<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Publications | Tak Ming Wong</title><link>https://tak-wong.github.io/publications/</link><atom:link href="https://tak-wong.github.io/publications/index.xml" rel="self" type="application/rss+xml"/><description>Publications</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 19 Mar 2026 00:00:00 +0000</lastBuildDate><image><url>https://tak-wong.github.io/media/icon_hu_14771e4d841b9128.png</url><title>Publications</title><link>https://tak-wong.github.io/publications/</link></image><item><title>An ontology-based description of nano computed tomography measurements in electronic laboratory notebooks</title><link>https://tak-wong.github.io/publications/2026-kirchner-ontology/</link><pubDate>Thu, 19 Mar 2026 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2026-kirchner-ontology/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Kirchner, Fabian, D. C. Florian Wieland, Sarah Irvine, Sven Schimek, Jan Reimers, Rossella Aversa, Alexey Boubnov, Christian Lucas, Silja Flenner, Imke Greving, André Lopes Marinho, Tak Ming Wong, Regine Willumeit-Römer, Catriona Eschke, and Berit Zeller-Plumhoff. &amp;ldquo;An ontology-based description of nano computed tomography measurements in electronic laboratory notebooks.&amp;rdquo; Scientific Data (2026).&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@article{kirchner2026ontology,
title={An ontology-based description of nano computed tomography measurements in electronic laboratory notebooks},
author={Kirchner, F and Wieland, DCF and Irvine, S and Schimek, S and Reimers, J and Aversa, R and Boubnov, A and Lucas, C and Flenner, S and Greving, I and others},
journal={Scientific Data},
year={2026},
publisher={Nature Publishing Group UK London}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Quantifying hygroscopic deformation in lignocellulosic tissues: a digital volume correlation tool comparison</title><link>https://tak-wong.github.io/publications/2025-ulrich-quantifying/</link><pubDate>Mon, 18 Aug 2025 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2025-ulrich-quantifying/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Ulrich, Kim, Fabian Scheckenbach, Tak Ming Wong&amp;gt;, Tom Masselter, Silja Flenner, Anaclara Visconti, Martin Nopens, Andreas Krause, Sergej Kaschuro, Jakob Benedikt Mietner, Thomas Speck, Imke Greving, Berit Zeller-Plumhoff, and Linnea Hesse. &amp;ldquo;Quantifying hygroscopic deformation in lignocellulosic tissues: a digital volume correlation tool comparison.&amp;rdquo; Frontiers in Plant Science 16 (2025): 1572745.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@article{ulrich2025quantifying,
title={Quantifying hygroscopic deformation in lignocellulosic tissues: a digital volume correlation tool comparison},
author={Ulrich, Kim and Scheckenbach, Fabian and Wong, Tak Ming and Masselter, Tom and Flenner, Silja and Visconti, Anaclara and Nopens, Martin and Krause, Andreas and Kaschuro, Sergej and Benedikt Mietner, Jakob and Speck, Thomas and Greving, Imke and Zeller-Plumhoff, Berif and Linnea, Hesse},
journal={Frontiers in Plant Science},
volume={16},
pages={1572745},
year={2025},
publisher={Frontiers}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram</title><link>https://tak-wong.github.io/publications/2025-yang-selfphish/</link><pubDate>Wed, 13 Aug 2025 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2025-yang-selfphish/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;div class="callout flex px-4 py-3 mb-6 rounded-md border-l-4 bg-blue-100 dark:bg-blue-900 border-blue-500"
data-callout="note"
data-callout-metadata=""&gt;
&lt;span class="callout-icon pr-3 pt-1 text-blue-600 dark:text-blue-300"&gt;
&lt;svg height="24" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"&gt;&lt;path fill="none" stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.5" d="m16.862 4.487l1.687-1.688a1.875 1.875 0 1 1 2.652 2.652L6.832 19.82a4.5 4.5 0 0 1-1.897 1.13l-2.685.8l.8-2.685a4.5 4.5 0 0 1 1.13-1.897zm0 0L19.5 7.125"/&gt;&lt;/svg&gt;
&lt;/span&gt;
&lt;div class="callout-content dark:text-neutral-300"&gt;
&lt;div class="callout-title font-semibold mb-1"&gt;Note&lt;/div&gt;
&lt;div class="callout-body"&gt;&lt;p&gt;&amp;#x1f3c6; This paper is highlighted as an Editors' Pick.&lt;/p&gt;&lt;/div&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Yang, Xiaogang, Dawit Hailu, Vojtěch Kulvait, Thomas Jentschke, Silja Flenner, Imke Greving, Stuart I. Campbell, Johannes Hagemann, Christian G. Schroer, Tak Ming Wong, and Julian Moosmann. &amp;ldquo;Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram.&amp;rdquo; Optics Express 33, no. 17 (2025): 35832-35851.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@article{yang2025self,
title={Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram},
author={Yang, Xiaogang and Hailu, Dawit and Kulvait, Vojt{\v{e}}ch and Jentschke, Thomas and Flenner, Silja and Greving, Imke and Campbell, Stuart I and Hagemann, Johannes and Schroer, Christian G and Wong, Tak Ming and Moosmann, Julian},
journal={Optics Express},
volume={33},
number={17},
