Biomedical Engineering Reference
In-Depth Information
triangular with spatial resolution approximately D / 2 [53]. It is therefore appar-
ent that a small detector must be used, in order to achieve high spatial resolu-
tion [54]. Most of the modern clinical PET scanners utilize multiple rings of BGO
block detectors to simultaneously achieve high spatial resolution and sensitiv-
ity (Section 2.7). BGO crystals are commonly used in commercial PET systems
because they have high stopping power (high efficiency) for the 511 keV gamma
rays and high spatial resolution ( 5 mm which is near the theoretical limit of
resolution), and are 50% more efficient than NaI(T1) crystals. However, the ma-
jor disadvantages of BGO crystals are that their photofluorescent decay time is
very long (0.3 µ s) which causes countrate limitations and that they have lower
light output. During the last decade, many scintillators have been explored and
some of them are currently in use in new generation of PET scanners. The best
known ones are barium fluoride [55] and gadolinium oxyorthosilicate [56]. Block
detectors are also being developed with lutetium oxyorthosilicate (LSO) [57],
a new detector material which has much shorter photofluorescent decay time
and provides higher spatial resolution images. The images obtained with PET
device built from LSO detectors are much sharper and they can be acquired at a
much faster rate than current PET scanners. Therefore, faster scans and higher
patient throughput can be achieved. Many of PET centers in the world have
installed, or planned to install, the latest generation of LSO-based PET scanner
such as the ECAT HRRT system (CTI/Siemens, Knoxville, TN).
Spatial resolution is also affected by the coincidence events detected by the
PET scanner, as described in Section 2.8. Image reconstruction algorithms also
have an impact on the spatial resolution that can be achieved with modern PET
scanner. The statistical nature of radioactive decay described by Poisson distri-
bution produces noise in the PET measurements. This noise can be amplified by
the reconstruction process and visualized in the reconstructed images due to its
high-frequency nature. In order to suppress noise in the reconstructed images
with FBP, the projection data (or sinogram) has to be filtered with a ramp filter
(in frequency domain) before the reconstruction process [31, 58]. However, the
side effect of the ramp filtering is that high-frequency components in the image
that tend to be dominated by statistical noise are amplified [32]. To obtain bet-
ter image quality, it is desirable to attenuate the high-frequency components by
using some window functions, such as the Shepp-Logan or the Hann windows,
which modify the shape of the ramp filter at higher frequencies [33]. Although the
use of window functions can help control the image noise and thereby increase
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