Abstract

In this paper, we present a single-shot X-ray speckle tracking (XST) phase-contrast imaging (PCI) method for a non-coherent polychromatic laboratory source. XST typically requires a coherent X-ray source, such as a synchrotron, to produce speckle. For a laboratory source without sufficient coherence, the absorption pattern of a random mask, such as sandpaper, have been proposed. However, to track the very small phase shifts in the absorption speckle below the size of the pixels of a standard flat panel detector in the range of 100μm, hundreds of detector images are taken, each moved by a linear stage by a fraction of a pixel to determine the phase shift. As a result, both acquisition time and radiation dose are high. Moreover, precise linear stages are required for sub-pixel movement of the random mask during acquisition of the projection images. In contrast, in this paper we propose a neural network called PCINet to acquire the differential phase image with only one reference image without the sample and one sample image. The proposed system does not require precise linear stages because only a single acquisition is needed. Due to the incoherent source, an absorption-based pseudo-speckle is generated as a reference image. In order to increase the contrast of the pseudo-speckle, a novel, cheap and easy to manufacture tungsten random spatial distrubution of particles is proposed as an alternative to sandpaper. A method for generating realistic training data for the neural network using real X-ray images in a laboratory setup was developed. The training data of the neural network was generated as close as possible to the real data by constructing the input image pairs pixel by pixel from multiple real X-ray images of the pseudo-speckle. The experimental resukts show that it is possible to obtain the differential phase image with only one reference image and one sample image with superimposed absorption speckles in the case of an incoherent laboratory setup.

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