pages={35832--35851},
year={2025},
publisher={Optica Publishing Group}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>A Framework for the AI-based visualization and analysis of massive amounts of 4D tomography data for end users of beamlines</title><link>https://tak-wong.github.io/publications/2025-kiess-framework/</link><pubDate>Sat, 01 Feb 2025 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2025-kiess-framework/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Kieß, S., Lang, T., Sauer, T., Stock, A., Chernov, A., Sun, Y., Maier, A., Faragó, T., Ershov, A., Lefloch, G., Silva, G., Baumbach, T., Zabler, S., Hölzing, A., Dremel, K., Durmaz, A., Thomas, A., Manke, I., Kardjilov, N., Arlt, T., Wong, T., Willumeit-römer, R., Moosmann, J., Zeller-Plumhoff, B., Froning, D., &amp;amp; Simon, S. (2025). A Framework for the AI-based visualization and analysis of massive amounts of 4D tomography data for end users of beamlines. 14th Conference on Industrial Computed Tomography (iCT), 4 - 7 February 2025, Antwerp, Belgium. e-Journal of Nondestructive Testing Vol. 30(2).&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@article{kiess2025framework,
title={A Framework for the AI-based Visualization and Analysis of Massive Amounts of 4D Tomography Data for End Users of Beamlines},
author={Kie{\ss}, Steffen and Lang, Thomas and Sauer, Tomas and Stock, A Michael and Chernov, Andrei and Sun, Yipeng and Maier, Andreas and Farag{\'o}, Tom{\'a}{\v{s}} and Ershov, Alexey and Lefloch, Gabriel and others},
year={2025}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Machine Learning for the Reconstruction and Analysis of Synchrotron-radiation Tomography Data</title><link>https://tak-wong.github.io/publications/2024-moosmann-machine/</link><pubDate>Wed, 23 Oct 2024 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2024-moosmann-machine/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Moosmann, Julian, Jennifer Ahrens, Sarah Irvine, Tak Ming Wong, Christian Lucas, Felix Beckmann, Jörg U. Hammel, DC Florian Wieland, Berit Zeller-Plumhoff, and Philipp Heuser. &amp;ldquo;Machine learning for the reconstruction and analysis of synchrotron-radiation tomography data.&amp;rdquo; In Developments in X-Ray Tomography XV, vol. 13152, pp. 65-71. SPIE, 2024.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@InProceedings{moosmann2024machine,
title = {Machine learning for the reconstruction and analysis of synchrotron-radiation tomography data},
author = {Moosmann, Julian P and Irvine, Sarah and Hailu, Dawit and Kazimi, Bashir and Wong, Tak and Yang, Xiaogang and Heuser, Philipp and Jentschke, Thomas and Kulvait, Vojtech and Zeller-Plumhoff, Berit and others},
booktitle = {Developments in X-Ray Tomography XV},
volume = {13152},
pages = {131520Z},
year = {2024},
organization= {SPIE}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>VolRAFT: Volumetric Optical Flow Network for Digital Volume Correlation of Synchrotron Radiation-based Micro-CT Images of Bone-Implant Interfaces</title><link>https://tak-wong.github.io/publications/2024-wong-volraft/</link><pubDate>Tue, 18 Jun 2024 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2024-wong-volraft/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Wong, Tak Ming, Julian Moosmann, and Berit Zeller-Plumhoff. &amp;ldquo;VolRAFT: Volumetric Optical Flow Network for Digital Volume Correlation of Synchrotron Radiation-based Micro-CT Images of Bone-Implant Interfaces.&amp;rdquo; In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 53-62. 2024.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@InProceedings{wong2024volraft,
author = {Wong, Tak Ming and Moosmann, Julian and Zeller-Plumhoff, Berit},
title = {VolRAFT: Volumetric Optical Flow Network for Digital Volume Correlation of Synchrotron Radiation-based Micro-CT Images of Bone-Implant Interfaces},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2024},
pages = {53-62}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Optimization-based Enhancement of THz Data and Image</title><link>https://tak-wong.github.io/publications/2023-wong-optimization/</link><pubDate>Fri, 05 May 2023 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2023-wong-optimization/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Wong, Tak Ming. &amp;ldquo;Optimization-based enhancement of THz data and image.&amp;rdquo; PhD diss., Dissertation, Siegen, Universität Siegen, 2023.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@phdthesis{wong2023optimization,
title={Optimization-based enhancement of THz data and image},
author={Wong, Tak Ming},
year={2023},
school={Dissertation, Siegen, Universit{\&amp;quot;a}t Siegen, 2023}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Deep Neural Network as an Optimizer for FMCW THz Image Deblurring</title><link>https://tak-wong.github.io/publications/2022-wong-dnn/</link><pubDate>Fri, 25 Nov 2022 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2022-wong-dnn/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Wong, Tak Ming, Hartmut Bauermeister, Matthias Kahl, Peter Haring Bolıvar, Michael Möller, and Andreas Kolb. &amp;ldquo;Deep Neural Network as an Optimizer for FMCW THz Image Deblurring.&amp;rdquo; ATHENA Research Book, Volume (2022): 13.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@article{wong2022deep,
