Model-based iterative reconstruction (MBIR) is implemented to process full clinical data sets of dedicated breast tomosynthesis (DBT) in a low dose condition and achieves less spreading of anatomical structure between slices. MBIR is a statistical based reconstruction which can control the trade-off between data fitting and image regularization. In this study, regularization is formulated with anisotropic prior weighting that independently controls the image regularization between in-plane and out-of-plane voxel neighbors. Studies at complete and partial convergence show that the appropriate formulation of data-fit and regularization terms along with anisotropic prior weighting leads to a solution with improved localization of objects within a more narrow range of slices. This result is compared with the solutions using simultaneous iterative reconstruction technique (SIRT), which is one of the state of art reconstruction in DBT. MBIR yields higher contrast-to-noise for medium and large size microcalcifications and diagnostic structures in volumetric breast images and supports opportunity for dose reduction for 3D breast imaging.
Model-based iterative reconstruction (MBIR) is an emerging technique for several imaging modalities and appli-
cations including medical CT, security CT, PET, and microscopy. Its success derives from an ability to preserve
image resolution and perceived diagnostic quality under impressively reduced signal level. MBIR typically uses a
cost optimization framework that models system geometry, photon statistics, and prior knowledge of the recon-
structed volume. The challenge of tomosynthetic geometries is that the inverse problem becomes more ill-posed
due to the limited angles, meaning the volumetric image solution is not uniquely determined by the incom-
pletely sampled projection data. Furthermore, low signal level conditions introduce additional challenges due to
noise. A fundamental strength of MBIR for limited-views and limited-angle is that it provides a framework for
constraining the solution consistent with prior knowledge of expected image characteristics. In this study, we
analyze through simulation the capability of MBIR with respect to prior modeling components for limited-views,
limited-angle digital breast tomosynthesis (DBT) under low dose conditions. A comparison to ground truth
phantoms shows that MBIR with regularization achieves a higher level of fidelity and lower level of blurring
and streaking artifacts compared to other state of the art iterative reconstructions, especially for high contrast
objects. The benefit of contrast preservation along with less artifacts may lead to detectability improvement of
microcalcification for more accurate cancer diagnosis.
Non-linear image processing and reconstruction algorithms that reduced noise while preserving edge detail are currently being evaluated in medical imaging research literature. We have implemented a robust statistics analysis of four widely utilized methods. This work demonstrates consistent trends in filter impact by which such non-linear algorithms can be evaluated. We calculate observer model test statistics and propose metrics based on measured non-Gaussian distributions that can serve as image quality measures analogous to SDNR and detectability. The filter algorithms that vary significantly in their approach to noise reduction include median (MD), bilateral (BL), anisotropic diffusion (AD) and total-variance regularization (TV). It is shown that the detectability of objects limited by Poisson noise is not significantly improved after filtration. There is no benefit to the fraction of correct responses in repeated n-alternate forced choice experiments, for n=2-25. Nonetheless, multi-pixel objects with contrast above the detectability threshold appear visually to benefit from non-linear processing algorithms. In such cases, calculations on highly repeated trials show increased separation of the object-level histogram from the background-level distribution. Increased conspicuity is objectively characterized by robust statistical measures of distribution separation.
The image quality entitlement is evaluated for multi-energy bin photon counting (PC) spectral CT relative to that of
energy integration an dual kVp (dkVp) imaging. Physics simulations of X-ray projection channel data and CT images
are used to map contrast-to-noise metrics for simple numerical phantoms objects with soft tissue, calcium and iodine
materials. The benefits are quantified under ideal detector conditions. Spectral optimization yields on the order of 2X
benefit for iodine visualization measured by CNR^2/dose in two different imaging modes: optimal energy weighting,
and optimal mono-energy imaging. In another case studied, strict dose equivalence is maintained by use of a composite
spectrum for PC simulation that combines simultaneously the two kVp excitations used sequentially for dkVp. In this
case, mono-energetic imaging of iodine contrast agent is shown to achieve 40% higher dose efficiency for photon
counting compared to dual kVp although non-ideal characteristics of the photon counting response can eliminate much
of this benefit.
