Title: Phase Recovery: A Unifying Theme in Computational Imaging   

Abstract: It has become clear that Phase Recovery is a unifying theme in a wide range of computational imaging problems. Perhaps this is because it is the simplest non-linear inverse problem that can be successfully solve when there is sufficient data. In this talk, we present the core equations of phase recovery and show how they can be applied to applications ranging from heterodyne demodulation, to ptychography, and imaging through turbulence. Unlike linear inverse problems, phase recovery typically demands an iterative solution, which makes it computationally expensive. However, when solved using the best algorithms, the solutions tend to be surprisingly robust and can lead to dramatic improvements in image quality. 

Bio: Charles A. Bouman is the Showalter Professor of Electrical and Computer Engineering and Biomedical Engineering at Purdue University. He is a founder of the field of computational imaging and has conducted much research in this area. He received his B.S.E.E. degree from the University of Pennsylvania, M.S. degree from the University of California at Berkeley, and Ph.D. from Princeton University in 1989. He is a member of the National Academy of Inventors, a Fellow of the IEEE, AIMBE, and SPIE, and an Honorary Member of the IS&T. He is the recipient of the 2021 IEEE Signal Processing Society, Claude Shannon-Harry Nyquist Technical Achievement Award, the 2014 Electronic Imaging Scientist of the Year award, and in 2020, his paper on Plug-and-Play Priors won the SIAM Imaging Science Best Paper Prize. He has served as the IEEE Signal Processing Society’s Vice President of Technical Directions, Editor-in-Chief of the IEEE Transactions on Image Processing, Vice President of Publications for the IS&T Society, and he led the creation of the IEEE Transactions on Computational Imaging. 

Title: Towards ptychographic single particle imaging 

Abstract: In this talk we discuss the use of generative models as priors for a robust reconstruction in ptychographic inversion with high uncertainty. As a simplified model towards ptychographic single particle imaging we consider the reconstruction in ptychography with unknown positions. We compare different approaches and discuss the potential and limitations of the approach.  

Bio: Martin Burger is a Lead Scientist at DESY and Professor of Mathematics at the University of Hamburg. He heads the Computional Imaging group at DESY, which is also a research unit of the Helmholtz Imaging cooperation platform. Together with his team, he develops imaging reconstruction methods and novel mathematical tools with the aim of improving the reconstruction and analysis of scientific images. Moreover, his group is concerned with the mathematical foundations of machine learning and of algorithms in data science.

Title: Joint Holotomography Solver for Large-Scale Experimental Data Processing

Abstract: Multi-distance holotomography enables quantitative three-dimensional phase-contrast imaging with coherent hard X-rays and routinely achieves sub-100 nm resolution. At such resolutions, reconstructions become sensitive to probe structure and scanning positions. Conventional workflows address these effects through sequential processing steps, which can limit accuracy.

We present a scalable joint reconstruction framework that simultaneously estimates the object, illumination probe, and scan-position corrections from the measured data. Using a bilinear-Hessian-based optimization strategy and a multi-GPU implementation, the method enables practical joint reconstruction of large experimental datasets and reduces artifacts compared with conventional pipelines.

Bio: Peter Cloetens is a scientist at the European Synchrotron Radiation Facility (ESRF) in Grenoble, France, where he is responsible for the ID16A beamline dedicated to nano-scale X-ray imaging. He studied engineering at the Vrije Universiteit Brussel and joined ESRF in 1994. His research focuses on advanced synchrotron-based imaging methods, including phase-contrast imaging and nano-tomography, enabling high-resolution investigations of materials and biological tissues. Cloetens collaborates widely with international research teams using synchrotron techniques to study complex structures across materials science and life sciences. 

Title: Ptycho-Gramian: the inner products between frames and correlated beam instabilities

Abstract: Ideally, in ptychography, each pair of exit waves is related by a spatial shift and a common illumination function. In practice, beams fluctuate and samples drift, adding up exit waves incoherently onto the detector. Here we investigate the pairwise discrepancy among reconstructed frames to scale up convergence rates for large scale problems. Joint work with Yuan Ni (SLAC) and Huibin Chang (Tianjin Normal University)

Bio: Master in Physics in Parma, Italy. Ph.D. in Physics, in Grenoble, France (2000), Lawrence Berkeleley National Lab (2000-2002, 2007-2020), Lawrence Livermore National Lab (2003-2007), SLAC/Stanford (2021-present). Directors awards for scientific achievements at LBNL, LLNL, SLAC, and Optica Fellow. 

