In the dual-phase grating system of X-ray phase-contrast imaging, the reduction in structural requirements for the absorption grating relaxes the constraints on its aspect ratio and period, thereby broadening the applicability of X-ray phase-contrast imaging techniques in a wider market. Traditionally, the extraction of phase-contrast information primarily relies on phase-stepping methods or Fourier transform algorithms, which often introduce artifacts and blurring into the images. To achieve higher quality image restoration, this study introduces generative adversarial networks (GANs) for high-quality image reconstruction. Our approach uses ideal images as labels and images containing object stripe information as inputs, utilizing GANs for feature learning to facilitate the transformation from object stripe images to high-quality phase-contrast images. The network also employs transfer learning to process previously unseen object stripe images and generate corresponding phase-contrast images. This technique not only significantly enhances image resolution but also substantially reduces artifacts and blurring in the image processing, paving the way for high-precision demands in medical diagnostics and industrial inspection.
Single-shot non-invasive imaging through a scattering medium has been an area of research focus for several years. Achieving an accurate autocorrelation distribution is crucial for effective image reconstruction. However, the obtained autocorrelation is always contaminated by various types of noise. In this study, we propose an effective method to extract the autocorrelation distribution of the sample from the noise-laden raw data before image retrieval. This is accomplished by incorporating an intensity threshold and a spatial Gaussian filter into the retrieval algorithm, which effectively eliminates the noise artifacts in the reconstructed image. The proposed algorithm exhibited remarkable robustness for both visible (laser, white light, and light-emitting diode light) and X-ray light sources, and its efficacy was verified through multiple experiments.
The cascade X-ray phase-contrast imaging system is composed of a set of Talbot-Lau interferometers and inverse Talbot-Lau interferometers, which can avoid the difficulty of making small-period high aspect ratio absorption gratings, and is expected to realize the application of X-ray phase-contrast imaging for large-field of view. This equipment can simultaneously obtain the absorption images, phase contrast images and scattering images of the sample using Fourier transform algorithm of a single sample exposure. The selection of the frequency domain window function of the sample fringe image and its influencing factors are the key to optimize image quality. Aiming at the X-ray cascade grating phase-contrast imaging system, this paper use the X-ray chest transmission image as the simulation sample, simulates the selection scheme of Fourier window function in frequency domain and its influencing factors by numerical calculation, and obtains the selection range of window function for the optimal image. The simulation results show that the optimal window function is selected by taking the high frequency edge of the sample fringe image as one side edge of the window function and extending linearly to the low frequency side. The selection range of window function is inversely proportional to the sample fringe period. The smaller the fringe period is, the larger the selection range of window function is, and the more favorable it is to obtain the optimal phase-contrast image.
It is known that the sensitivity of X-ray phase-contrast grating interferometry with regard to electron density variations present in the sample is related to the minimum detectable refraction angle. In this article an X-ray phase template is developed that allows for a realistic and quantitative determination of the sensitivity in X-ray phase-contrast imaging using cascaded grating interferometers. The template is designed as a periodic structure composed of different inclination angles and fabricated on a PMMA substrate. Fourier analysis of the moiré fringe patterns generated by the interferometer is used to obtain the phase-contrast image of the template. Experimental results show that the sensitivity, i.e. the minimum detectable refraction angle of this interferometer, is between 0.1 μrad and 0.2 μrad for the template with structure period of 4 mm. This work will help to evaluate and optimize existing cascaded grating interferometers for x-ray differential phase-contrast imaging.
When there is mechanical drift in X-ray phase contrast imaging system, the position of the grating will produce random error, and the intensity of the obtained image will have a certain deviation, and the information retrieved by using the phase step method may be accompanied with Moire artifacts. In order to overcome this limitation, we introduce the convolutional neural network (CNN) to address it. The training data is downloaded from Kaggle, and the fringe graph with random deviation is combined as the network input, while the label is defined as the first-order difference image along the horizontal direction of the image. Both simulation and experiment show that CNN can not only retrieve the phase signal of the sample, but also remove some Moire artifacts with regular shape to improve the image quality. As a result, the utilization rate of X-ray in imaging system can be improved.
An optimization-based algorithm is introduced to achieve the subpixel resolution in x-ray imaging. In this approach, the image captured by a detector is to be considered as a degradation of a high-resolution image. The inverse problem of the degradation is formulated as an optimization program. Through solving the cost function with Chambolle–Pock (CP) algorithm, we can reconstruct the subpixel image from multiple images shifted with subpixel precision. Numerical studies indicate that the iterative algorithm can numerically accurately invert the degradation. A set of x-ray imaging experiments were performed, and some structural information can be found in the reconstruction of the high-resolution image but not existing in the original image data. It would have potential applications in x-ray high-resolution imaging and industrial detection.
Long exposure time is one of the major limitations in x-ray phase-contrast imaging (XPCI). Therefore, we demonstrate a promising alternative method for grating-based XPCI coupled with cascaded Talbot–Lau interferometers (TLIs). A Fourier analysis of the moiré fringe patterns generated by the interferometers was used to obtain the multicontrast images (such as absorption, differential phase-contrast, and normalized visibility-contrast images) with a single exposure. The cascaded configuration with TLI and inverse TLI using large-period absorption gratings was established to verify the effectiveness of the algorithm and three multicontrast images of a polytetrafluoroethylene (PTFE) tube were obtained experimentally. The groove structures in the PTFE can be clearly identified in the differential phase-contrast image. This method shows potential for application of cascaded TLI in medical imaging.
Grating-based X-ray phase-contrast imaging (XPCI), have shown great potential for biological and medical imaging applications. However, the fabrication of the absorption grating, an indispensable element in conventional Talbot-Lau interferometer (TLI), making it a great challenge to this technology into practical use. In this paper, we implemented a cascade TLI (CTLI) for XPCI composed by a TLI and an inverse TLI, the self-image of TLI being used as the source of the inverse TLI, with the purpose to avoid the fabrication of small-period high aspect-ratio absorption gratings. Experiments validated the method and demonstrated the versatility and tunability of the system. The angular sensitivity as a function of the sample position was measured and discussed. Results show that the highest sensitivity is obtained, when the investigated object is close to any of two phase gratings. Furthermore, a CTLI with interference fringes being magnified to be directly detected by a common large-area detector would be established using this method. This will be useful for designing an XPCI system for applications of biomedical imaging in large field of view.
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