Coherence property of x-rays is critical in the grating-based differential phase contrast (DPC) imaging because it is the physical foundation that makes any form of phase contrast imaging possible. Loss of coherence is an important experimental issue, which results in increased image noise and reduced object contrast in DPC images and DPC cone beam CT (DPC-CBCT) reconstructions. In this study, experimental results are investigated to characterize the visibility loss (a measurement of coherence loss) in several different applications, including different-sized phantom imaging, specimen imaging and small animal imaging. Key measurements include coherence loss (relative intensity changes in the area of interest in phase-stepping images), contrast and noise level in retrieved DPC images, and contrast and noise level in reconstructed DPC-CBCT images. The influence of size and composition of imaged object (uniform object, bones, skin hairs, tissues, and etc) will be quantified. The same investigation is also applied for moiré pattern-based DPC-CBCT imaging with the same exposure dose. A theoretical model is established to relate coherence loss, noise level in phase stepping images (or moiré images), and the contrast and noise in the retrieved DPC images. Experiment results show that uniform objects lead to a small coherence loss even when the attenuation is higher, while objects with large amount of small structures result in huge coherence loss even when the attenuation is small. The theoretical model predicts the noise level in retrieved DPC images, and it also suggests a minimum dose required for DPC imaging to compensate for coherence loss.
Differential phase contrast (DPC) imaging is reported to be able to deliver higher contrast-to-noise ratio (CNR)
compared to attenuation-based x-ray imaging technologies. Due to the nature of attenuation contrast, the conventional
cone beam CT (CBCT) technology has limitations in characterizing breast lesions with sufficiently high contrast and
spatial resolution. As an alternative, the grating-based DPC-CBCT technology is potentially a powerful tool for breast
imaging. However, limited by current grating fabrication techniques, a full field-of-view (FOV) that covers the whole
breast is not practical at present. Previously by our group, a volume-of-interest (VOI) imaging method, which
incorporates DPC-CBCT into a dedicated attenuation-based CBCT imaging system, was presented. In the method, the
CBCT scan was performed to localize the suspicious volume and then a VOI scan by DPC-CBCT characterized the
suspicious volume with higher contrast and resolution. In this work, we investigated the performance of DPC-CBCT
VOI imaging by performing a phantom study using our bench-top DPC-CBCT system with a hospital-grade X-ray tube.
A cylinder water phantom with a size of over twice of the FOV of our DPC-CBCT system was designed. The phantom
contains four different materials and it was scanned at four different dose levels. In thick object scanning, phase
wrapping errors cause artifacts for DPC-CBCT VOI imaging. A low-pass filter was designed to reduce the artifacts. In
order to compare the DPC-CBCT VOI with attenuation-based CBCT, the scanning data were used to reconstruct both
phase coefficient image and attenuation coefficient image. The reconstructed images will be quantitatively and visually
evaluated with regards to contrast, noise level and artifacts.
In principle, differential phase contrast (DPC) imaging allows the use of a hospital grade x-ray tube that has a large focal
spot size and a wide polychromatic spectrum. It should be noted that due to the integration of interference patterns over
the entire spectrum, the fringe contrast in the final intensity image is lower than that from a monochromatic spectrum.
Therefore better image quality should be potentially obtained if the energy-dependent interference patterns can be
analyzed separately. The key idea of the proposed spectral DPC imaging approach is to acquire DPC images for each
photon energy channel, which is named spectral DPC images. The final DPC image can be computed by summing up
these spectral DPC images or just computed using certain 'color' representation algorithms to enhance desired features.
This research is a feasibility study based on computer simulations to investigate how the spectral DPC method works for
a DPC-based cone beam CT (DPC-CBCT) system. The spectral DPC imaging approach is applied to an x-ray spectral
centered at 30keV, which is divided into four energy channels in simulation. A simple numerical phantom with low
contrast inserts is used and the entire imaging process is simulated using Fresnel diffraction theory. Phase stepping
approach is used to manifest and retrieve phase information. The phantom is scanned over a full circular trajectory and
the Hilbert filter-based FBP algorithm is used to compute the DPC-CBCT reconstruction. The reconstruction from the
proposed spectral DPC-CBCT is compared to that from the conventional DPC-CBCT that only takes detector images for
the integrated polychromatic spectrum. The uniformity, noise level and contrast of the inserts in the reconstruction are
measured and compared. Simulation results indicate that the spectral DPC imaging approach can improve object contrast and reduce noise for DPC-CBCT.
Differential phase contrast (DPC) imaging, which utilizes phase shift information of X-ray, has the potential of
dramatically increasing the contrast in biological sample imaging compared to attenuation-based method that relies on
X-ray absorption information, since the X-ray phase is much more sensitive than the attenuation during transmission. In
a DPC imaging system, the phase stepping method is widely used to obtain DPC images: at each angle the phase grating
is shifted incrementally to produce a set of images and then the so obtained images are used to retrieve DPC image.
