Discrimination analysis of breast calcifications using x-ray dark-field radiography

Deep-learning-based denoising of X-ray differential phase and dark-field images

PURPOSE

Statistical photon noise has always been a common problem in X-ray multi-contrast imaging and significantly influenced the quality of retrieved differential phase and dark-field images. We intend to develop a deep learning-based denoising algorithm to reduce the noise of retrieved X-ray differential phase and dark-field images.

METHODS

A novel deep learning based image noise suppression algorithm (named DnCNN-P) is presented. We proposed two different denoising modes: Retrieval-Denoising mode (R-D mode) and Denoising-Retrieval mode (D-R mode). While the R-D mode denoises the retrieved images, the D-R mode denoises the raw phase stepping data. The two denoising modes are evaluated under different photon counts and visibilities.

RESULTS

Experimental results show that with the algorithm DnCNN-P used, the D-R mode always exhibits a better noise reduction under diverse experimental conditions, even in the case of a low photon count and/or a low visibility. With a detected photon count of 1800 and a visibility of 0.3, compared to the differential phase images without denoising, the standard deviation is reduced by 89.1% and 16.4% in the D-R and R-D modes. Compared to the dark-field images without denoising, the standard deviation is reduced by 83.7% and 12.6% in the D-R and R-D modes, respectively.

CONCLUSIONS

The novel supervised DnCNN-P algorithm can significantly reduce the noise in retrieved X-ray differential phase and dark-field images. We believe this novel algorithm can be a promising approach to improve the quality of X-ray differential phase and dark-field images, and therefore dose efficiency in future biomedical applications.

A novel fusion method for X-ray phase contrast imaging based on fast adaptive bidimensional empirical mode decomposition

BACKGROUNDS

X-ray phase contrast imaging (XPCI) can separate the attenuation, refraction, and scattering signals of the object. The application of image fusion enables the concentration of distinctive information into a single image. Some methods have been applied in XPCI field, but wavelet-based decomposition approaches often result in loss of original data.

OBJECTIVE

To explore the application value of a novel image fusion method for XPCI system and computed tomography (CT) system.

METHODS

The means of fast adaptive bidimensional empirical mode decomposition (FABEMD) is considered for image decomposition to avoid unnecessary information loss. A parameter δ is proposed to guide the fusion of bidimensional intrinsic mode functions which contain high-frequency information, using a pulse coupled neural network with morphological gradients (MGPCNN). The residual images are fused by the energy attribute fusion strategy. Image preprocessing and enhancement are performed on the result to ensure its quality. The effectiveness of other image fusion methods has been compared, such as discrete wavelet transforms and anisotropic diffusion fusion.

RESULTS

The δ-guided FABEMD-MGPCNN method achieved either the first or second position in objective evaluation metrics with biological samples, as compared to other image fusion methods. Moreover, comparisons are made with other fusion methods used for XPCI. Finally, the proposed method applied in CT show expected results to retain the feature information.

CONCLUSIONS

The proposed δ-guided FABEMD-MGPCNN method shows potential feasibility and superiority over traditional and recent image fusion methods for X-ray differential phase contrast imaging and computed tomography systems.

Intensity-based iterative reconstruction for helical grating interferometry breast CT with static grating configuration

Grating interferometry breast computed tomography (GI-BCT) has the potential to provide enhanced soft tissue contrast and to improve visualization of cancerous lesions for breast imaging. However, with a conventional scanning protocol, a GI-BCT scan requires longer scanning time and higher operation complexity compared to conventional attenuation-based CT. This is mainly due to multiple grating movements at every projection angle, so-called phase stepping, which is used to retrieve attenuation, phase, and scattering (dark-field) signals. To reduce the measurement time and complexity and extend the field of view, we have adopted a helical GI-CT setup and present here the corresponding tomographic reconstruction algorithm. This method allows simultaneous reconstruction of attenuation, phase contrast, and scattering images while avoiding grating movements. Experiments on simulated phantom and real initial intensity, visibility and phase maps are provided to validate our method.

The effect of a variable focal spot size on the contrast channels retrieved in edge-illumination X-ray phase contrast imaging

Multi-modal X-ray imaging allows the extraction of phase and dark-field (or “Ultra-small Angle Scatter”) images alongside conventional attenuation ones. Recently, scan-based systems using conventional sources that can simultaneously output the above three images on relatively large-size objects have been developed by various groups. One limitation is the need for some degree of spatial coherence, achieved either through the use of microfocal sources, or by placing an absorption grating in front of an extended source. Both these solutions limit the amount of flux available for imaging, with the latter also leading to a more complex setup with additional alignment requirements. Edge-illumination partly overcomes this as it was proven to work with focal spots of up to 100 micron. While high-flux, 100 micron focal spot sources do exist, their comparatively large footprint and high cost can be obstacles to widespread translation. A simple solution consists in placing a single slit in front of a large focal spot source. We used a tunable slit to study the system performance at various effective focal spot sizes, by extracting transmission, phase and dark-field images of the same specimens for a range of slit widths. We show that consistent, repeatable results are obtained for varying X-ray statistics and effective focal spot sizes. As the slit width is increased, the expected reduction in the raw differential phase peaks is observed, compensated for in the retrieval process by a broadened sensitivity function. This leads to the same values being correctly retrieved, but with a slightly larger error bar i.e. a reduction in phase sensitivity. Concurrently, a slight increase in the dark-field signal is also observed.

