Grating-based phase contrast mammography can help facilitate breast cancer diagnosis, as several research works have demonstrated. To translate this technique to the clinics, it has to be adapted to cover a large field of view within a limited exposure time and with a clinically acceptable radiation dose. This indicates that a straightforward approach would be to install a grating interferometer (GI) into a commercial mammography device. We developed a wave propagation based optimization method to select the most convenient GI designs in terms of phase and dark-field sensitivities for the Philips Microdose Mammography (PMM) setup. The phase sensitivity was defined as the minimum detectable breast tissue electron density gradient, whereas the dark-field sensitivity was defined as its corresponding signal-to-noise Ratio (SNR). To be able to derive sample-dependent sensitivity metrics, a visibility reduction model for breast tissue was formulated, based on previous research works on the dark-field signal and utilizing available Ultra-Small-Angle X-ray Scattering (USAXS) data and the outcomes of measurements on formalin-fixed breast tissue specimens carried out in tube-based grating interferometers. The results of this optimization indicate the optimal scenarios for each metric are different and fundamentally depend on the noise behavior of the signals and the visibility reduction trend with respect to the system autocorrelation length. In addition, since the inter-grating distance is constrained by the space available between the breast support and the detector, the best way we have to improve sensitivity is to count on a small G2 pitch.
Despite the fact that the resolution of conventional contact/proximity lithography can reach feature sizes down to ~0.5- 0.6 micrometers, the accurate control of the linewidth and uniformity becomes already very challenging for gratings with periods in the range of 1-2 μm. This is particularly relevant for the exposure of large areas and wafers thinner than 300 μm. If the wafer or mask surface is not fully flat due to any kind of defects, such as bowing/warpage or remaining topography of the surface in case of overlay exposures, noticeable linewidth variations or complete failure of lithography step will occur. We utilized the newly developed Displacement Talbot lithography to pattern gratings with equal lines and spaces and periods in the range of 1.0 to 2.4 μm. The exposures in this lithography process do not require contact between the mask and the wafer, which makes it essentially insensitive to surface planarity and enables exposures with very high linewidth uniformity on thin and even slightly deformed wafers. We demonstrated pattern transfer of such exposures into Si substrates by reactive ion etching using the Bosch process. An etching depth of 30 μm or more for the whole range of periods was achieved, which corresponds to very high aspect ratios up to 60:1. The application of the fabricated gratings in phase contrast x-ray imaging is presented.
Dark-field imaging has the potential to overcome limitations in computed tomography (CT) investigating relatively
weakly absorbing material. However, an object-position dependence of the visibility loss in dark-field
imaging is observed. This effect might be negligible for small objects, but, for acquisition geometries using fanangle
apertures and field of views as those in human CT scanners, the object-position dependence of visibility
loss has to be taken into consideration if the scattering structure within the object is in the range of the grating
periods, i.e. micrometer. This work examines the effect of object-position dependent visibility loss in dark-field
imaging experimentally, investigates its consequences and presents an algorithm which solves the corresponding
X-ray phase contrast imaging (PCI) can provide high sensitivity of weakly absorbing low-Z objects in medical and biological fields, especially in mammography. Grating-based differential phase contrast (DPC) method is the most potential PCI method for clinic applications because it can works well with conventional X-ray tube and it can retrieve attenuation, DPC and dark-field information of the samples in a single scanning. Three kinds of information have different details and contrast which represent different physical characteristics of X-rays with matters. Hence, image fusion can show the most desirable characteristics of each image. In this paper, we proposed a multi-scale image fusion for X-ray grating-based DPC mammography. Firstly, non-local means method is adopted for denoising due to the strong noise, especially for DPC and dark-field images. Then, Laplacian pyramid is used for multi-scale image fusion. The principal component analysis (PCA) method is used on the high frequency part and the spatial frequency method is used on the low frequency part. Finally, the fused image is obtained by inverse Laplacian pyramid transform. Our algorithm is validated by experiments. The experiments were performed on mammoDPC instrumentation at the Paul Scherrer Institut in Villigen, Switzerland. The results show that our algorithm can significantly show the advantages of three kinds of information in the fused image, which is very helpful for the breast cancer diagnosis.
