The Ultrasound Visualization Pipeline - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 267

24.1 Introduction
Medical ultrasound has a strong impact on clinical decision making and its high sig-
nificance in patient management is well established [ 49 , 50 ]. Ultrasonography (US)
has in comparison with CT, MRI, SPECT and PET scanning very favorable cost,
great availability world-wide, high flexibility, and extraordinary patient friendliness.
In addition to these factors, ultrasonography stands out as the imaging method with
the highest temporal resolution and also often the best spatial resolution. Further-
more, ultrasonography is a clinical method that easily can be applied bedside, even
using mobile, hand-carried scanners [ 23 ] and even pocket sized scanners [ 19 ], thus
expanding the field of applications considerably. However, a low signal-to-noise ra-
tio, “shadowing” and the relatively small scan sector make ultrasound images very
difficult to interpret. Accordingly, improved visualization of the broad spectrum of
ultrasound images has a great potential to further increase the impact of ultrasonog-
raphy in medicine.
As advancement of technology is fertilizing and stimulating medical develop-
ment, there is a continuous need for research and new applications in visualization.
Visualization methods have the capacity to transform complex data into graphical
representations that enhance the perception and meaning of the data [ 22 ]. Ordinary
ultrasound scanning produces real-time 2D slices of data, and these dynamic se-
quences pose in itself a challenge to visualizationmethods. One example is functional
ultrasonography (f-US), i.e. ultrasound imaging of (patho)physiology and/or organ
function, in contrast to conventional imaging of anatomic structures. Using f-US,
information on motility, biomechanics, flow, perfusion, organ filling and emptying
can be obtained non-invasively [ 24 , 57 ]. Moreover, the 2D images can be aligned
to form 3D data sets. In such cases, 3D visualization provides added value in terms
of a more holistic understanding of the data. Typical examples are demonstration of
complex anatomy and pathology, pre-operative surgical planning or virtual training
of medical students. Furthermore, there are now matrix 3D probes on the market
that allow real-time 3D acquisition. To benefit from the high temporal resolution, ad-
vanced graphics techniques are required in ultrasound visualization, preventing the
visualization technique from being the performance bottleneck . This opens up new
challenges to the visualization community to develop fast and efficient algorithms
for rendering on-the-fly.
In addition, co-registration techniques enable use of multi-modal data sets. Fusion
imaging, where ultrasound is combined with either CT, MRI, or PET images, allows
for more precise navigation in ultrasound-guided interventions. This challenging new
arena demands advanced visualization research to enlighten how different data types
can be combined and presented in novel ways.
The diversity of the ultrasound imaging technology provides a great tool for
medical diagnostics, but the nature of the data can make it challenging to process.
Techniques which work well for other modalities are being adapted to suit the special
characteristics of ultrasound. In this chapter, we present an overview of the pipeline