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32 results for “ptychography”
Raw data for "Multi-slice ptychography enables high-resolution in situ measurements in extended chemical reactors"
<p>Raw data used in "Multi-slice ptychography enables high-resolution in situ measurements in extended chemical reactors" by M. Kahnt, L. Grote, D. Brückner, M. Seyrich, F. Wittwer, D. Koziej and C.G. Schroer.</p>
Live Iterative Ptychography
<p>This deposition contains data and code for live-updating ptychographic reconstruction with ePIE, an iterative ptychography method, during ongoing data acquisition.</p> <p>Corresponding paper: <a href="https://doi.org/10.1093/mam/ozae004">https://doi.org/10.1093/mam/ozae004</a> and <a href="https://doi.org/10.48550/arXiv.2308.10674">https://doi.org/10.48550/arXiv.2308.10674</a></p>
Datasets for 'Electron ptychography reveals a ferroelectricity dominated by anion displacements'
<p>4D-STEM datasets for the multislice electron ptychographic reconstructions reported in the paper 'Electron ptychography reveals a ferroelectricity dominated by anion displacements' <a href="https://doi.org/10.48550/arXiv.2408.14795" target="_blank" rel="noopener">arXiv.2408.14795</a>. The reconstruction code based on the <a href="https://github.com/yijiang1/fold_slice" target="_blank" rel="noopener">fold_slice</a> package is also provided along with the data.</p>
Datasets for Lorentz electron ptychography towards sub-nanometer resolution imaging of magnetic textures
<p>These data sets are the raw experimental data used in a Letter titled, Lorentz electron ptychography for imaging magnetic textures beyond the diffraction limit published on Nature Nanotechnology. The related paper should be cited whenever the datasets are used.</p> <p>Reference:</p> <p>Zhen Chen, Emrah Turgut, Yi Jiang, Kayla X. Nguyen, Matthew J. Stolt, Song Jin, Daniel C. Ralph, Gregory D. Fuchs, David A. Muller, Lorentz electron ptychography for imaging magnetic textures beyond the diffraction limit. Nature Nanotechnology, in press, https://doi.org/10.1038/s41565-022-01224-y (2022).</p> <p>The file format is Matlab's *.mat file with version 7.3.</p> <p>The diffraction patterns are stored as the variable 'cbed'.</p> <p>Experimental conditions can be found in data_info.txt and the related paper.</p> <p> </p>
Example Ptychography Data for the PtyPy Tutorials
<p>Experimental ptychography data collected at different X-ray instruments and electron microscopes at the Diamond Light Source. The purpose of this data deposition is to provide relevant experimental ptychography data for a comprehensive collection of tutorials for the PtyPy software framework, all which are available at <a href="https://ptycho.github.io/tutorials" target="_blank" rel="noopener">https://ptycho.github.io/tutorials</a>.</p>
Raw data for "Coupled ptychography and tomography algorithm improves reconstruction of experimental data"
<p>Raw data used in "<a href="https://www.osapublishing.org/optica/abstract.cfm?uri=optica-6-10-1282"><em>Coupled ptychography and tomography algorithm improves reconstruction of experimental data</em></a>" by M. Kahnt, J. Becher, D. Brückner, Y. Fam, T. Sheppard, T. Weissenberger, F. Wittwer, J.-D. Grunwaldt, W. Schwieger and C.G. Schroer</p>
Fourier Ptychography of kidney tissues
<p>Beyond conventional microscopy: observing Kidney tissues by means of Fourier Ptychography -</p> <p>Fourier Ptychography (FP) phase contrast image of a 3 µm thick unstained renal tissue slide and FP phase contrast image of the same region after staining with H&E. The previous images are compared with the corresponding H&E bright image captured by conventional microcopy of the same region on a different section. Moreover, we report a FP phase contrast image of a 10 µm thick unstained renal tissue slide, which has been obtained by stitching 16 FP fields of view to image a big portion of the kidney tissue slide under analysis.</p>
Deep Reinforcement Learning for Data-Driven Adaptive Scanning in Ptychography
