About us
Imaging at large-scale facilities offers unique opportunities for measuring a material’s microstructure. Most often, these measurements require quantitative image analysis to obtain the relevant information. To ensure a high scientific output from MAX IV, the QIM center aims at developing and using the most relevant tools for analyzing the data for a given problem.
3D Imaging is an extremely powerful technique to learn about the inside of materials, samples and specimens across a wide range of scientific disciplines, including industrial and clinical applications, as well as other uses. At the newly established and one of the most brilliant synchrotron sources in the world – the MAX IV synchrotron – five imaging beamlines are being planned. Each of these has a worldwide superior specification allowing for unprecedented spatial and temporal resolution across a series of different X-ray imaging modalities. These instruments will produce very large data in the form of sequences of 3D images. These data become useful only when it is turned into information by means of image quantification. This transformation calls for image analysts and expertise from the QIM center.
Our ambition is to bridge the gap between the researchers using the MAX IV and image analysis knowledge. We provide consultancy and collaboration in order to make the process of going from a scan to results as seamless and streamlined as possible. Collaborative efforts will be required to go from the scientific questions to the quantification of the data.
You can contact the QIM team by emailing info@qim.dk or approach one of the team members below.
Meet Our Team
The individuals associated with the QIM project are:
The QIM Center is being established as a hub for quantitative image analysis associated with various facilities and research environments including MAX IV, ESS, Danish BioImaging, Euro-Bioimaging, hospitals, and the 3D Imaging Center at DTU. As Manager Rebecca’s role is to coordinate the center activities, manage the daily operations, and organize the collaborations with the above-mentioned partners.
Anders is the Head of the QIM Center and the Head of the Section for Visual Computing at DTU Compute since 2015. He finished his PhD at DTU in 2009 and has been at DTU since. His research focuses on a variety of things related to image analysis, where his main focus has been on quantification of 3D volumetric data. (Google Scholar Profile)
Jon Sporring received his Master and Ph.D. degree from the Department of Computer Science, University of Copenhagen, Denmark. In 2007-2012 and again since 2015 he is Vice-Chair for Research at Department of Computer Science, University of Copenhagen. His primary research field is Computer Science and particularly mathematical and medical image processing, computer graphics, information theory, and pattern recognition. To read more about his research, click here.
Stephen is an associate professor at the Dept. of Solid Mechanics at the Faculty of Engineering (LTH) at Lund University. He is also in charge of the 4D-Imaging Lab x-ray tomography facility since 2011 after moving from Laboratoire 3R in Grenoble, France. To read more about his research, click here.
Rajmund is a researcher and project manager at the MAX IV Laboratory (Lund University) and an honorary professor at the Technical University of Denmark. He is a specialist in X-ray physics with emphasis on the enhancement of X-ray imaging for biology and material science applications: development and applications of coherent imaging with improved temporal and spatial resolution. To read more about his research, click here.
Vedrana Andersen Dahl received a Ph.D. degree in geometry processing in 2011. Her research interests revolve around geometric models for analysis of volumetric data. This includes volumetric segmentation, tomographic segmentation and methods based on deformable meshes. She developed image analysis tools with application in material science, industrial inspection and biomedicine. To read more about her research, click here.
François is associate professor at the Department of Computer Science, University of Copenhagen. He received a PhD degree in Algebraic Geometry from the University of Nice – Sophia Antipolis and a PhD degree in Image Analysis for the IT University in Copenhagen in 2004. His primary research interests are Mathematics of Image processing, especially related to Geometry and Inverse Problems. Link
Martin is an associate professor at the Department of Medical Radiation Physics at Lund University. With a background in the physics of synchrotron based x-ray imaging he has specialised in imaging of biomedical samples and biopsies. Martin is also in charge of an experimental micro-CT laboratory, developing methods for inhouse phase-contrast and dark-field x-ray imaging.
To read more about his research, click here
To read more about his research, click here
With a background in biomedical engineering and a PhD in image analysis, Martins primary interest is the development of practical methods and pipelines for efficient 3D data analysis of biological samples. Proficient with a wide array of tools from the image analysis toolbox, he is geared to enable researchers and collaborators to pry out the quantitative information hidden within their data.
Emanuel works as a Researcher at the Department of Experimental Medical Science at the Faculty of Medicine, Lund University. He is also LINXS Co-Director responsible for the focus area of Life Science. He also works as a Lund University Node Coordinator for InfraVis – a Swedish National Research Infrastructure for Data Visualization, and as Coordinator at CIPA – a cross faculty infrastructure for image processing and analysis at Lund University. He also works as a Cross-border Infrastructure Ambassador for the Hanseatic Life Science Research Infrastructure Consortium (HALRIC). His work includes everything from experimental planning, image acquisition, reconstruction, processing, analysis, and visualization of X-ray and Neutron tomography datasets.