title={Deep Neural Network as an Optimizer for FMCW THz Image Deblurring},
author={Wong, Tak Ming and Bauermeister, Hartmut and Kahl, Matthias and Bol{\i}var, Peter Haring and M{\&amp;quot;o}ller, Michael and Kolb, Andreas},
journal={ATHENA Research Book, Volume},
pages={13},
year={2022}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Deep Optimization Prior for THz Model Parameter Estimation</title><link>https://tak-wong.github.io/publications/2022-wong-dop/</link><pubDate>Fri, 07 Jan 2022 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2022-wong-dop/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Wong, Tak Ming, Hartmut Bauermeister, Matthias Kahl, Peter Haring Bolívar, Michael Möller, and Andreas Kolb. &amp;ldquo;Deep optimization prior for thz model parameter estimation.&amp;rdquo; In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 3811-3820. 2022.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@inproceedings{wong2022deep,
title={Deep optimization prior for thz model parameter estimation},
author={Wong, Tak Ming and Bauermeister, Hartmut and Kahl, Matthias and Bol{\'\i}var, Peter Haring and M{\&amp;quot;o}ller, Michael and Kolb, Andreas},
booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
pages={3811--3820},
year={2022}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Training Auto-Encoder-Based Optimizers for Terahertz Image Reconstruction</title><link>https://tak-wong.github.io/publications/2019-wong-training/</link><pubDate>Fri, 25 Oct 2019 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2019-wong-training/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Wong, Tak Ming, Matthias Kahl, Peter Haring-Bolívar, Andreas Kolb, and Michael Möller. &amp;ldquo;Training auto-encoder-based optimizers for terahertz image reconstruction.&amp;rdquo; In German Conference on Pattern Recognition, pp. 93-106. Cham: Springer International Publishing, 2019.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@inproceedings{wong2019training,
title={Training auto-encoder-based optimizers for terahertz image reconstruction},
author={Wong, Tak Ming and Kahl, Matthias and Haring-Bol{\'\i}var, Peter and Kolb, Andreas and M{\&amp;quot;o}ller, Michael},
booktitle={German Conference on Pattern Recognition},
pages={93--106},
year={2019},
organization={Springer}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Computational Image Enhancement for Frequency Modulated Continuous Wave (FMCW) THz Image</title><link>https://tak-wong.github.io/publications/2019-wong-computational/</link><pubDate>Tue, 02 Jul 2019 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2019-wong-computational/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Wong, Tak Ming, Matthias Kahl, Peter Haring Bolívar, and Andreas Kolb. &amp;ldquo;Computational image enhancement for frequency modulated continuous wave (FMCW) THz image.&amp;rdquo; Journal of Infrared, Millimeter, and Terahertz Waves 40 (2019): 775-800.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@article{wong2019computational,
title={Computational image enhancement for frequency modulated continuous wave (FMCW) THz image},
author={Wong, Tak Ming and Kahl, Matthias and Haring Bol{\'\i}var, Peter and Kolb, Andreas},
journal={Journal of Infrared, Millimeter, and Terahertz Waves},
volume={40},
pages={775--800},
year={2019},
publisher={Springer}
}
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Advanced signal processing techniques for THz imaging and sensing enhancement in material quality control applications</title><link>https://tak-wong.github.io/publications/2019-stock-advanced/</link><pubDate>Fri, 01 Mar 2019 00:00:00 +0000</pubDate><guid>https://tak-wong.github.io/publications/2019-stock-advanced/</guid><description>&lt;!-- Add the paper text or supplementary notes. Markdown, math, and code are supported. --&gt;
&lt;h2 id="how-to-cite"&gt;How to cite&lt;/h2&gt;
&lt;p&gt;Stock, Daniel, Matthias Kahl, Anna K. Wigger, Tak Ming Wong, Andreas Kolb, and Peter Haring Bolívar. &amp;ldquo;Advanced signal processing techniques for THz imaging and sensing enhancement in material quality control applications.&amp;rdquo; In Terahertz, RF, Millimeter, and Submillimeter-Wave Technology and Applications XII, vol. 10917, pp. 127-133. SPIE, 2019.&lt;/p&gt;
&lt;h2 id="bibtex"&gt;Bibtex&lt;/h2&gt;
&lt;pre&gt;&lt;code&gt;@inproceedings{stock2019advanced,
title={Advanced signal processing techniques for THz imaging and sensing enhancement in material quality control applications},
author={Stock, Daniel and Kahl, Matthias and Wigger, Anna K and Wong, Tak Ming and Kolb, Andreas and Bol{\'\i}var, Peter Haring},
booktitle={Terahertz, RF, Millimeter, and Submillimeter-Wave Technology and Applications XII},
volume={10917},
pages={127--133},
year={2019},
organization={SPIE}
}
&lt;/code&gt;&lt;/pre&gt;</description></item></channel></rss>