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Synchrotron radiation can be used as a light source in X-ray microscopy to acquire a high-resolution image of a microscale object for tomography. However, numerous projections must be captured for a high-quality tomographic image to be reconstructed; thus, image acquisition is time consuming. Such dense imaging is not only expensive and time consuming but also results in the target receiving a large dose of radiation. To resolve these problems, sparse acquisition techniques have been proposed; however, the generated images often have many artefacts and are noisy. In this study, a deep-learning-based approach is proposed for the tomographic reconstruction of sparse-view projections that are acquired with a synchrotron light source; this approach proceeds as follows. A convolutional neural network (CNN) is used to first interpolate sparse X-ray projections and then synthesize a sufficiently large set of images to produce a sinogram. After the sinogram is constructed, a second CNN is used for error correction. In experiments, this method successfully produced high-quality tomography images from sparse-view projections for two data sets comprising Drosophila and mouse tomography images. However, the initial results for the smaller mouse data set were poor; therefore, transfer learning was used to apply the Drosophila model to the mouse data set, greatly improving the quality of the reconstructed sinogram. The method could be used to achieve high-quality tomography while reducing the radiation dose to imaging subjects and the imaging time and cost., (open access.)

Microscopy by Achromatic X-rays With Emission of Laminar Light (MAXWELL) is a new X-ray/visible technique with attractive characteristics including isotropic resolution in all directions, large-volume imaging and high throughput. An ultrathin, laminar X-ray beam produced by a Wolter type I mirror irradiates the sample stimulating the emission of visible light by scintillating nanoparticles, captured by an optical system. Three-dimensional (3D) images are obtained by scanning the specimen with respect to the laminar beam. We implemented and tested the technique with a high-brightness undulator at SPring-8, demonstrating its validity for a variety of specimens. This work was performed under the Synchrotrons for Neuroscience-an Asia-Pacific Strategic Enterprise (SYNAPSE) collaboration., (© 2022. The Author(s).)

The new Brain Imaging Beamline (BIB) of the Taiwan Photon Source (TPS) has been commissioned and opened to users. The BIB and in particular its endstation are designed to take advantage of bright unmonochromatized synchrotron X-rays and target fast 3D imaging, ∼1 ms exposure time plus very high ∼0.3 µm spatial resolution. A critical step in achieving the planned performances was the solution to the X-ray induced damaging problems of the detection system. High-energy photons were identified as their principal cause and were solved by combining tailored filters/attenuators and a high-energy cut-off mirror. This enabled the tomography acquisition throughput to reach >1 mm 3  min -1 , a critical performance for large-animal brain mapping and a vital mission of the beamline.