<p>These are the data sets used for the publication https://arxiv.org/abs/2203.15413.</p> <p>In more detail, the DataFile.pkl files in the training_data and testing_data folders are the actual data, including diffraction patterns, the corresponding reconstructions and the used illumination probe. The folders dwcnt_training_data and dwcnt_testing_data include the data sets of the simulated double-walled carbon nanotube.</p> <p>The reconstruction folder includes the source code of the reconstruction algorithm ROP and the used parameter files.</p> <p>The results folder includes the updated weights of the network model and the reconstructed potentials for the 25 test data sets used in the comparison of the publication.</p> <p>The sequence_grid.npy file stores the sparse grid scanning sequence used for initialization and comparison as described in the publication. The dwcnt_sequence_grid.npy file is the corresponding file for the double-walled carbon nanotube data.</p> <p>If you want more information, please contact the corresponding author of the publication, at schlozma@hu-berlin.de. </p>
Raw ptychography data for manuscript with title 'Structured Illumination Ptychography and At-wavelength Characterization with an EUV diffuser at 13.5 nm Wavelength'
<p>- Given are the HDF files containing the raw diffraction patterns<br> - Although some meta-data might be available in these files, these might not be correct. The following data were used for reconstruction:<br> wavelength: 13.5 nm<br> distance sample <-> detector: ~29.2 mm<br> sCMOS pixel size: 11 um<br> Number of incoherent modes: 4<br> Initial probe guess: 9 um<br> For the reconstruction, OPR was used (Although it might have not been necessary for all data. However, to have comparable results it was used for each reconstruction)<br> - For each scenario, there are two data sets to calculate the Fourier ring correlation (FRC)<br> - For the analysis of the diffuser the reconstructed probe of the data set "dp_diffuser_max_dynam_range.hdf5" was used</p> <p>- Data were measured at the Institute of Applied Physics in Jena using a Fiber Laser driven High-order harmonic source</p> <p>Please contact me (wilhelm.eschen@uni-jena.de) for additional support.</p>
Dataset: Aberration characterisation of X-ray optics using multi-modal ptychography and a partially coherent source
<p>These are the ptychography datasets used for the publication "Aberration characterisation of X-ray optics using multi-modal ptychography and a partially coherent source". File are in the HDF format and contain a number of datasets detailed below.</p> <p>If you require more information, please contact the corresponding author of the publication, at thomas.moxham@eng.ox.ac.uk</p> <p>Raw files contain: diffraction intensities, scanning positions in millimeters</p> <p>Recon files contain: fourier error, complex probe function, complex object function, recon pixel size, energy</p> <p>raw_siemens_star_be_lens.hdf, raw_fourier_ring_correlation.hdf, merlin_medipix_detector_mask.hdf, recon_multi-modal_probe.hdf, recon_multi-modal_object.hdf, recon_fourier_ring_correlation.hdf</p>
X-ray beam characterization of an aberration-corrected pair of multilayer Laue lenses with ptychography
<p>This data set is split over three zip archives. Each archive contains a scanning coherent X-ray diffraction (ptychography) data set recorded at an X-ray energy of 16.2 keV. A crossed pair of multilayer Laue lenses (MLL) is used to focus the beam and scan a Siemens star test sample. Each data set includes a configuration file and scan position file. In addition, the final result of the obtained ptychographic reconstruction is included.</p><p><strong>Description of the three data sets:</strong></p><ul><li>scan_00086: X-ray beam characterization of the MLL. On this data set the design of the refractive phase corrector was based upon.</li><li>scan_00338: X-ray beam characterization of the MLL four days after scan_00086 without phase corrector.</li><li>scan_00346: X-ray beam characterization of the MLL with refractive phase corrector.</li></ul><p><strong>Additional information:</strong></p><p>The diffraction patterns can be found in the 'eiger4m_01' folder. They are split up over multiple h5 files and located in the group '/entry/data/data'. The assignment of diffraction patterns to scan positions can be found in the positions.txt file. All relevant input parameters for ptychography are located in the 'input' group in the ptycho.conf files. The reconstruction results are in the European Data Format (EDF).</p><p><strong>The data set has been published in:</strong></p><p>F. Seiboth, A. Kubec, A. Schropp, S. Niese, P. Gawlitza, J. Garrevoet, V. Galbierz, S. Achilles, S. Patjens, M. E. Stuckelberger, C. David, and C. G. Schroer, "Rapid aberration correction for diffractive X-ray optics by additive manufacturing," Optics Express 30(18), 31519 (2022).</p>
