In this paper we report the development of a high resolution dynamic micro-computed tomography (CT) scanner
with a stationary mouse bed using a compact carbon nanotube (CNT)
x-ray tube. The scanner comprises a
rotating x-ray tube and detector pair and a stationary and a horizontally positioned small animal bed. The system
is optimized for in vivo mouse cardiac imaging. Its performance is evaluated with CT scans of phantoms and
free-breathing mice. The modulation transfer function (MTF) at 10% is 5 lp/mm. At single frame acquisition,
mouse cardiac micro-CT at 20msec temporal resolution has been demonstrated by prospectively gating the
imaging acquisitions to both respiration and cardiac signals.
We have designed and built a stationary digital breast tomosynthesis (DBT) system containing a carbon nanotube
based field emission x-ray source array to examine the possibility of obtaining a reduced scan time and improved
image quality compared to conventional DBT systems. There are 25 individually addressable x-ray sources in our
linear source array that are evenly angularly spaced to cover an angle of 48°. The sources are turned on sequentially
during imaging and there is no motion of either the source or the detector. We present here an iterative reconstruction
method based on a modified Ordered-Subset Convex (MOSC) algorithm that was employed for the reconstruction of
images from the new DBT system. Using this algorithm based on a maximum-likelihood model, we reconstruct on
non-cubic voxels for increased computational efficiency resulting in high in-plane resolution in the images. We have
applied the reconstruction technique on simulated and phantom data from the system. Even without the use of the
subsets, the reconstruction of an experimental 9-beam system with 960×768 pixels took less than 6 minutes (10
iterations). The projection images of a simulated mammography accreditation phantom were reconstructed using
MOSC and a Simultaneous Algebraic Reconstruction technique (SART) and the results from the comparison between
the two algorithms allow us to conclude that the MOSC is capable of delivering excellent image quality when used in
tomosynthesis image reconstruction.
We study a class of binary matrices with excellent noise properties for controlling multiplexing patterns in a multiple-source,
single-detector X-ray system. For such a system, turning multiple sources on at a time in a prescribed pattern
(multiplexing), can offer noise advantages under certain conditions. The patterns used can be represented by binary
matrices which determine the noise properties of the decoded images. Hadamard S-matrices have long been used in
spectroscopy, but they are optimal only in systems with little photonic noise. In X-ray systems with energy-integrating
detectors, the noise structure may be a mix of constant (electronic) noise and noise proportional to the signal (photonic
noise). Under mixed noise conditions, we demonstrate that a certain class of balanced incomplete block design (BIBD)
matrices offers better noise performance over a wider range of noise mixes than the Hadamard matrices. Symmetric
BIBD matrices are characterized by three parameters: v = the number of sources in the multiplexing array; k = the
number of sources on at a time; and λ = the number of multiplexed frames shared by any pair of sources. We compare
noise performance in decoded images for several families of BIBD matrices and show that the BIBD matrices with λ = 1
offer the best performance. We also offer insight into how the available matrices affect parameters of system design in a
multiplexing X-ray system. We conclude that the BIBD(v,k,λ = 1) matrices or matrices derived from them are the best
choices for multiplexing in multi-source X-ray systems.
We perform simulation studies of proposed square and hexagonal geometries of a multi-source X-ray micro-computed
tomography (CT) system. The system uses linear arrays of the carbon nano-tube (CNT)-based X-ray sources which are
individually addressable. In the square geometry, two linear source arrays and two area detectors form a square; whereas
in the hexagonal geometry, three linear source arrays and three area detectors form a hexagon. The tomographic angular
sampling for both geometries requires no motion of the sources or subject. Based on the sinogram maps, the hexagonal
geometry has improved angular coverage than the square geometry. The ordered-subset convex iterative algorithm is
implemented in both geometries for reconstructions from cone-beam projection data. The reconstructed images from
both geometries are generally consistent with the phantom, although some streaking artifacts due to the limited-angle
nature of the geometries are observed. The two geometries show similar performance in resolution-noise tradeoff. The
gap-free hexagonal geometry produces lower mean squared error in the reconstructed images; when gaps between the
source arrays and detectors are introduced, the angular coverage of the hexagonal geometry degrades faster and becomes
worse than the square geometry. The impact of gaps on the imaging properties must be studied further.
A prototype physiologically gated micro-computed tomography (micro-CT) system based on a field emission
micro-focus x-ray source has been developed for in vivo imaging of small animal models. The novel x-ray
source can generate radiation with a programmable waveform that can be readily synchronized and gated with
non-periodic physiological signals. The system performance is evaluated using phantoms and sacrificed and
anesthetized mouse models. Prospective respiratory-gated CT images of anesthetized free-breathing mice are
collected using this scanner at 100msec temporal resolution and 10 lp/mm of 10% system MTF.
A stationary digital breast tomosynthesis (DBT) system using a carbon nanotube based multi-beam field emission x-ray
(MBFEX) source has been designed. The purpose is to investigate the feasibility of reducing the total imaging time,
simplifying the system design, and potentially improving the image quality comparing to the conventional DBT
scanners. The MBFEX source consists of 25 individually programmable x-ray pixels which are evenly angular spaced
covering a 48° field of view. The device acquires the projection images by electronically switching on and off the
individual x-ray pixels without mechanical motion of either the x-ray source or the detector. The designs of the x-ray
source and the imaging system are presented. Some preliminary results are discussed.
The spline-based Mathematical Cardiac Torso (MCAT) phantom is a realistic software simulation designed to simulate single photon emission computed tomographic (SPECT) data. It incorporates a heart model of known size and shape; thus, it is invaluable for measuring accuracy of acquisition, reconstruction, and post-processing routines. New functionality has been added by replacing the standard heart model with left ventricular (LV) epicaridal and endocardial surface points detected from actual patient SPECT perfusion studies. LV surfaces detected from standard post-processing quantitation programs are converted through interpolation in space and time into new B-spline models. Perfusion abnormalities are added to the model based on results of standard perfusion quantification. The new LV is translated and rotated to fit within existing atria and right ventricular models, which are scaled based on the size of the LV. Simulations were created for five different patients with myocardial infractions who had undergone SPECT perfusion imaging. Shape, size, and motion of the resulting activity map were compared visually to the original SPECT images. In all cases, size, shape and motion of simulated LVs matched well with the original images. Thus, realistic simulations with known physiologic and functional parameters can be created for evaluating efficacy of processing algorithms.
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