Title: Ptychography reconstruction: Fast optimization methods from a signal processing perspective

Abstract: Ptychography, a versatile computational imaging technique that jointly reconstructs the sample's complex function and the illumination probe from a series of overlapping intensity measurements, is a challenging nonconvex inverse problem whose applications span across physics, materials science, and biology.

From a signal processing standpoint, existing reconstruction methods can be broadly categorized according to their optimization paradigm, namely alternating optimization schemes—such as Error Reduction (ER) and extended Ptychographic Iterative Engine (ePIE)—and simultaneous optimization approaches, exemplified by Wirtinger Flow.

This talk revisits this classification and provides a unified analysis demonstrating that classical acceleration techniques, including Nesterov-type momentum, can be naturally incorporated. This perspective also offers new insight into the historical limitations of the ePIE algorithm family and explains why their convergence properties were not fully leveraged in earlier implementations.

Furthermore, in this talk I will also introduce an illumination probe positions' uncertainty aware AO-based algorithm whose practical RoC (rate of convergence) is either competitive or surpases the performance of several state-of-the-art Ptychography reconstruction algorithms.

Title: Phase Retrieval and Tomographic Reconstruction in X-ray Near-field Diffractive Imaging beyond Idealised and Linearised Solutions 

Abstract: X-rays can provide information about the structure of matter, on multiple length scales from bulk materials to nanoscale devices. Due to the widespread lack of suitable lenses, the majority of data are rather indirect – apart from classical shadow radiography perhaps.

Phase retrieval is a particular challenge in lensless X-ray imaging, in particular at the nanoscale. How can we address and implement optimized phase retrieval and tomography solutions under non-ideal conditions, taking into account unwanted motion and drift , partial coherence, propagation, region-of-interest tomography, diffraction within the object and cone beam geometry? We show how solutions and algorithms of mathematics of inverse problems [1-3] help us to meet the challenges of phase retrieval, tomographic reconstruction, and also image processing of bulky data. We then present a novel approach to achieve super-resolution in X-ray inline holography [3,4], and go on to show that holographic phase retrieval can also be used for full-field incoherent imaging [5].

We illustrate the performance of the algorithmic tools by ambitious examples, addressing high resolution in large volume for ambitious applications in histology and histopathology.

Bio: Tim Salditt is a German physicist and professor at the University of Göttingen. His research focuses on experimental biophysics and X-ray physics, particularly the study of biological membranes, cells, and soft matter using advanced imaging and scattering techniques. He is known for his contributions to coherent X-ray imaging and for bridging physics with life sciences. 

References:

[1] T. Salditt, A. Egner and R. D. Luke. Nanoscale Photonic Imaging Springer Nature Topics in Applied Physics 134, Open Access Book (2020).

[2] L. M. Lohse, A.-L. Robisch, M. Töpperwien, S. Maretzke, M. Krenkel, J. Hagemann and T. Salditt. A phase-retrieval toolbox for X-ray holography and tomography Journal of Synchrotron Radiation 27, 3 (2020); J. Lucht, P. Meyer, L.M. Lohse, T. Salditt. HoToPy: A toolbox for X-ray holo-tomography in Python, J Synchrotron Radiat. 32:1586-1594. doi: 10.1107/S1600577525008550.

[3] J. Soltau, M. Vassholz, M. Osterhoff and T. Salditt. In-line holography with hard x-rays at sub-15 nm resolution. Optica 8,823 (2021);

[4] P. Meyer, L. M. Lohse, J. Lucht, Y. R. Tonin, M. Osterhoff, T. Salditt, On super-resolution holography: effective geometry, sampling, and constraints- Opt Express 26. 53966 (2025) doi: 10.1364/OE.579705.

[5] J. Soltau, P. Meyer, …T. Salditt. Optica 10, 127-133 (2023); P. Meyer, T. Salditt, Full-field x-ray fluorescence imaging based on coded aperture ghost imaging Opt.Express 33, 41802 (2025); doi: 10.1364/OE.570310.