The latest technology enables scanning of the body with multiple simultaneous energy levels. Multiple energy
levels enable better tissue separation
and, at the same time, give rise to new
challenges related to visualization of
this new type of data. Also, the radiation dose has been reduced approximately 70-fold over the past 10 years.
A heart scan today results in less than
one month worth of average background radiation.
The increased availability of CT
scanners in modern hospitals and radiology clinics has provided an opportunity to scan the fragile mummies and
learn about and reveal their interior
content and structure without having
to open or damage them. Not even the
wrapping has to be touched. The first
report on CT scanning of mummies
was presented in 1979 by Harwood-Nash.
7 Scanning protocols for mummies require custom settings, as the
body is completely dehydrated and
regular CT protocols assume naturally
hydrated tissues, as discussed by Conlogue.
5 Furthermore, standard protocols aim to minimize the radiation
dose, and parameters (such as slice
thickness) are set to the largest value
that still yields sufficient image quality for clinical diagnosis. The scanning
settings need a custom configuration
to yield the best image quality. For
mummies, the radiation dose is generally viewed as less of an issue, but some
scholars have begun to raise concerns
about DNA degradation.
6
The presence of metallic objects
(such as amulets) can pose a challenge to CT scanning, as these objects
potentially block X-ray radiation from
reaching the sensor array, and the
signal reconstruction suffers from
artifacts. Such artifacts can now be
reduced with state-of-the-art reconstruction algorithms but may also be
reduced with modified scanning protocols and multi-energy CT. As museums around the world are increasingly
digitizing their collections, a shift toward dedicated CT scanners (such as
industrial and micro-CT scanners) is a
possible development.
Rendering What Hides Inside
The data generated from a CT scan
after reconstruction is simply a stack
of tomographic images, where the pix-
Figure 3). This approach represents an
excellent case of a massively data par-
allel algorithm that fits modern GPU
architectures, with thousands of par-
allel processors, that execute threads
of ray casting programs. Each ray esti-
mates how simulated light is reflected
and attenuated as the ray propa-
gates from the user’s eye through the
volume,a and the final footprint of
a This follows the principle of reverse ray trac-
ing and allows for several optimizations of the
computation.
els within each image slice become
samples, or voxels, in a 3D volume.
The rendering of images of the volumetric dataset on a computer screen
is known as volume rendering,
13 or
direct volume rendering (DVR), as the
image is generated directly from the
data without any intermediate (
polygonal) representation. The most common approach to DVR is raycasting,
where the stack of images is traversed
by simulated rays that collect the color
contribution, g(s), from each sampled
point as the rays traverse the stack (see
What would eventually become the Inside Explorer visualization table began in 2004,
when the Research Group in Scientific Visualization at the Department of Science and
Technology, Campus Norrköping, Linköping University, Sweden, began a collaboration
with the Center for Medical Imaging and Visualization at Linköping University on a
newly started project on virtual autopsies. The need to scan and visualize an entire
cadaver before the forensic autopsy posed technical challenges. The most critical
were how to deal with the large amounts of data and how to interactively view it when
the available memory in a typical workstation was not enough to hold the data of an
entire body. This challenge drove our thinking and development of fundamental data-handling components and rendering techniques to support full-body virtual autopsy
visualization.
12 The resulting software laid the groundwork for the initial versions of the
Inside Explorer Visualization table. It essentially addressed the challenges by adjusting
the local level of detail based on the perceived visual impact on the final image and
adapting image quality at runtime during interactive exploration. Much research has
been devoted over the past 20 years to developing and refining DVR, as well as managing
increasingly large and complex datasets, as surveyed by Beyer et al.
3 in 2015.
In the virtual autopsy project, we put each forensic case with casualties through
a full-body CT scan prior to the traditional clinical autopsy of the cadaver. Since
inception of the virtual autopsy project in 2003, approximately 800 cases have been
processed at the Center for Medical Imaging and Visualization, and all cadavers
now routinely undergo postmortem full-body CT imaging when there is suspicion of
murder. A large body of knowledge has been established, and various studies have been
conducted for specific types of autopsy examinations, including classification of dental
fillings. This work has been beneficial, if not pivotal, for the subsequent scanning of
mummified cadavers. The knowledge gained from scanning and visualizing cadavers
could be translated and adapted into scanning and visualizing mummies and other
interesting artifacts at the world’s premier museums.
Historical Notes on
Virtual Autopsy
Figure 3. The volume-rendering integral. On a modern GPU, thousands of these ray integrals
can be computed in parallel. enabling full HD resolution rendering at 30Hz–60Hz.
light
volume image plane
eye/camera a I
b
g(s)