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BibTeX entry
@Article{Correa:2009:VWL,
author = "Carlos D. Correa",
title = "Visualizing what lies inside",
journal = j-COMP-GRAPHICS,
volume = "43",
number = "2",
pages = "5:1--5:??",
month = may,
year = "2009",
CODEN = "CGRADI, CPGPBZ",
DOI = "https://doi.org/10.1145/1629216.1629224",
ISSN = "0097-8930",
bibdate = "Wed Oct 7 09:20:42 MDT 2009",
bibsource = "http://www.math.utah.edu/pub/tex/bib/siggraph2000.bib",
abstract = "Medical imaging has given radiologists an ability that
photography was not able to provide: it lets them see
inside the human body. With the advent of 3D
visualization systems, these images can be put together
into crisp and impressive renderings of the human body
from a variety of perspectives that were only dreamt of
before, revolutionizing clinical practice.\par
Light transport models soon emerged to allow light
interactions that, although not realistic in the
physical sense, proved to be more effective for
understanding the complex relationships among the
anatomical structures. For instance, bone could be made
semi-transparent to provide visibility of brain tissue.
Skin could be removed altogether from an image to show
only muscle or internal organs. However, soon it became
evident that simply rendering these images in their raw
form was no longer effective and the clear
visualization of internal structures remains
elusive.\par
The depiction of internal parts in the context of the
enclosing space is a difficult problem that has
occupied the mind of artists, illustrators and
visualization practitioners. Despite the advances made
in computer graphics for simulating the light transport
in semi-transparent media, the problem of visualizing
internal objects is no longer a rendering problem, but
that of classification. Medical imaging technology
obtains representations of anatomical structures via
indirect ways, such as the response of tissue to X-rays
or the alignment of electrons in a magnetic field.
Therefore, the absence of semantic information prevents
visualization practitioners from clearly marking up the
regions that must be visualized. Without access to
those regions, exploration becomes tedious and
time-consuming. The predominant approach has been the
use of transfer functions, or opacity mappings, which
assign transparency properties to different intervals
in the data. This method, however, does not guarantee
that internal structures are visible. Other strategies
must be used. In this article, I describe some
visualization techniques that have emerged to obtain
clear views of internal features in 3D volume data.",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "Computer Graphics",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J166",
}
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