Visual Exploration of Simulated and Measured Blood Flow - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 300

Fig. 25.8 Two examples of the FlowLens, which is depicted with a red contour line and two
handles. Outside the lens the flow is visualized with illustrative and color-coded streamlines. Inside
the lens a view-aligned probe plane with a LIC visualization for the investigation of the degree of
vorticity ( a ) as well as the flow pressure as isosurfaces ( b ) are embedded
25.4.5 Blood Flow Visualization
Flow visualization has been an active field of research for decades. It has developed
a large number of methods for inspecting flow data, and there are different review
articles that define and classify these techniques [ 23 , 36 ]. Although these techniques
can be directly applied to blood flow fields, it is important to note that not all tech-
niques are meaningful due to the characteristics of the data, e.g., measured data has
low temporal resolution. Furthermore, the chosen visualization should be compre-
hensible to physicians and clinical researchers. In other words, the features shown
should be linked to an intuitive understanding of the flow, and the pathology. In the
remainder of this section, we will present the most common blood flow visualization
techniques that have been proposed in literature, and their variations.
One of the most common ways to depict flow is using integral curves . There are
two main approaches used for blood flow the so-called streamlines and pathlines.
These integral curves represent the trajectory that a massless particle would follow
through the vector field. Streamlines assume steady flow, so the vector field does not
change in time. Pathlines are the extension of the streamlines that convey the temporal
behavior of unsteady flow fields. Therefore, pathlines are the curves to depict parti-
cles trajectories in the vascular system. However, streamlines are still often used to
depict instantaneous flow-field structure. In measured flow data, where the temporal
resolution is low, streamlines can be informative, since error is accumulated at each
integration step of the pathlines, and therefore the reliability of the lines decreases
rapidly. Streaklines are another category of integral curves which have been used
less often for blood flow. Streaklines are generated by a continuous seeding through
time. Each point of the line corresponds to a seed that is continuously integrated
through time.