Over the last year a group of imaging enthusiasts has met to discuss
current issues of phase contrast imaging and tomography at PETRA III. I
will give a short introduction to the experimental modality and
introduce some of the challenges we investigate currently.
In near-field imaging, accurate phase retrieval is crucial for reconstructing complex wavefronts, with applications in optics, microscopy, and X-ray imaging. The beamlines at PETRA III, DESY, like many advanced imaging facilities, involve various inverse problems, including computed tomography, phase retrieval, and image deblurring. Among these, phase retrieval stands out as a non-linear,...
In this talk, we're exploring possible data-driven ML methods to make quality estimation of retrieved phases in the context of near-field holograpy.
Near-field holography imaging is essential in science and industry for high-resolution imaging at nanostructures and microscopic scales, but it is highly sensitive to noise, which varies depending on both the detector type and the exposure time. This study introduces a machine learning based denoising method using dilated convolutional neural networks (DnCNN), which effectively reduces noise...
We present a deep learning approach based on the Noise2Noise framework to denoise multidimensional photoemission spectroscopy (MPES) data obtained with a time-of-flight momentum microscope. Specifically, a 3D U-Net architecture is trained using low- and high-count noisy data, enabling the model to learn noise characteristics without requiring clean images. Our approach excels at reconstructing...
As part of our correlative characterisation studies of biodegradable metal bone implants we have performed both synchrotron-radiation microtomography (SR-µCT) and histology sequentially on the same samples and regions of interest. Histological staining is still the gold standard for tissue visualisation yet requires multiple time-consuming sample preparation steps (fixing, embedding,...
In materials science research, digital volume correlation (DVC) analysis is commonly used to track deformations and strains to elucidate morphology-function relationships. Recently, we proposed the neural network, VolRAFT, which estimated the 3D displacement vector between the reference volume and the deformed volume by extending the state-of-the-art optical flow network from 2D images to 3D...
With the high brilliance and ultrashort pulses of X-ray Free Electron Lasers, Serial Femtosecond Crystallography (SFX) achieved atomic-resolution for micro and nano protein crystals. Throughout the data collection the beam is prone to fluctuations caused by the self-amplified spontaneous emission process which generates the beam and is intrinsically a stochastic phenomenon. These fluctuations...
X-ray--induced Coulomb explosion imaging is one promising method to perform single-particle molecular imaging on a femtosecond timescale. By firing an intense ultrashort XFEL pulse at single molecules, it gets strongly ionized and violently dissociates into atomic fragments that are measured in coincidence. However, due to the finite detection efficiency in the experiment, the collected data...
Virtual diagnostics can provide complementary diagnostics, by combining information from several sources, thereby profiting from the advantages of each one. To this end, we present the Virtual Spectrometer, which maps data from a low-resolution time-of-flight spectrometer to a high-resolution one. While the low-resolution spectrometer is non-invasive, can operate at 4.5 MHz and has complex...
Plasma-based accelerators hold the potential to achieve mulit-giga-volt-per-metre accelerating gradients, offering a promising route to more compact and cost-effective accelerators for future light sources and colliders. However, plasma wakefield acceleration (PWFA) is often a nonlinear, high-dimensional process that is sensitive to jitters in multiple input parameters, making the setup,...
