features (ITF) analyses conducted in different regions of interest (ROIs) overcomes limitations and reliably reflects image quality. The aim of this study is to propose a nonparametrical method and classify the quality of a magnetic resonance (MR) image that has undergone controlled degradation by using textural features in the image. Images of 41 patients, 17 women and 24 men, aged between 23 and 56 years were analyzed. T2-weighted sagittal sequences of the lumbar spine, cervical spine, and knee and T2-weighted coronal sequences of the shoulder and wrist were generated. The implementation of parallel imaging with the use of GRAPPA2, GRAPPA3, and GRAPPA4 led to a substantial reduction in the scanning time but also degraded image quality. The number of degraded image textural features was correlated with the scanning time. Longer scan times correlated with markedly higher ITF image persistence in comparison with images computed with reduced scan times. Higher ITF preservation was observed in images of bones in the spine and femur as compared to images of soft tissues, i.e., tendons and muscles. Finally, a nonparametrized image quality assessment based on an analysis of the ITF, computed for different tissues, correlating with the changes in acquisition time of the MR images, was successfully developed. The correlation between acquisition time and the number of reproducible features present in an MR image was found to yield the necessary assumptions to calculate the quality index. 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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