Volume Tracking: A new method for quantitative assessment and visualization of intracardiac blood flow from three-dimensional, time-resolved, three-component magnetic resonance velocity mapping

<p>Abstract</p> <p>Background</p> <p>Functional and morphological changes of the heart influence blood flow patterns. Therefore, flow patterns may carry diagnostic and prognostic information. Three-dimensional, time-resolved, three-directional phase contrast cardiovascular magnetic resonance (4D PC-CMR) can image flow patterns with unique detail, and using new flow visualization methods may lead to new insights. The aim of this study is to present and validate a novel visualization method with a quantitative potential for blood flow from 4D PC-CMR, called Volume Tracking, and investigate if Volume Tracking complements particle tracing, the most common visualization method used today.</p> <p>Methods</p> <p>Eight healthy volunteers and one patient with a large apical left ventricular aneurysm underwent 4D PC-CMR flow imaging of the whole heart. Volume Tracking and particle tracing visualizations were compared visually side-by-side in a visualization software package. To validate Volume Tracking, the number of particle traces that agreed with the Volume Tracking visualizations was counted and expressed as a percentage of total released particles in mid-diastole and end-diastole respectively. Two independent observers described blood flow patterns in the left ventricle using Volume Tracking visualizations.</p> <p>Results</p> <p>Volume Tracking was feasible in all eight healthy volunteers and in the patient. Visually, Volume Tracking and particle tracing are complementary methods, showing different aspects of the flow. When validated against particle tracing, on average 90.5% and 87.8% of the particles agreed with the Volume Tracking surface in mid-diastole and end-diastole respectively. Inflow patterns in the left ventricle varied between the subjects, with excellent agreement between observers. The left ventricular inflow pattern in the patient differed from the healthy subjects.</p> <p>Conclusion</p> <p>Volume Tracking is a new visualization method for blood flow measured by 4D PC-CMR. Volume Tracking complements and provides incremental information compared to particle tracing that may lead to a better understanding of blood flow and may improve diagnosis and prognosis of cardiovascular diseases.</p

Magnitude-based streamlines seed point selection for unsteady flow visualization

Flow visualization is a method utilized to obtain information from flow data sets. Proper blood flow visualization can assist surgeons in treating the patients. However, the main problem in visualizing the blood flow inside the aorta is the unsteady blood flow rate. Thus, an unsteady flow visualization method is required to show the blood flow clearly. Unfortunately, streamlines cannot be used by time-dependent flow visualization. This research aims to propose an improvement for the current streamline visualization technique and appearance by implementing an improved streamline generation method based on structured grid vector data to visualize the unsteady flow. The research methodology follows a comparative study method with the Evenly-Spaced Seed Point placement (ESSP) method as the benchmark. Magnitude-Based Seed Point placement (MBSP) and selective streamlines enhancement are introduced to produce longer, uniform, and clutter-free streamlines output. A total of 20 visualization results are produced with different streamlines separation distance. Results are then evaluated by comparing streamlines count and uniformity score. Subsequently, survey and expert reviews are carried out to strengthen the analysis. Survey questions are distributed to respondents that have data visualization knowledge background in order to get feedback related to streamlines uniformity and enhancement. In addition, experts review is conducted to get feedback based on current researches and techniques utilized in the related fields. Results indicate that streamlines count for MBSP are higher, but the differences are neglectable. Uniformity analysis shows good performance; with 80% of the MBSP results have better uniformity. Survey responses show 65% of respondents agreed MBSP results have better uniformity compared to ESSP. Majority of the respondents (92%) agreed that selective streamlines is a better approach. Experts review highlights that MBSP can distribute streamlines better in 3-dimension space compared to ESSP. Two significant findings are identified in this research: magnitude is proven to be an important input to locate seed points; and selective streamlines enhancement is a more effective approach as compared to global streamlines enhancement

Approximating Computational Fluid Dynamics for Generative Design

Wind loads are a critical consideration in the early-stage design of tall buildings for mitigation of wind-induced forces through form modification. Existing research in computational fluid dynamics (CFD) development tends either towards fast-inaccurate or slow-accurate approaches; therefore offering either constrictive response time or inadequate accuracy. Novel approaches that combine both speed and accuracy are required to keep pace with developments in parametric design softwares, such as GenerativeComponents. These software tools, primarily used in early-stage generative design, allow for broad exploration and optimisation within the potential design space, which in turn requires commensurate fast-yet-accurate analysis tools. This thesis investigates the use of reduced-order models to approximate CFD simulations of wind pressure on tall buildings. It is hypothesised that: firstly, wind-induced surface pressure on tall buildings simulated by CFD can be locally approximated by geometric features; and secondly, reduced-order model predictions dominate CFD simulations in both time or accuracy and are therefore a novel non-dominated approach. Predictions are made of individual vertex pressure based on input features formed from local shape analysis. The vertex samples originate from a procedural model set which is evaluated with either steady-state Reynolds-averaged Navier-Stokes (RANS) or transient large eddy simulation (LES). An artificial neural network is used for model reduction with the training set of vertex samples; the basis methodology of which is tested on a range of study complexities. To prove the scalability of the approach, this culminates in the use of LES as the basis simulation, a test set of realistically complex building models, and an alternative approach to urban wind interference generalisation is also described, whereby a one-off large-scale context CFD simulation can be used as input to repeatable design model predictions. Furthermore, a prototype tool and an outline for its integration with an existing online analysis framework currently under development is presented. The quantitative and qualitative results of the studies show it is possible to approximate surface pressure from local shape features, thereby decoupling the prediction from the basis simulation. The reduced-order model can achieve fast-yet-accurate results, since prediction accuracy and time are invariant, or independent, of basis simulation accuracy and time; being instead solely a function of the reduced-order model performance and the geometric complexity or number of test mesh vertices. Evidence is demonstrated by the positioning of the results as a non-dominated solution in the time-accuracy objective space and the subsequent alteration of the existing Pareto frontier