In this paper, the design and evaluation of a 3D stereo, near infrared (IR), defect mapping system for CZT inspection is
described. This system provides rapid acquisition and data analysis that result in detailed mapping of CZT crystal defects
across the area of wafers up to 100 millimeter diameter and through thicknesses of up to 20 millimeter. In this paper,
system characterization has been performed including a close evaluation of the bright field and dark field illumination
configurations for both wafer-scale and tile-scale inspection. A comparison of microscope image and IR image for the
same sample is performed. As a result, the IR inspection system has successfully demonstrated the capability of
detecting and localizing inclusions within minutes for a whole CZT wafer. Important information is provided for
selecting defect free areas out of a wafer and thereby ensuring the quality of the tile. This system would support the CZT
wafer dicing and assembly techniques that enable the economical production of CZT detectors. This capability can
improve the yield and reduce the cost of the thick detector devices that are rarely produced today.
The contrast-to-noise (CNR) is optimized over the weights and energy threshold settings of energy bins in a photon
counting detector using "delta-pulse" model simulations. Comparison is made to single-bin photon counting and energy
integration detectors. The CNR<sup>2</sup> for iodine imaging is about a factor of 2.5X higher for a perfect, photon counting
detector compared to energy integration. Monte Carlo simulations are used to determine the impact of pile-up and other
factors that degrade the spectral performance. The benefits of multi-bin photon counting vanish at about 40-60% tail
fraction and 20-30 keV RMS noise. Because of pile-up, the CNR<sup>2</sup> benefit also decreases as the incident count rate
approaches the maximum periodic rate (MPR). However the impact of pile-up is less for a three-bin detector than for a
two-bin detector when the multiple bins are weighted optimally.
CdZnTe is a high efficiency, room temperature radiation detection material that has attracted great interesting in
medical and security applications. CZT crystals can be grown by various methods. Particularly, CZT grown with the
Transfer Heater Method (THM) method have been shown to have fewer defects and greater material uniformity. In this
work, we developed a proof-of-concept dual lighting NIR imaging system that can be implemented to quickly and
nondestructively screen CZT boule and wafers during the manufacturing process. The system works by imaging the
defects inside CZT at a shallow depth of focus, taking a stack of images step by step at different depths through the
sample. The images are then processed with in-house software, which can locate the defects at different depths, construct
the 3D mapping of the defects, and provide statistical defect information. This can help with screening materials for use
in detector manufacturing at an early stage, which can significantly reduce the downstream cost of detector fabrication.
This inspection method can also be used to help the manufacturer understand the cause of the defect formation and
ultimately improve the manufacturing process.
Current spectroscopic detector crystals contain defects that prevent economic production of devices with sufficient
energy resolution and stopping power for radioisotope discrimination. This is especially acute for large monolithic
crystals due to increased defect opportunity. The proposed approach to cost reduction starts by combining stereoscopic
IR and ultrasound (UT) inspection coupled with segmentation and 3D mapping algorithms. A "smart dicing" system
uses "random-access" laser-based machining to obtain tiles free of major defects. Application specific grading matches
defect type to anticipated performance. Small pieces combined in a modular sensor pack instead of a monolith will
make the most efficient use of wafer area.
The fabrication of new optical materials has many challenges that suggest the need for new metrology tools. To this
purpose, the authors designed a system for localizing 10 micron embedded defects in a 10-millimeter thick semitransparent
medium. The system, comprising a single camera and a motion system, uses a combination of brightfield and
darkfield illumination. This paper describes the optical design and algorithm tradeoffs used to reach the desired detection
and measurement characteristics using stereo photogrammetry and parallel-camera stereoscopic matching. Initial
experiment results concerning defect detection and positioning, as well as analysis of computational complexity of a
complete wafer inspection are presented. We concluded that parallel camera stereoscopic matching combined with
darkfield illumination provides the most compatible solution to the 3D defect detection and positioning requirement,
detecting 10 micron defects at a positioning accuracy of better than +/- 0.5 millimeters and at a speed of less than 3
minutes per part.
Recently there has been significant interest in dual energy CT imaging with several acquisition methods being
actively pursued. Here we investigate fast kVp switching where the kVp alternates between low and high kVp
every view. Fast kVp switching enables fine temporal registration, helical and axial acquisitions, and full field
of view. It also presents several processing challenges. The rise and fall of the kVp, which occurs during the
view integration period, is not instantaneous and complicates the measurement of the effective spectrum for low
and high kVp views. Further, if the detector digital acquisition system (DAS) and generator clocks are not fully
synchronous, jitter is introduced in the kVp waveform relative to the view period.
