TY  - CONF
AU  - Grün, Johannes Philipp
AU  - Eberle, Sebastian
AU  - Greving, Imke
AU  - Flenner, Silja
AU  - Burger, Martin
AU  - Schroer, Christian
AU  - Hagemann, Johannes
TI  - X-ray Near-Field Holotomography Reconstruction Using Implicit Neural Representations
M1  - PUBDB-2026-00305
SP  - 5
PY  - 2026
N1  - P05: Beamtime-ID (11019330).
AB  - X-ray near-field holotomography provides non-destructive, in situ 3D visualization of specimen interiors at nanometer-scale resolution.Reconstruction traditionally involves two separate steps: first retrieving the projected phase for different rotation angles, then applying tomographic reconstruction to obtain a 3D volume from 2D projections.Both steps are ill-posed inverse problems and separating them leads to information loss, due to reconstruction errors.Recent advances in implicit neural representations (INRs) have demonstrated remarkable capabilities in scene rendering and tomographic reconstruction.In this work, we propose a unified INR-based framework that jointly solves the phase retrieval and tomographic reconstruction problems.This joint formulation enforces 3D consistency, resulting in significantly improved phase, absorption, and volumetric reconstructions.Moreover, INRs provide substantial data compression.This compression reduces storage requirements by 95%, which is particularly important with the advent of fourth-generation synchrotron sources and the corresponding growth in data volume.
T2  - International Conference on Acoustics, Speech, and Signal Processing
CY  - 4 May 2026 - 9 May 2026, Barcelona (Spain)
Y2  - 4 May 2026 - 9 May 2026
M2  - Barcelona, Spain
LB  - PUB:(DE-HGF)8
UR  - https://bib-pubdb1.desy.de/record/643594
ER  -