Motion-aware stroke volume quantification in 4D PC-MRI data of the human aorta

Köhler, Benjamin; Preim, Uta; Gutberlet, Matthias; Fischbach, Katharina; Preim, Bernhard

doi:10.1007/s11548-015-1256-4

Cited by 8 publications

(6 citation statements)

References 32 publications

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“…Köhler et al . [KPG*16a] presented a modified graph cut approach and established surface correspondence over time by means of closest‐point projections. For more detailed information on aorta segmentation, we refer to the survey by Köhler et al .…”

Section: Flow Data Generation Pipelinementioning

confidence: 99%

“…A few ex vivo studies reported on the application of OCT for analysing wall degradation in aortic aneurysms [RVBR*14, OPW*16]. The dynamic motion of the inner vessel wall has been related to the underlying pulsatile flow [LDE14, KPG*16a]. This requires a segmentation of the aorta in 4D PC‐MRI data over time (Section 3.3.3).…”

Section: Flow Data Generation Pipelinementioning

confidence: 99%

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Generation and Visual Exploration of Medical Flow Data: Survey, Research Trends and Future Challenges

Oeltze-Jafra

Meuschke

Neugebauer

et al. 2018

Computer Graphics Forum

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Simulations and measurements of blood and airflow inside the human circulatory and respiratory system play an increasingly important role in personalized medicine for prevention, diagnosis and treatment of diseases. This survey focuses on three main application areas. (1) Computational fluid dynamics (CFD) simulations of blood flow in cerebral aneurysms assist in predicting the outcome of this pathologic process and of therapeutic interventions. (2) CFD simulations of nasal airflow allow for investigating the effects of obstructions and deformities and provide therapy decision support. (3) 4D phase‐contrast (4D PC) magnetic resonance imaging of aortic haemodynamics supports the diagnosis of various vascular and valve pathologies as well as their treatment. An investigation of the complex and often dynamic simulation and measurement data requires the coupling of sophisticated visualization, interaction and data analysis techniques. In this paper, we survey the large body of work that has been conducted within this realm. We extend previous surveys by incorporating nasal airflow, addressing the joint investigation of blood flow and vessel wall properties and providing a more fine‐granular taxonomy of the existing techniques. From the survey, we extract major research trends and identify open problems and future challenges. The survey is intended for researchers interested in medical flow but also more general, in the combined visualization of physiology and anatomy, the extraction of features from flow field data and feature‐based visualization, the visual comparison of different simulation results and the interactive visual analysis of the flow field and derived characteristics.

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Section: Flow Data Generation Pipelinementioning

confidence: 99%

Section: Flow Data Generation Pipelinementioning

confidence: 99%

Generation and Visual Exploration of Medical Flow Data: Survey, Research Trends and Future Challenges

Oeltze-Jafra

Meuschke

Neugebauer

et al. 2018

Computer Graphics Forum

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show abstract

“…Graph‐based approaches : Köhler et al. [KPG*15b] described a procedure to automatically segment the aorta in each temporal position. The user performs an initial 3D graph‐cut‐based segmentation (Section ) on a TMIP image as basis.…”

Section: Vessel Segmentationmentioning

confidence: 99%

“…Köhler et al. [KPG*15b] used a graph‐cut‐based 4D segmentation (Section ) to obtain meshes of each temporal position, as well as a base mesh representing an upper boundary. Projections from the base mesh onto the time‐dependent meshes were then used to obtain a list of displacement vectors for each vertex.…”

Section: Anatomical Context Visualizationmentioning

confidence: 99%

A Survey of Cardiac 4D PC‐MRI Data Processing

Köhler

Born

Pelt

et al. 2016

Computer Graphics Forum

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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.

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“…Previous studies have generally focused on three-dimensional segmentation due to its relative simplicity and shorter time requirements with respect to fourdimensional segmentation methods; however, some semi-automatic attempts have been made [120]. Four-dimensional segmentations can be useful for calculations that must be performed near the vessel walls or for a more detailed visualization of blood flow throughout the cardiac cycle.…”

Section: Vessel Segmentationmentioning

confidence: 99%

Automated Assessment of Blood Flow in the Cardiovascular System Using 4D Flow MRI

Bustamante¹

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No part of this publication may be reproduced, stored in a retrieval system, or be transmitted, in any form or by any means, electronic, mechanic, photocopying, recording, or otherwise, without prior permission of the author. Cover: Instantaneous streamline visualization of the thoracic and cardiac blood flows at different phases of the cardiac cycle for five datasets. Flip book: Segmentation of the cardiac chambers and great thoracic vessels over the cardiac cycle.

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Motion-aware stroke volume quantification in 4D PC-MRI data of the human aorta

Cited by 8 publications

References 32 publications

Generation and Visual Exploration of Medical Flow Data: Survey, Research Trends and Future Challenges

Generation and Visual Exploration of Medical Flow Data: Survey, Research Trends and Future Challenges

A Survey of Cardiac 4D PC‐MRI Data Processing

Automated Assessment of Blood Flow in the Cardiovascular System Using 4D Flow MRI

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