In this paper we develop a method for estimation of the resulting spectrum for low and high kVp views. The
method utilizes static kVp acquisitions of air with a small bowtie filter as a basis set. A fast kVp acquisition of
air with a small bowtie filter is performed and the effective kVp is estimated as a linear combination of the basis
vectors. The effectiveness of this method is demonstrated through the reconstruction of a water phantom acquired
with a fast kVp acquisition. The impact of jitter due to the generator and detector DAS clocks is explored via
simulation. The error is measured relative to spectrum variation and material decomposition accuracy.
Dual energy CT cardiac imaging is challenging due to cardiac motion and the resolution requirements of clinical
applications. In this paper we investigate dual energy CT imaging via fast kVp switching acquisitions of a novel
dynamic cardiac phantom. The described cardiac phantom is realistic in appearance with pneumatic motion control
driven by an ECG waveform.
In the reported experiments the phantom is driven off a 60 beats per minute simulated ECG waveform. The cardiac
phantom is inserted into a phantom torso cavity. A fast kVp switching axial step and shoot acquisition is detailed. The
axial scan time at each table position exceeds one heart cycle so as to enable retrospective gating. Gating is performed
as a mechanism to mitigate the resolution impact of heart motion.
Processing of fast kVp data is overviewed and the resulting kVp, material decomposed density, and monochromatic
reconstructions are presented. Imaging results are described in the context of potential clinical cardiac applications.
In a conventional X-ray CT system, where an object is scanned with a selected incident x-ray spectrum, or kVp, the
reconstructed images only approximate the linear X-ray attenuation coefficients of the imaged object at an effective
energy of the incident X-ray beam. The errors are primarily the result of beam hardening due to the polychromatic nature
of the X-ray spectrum. Modem clinical CT scanners can reduce this error by a process commonly referred to as spectral
calibration. Spectral calibration linearizes the measured projection value to the thickness of water. However, beam
hardening from bone and contrast agents can still induce shading and streaking artifacts and cause CT number
inaccuracies in the image.
In this paper, we present a dual kVp scanning method, where during the scan, the kVp is alternately switching between
target low and high preset values, typically 80kVp and 140 kVp, with a period less than 1ms. The measured projection
pairs are decomposed into the density integrals of two basis materials in projection space. The reconstructed density
images are further processed to obtain monochromatic attenuation coefficients of the object at any desired energy.
Energy levels yielding optimized monochromatic images are explored, and their analytical representations are derived.
Linear discriminate analysis (LDA) is applied to dual kVp CT and used for tissue characterization. The
potential to quantitatively model both malignant and benign, hypo-intense liver lesions is evaluated by analysis of
portal-phase, intravenous CT scan data obtained on human patients. Masses with an a priori classification are mapped
to a distribution of points in basis material space. The degree of localization of tissue types in the material basis space
is related to both quantum noise and real compositional differences. The density maps are analyzed with LDA and
studied with system simulations to differentiate these factors. The discriminant analysis is formulated so as to
incorporate the known statistical properties of the data. Effective kVp separation and mAs relates to precision of tissue
localization. Bias in the material position is related to the degree of X-ray scatter and partial-volume effect.
Experimental data and simulations demonstrate that for single energy (HU) imaging or image-based decomposition
pixel values of water-like tissues depend on proximity to other iodine-filled bodies. Beam-hardening errors cause a
shift in image value on the scale of that difference sought between in cancerous and cystic lessons. In contrast,
projection-based decomposition or its equivalent when implemented on a carefully calibrated system can provide
accurate data. On such a system, LDA may provide novel quantitative capabilities for tissue characterization in dual
The output response characteristics of an X-ray photon counting detector are measured experimentally and
simulated using a Monte Carlo method in order to quantify the loss of statistical information due to pile-up. The
analysis is applied to idealize counting detector models, but is adaptable to realistic event processing that is not
amenable to analytic solution. In particular, the detective quantum efficiency (DQE) is calculated as a function of flux
rate and shown to have an intermediate zero for the paralyzable case at the maximum periodic rate. The progressive
degradation of the spectral response as a function of increasing flux rate is also modeled. Analogous metrics to DQE
are defined in regards to the detector's ability to resolve atomic number and enhance image contrast based on atomic
number differentiation. Analytic solutions are provided for the output and linearized response statistics and these
interpolate well across the Monte Carlo and experimental results.