William holds a bachelor’s degree in mathematics and computer science from Westfield State University and a master’s degree in computer science from the University of Copenhagen. He is interested in machine learning and working with medical imaging data in developing software and algorithms that help to advance research and solve problems in the medical fields. Currently, he is working as a PhD student in the Visual Computing section at DTU Compute
Felipe is a software developer who creates user-friendly tools and applications for QIM’s computational resources. He holds a Masters degree from Universidade Estadual Paulista (UNESP, Assis – Brazil) and a PhD from École Normale Supérieure (ENS, Paris – France), specializing in 3D+time imaging and data visualization. Prior to joining QIM, he worked as a Data Scientist at ImVitro, a Paris-based healthcare startup that focuses on developing deeplearning models for image analysis.
Jakob received his PhD in Applied Mathematics from DTU in 2013 on the topic of sparsity-regularised reconstruction algorithms for computed tomography with noisy or incomplete data. After a postdoc at DTU, he moved to The University of Manchester, UK in 2015 where he developed reconstruction algorithms and software in the Manchester X-ray Imaging Facility. In 2018 he secured a Manchester Presidential Fellowship (tenure track) to work on hyperspectral tomography. In April 2020 he re-joined DTU as a Researcher affiliated with the Villum Investigator Project on Computational Uncertainty Quantification for Inverse Problems (CUQI). Google Scholar Profile
Chenhao received his Bachelor’s degree in Science & IT in 2017, and Master’s degree in Bioinformatics in 2019, both from University of Copenhagen. He is interested in general scientific image analysis and developing the supporting software tools. He is based at the IMAGE section of DIKU.
Sophia is a PhD student at the Visual Computing section at DTU Compute. Her project is funded by SOLID, which investigates solid materials using advanced imaging modalities. She holds a master’s degree in mathematical modelling and computation from DTU as well as a teaching degree, and she has spent five years between her master’s and PhD teaching math and science for grades 5-9.
Her project focuses on developing new image analysis methods for volumetric image data.
Her project focuses on developing new image analysis methods for volumetric image data.
Patrick is a postdoc at the section for Visual Computing at the Technical University of Denmark (DTU). He works on methods for segmentation and analysis of 3D images from experimental imaging sources, such as laboratory or synchrotron X-ray CT, with a particular interest in cases with large computationally demanding data sets.
Thorbjørn recieved his PhD in Nanosciecne from Aarhus university in 2023.
During his PhD Thorbjørn participated in multiple synchrotron experiments, and gained expertice in visualizing and analyzing multiple different types of imaging data.
The same year Thorbjørn Joined the team at QIM and the DanMAX beamline where he is part of getting the imaging endstation up and running.
Thorbjørn works with bioinorganic materials, such as bone or shelfish, studying the intricate structure of said materials using a diverse portefolio of techniques, such as tomography and diffraction.
Thorbjørn helps out at the DanMAX beamline, ensuring that everything is running well for the beamline users during their beamtimes.
During his PhD Thorbjørn participated in multiple synchrotron experiments, and gained expertice in visualizing and analyzing multiple different types of imaging data.
The same year Thorbjørn Joined the team at QIM and the DanMAX beamline where he is part of getting the imaging endstation up and running.
Thorbjørn works with bioinorganic materials, such as bone or shelfish, studying the intricate structure of said materials using a diverse portefolio of techniques, such as tomography and diffraction.
Thorbjørn helps out at the DanMAX beamline, ensuring that everything is running well for the beamline users during their beamtimes.
Julia is a scientific programmer and bioimage analyst working at the image analysis core facility (IACF) in Copenhagen, which is part of the Danish BioImaging Infrastructure (DBI-Infra). At IACF, she supports researchers and life scientists in analyzing their bioimage data through tailored software solutions, workshops, and consultations. In collaboration with the IMAGE section of DIKU and the QIM Center, Julia works on making bioimage processing tools available to life scientists in a user-friendly way. She holds a master’s degree in computer science from the University of Freiburg, specializing on unsupervised deep learning methods for image and video analysis.
Endri is a postdoc in the Department of Solid Mechanics at the Faculty of Engineering (LTH), Lund University. His work focuses on the characterization of materials through in-situ loading, 3D image analysis and Digital Volume Correlation. Part of his mission also involves supporting the use of tomography at MAXIV.
Rasmus is a research assistant at the section for Visual Computing at DTU Compute. He holds a bachelor’s degree in “Artificial Intelligence and Data” and master’s degree in “Human-Centered Artificial Intelligence”, both from the Technical University of Denmark (DTU). His current work focuses on developing tomographic reconstruction methods using neural representation and deep learning. His general interests are deep learning for 3D image analysis and high-performance computing.
Miguel is a postdoc at the Visual Computing section at DTU compute. His research is at the intersection between deep learning, image segmentation, and topology. He develops methods for medical and material science images, including very large 3D images.