Validation and Development of a New Automatic Algorithm for Time-Resolved Segmentation of the Left Ventricle in Magnetic Resonance Imaging.
Introduction. Manual delineation of the left ventricle is clinical standard for quantification of cardiovascular magnetic resonance images despite being time consuming and observer dependent. Previous automatic methods generally do not account for one major contributor to stroke volume, the long-axi...
| Publicado en: | BioMed Research International Vol. 2015; pp. 1 - 13 |
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| Autores principales: | , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
6/21/2015
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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=109274647&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109274647 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 6/21/2015 vid: 2015 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 109274647 109274647 109274647 10.1155/2015/970357 109274647 ppf: 1 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Validation and Development of a New Automatic Algorithm for Time-Resolved Segmentation of the Left Ventricle in Magnetic Resonance Imaging. aug: au: Tufvesson, Jane Hedström, Erik Steding-Ehrenborg, Katarina Carlsson, Marcus Arheden, Håkan Heiberg, Einar affil: Department of Clinical Physiology, Lund University Hospital, Lund University, 221 85 Lund, Sweden sug: subj: Cardiovascular System Physiology Heart Ventricle, Left Physiology Magnetic Resonance Imaging Algorithms Evaluation Human Descriptive Statistics Validation Studies Stroke Volume Paired T-Tests Linear Regression Ventricular Ejection Fraction Diastolic Pressure Interrater Reliability Funding Source ab: Introduction. Manual delineation of the left ventricle is clinical standard for quantification of cardiovascular magnetic resonance images despite being time consuming and observer dependent. Previous automatic methods generally do not account for one major contributor to stroke volume, the long-axis motion. Therefore, the aim of this study was to develop and validate an automatic algorithm for time-resolved segmentation covering the whole left ventricle, including basal slices affected by long-axis motion. Methods. Ninety subjects imaged with a cine balanced steady state free precession sequence were included in the study (training set n=40, test set n=50). Manual delineation was reference standard and second observer analysis was performed in a subset (n=25). The automatic algorithm uses deformable model with expectation-maximization, followed by automatic removal of papillary muscles and detection of the outflow tract. Results. The mean differences between automatic segmentation and manual delineation were EDV −11 mL, ESV 1 mL, EF −3%, and LVM 4 g in the test set. Conclusions. The automatic LV segmentation algorithm reached accuracy comparable to interobserver for manual delineation, thereby bringing automatic segmentation one step closer to clinical routine. The algorithm and all images with manual delineations are available for benchmarking. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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