The material specificity of computed tomography is quantified using an experimental benchtop imaging system
and a physics-based system model. The apparatus is operated with different detector and system configurations each
giving X-ray energy spectral information but with different overlap among the energy-bin weightings and noise
statistics. Multislice, computed tomography sinograms are acquired using dual kVp, sequential source filters or a
detector with two scintillator/photodiodes layers. Basis-material and atomic number images are created by first
applying a material decomposition algorithm followed by filtered backprojection. CT imaging of phantom materials
with known elemental composition and density were used for model validation. X-ray scatter levels are measured with a
beam-blocking technique and the impact to material accuracy is quantified. The image noise is related to the intensity
and spectral characteristics of the X-ray source. For optimal energy separation adequate image noise is required. The
system must be optimized to deliver the appropriate high mA at both energies. The dual kVp method supports the
opportunity to separately engineer the photon flux at low and high kvp. As a result, an optimized system can achieve
superior material specificity in a system with limited acquisition time or dose. In contrast, the dual-layer and sequential
acquisition modes rely on a material absorption mechanism that yields weaker energy separation and lower overall
A convolution model of scatter that is adaptable to rapid simulation and correction algorithms is tested against the measured scatter profiles. In the simple case of a uniform acrylic sheet, the convolution approach yields about 10% absolute agreement with the measured scatter profile. However, significant qualitative differences are demonstrated for phantoms with non-uniform thickness or composition. For example, the scatter profile is dependent on a bone's vertical position in the phantom whereas the primary is unchanged. Similarly, a cusp shape in the scatter profile observed near the abrupt edge of an acrylic sheet is not produced in the convolution model. An alternate approach that calculates the scatter as a 3D integral over the object volume can reproduce this behavior.
We present the analysis of the accuracy and precision of dual energy material basis decomposition for the quantification of tissue fat content in computed tomography. We compare the benefits of a pre-reconstruction (sinogram-based) dual energy imaging technique versus a post-reconstruction (image) based dual energy decomposition technique using a numerical simulation. A phantom containing plastics of known composition is measured to validate the technique. The accuracy of the image based dual energy decomposition technique is contingent on the amount of beam hardening encountered in the phantom. The accuracy of the pre-reconstruction dual energy technique depends on how accurately the system spectral response can be modeled. In both cases the precision of the dual energy imaging is determined by the photon flux.
Two mechanisms for MTF dependence on incident x-ray angle are demonstrated by an experimental technique that separates the two phenomena. The dominant effect is that travel of x-ray photons through the scintillator at non-normal incidence involves an in-plane component. This mechanism leads to a significant but deterministic blurring of the incident image, but has no effect on the noise transfer characteristics of the detector. A secondary effect is that at large angles to the surface normal, x-ray-to-optical conversion occurs at positions in the scintillator further away from the photodiode surface. This leads to a small net decrease in MTF and NPS at angles above 60 degrees. The deterministic character of the angular dependence of gain, MTF and NPS leads to the conclusion that sufficient angular range can be supported by this detector construction. Excellent functionality in the context of tomography is expected.
The purpose of this paper is to investigate the use of electron-beam Computed Tomography (EBCT) dual energy scanning for improved differentiation of calcified coronary arteries from iodinated-contrasted blood, in fast moving cardiac vessels. The dual energy scanning technique can lead to an improved cardiac examination in a single breath hold with more robust calcium scoring and better vessel characterization. Dual energy can be used for material discrimination in CT imaging to differentiate materials with similar CT number, but different material attenuation properties. Mis-registration is the primary source of error in a dual energy application, since acquisitions have to be made at each energy, and motion between the acquisitions causes inconsistencies in the decomposition algorithm, which may lead to artifacts in the resultant images. Using EBCT to quickly switch x-ray source peak voltage potential (kVp), the mis-registration of patient anatomy is minimized since acquisitions at both energy spectra are completed in one study at the same cardiac phase. Two protocols for scanning the moving heart using EBCT were designed to minimize registration issues. Material basis function decomposition was used to differentiate regions containing calcium and iodine in the image. We find that this protocol is superior to CT imaging at one energy spectrum in discriminating calcium from contrast-enhanced lumen. Using dual energy EBCT scanning can enable accurate calcium scoring, and angiography applications to be performed in one exam.