Extraction of topological structures in 2D and 3D vector fields

feature extraction, feature tracking, vector field visualizationMagdeburg, Univ., Fak. für Informatik, Diss., 2008von Tino WeinkaufZsfassung in dt. Sprach

Visualisation of complex flows using texture-based techniques

Detailed representations of complex flow datasets are often difficult to generate using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows. We review two popular texture based techniques and their application to flow datasets sourced from active research projects. The techniques investigated were Line integral convolution [Cabral and Leedom, SIGGRAPH'93, pp.263--270, 1993], and Image based flow visualisation [van Wijk, SIGGRAPH'02, pp.745--754, 2002]. We evaluate these and report on their effectiveness from a visualisation perspective. We also report on their ease of implementation and computational overheads. References B. Cabral and L. C. Leedom. Imaging vector fields using line integral convolution. In SIGGRAPH'93, pages 263--270, 1993. doi:10.1145/166117.166151 B. Cumming, T. Moroney, and I. Turner. A mass-conservative control volume-finite element method for solving Richards' equation in heterogeneous porous media. BIT Numer. Math., 51(2):845--864, 2011. doi:10.1007/s10543-011-0335-3 H.-J. G. Diersch and O. Kolditz. Variable-density flow and transport in porous media: approaches and challenges. Advances in Water Resources, 25:899--944, 2002. doi:10.1016/S0309-1708(02)00063-5 C. D. Hansen and C. R. Johnson. The visualization handbook. Elsevier Butterworth-Heinemann, Burlington, MA, 2005. B. Jobard, G. Erlebacher, and M. Yousuff Hussaini. Lagrangian-Eulerian advection of noise and dye textures for unsteady flow visualization. IEEE Trans. Visualization and Computer Graphics, 8(3):211--222, 2002. doi:10.1109/TVCG.2002.1021575 P. R. Keller and M. M. Keller. Visual cues: practical data visualization. IEEE Computer Society Press, Los Alamitos, CA, 1993. D. H. Laidlaw, R. M. Kirby, J. S. Davidson, T. S. Miller, M. da Silva, W. H. Warren, and M. Tarr. Quantitative comparative evaluation of 2D vector field visualization methods. In Proc. IEEE Conf. Visualization '01, pages 143--150, 2001. doi:10.1109/VISUAL.2001.964505 R. S. Laramee, G. Erlebacher, C. Garth, T. Schafhitzel, H. Theisel, X. Tricoche, T. Weinkauf, and D. Weiskopf. Applications of texture-based flow visualization. Engineering Applications of Computational Fluid Mechanics, 2(3):264--274, 2008. http://www.mpi-inf.mpg.de/ weinkauf/publications/abslaramee08.html R. S. Laramee, H. Hauser, H. Doleisch, B. Vrolijk, F. H. Post, and D. Weiskopf. The state of the art in flow visualisation: dense and texture-based techniques. Computer Graphics Forum, 23(2):203--221, 2004. doi:10.1111/j.1467-8659.2004.00753.x G. Larsen. Modelling hydrodynamic processes within Pumicestone Passage, northern Moreton Bay, Queensland. Master's thesis, Queensland University of Technology, School of Natural Resource Sciences, 2007. http://eprints.qut.edu.au/16634/ J. T. Madhani, J. Young, and R. J. Brown. Image based flow visualisation of experimental flow fields inside a gross pollutant trap. In AFMC 2012, 2012. http://www.afms.org.au/conference/18/174 - Brown.pdf J. T. Madhani, J. Young, N. A. Kelson, and R. J. Brown. A novel method to capture and analyze flow in a gross pollutant trap using image-based vector visualization. Water Air Soil Pollut.: Focus, 9:357--369, 2009. doi:10.1007/s11267-009-9225-y F. H. Post, B. Vrolijk, H. Hauser, R. S. Laramee, and H. Doleisch. Feature extraction and visualisation of flow fields. In Eurographics 2002 State of the Art Reports, pages 69--100, 2002. http://diglib.eg.org/EG/DL/Conf/EG2002/STARs/S4_FlowVis_Post.pdf F. H. Post, B. Vrolijk, H. Hauser, R. S. Laramee, and H. Doleisch. The state of the art in flow visualisation: feature extraction and tracking. Computer Graphics Forum, 22(4):775--792, 2003. doi:10.1111/j.1467-8659.2003.00723.x A. Telea. Data visualization: principles and practice. A K Peters, Ltd, Wellesley, MA, 2008. T. Theoharis, G. Papaioannou, N. Platis, and N. M. Patrikalakis. Graphics and visualization: principles and algorithms. A K Peters, Ltd, Wellesley, MA, 2008. E. R. Tufte. The visual display of quantitative information. Graphics Press, Cheshire, Conn, 2001. J. J. van Wijk. Image based flow visualization. In SIGGRAPH'02, pages 745--754, 2002. doi:10.1145/566570.566646 J. J. van Wijk. Views on visualization. IEEE Trans. Visualization and Computer Graphics, 12(4):421--432, 2006. doi:10.1109/TVCG.2006.80 D. Weiskopf. GPU-based interactive visualization techniques. Springer-Verlag, Berlin, Heidelberg, 2007