However, DPC imaging requires a high mechanical precision to perform phase stepping, which is generally one order
higher than the period of phase grating. Given that phase grating period is generally 2-4 um, the requirement of
mechanical accuracy and stability are very demanding (<0.5um) and difficult to meet in a system with rotating gantry. In
this paper, we present a method that is able to greatly relax the requirement of mechanical accuracy and stability by
stepping the source grating rather than the analyzer grating. This method is able to increase the system's mechanical
tolerance without compromising image quality and make it feasible to install the system on a rotating gantry to perform
differential phase-contrast cone beam CT (DPC-CBCT). It is also able to increase the grating shifting precision and as a
result improve the reconstructed image quality. Mechanical tolerance investigation and image quality investigation at
different phase stepping schemes and different dose levels will be carried out on both the original modality and the new
modality, the results will be evaluated and compared. We will deliberately create random mechanical errors in phase
stepping and evaluate the resulting DPC images and DPC-CBCT reconstructions. The contrast, noise level and sharpness
will be evaluated to assess the influence of mechanical errors. By stepping the source grating, the system is expected to
tolerate an error of 6-7 times bigger than that with analyzer grating stepping.
The phase stepping algorithm is commonly used for phase retrieval in grating-based differential phase-contrast (DPC)
imaging, which requires multiple intensity images to compute one DPC image. It is not efficient for data acquisition,
especially in the case of dynamic imaging using either DPC imaging or DPC-based come beam CT (DPC-CBCT)
imaging. A Fourier transform-based approach has been developed for fringe pattern analysis in optics, and it was
recently implemented into a synchrotron-based DPC tomography system. In this research, this approach is further
developed for a bench-top DPC-CBCT imaging system with a hospital-grade x-ray tube. The key idea is to separate
carrier fringes and object information in Fourier domain of the interferogram and to reconstruct the differentiated phase
information using the object information. Only one interferogram is required for phase retrieval at a cost of spatial
resolution. The fringes of moiré patterns are used as the carrier fringes, and a phantom is scanned to evaluate the
approach. Various interferograms with different carrier fringe frequencies are investigated and the reconstruction image
quality is evaluated in terms of contrast, noise and sharpness. The results indicated that the DPC images can be
effectively retrieved using the Fourier transform-based approach and the reconstructed phase coefficient showed better
contrast compared to that of attenuation-based contrast. The spatial resolution is acceptable in the phantom studies
although it is not as good as the results of phase-stepping approach. The Fourier transform-based phase retrieval
approach is able to greatly simplify data acquisition, to improve the temporal resolution and to make it possible for
dynamic DPC-CBCT imaging. It is promising for perfusion imaging where spatial resolution is not a concern.
Differential phase contrast technique could be the next breakthrough in the field of CT imaging. While traditional
absorption-based X-ray CT imaging is inefficient at differentiating soft tissues, phase-contrast technique offers great
advantage as being able to produce higher contrast images utilizing the phase information of objects. Our long term goal
is to develop a gantry-based hospital-grade X-ray tube differential phase contrast cone-beam CT (DPC-CBCT)
technology which is able to achieve higher contrast noise ratio (CNR) in soft tissue imaging without increasing the dose
level. Based on the micro-focus system built last year, a bench-top hospital-grade X-ray tube DPC-CBCT system is
designed and constructed. The DPC-CBCT system consists of an X-ray source, i.e. a hospital-grade X-ray tube and a
source grating, a high-resolution detector, a rotating phantom holder, a phase grating and an analyzer grating. Threedimensional
(3-D) phase-coefficients are reconstructed, providing us with images enjoying higher CNR than, yet
equivalent dose level to, a conventional CBCT scan. Three important aspects of the system are investigated: a) The The
system's performance in term of CNR of the reconstruction image with regard to dose levels, b) the impacts of different
phase stepping schemes, i.e. 5 steps to 8 steps, in term of CNR on the reconstruction images, and c) the influence of
magnification or position of the phantom on image quality, chiefly CNR. The investigations are accomplished via
phantom study.
Cone Beam Breast CT imaging (CBBCT) is a promising tool for diagnosis of breast tumors and calcifications. However, as the sizes of calcifications in early stages are very small, it is not easy to distinguish them from background tissues because of the relatively high noise level. Therefore, it is necessary to enhance the visualization of calcifications for accurate detection. In this work, the Papoulis-Gerchberg (PG) method was introduced and modified to improve calcification characterization. PG method is an iterative algorithm of signal extrapolation and has been demonstrated to be very effective in image restoration like super-resolution (SR) and inpainting. The projection images were zoomed by bicubic interpolation method, then the modified PG method were applied to improve the image quality. The reconstruction from processed projection images showed that this approach can effectively improve the image quality by improving the Modulation Transfer Function (MTF) with a limited increase in noise level. As a result, the detectability of calcifications was improved in CBBCT images.
In Cone Beam Breast CT (CBBCT), breast calcifications have higher intensities than the surrounding tissues. Without
the superposition of breast structures, the three-dimensional distribution of the calcifications can be revealed. In this
research, based on the fact that calcifications have higher contrast, a local thresholding and a histogram thresholding
were used to select candidate calcification areas. Six features were extracted from each candidate calcification: average
foreground CT number value, foreground CT number standard deviation, average background CT number value,
background CT number standard deviation, foreground-background contrast, and average edge gradient. To reduce the
false positive candidate calcifications, a feed-forward back propagation artificial neural network was designed. The
artificial neural network was trained with the radiologists confirmed calcifications and used as classifier in the
calcification auto-detection task. In the preliminary experiments, 90% of the calcifications in the testing data sets were
detected correctly with an average of 10 false positives per data set.
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