A Survey of Cardiac 4D PC‐MRI Data Processing
Cardiac four‐dimensional phase‐contrast magnetic resonance imaging (4D PC‐MRI) acquisitions have gained increasing clinical interest in recent years. They allow to non‐invasively obtain extensive information about patient‐specific hemodynamics, and thus have a great potential to improve the diagnosi...
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| Vydáno v: | Computer graphics forum Ročník 36; číslo 6; s. 5 - 35 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Oxford
Blackwell Publishing Ltd
01.09.2017
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| Témata: | |
| ISSN: | 0167-7055, 1467-8659 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Cardiac four‐dimensional phase‐contrast magnetic resonance imaging (4D PC‐MRI) acquisitions have gained increasing clinical interest in recent years. They allow to non‐invasively obtain extensive information about patient‐specific hemodynamics, and thus have a great potential to improve the diagnosis, prognosis and therapy planning of cardiovascular diseases. A dataset contains time‐resolved, three‐dimensional blood flow directions and strengths, making comprehensive qualitative and quantitative data analysis possible. Quantitative measures, such as stroke volumes, help to assess the cardiac function and to monitor disease progression. Qualitative analysis allows to investigate abnormal flow characteristics, such as vortices, which are correlated to different pathologies. Processing the data comprises complex image processing methods, as well as flow analysis and visualization. In this work, we mainly focus on the aorta. We provide an overview of data measurement and pre‐processing, as well as current visualization and quantification methods. This allows other researchers to quickly catch up with the topic and take on new challenges to further investigate the potential of 4D PC‐MRI data.
Cardiac 4D PC‐MRI acquisitions have gained increasing clinical interest in recent years. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0167-7055 1467-8659 |
| DOI: | 10.1111/cgf.12803 |