Supplementary data: Bayesian multi-exposure image fusion for robust high dynamic range ptychography
<p>Accompanying supplementary data for the paper. To download this data automatically and use the software, please refer to the details in the README of the linked github repository. </p> <p><strong>Github URL: </strong><a href="https://github.com/microscopic-image-analysis/bayes-mef"><strong>https://github.com/microscopic-image-analysis/bayes-mef</strong></a></p>
Dataset: Two-dimensional wavefront characterization of adaptable corrective optics and Kirkpatrick–Baez mirror system using ptychography
<p>The ptychography datasets and processed wavefront data in support of the publication "Two-dimensional wavefront characterization of adaptable corrective optics and Kirkpatrick–Baez mirror system using ptychography". File are in the HDF format and contain a number of datasets detailed below. If you require more information, please contact the corresponding author of the publication or thomas.moxham@eng.ox.ac.uk</p>
Overcoming contrast reversals in focused probe ptychography of thick materials: an optimal pipeline for efficiently determining local atomic structure in materials science
<p>Files concerning the publication "Overcoming contrast reversals in focused probe ptychography of thick materials: an optimal pipeline for efficiently determining local atomic structure in materials science"(arxiv:2205.13308 )</p>
Raw data for "Complete Alignment of a KB-Mirror System guided by Ptychography"
<p>All raw datasets for each figure presented in the article.</p>
Data for "X-ray Fourier ptychography"
<p>Data needed to evaluate the conclusions of the paper</p> <p>K. Wakonig, A. Diaz, A. Bonnin, M. Stampanoni, A. Bergamaschi, J. Ihli, M. Guizar-Sicairos,<br> A. Menzel, X-ray Fourier ptychography. <em>Sci. Adv. </em><strong>5</strong>, eaav0282 (2019).</p> <p> </p>
Raw ptychographic synthetic data for manuscript with title 'Purity-based self-calibration in ptychography'
<ul> <li>Here given are the dataset for purity scan, numerically created based on the synthetic setup in the manuscript titled "Purity-based self-calibration in ptychography". The dataset includes raw diffraction patterns, preprocessed diffraction patterns for reconstruction, as well as the preprocessed script.</li> <li>For the two experimental verificatoin cases, the preprocessed diffraction patterns are provided, where the scanning grid is included.</li> <li>The reconstruction, calculation of purity, and zPIE were conducted at open-source PtyLab framework.</li> <li>Experimental data were measured at the Institute of Applied Physics in Jena using a Fiber Laser driven High-order harmonic source, which can be referenced in </li> </ul> <p>Please contact me (liu.chang@uni-jena.de) for additional support.</p>
Spatial- and Fourier-domain ptychography for high throughput bio-imaging
<p>Title: Spatial and Fourier domain ptychography for high-throughput bio-imaging<br> Version: 1.0 <br> Copyright: Shaowei Jiang, Pengming Song, Guoan Zheng, 2023<br> License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License</p> <p>******************************************************************************</p> <p>If you use this code, please cite the following paper:<br> Shaowei Jiang, Pengming Song, Tianbo Wang, Liming Yang,Ruihai Wang, Chengfei Guo, Bin Feng, Andrew Maiden, and Guoan Zheng,<br> "Spatial and Fourier domain ptychography for high-throughput bio-imaging", Nature Protocols, 2023. </p> <p>For algorithmic details, please refer to our paper.