In addition to a conventional Computed Tomography (CT) image, dual energy (dual kVp) imaging can be used to generate an image of the same anatomy that represents the equivalent density of a particular material, for example, calcium, iodine, water, etc. This image can be used to improve the differentiation of materials as well as improve the accuracy of absolute density measurements in a cross-sectional image. It is important to understand the certainty of the estimation of the density of the material. Both simulations and measurements are used to quantify these errors. Data are acquired using a flat-panel based volumetric CT system, by taking two scans and adjusting the maximum energy of the source spectrum (kVp). Physics based simulations are used to compare with the measurements. After validating the simulation algorithms, the accuracy of the dual kVp method is determined using the simulations in a perturbation study.
Dose is becoming increasingly important for computed tomography clinical practice. It is of general interest to understand the impact that system design can have on dose and image quality. This study addresses the effect of bowtie shape on the dose and contrast-to-noise across the field of view. Simulation of the CT acquisition is used to calculate the energy deposition throughout a numerical phantom for a set of relevant system operating parameters and bowtie shapes. Mean absorbed dose is calculated by summing over the phantom volume and is compared with other typical dose specifications. A more aggressive attenuation profile of the bowtie which offers higher attenuation in the periphery of the field of view can offer the benefit of lower dose but at the expense of reduced contrast-to-noise at the edge of the cross-sectional image.
We have implemented a scatter-correction algorithm (SCA) for digital mammography based on an iterative restoration filter. The scatter contribution to the image is modeled by an additive component that is proportional to the filtered unattenuated x-ray photon signal and dependent on the characteristics of the imaged object. The SCA's result is closer to the scatter-free signal than when a scatter grid is used. Presently, the SCA shows improved contrast-to-noise performance relative to the scatter grid for a breast thickness up to 3.6 cm, with potential for better performance up to 6 cm. We investigated the efficacy of our scatter-correction method on a series of x-ray images of anthropomorphic breast phantoms with maximum thicknesses ranging from 3.0 cm to 6.0 cm. A comparison of the scatter-corrected images with the scatter-free signal acquired using a slit collimator shows average deviations of 3 percent or less, even in the edge region of the phantoms. These results indicate that the SCA is superior to a scatter grid for 2D quantitative mammography applications, and may enable 3D quantitative applications in X-ray tomosynthesis.
The modulation transfer function and detective quantum efficiency are modeled for a Full Field Digital Mammography detector constructed with a CsI scintillator deposited on an amorphous silicon active matrix array. The model is evaluated against experimental measurements using different exposure levels, x-ray tube voltages, target composition and beam filtrations as well as varying thicknesses and compositions of filtration materials placed in the path between the tube and detector. Available x-ray tube emission spectrum models were evaluated by comparison against the measured transmission through aluminum. The observed variation of DQE at zero spatial frequency among different target/filter conditions, acrylic filtration thicknesses and kVp is well characterized by a x-ray model. This variation is largely accounted for by just two effects -- the attenuation of x-rays through the detector enclosure and the stopping power of x-rays in the CsI layer. Additional considerations such as the Lubberts effect were included in the analysis in order to match the measured DQE(k) as a function of spatial frequency, k. The pixel aperture and light channeling through the scintillator shape the MTF which acts favorably to avoid aliasing due to digital sampling.
We report the results of performance measurements for an amorphous silicon flat panel detector used in a cardiovascular imaging system. The detector contains 1024 x 1024 elements on a 0.2 mm pitch for an active image area of about 20.5 x 20.5 cm<SUP>2</SUP>. The system allows imaging at fluoroscopic and dynamic cardiac record exposure levels at rates of up to 30 Hz. We measured MTF, NPS, DQE, contrast ratio, response uniformity, resolution uniformity, and lag. Measurements were made on 28 production detectors. The MTF was greater than 0.2 at 2.5 cycles/mm. Contrast ratio was several hundred, indicating negligible long range scatter (veiling glare) within the detector. The DQE of the detector was measured at exposures typical of fluoroscopic imaging, dynamic cardiac record imaging, and digital subtraction angiography (DSA). The DQE was at least 0.65, 0.54, and 0.34 at 0, 1, and 2 cycles/mm, respectively, for all of these exposure levels. The response of the detector varied by less than 12% across its surface. The MTF, measured at nine positions over the surface of the detector, was found to have a maximum difference among positions of less than 0.05 at both 1 and 2 cycles/mm. First frame lag was less than 5%.