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Online Webinar

Seeing the unseen

AI-powered X-ray Microscope Reconstruction Technologies

Online Webinar

Seeing the unseen: AI-powered X-ray Microscope Reconstruction Technologies

February 6th, 2024 | Online Webinar

X-ray tomography is an indirect imaging technique that captures 2D X-ray attenuation projections of an object as it rotates along a circular trajectory. The crucial step of reconstructing these 2D projections into 3D volumes relies on having good contrast, low noise, and sufficient angular sampling in the original projections. As with any microscopic imaging method, users face the dilemma of obtaining a representative image of the sample (large field of view) at the cost of resolution, or imaging at high resolution but losing context and statistical relevance.

While technological advancements in hardware components (such as larger, faster detectors and more powerful sources) can partially address this issue, improving one performance parameter (e.g., speed, image quality, resolution) often negatively impacts the others. Consequently, users must make difficult compromises between throughput, statistical representativity, and image quality in their XRM instrument.
Our recent work has successfully overcome these fundamental barriers by innovating the reconstruction process in the imaging chain. The ZEISS Advanced Reconstruction Toolbox (ART) offers a comprehensive, user-friendly solution to enhance X-ray microscopy imaging performance, paving the way for new scientific discoveries.

In this webinar, we will discuss the challenges that typical X-ray CT and XRM users face and introduce DeepRecon Pro, ZEISS's proprietary deep learning-based reconstruction solution. DeepRecon Pro significantly reduces noise levels in tomographic images and enables up to 10X speed improvement. Lastly, we will explore how DeepScout delivers resolution restoration to XRM users, unlocking new scientific possibilities.

Highlights of the Webinar

  • Discover Hidden Details with ZEISS X-Ray Microscopes

    Uncover the concealed aspects of your samples by overcoming conventional X-ray CT limitations using advanced ZEISS X-ray microscopy techniques.

  • Leverage Deep Learning for Enhanced 3D Reconstructions

    Utilize deep learning-based 3D reconstruction methods for obtaining low-noise, high-quality images of even the most intricate samples.

  • Unlock New Scientific Possibilities with AI-Powered Super-Resolution

    Embrace the potential of AI-driven super-resolution technology to address a broad spectrum.


Nicolas Gueninchault

Nicolas holds a M.E. from the Université of Marne la Vallée and a PhD. from Paris Sciences et Lettres University (Paris), both in Mechanics. Following his doctoral studies on the observation and the simulation of grain bulk crystal plasticity, he joined the Copenhagen based startup Xnovo Technology as an application scientist, where he has participated in the development of the LabDCT module, which enables crystallographic imaging with laboratory instruments. In 2019, he has joined Zeiss as the Product and application specialist for the EMEA-LATAM region, specialized in Xray microscopy instruments for Zeiss’ Research and Microscopy Solutions segment. Since 2022, Nicolas is located in Dublin, California, at ZEISS X-ray microscopy Headquarters. He is a Product manager in charge of the reconstruction technologies and of the Ultra XRM product line.

Mohsen Samadi-Khoshkhoo

Mohsen Samadi Khoshkhoo is a business development manager at ZEISS for X-ray microscopy systems in the region Europe, the middle east and Africa (EMEA). With his BSc and MSc in metallurgy he worked for a year in a steel company followed by a year in a materials and energy research center in Iran. In 2009 he joined to Leibniz Institute for Solid State and Materials Research in Dresden (IFW Dresden) and TU Dresden, where he conducted his PhD in Materials Science. Materials characterization was the core of his work at IFW where he dealt with scanning electron microscopy (SEM), transmission electron microscopy (TEM), in-situ SEM, X-ray line profile analysis, and time resolved synchrotron X-ray diffraction investigations. Since 2014 he is a member of ZEISS team.

Watch the recording here