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

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 dynamic...

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Bibliographic Details
Published in:Computer graphics forum Vol. 38; no. 1; pp. 87 - 125
Main Authors: Oeltze‐Jafra, S., Meuschke, M., Neugebauer, M., Saalfeld, S., Lawonn, K., Janiga, G., Hege, H.‐C., Zachow, S., Preim, B.
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.02.2019
Subjects:
4D PC‐MRI
Aerodynamics
Air flow
airflow visualization
aortic haemodynamics
Applied computing – Life and medical sciences
Blood flow
blood flow visualization
cerebral aneurysm haemodynamics
CFD simulation
Computational fluid dynamics
Computer graphics
Computer simulation
Computing methodologies – Modelling and simulation
Data analysis
Deformation effects
Diagnosis
Feature extraction
flow exploration task taxonomy
Health services
Hemodynamics
Human‐centred computing – Visualization application domains
Magnetic resonance imaging
medical flow data
Medical research
nasal aerodynamics
Obstructions
Personal computers
Respiratory system
Simulation
Taxonomy
Trends
Visualization
ISSN:0167-7055, 1467-8659
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Summary: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. 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.
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.13394