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Register a new userHard X-ray multi-projection imaging for single-shot approaches
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Added by
Pablo Villanueva Perez
Publication date
2018
fields
Physics
and research's language is
English
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Obtaining 3D information from a single X-ray exposure at high-brilliance sources, such as X-ray free-electron lasers (XFELs) [1] or diffraction-limited storage rings [2], allows the study of fast dynamical processes in their native environment. However, current X-ray 3D methodologies are either not compatible with single-shot approaches because they rely on multiple exposures, such as confocal microscopy [3, 4] and tomography [5, 6]; or they record a single projection per pulse [7] and are therefore restricted to approximately two-dimensional objects [8]. Here we propose and verify experimentally a novel imaging approach named X-ray multi-projection imaging (XMPI), which simultaneously acquires several projections without rotating the sample at significant tomographic angles. When implemented at high-brilliance sources it can provide volumetric information using a single pulse. Moreover, XMPI at MHz repetition XFELs could allow a way to record 3D movies of deterministic or stochastic natural processes in the micrometer to nanometer resolution range, and at time scales from microseconds down to femtoseconds.
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Full coherent soft X-ray attosecond pulses are now available through high-order harmonic generation (HHG); however, its insufficient output energy hinders various applications, such as attosecond-scale soft X-ray nonlinear experiments, the seeding of soft X-ray free-electron lasers, attosecond-pump-attosecond-probe spectroscopies, and single-shot imaging. In this paper, towards the implementation of these exciting studies, we demonstrate a soft X-ray harmonic beam that is more than two orders of magnitudes stronger up to the water window region compared to previous works. This was achieved by combining a newly developed TW class mid-infrared femtosecond laser and a loosely focusing geometry for HHG in the mid-infrared region for the first time. Thanks to a loosely focusing geometry with a neutral medium target, we achieve a high conversion efficiency, a low beam divergence, and a significantly reduced medium gas pressure. As the first application of our nano-joule level water window soft X-ray harmonic source, we demonstrate near edge X-ray absorption fine structure (NEXAFS) experiments with clear fine absorption spectra near the K- and L-edges observed in various samples. The systematic study of a robust energy scaling method on HHG opens the door for demonstrating single-shot absorption spectrum and live cell imaging with a femtosecond time resolution.
A well-characterised wavefront is important for many X-ray free-electron laser (XFEL) experiments, especially for single-particle imaging (SPI), where individual bio-molecules randomly sample a nanometer-region of highly-focused femtosecond pulses. We demonstrate high-resolution multiple-plane wavefront imaging of an ensemble of XFEL pulses, focused by Kirkpatrick-Baez (KB) mirrors, based on mixed-state ptychography, an approach letting us infer and reduce experimental sources of instability. From the recovered wavefront profiles, we show that while local photon fluence correction is crucial and possible for SPI, a small diversity of phase-tilts likely has no impact. Our detailed characterisation will aid interpretation of data from past and future SPI experiments, and provides a basis for further improvements to experimental design and reconstruction algorithms.
In this paper, we present a new method to generate an instantaneous volumetric image using a single x-ray projection. To fully extract motion information hidden in projection images, we partitioned a projection image into small patches. We utilized a sparse learning method to automatically select patches that have a high correlation with principal component analysis (PCA) coefficients of a lung motion model. A model that maps the patch intensity to the PCA coefficients is built along with the patch selection process. Based on this model, a measured projection can be used to predict the PCA coefficients, which are further used to generate a motion vector field and hence a volumetric image. We have also proposed an intensity baseline correction method based on the partitioned projection, where the first and the second moments of pixel intensities at a patch in a simulated image are matched with those in a measured image via a linear transformation. The proposed method has been valid in simulated data and real phantom data. The algorithm is able to identify patches that contain relevant motion information, e.g. diaphragm region. It is found that intensity correction step is important to remove the systematic error in the motion prediction. For the simulation case, the sparse learning model reduced prediction error for the first PCA coefficient to 5%, compared to the 10% error when sparse learning is not used. 95th percentile error for the predicted motion vector is reduced from 2.40 mm to 0.92mm. In the phantom case, the predicted tumor motion trajectory is successfully reconstructed with 0.82 mm mean vector field error compared to 1.66 mm error without using the sparse learning method. The algorithm robustness with respect to sparse level, patch size, and existence of diaphragm, as well as computation time, has also been studied.
For conventional imaging, the imaging resolution limit is given by the Rayleigh criterion. Exploiting the prior knowledge of imaging objects sparsity and fixed optical system, imaging beyond the conventional Rayleigh limit, which is backed up by numerical simulation and experiments, is achieved by illuminating the object with single-shot thermal light and detecting the objects information at the imaging plane with some sparse-array single-pixel detectors. The quality of sub-Rayleigh imaging with sparse detection is also shown to be related to the effective number of single-pixel detectors and the detection signal-to-noise ratio at the imaging plane.
Multispectral imaging plays an important role in many applications from astronomical imaging, earth observation to biomedical imaging. However, the current technologies are complex with multiple alignment-sensitive components, predetermined spatial and spectral parameters by manufactures. Here, we demonstrate a single-shot multispectral imaging technique that gives flexibility to end-users with a very simple optical setup, thank to spatial correlation and spectral decorrelation of speckle patterns. These seemingly random speckle patterns are point spreading functions (PSFs) generated by light from point sources propagating through a strongly scattering medium. The spatial correlation of PSFs allows image recovery with deconvolution techniques, while the spectral decorrelation allows them to play the role of tune-able spectral filters in the deconvolution process. Our demonstrations utilizing optical physics of strongly scattering media and computational imaging present the most cost-effective approach for multispectral imaging with great advantages.
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