A PyTorch-based ptychography framework achieves up to 24x faster reconstructions than existing packages and adds a real-space depth regularization that reduces wrap-around artifacts in 3D imaging.
Improved Three-Dimensional Reconstructions in Electron Ptychography through Defocus Series Measurements
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
A detailed analysis of ptychography for 3D phase reconstructions of thick specimens is performed. We introduce multi-focus ptychography, which incorporates a 4D-STEM defocus series to enhance the quality of 3D reconstructions along the beam direction through a higher overdetermination ratio. This method is compared with established multi-slice ptychography techniques, such as conventional ptychography, regularized ptychography, and multi-mode ptychography. Additionally, we contrast multi-focus ptychography with an alternative method that uses virtual optical sectioning through a reconstructed scattering matrix ($\mathcal{S}$-matrix), which offers more precise 3D structure information compared to conventional ptychography. Our findings from multiple 3D reconstructions based on simulated and experimental data demonstrate that multi-focus ptychography surpasses other techniques, particularly in accurately reconstructing the surfaces and interface regions of thick specimens.
fields
cond-mat.mtrl-sci 1years
2025 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
PtyRAD: A High-performance and Flexible Ptychographic Reconstruction Framework with Automatic Differentiation
A PyTorch-based ptychography framework achieves up to 24x faster reconstructions than existing packages and adds a real-space depth regularization that reduces wrap-around artifacts in 3D imaging.