</p> <p>******************************************************************************</p> <p>How to use: </p> <p>Foruier-domain ptychography (FP)<br> 1. Unpack the full package and install related softwares. <br> Refer to 'Materials for Procedure 1: Fourier-domain ptychography' and 'Procedure 1: Fourier-domain ptychography' sections in our paper for additional details (including version number and instructions). <br> 2. We provide 4 different FP experimental datasets. Please refer to 'Content in this package' section for additional details. <br> 3. Run FP_Recovery.m for FP image reconstruction. The reconstruction time for a tile of 256x256 dimensions, with 4-times padding, is ~2 seconds. Please refer to our paper for additional information. </p> <p>Spatial-domain coded ptychography (CP)<br> 1. Unpack the full package and install related softwares. <br> Refer to 'Materials for Procedure 2: Spatial-domain coded ptychography' and 'Procedure 2: Spatial-domain coded ptychography' sections in our paper for additional details (including version number and instructions). <br> 2. We provide 3 different CP experimental datasets. Please refer to 'Content in this package' section for additional details. <br> 3. Run CP_Recovery.m for CP image reconstruction. The reconstruction time for raw images with 1024*1024 dimensions, with 3-times padding, is ~58 seconds. Please refer to our paper for additional information. </p> <p>******************************************************************************</p> <p>Content in this package: <br> CP_HeLaCellCulture Dataset and reconstruction code of HeLa cell sample for CP<br> CP_Immunohistochemistry Dataset and reconstruction code of IHC stained sample for CP<br> CP_UnstainedCytologySmear Dataset and reconstruction code of unstained cytology smear for CP<br> FP_Intestine_Aberrations Dataset and reconstruction code of Intestine cancer sample for FP<br> FP_H&E_RGB Dataset (RGB) and reconstruction code of H&E stained sample for FP<br> FP_Immunohistochemistry_RGB Dataset (RGB) and reconstruction code of IHC stained sample for FP<br> FP_Leukemia_RGB Dataset (RGB) and reconstruction code of Leukemia sample for FP</p> <p>******************************************************************************</p> <p>License of using this package (refer to 'license.txt'): </p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 4.0<br> International Public License</p> <p>Any inclusion or other use of this package means acceptance of this license.</p>
Raw ptychography data for manuscript with title 'Multiplexing limitis in ptychography'
<p>- Given are the HDF files containing the raw diffraction patterns, and the reconstructed files.<br>- The metadata for the reconstruction of each dataset is stored in the raw files, and in the reconstructed files<br>- For each scenario, the Fourier ring correlation (FRC) was calculated against the reconstruction with a single beam as reference, and against the corresponding region for the simulated dataset.</p> <p>The reconstruction of these datasets was carried out with ptylab:<br>Loetgering, L., Du, M., Boonzajer Flaes, D., Aidukas, T., Wechsler, F., Penagos Molina, D. S., Rose, M., Pelekanidis, A., Eschen, W., Hess, J., Wilhein, T., Heintzmann, R., Rothhardt, J., & Witte, S. (2023). PtyLab.m/py/jl: a cross-platform, open-source inverse modeling toolbox for conventional and Fourier ptychography. In Optics Express (Vol. 31, Number 9, pp. 13763–13797).<br>Zenodo. https://doi.org/10.5281/zenodo.8287047<br>Github: https://github.com/PtyLab/PtyLab.py</p> <p>EDIT:<br>The first version of this repository corresponds to the datasets used in the preprint:<br>Molina, Daniel Penagos; Eschen, Wilhelm; Liu, Chang; Limpert, Jens; Rothhardt, Jan (2024). Multiplexing information limits in ptychography. Optica Open. Preprint. https://doi.org/10.1364/opticaopen.25941427.v2</p> <p>A second set of datasets was added. These correspond to the experimental results in the final version of the published paper:<br>Daniel S. Penagos Molina, Wilhelm Eschen, Chang Liu, Jens Limpert, and Jan Rothhardt, "Multiplexing information limits in multi-beam ptychography," Opt. Express 33, 12925-12938 (2025)</p> <p>- Data were measured at the Institute of Applied Physics in Jena.</p> <p>Please contact me (santiago.penagos@uni-jena.de) for additional support.</p>
Data from: Insights into chemical and structural order at planar defects in Pb2(MgW)O6 using multislice electron ptychography
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