Image Processing Reference
In-Depth Information
are used to extract important features. Methods for registration, both rigid and non-
rigid, are discussed to align the ultrasound data with other modalities. The rendering
task presents a visual presentation of the data to the user, and important techniques
in transfer function design, multi-modal rendering, shading, and illumination are
discussed. Lastly, augmented reality projects are discussed which, though currently
not popularly available in clinical systems, show great potential for the future. The
differences between ultrasound-based techniques and techniques for other imaging
modalities are also discussed.
flow. This is of high importance in diagnosis and treatment planning for severe
cardiovascular diseases. Assessment of cardiovascular disease is facilitated by vari-
ous imaging modalities. Vascular diseases occur primarily at regions with complex
or unstable flow, which significantly influences the morphology of cardiovascular
tissue. The flow behavior is therefore of vital importance to the cardiovascular system
and potentially harbors a considerable value for both diagnosis and risk assessment.
The analysis of haemodynamic characteristics involves qualitative and quantitative
inspection of the blood-flow field. Visualization plays an important role in the qual-
itative exploration, as well as the definition of relevant quantitative measures and its
validation.
There are twomain approaches to obtain information about the blood flow: simula-
tion by computational fluid dynamics, and real measurements. Although research on
blood flow simulation has been conducted for decades, many open problems remain
concerning accuracy and patient-specific solutions. Possibilities for real measure-
ment of blood flow have recently increased considerably through new developments
in magnetic resonance imaging which enable the acquisition of 3D quantitative mea-
surements of blood-flow velocity fields. MRI scanners with higher magnetic field
strengths (7-9 Tesla) provide the required resolution and signal-to-noise ratios to
analyze blood flow in smaller vessels than the main arteries around the heart.
This chapter presents the visualization challenges for both simulation and real
measurements of unsteady blood-flowfields. For simulation, challenges arise because
of the many assumptions made, the difficulty to make it patient specific, and the val-
idation. Measured flow data, on the other hand, although being patient specific, has
many limitations regarding resolution, artifacts, and noise in the data. An interesting
direction is to combine both methods for higher performance. Recent blood-flow
visualization techniques involve ad-hoc decisions with respect to seeding, segmen-
tation, or the use of illustration techniques, which need to be better linked to the
user needs. A major challenge is the novelty of this type of data for the domain
experts. Many existing methods involve rather complex visual representations that
might overwhelm a considerable portion of the target user group. Future research
should address simplifications of the blood flow and aim at a better understanding
of specific tasks, decisions and relevant information necessary to support blood flow
exploration with a guided workflow-based interaction.
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