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A new vessel segmen...
A new vessel segmentation algorithm for robust blood flow quantification from two-dimensional phase-contrast magnetic resonance images
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- Bidhult, Sebastian (author)
- Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Hjärt-MR-gruppen i Lund,Forskargrupper vid Lunds universitet,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH,Lund Cardiac MR Group,Lund University Research Groups,Skåne University Hospital
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- Hedström, Erik (author)
- Lund University,Lunds universitet,Hjärt-MR-gruppen i Lund,Forskargrupper vid Lunds universitet,Pediatrisk radiologi,Lund Cardiac MR Group,Lund University Research Groups,Skåne University Hospital
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- Carlsson, Marcus (author)
- Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Hjärt-MR-gruppen i Lund,Forskargrupper vid Lunds universitet,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Lund Cardiac MR Group,Lund University Research Groups,Skåne University Hospital
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- Töger, Johannes (author)
- Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,MR Physics,Forskargrupper vid Lunds universitet,Hjärt-MR-gruppen i Lund,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Lund University Research Groups,Lund Cardiac MR Group,Skåne University Hospital
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- Steding-Ehrenborg, Katarina (author)
- Lund University,Lunds universitet,Människan i rörelse: hälsa och rehabilitering,Forskargrupper vid Lunds universitet,Hjärt-MR-gruppen i Lund,Human Movement: health and rehabilitation,Lund University Research Groups,Lund Cardiac MR Group,Skåne University Hospital
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- Arheden, Håkan (author)
- Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Hjärt-MR-gruppen i Lund,Forskargrupper vid Lunds universitet,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Lund Cardiac MR Group,Lund University Research Groups,Skåne University Hospital
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- Aletras, Anthony H (author)
- Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Hjärt-MR-gruppen i Lund,Forskargrupper vid Lunds universitet,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Lund Cardiac MR Group,Lund University Research Groups,Skåne University Hospital
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- Heiberg, Einar (author)
- Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Hjärt-MR-gruppen i Lund,Forskargrupper vid Lunds universitet,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Lund Cardiac MR Group,Lund University Research Groups,Skåne University Hospital
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(creator_code:org_t)
- 2019-06-06
- 2019
- English 12 s.
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In: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 39:5, s. 327-338
- Related links:
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Abstract
Subject headings
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- Blood flow measurements in the ascending aorta and pulmonary artery from phase-contrast magnetic resonance images require accurate time-resolved vessel segmentation over the cardiac cycle. Current semi-automatic segmentation methods often involve time consuming manual correction, relying on user experience for accurate results. The purpose of this study was to develop a semi-automatic vessel segmentation algorithm with shape constraints based on manual vessel delineations for robust segmentation of the ascending aorta and pulmonary artery, to evaluate the proposed method in healthy volunteers and patients with heart failure and congenital heart disease, to validate the method in a pulsatile flow phantom experiment, and to make the method freely available for research purposes. Algorithm shape constraints were extracted from manual reference delineations of the ascending aorta (n=20) and pulmonary artery (n=20) and were included into a semi-automatic segmentation method only requiring manual delineation in one image. Bias and variability (bias±SD) for flow volume of the proposed algorithm versus manual reference delineations were 0·0±1·9ml in the ascending aorta (n=151; 7 healthy volunteers; 144 heart failure patients) and -1·7±2·9 ml in the pulmonary artery (n=40; 25 healthy volunteers; 15 patients with atrial septal defect). Inter-observer bias and variability were lower (p=0·008) for the proposed semi-automatic method (-0·1±0·9ml) compared to manual reference delineations (1·5±5·1ml). Phantom validation showed good agreement between the proposed method and timer-and-beaker flow volumes (0·4±2·7ml). In conclusion, the proposed semi-automatic vessel segmentation algorithm can be used for efficient analysis of flow and shunt volumes in the aorta and pulmonary artery. This article is protected by copyright. All rights reserved.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
Publication and Content Type
- art (subject category)
- ref (subject category)
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