Whole-body x-ray dark-field radiography of a human cadaver

BACKGROUND

Grating-based x-ray dark-field and phase-contrast imaging allow extracting information about refraction and small-angle scatter, beyond conventional attenuation. A step towards clinical translation has recently been achieved, allowing further investigation on humans.

METHODS

After the ethics committee approval, we scanned the full body of a human cadaver in anterior-posterior orientation. Six measurements were stitched together to form the whole-body image. All radiographs were taken at a three-grating large-object x-ray dark-field scanner, each lasting about 40 s. Signal intensities of different anatomical regions were assessed. The magnitude of visibility reduction caused by beam hardening instead of small-angle scatter was analysed using different phantom materials. Maximal effective dose was 0.3 mSv for the abdomen.

RESULTS

Combined attenuation and dark-field radiography are technically possible throughout a whole human body. High signal levels were found in several bony structures, foreign materials, and the lung. Signal levels were 0.25 ± 0.13 (mean ± standard deviation) for the lungs, 0.08 ± 0.06 for the bones, 0.023 ± 0.019 for soft tissue, and 0.30 ± 0.02 for an antibiotic bead chain. We found that phantom materials, which do not produce small-angle scatter, can generate a strong visibility reduction signal.

CONCLUSION

We acquired a whole-body x-ray dark-field radiograph of a human body in few minutes with an effective dose in a clinical acceptable range. Our findings suggest that the observed visibility reduction in the bone and metal is dominated by beam hardening and that the true dark-field signal in the lung is therefore much higher than that of the bone.

Dark-field signal extraction in propagation-based phase-contrast imaging

A method for extracting the dark-field signal in propagation-based phase-contrast imaging is proposed. In the case of objects consisting predominantly of a single material, or several different materials with similar ratios of the real decrement to the imaginary part of the complex refractive index, the proposed method requires a single image for extraction of the dark-field signal in two-dimensional projection imaging. In the case of three-dimensional tomographic imaging, the method needs only one image to be collected at each projection angle. Initial examples using simulated and experimental data indicate that this method can improve visualization of small sharp features inside a larger object, e.g. the visualization of microcalcifications in propagation-based x-ray breast cancer imaging. It is suggested that the proposed approach may be useful in other forms of biomedical imaging, where it can help one to obtain additional small-angle scattering information without increasing the radiation dose to the sample.

Recent advances in X-ray imaging of breast tissue: From two- to three-dimensional imaging

Breast cancer is a globally widespread disease whose detection has already been significantly improved by the introduction of screening programs. Nevertheless, mammography suffers from low soft tissue contrast and the superposition of diagnostically relevant anatomical structures as well as from low values for sensitivity and specificity especially for dense breast tissue. In recent years, two techniques for X-ray breast imaging have been developed that bring advances for the early detection of breast cancer. Grating-based phase-contrast mammography is a new imaging technique that is able to provide three image modalities simultaneously (absorption-contrast, phase-contrast and dark-field signal). Thus, an enhanced detection and delineation of cancerous structures in the phase-contrast image and an improved visualization and characterization of microcalcifications in the dark-field image is possible. Furthermore, latest studies about this approach show that dose-compatible imaging with polychromatic X-ray sources is feasible. In order to additionally overcome the limitations of projection-based imaging, efforts were also made towards the development of breast computed tomography (BCT), which recently led to the first clinical installation of an absorption-based BCT system. Further research combining the benefits of both imaging technologies is currently in progress. This review article summarizes the latest advances in phase-contrast imaging for the female breast (projection-based and three-dimensional view) with special focus on possible clinical implementations in the future.

Emerging methods in radiology

Imaging modalities have developed rapidly in recent decades. In addition to improved resolution as well as whole-body and faster image acquisition, the possibilities of functional and molecular examination of tissue pathophysiology have had a decisive influence on imaging diagnostics and provided ground-breaking knowledge. Many promising approaches are currently being pursued to increase the application area of devices and contrast media and to improve their sensitivity and quantitative informative value. These are complemented by new methods of data processing, multiparametric data analysis, and integrated diagnostics. The aim of this article is to provide an overview of technological innovations that will enrich clinical imaging in the future, and to highlight the resultant diagnostic options. These relate to the established imaging methods such as CT, MRI, ultrasound, PET, and SPECT but also to new methods such as magnetic particle imaging (MPI), optical imaging, and photoacoustics. In addition, approaches to radiomic image evaluation are explained and the chances and difficulties for their broad clinical introduction are discussed. The potential of imaging to describe pathophysiological relationships in ever increasing detail, both at whole-body and tissue level, can in future be used to better understand the mechanistic effect of drugs, to preselect patients to therapies, and to improve monitoring of therapy success. Consequently, the use of interdisciplinary integrated diagnostics will greatly change and enrich the profession of radiologists.