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Automated multi-atlas segmentation of cardiac 4D flow MRI
Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Sectra, Linköping, Sweden.ORCID-id: 0000-0003-0908-9470
Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Hjärt- och Medicincentrum, Fysiologiska kliniken US.ORCID-id: 0000-0003-2198-9690
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2018 (engelsk)Inngår i: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 49, s. 128-140Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Four-dimensional (4D) flow magnetic resonance imaging (4D Flow MRI) enables acquisition of time-resolved three-directional velocity data in the entire heart and all major thoracic vessels. The segmentation of these tissues is typically performed using semi-automatic methods. Some of which primarily rely on the velocity data and result in a segmentation of the vessels only during the systolic phases. Other methods, mostly applied on the heart, rely on separately acquired balanced Steady State Free Precession (b-SSFP) MR images, after which the segmentations are superimposed on the 4D Flow MRI. While b-SSFP images typically cover the whole cardiac cycle and have good contrast, they suffer from a number of problems, such as large slice thickness, limited coverage of the cardiac anatomy, and being prone to displacement errors caused by respiratory motion. To address these limitations we propose a multi-atlas segmentation method, which relies only on 4D Flow MRI data, to automatically generate four-dimensional segmentations that include the entire thoracic cardiovascular system present in these datasets. The approach was evaluated on 4D Flow MR datasets from a cohort of 27 healthy volunteers and 83 patients with mildly impaired systolic left-ventricular function. Comparison of manual and automatic segmentations of the cardiac chambers at end-systolic and end-diastolic timeframes showed agreements comparable to those previously reported for automatic segmentation methods of b-SSFP MR images. Furthermore, automatic segmentation of the entire thoracic cardiovascular system improves visualization of 4D Flow MRI and facilitates computation of hemodynamic parameters.

sted, utgiver, år, opplag, sider
Elsevier, 2018. Vol. 49, s. 128-140
Emneord [en]
4D Flow MRI, Cardiac segmentation, Multi-atlas segmentation, Heart, Magnetic resonance imaging, Automatic segmentations, Directional velocities, Hemodynamic parameters, Left ventricular function, Segmentation methods, Semiautomatic methods, Steady state free precessions, Image segmentation, adult, anatomy, article, cohort analysis, controlled study, error, female, heart cycle, heart left ventricle function, human, human tissue, major clinical study, male, motion, nuclear magnetic resonance imaging, steady state, thickness, volunteer
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Identifikatorer
URN: urn:nbn:se:liu:diva-150788DOI: 10.1016/j.media.2018.08.003ISI: 000446286600011PubMedID: 30144652Scopus ID: 2-s2.0-85051830661OAI: oai:DiVA.org:liu-150788DiVA, id: diva2:1243429
Merknad

Funding details: 310612; Funding details: FP7, Seventh Framework Programme; Funding details: 621-2014-6191, VR, Vetenskapsrådet; Funding details: 223615; Funding details: 20140398; Funding text: This work was partially funded by the FP7-funded project DOPPLER-CIP [grant number 223615]; the European Union’s Seventh Framework Programme ( FP7/2007-2013 ) [grant number 310612 ]; the Swedish Research Council [grant number 621-2014-6191 ]; and the Swedish Heart and Lung Foundation [grant number 20140398 ]. 

Tilgjengelig fra: 2018-08-31 Laget: 2018-08-31 Sist oppdatert: 2018-10-17bibliografisk kontrollert

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Bustamante, MarianaGupta, VikasForsberg, DanielCarlhäll, CarljohanEngvall, JanEbbers, Tino

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