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

Authors :
Stefan Zachow
Steffen Oeltze-Jafra
Hans-Christian Hege
Mathias Neugebauer
Kai Lawonn
Monique Meuschke
Bernhard Preim
Sylvia Saalfeld
Gábor Janiga
Publica
Source :
Computer Graphics Forum. 38:87-125
Publication Year :
2018
Publisher :
Wiley, 2018.

Abstract

Simulations and measurements of blood and air flow 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 (MRI) of aortic hemodynamics 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.

Details

ISSN :
14678659 and 01677055
Volume :
38
Database :
OpenAIRE
Journal :
Computer Graphics Forum
Accession number :
edsair.doi.dedup.....57d39a765a6d01c9c92df27214612ea2
Full Text :
https://doi.org/10.1111/cgf.13394