Differential phase-contrast imaging in the x-ray domain provides three physically complementary signals:1, 2 the
attenuation, the differential phase-contrast, related to the refractive index, and the dark-field signal, strongly
influenced by the total amount of radiation scattered into very small angles. In medical applications, it is of
the utmost importance to present to the radiologist all clinically relevant information in as compact a way as
possible. Hence, the need arises for a method to combine two or more of the above mentioned signals into
one image containing all information relevant for diagnosis. We present an image composition algorithm that
fuses the attenuation image and the differential phase contrast image into a composite, final image based on the
assumption that the real and imaginary part of the complex refractive index of the sample can be related by a
constant scaling factor. The merging is performed in such a way that the composite image is characterized by
minimal noise-power at each frequency component.
A new imaging setup, aimed to perform differential X-ray phase contrast (DPC) imaging with a Talbot interferometer
on a microfocus X-ray tube, is demonstrated. The main features compared to recently proposed setups
are an extremely short source to detector distance, high spatial resolution and a large field of view. The setup
is designed for an immediate integration into a industrial micro CT scanner. In this paper, technical challenges
of a compact setup, namely the critical source coherence and divergence, are discussed. A theoretical analysis
using wave optics based computer simulations is performed to estimate the DPC signal visibility and the size
of the field of view for a given setup geometry. The maximization of the signal visibility as a function of the
inter-grating distance yields the optimal grating parameters. Imaging results using the optimized grating parameters
are presented. The reduction of the field of view, being a consequence of the high beam divergence,
was solved by fabricating new, cylindrically bent diffraction gratings. The fabrication process of these gratings
required a change of the currently used wafer materials and an adaption of the manufacturing techniques. The
implementation of the new setup represents a major step forward for the industrial application of the DPC
Hard X-ray phase-contrast imaging has been a hot research field in the last decade. It can provide high sensitivity of
weakly absorbing low-Z objects in medical and biological fields. Grating-based differential phase-contrast (DPC)
method has been paid more attention to because it can work with conventional X-ray tube and shows great potential for
clinic application. Tomosynthesis with the combination of phase-contrast imaging is considered as a promising imaging
method which can significantly enhance the contrast of low absorbing tissues and eliminate the effects of superimposed
tissue on anatomical structures and is especially useful for medical applications such as mammography. In this paper, an
experimental phase-contrast tomosynthesis system is implemented based on a weakly coherent hard X-ray phase-contrast
method proposed by our group recently. The effectiveness of the proposed method is proved by actual experiments.
Multiple information (absorption, refraction and dark-field) of the samples can be retrieved in one single imaging
process by information retrieving methods. Then tomosynthesis reconstructions can be performed based on the retrieved
information. It can eliminate the overlap of the sample structures and provide more extensive image information
compared with conventional tomosynthesis.
The aim of the present study is to investigate a type of Bayesian reconstruction which utilizes partial differential
equations (PDE) image models as regularization. PDE image models are widely used in image restoration and
segmentation. In a PDE model, the image can be viewed as the solution of an evolutionary differential equation. The
variation of the image can be regard as a descent of an energy function, which entitles us to use PDE models in Bayesian
reconstruction. In this paper, two PDE models called anisotropic diffusion are studied. Both of them have the
characteristics of edge-preserving and denoising like the popular median root prior (MRP). We use PDE regularization
with an Ordered Subsets accelerated Bayesian one step late (OSL) reconstruction algorithm for emission tomography.
The OS accelerated OSL algorithm is more practical than a non-accelerated one. The proposed algorithm is called
OSEM-PDE. We validated the OSEM-PDE using a Zubal phantom in numerical experiments with attenuation correction
and quantum noise considered, and the results are compared with OSEM and an OS version of MRP (OSEM-MRP)
reconstruction. OSEM-PDE shows better results both in bias and variance. The reconstruction images are smoother and
have sharper edges, thus are more applicable for post processing such as segmentation. We validate this using a k-means
segmentation algorithm. The classic OSEM is not convergent especially in noisy condition. However, in our experiment,
OSEM-PDE can benefit from OS acceleration and keep stable and convergent while OSEM-MRP failed to converge.