X-Ray Tomography Group
Prof. Stampanoni heads a group of over 20 people, including three staff scientists, two technicians, one controls engineer, and many postdocs and PhD students. The team focuses on the development of tools, both instrumentation and algorithms, for tomographic X-ray imaging, exploiting synchrotron and laboratory sources. The group is engaged in the design and construction of ultra-fast data acquisition systems (stroboscopic coherent X-ray radiology and tomography) to provide dynamic investigation of rapidly evolving systems. The group also intensively develops optimized applications for fast, concurrent post-processing of tomographic data starting from simple normalization corrections to ad-hoc reconstruction and artifact reductions algorithms. Finally, the group investigates, creates and optimizes novel imaging modalities based on the coherent properties of synchrotron radiation and works on the transition of such work to conventional x-ray sources.
Scientific Highlights
World record in time-resolved tomography
Researchers from the Helmholtz Zentrum Berlin (HZB) and the TOMCAT beamline have achieved a new world record in time-resolved tomography by measuring over 200 tomographies per second during heating of an evolving aluminium metal foam.
Virtual lens improves X-ray microscopy
A method developed by PSI researchers makes X-ray images of materials even better. The researchers took a number of individual images while moving an optical lens. From these, with the help of computer algorithms, they generated one overall image.
Soft-tissue evidence for homeothermy and crypsis in a Jurassic ichthyosaur
Synchrotron-based X-ray tomographic microscopy of melanophores (skin pigment cells) of an amazingly well preserved 180 million years old ichtyosaur (extinct marine reptile similar to whales) contributed in a multidisciplinary investigation to the new findings published today in Nature.
PSI spin-off GratXray wins Swiss Technology Award 2017
A spin-off from PSI has received this year's Swiss Technology Award: The young company GratXray is developing a new method for early diagnosis of breast cancer.
Jinqiu Xu joins the X-ray Tomography Group as a Post Doc
Jinqiu Xu will work with the team developing X-ray phase contrast CT for breast cancer diagnosis. Before coming to PSI, she worked on CT reconstruction from incomplete data at Capital Normal University (Beijing, China).
PSI Thesis Medal goes to Dr. Matias Kagias
The PSI Thesis Medal is awarded every second year to the best PhD thesis performed at the Paul Scherrer Institut. Matias received the prize for his excellent thesis entitled "Direct Self-Imaging Methods for X-ray Differential Phase and Scattering Imaging". Congratulations!
Hector Dejea receives an Outstanding Poster Presentation Award at the bMASR Conference
Hector Dejea, a PhD at TOMCAT, received an Outstanding Poster Presentation Award at the 9th bioMedical Applications of Synchrotron Radiation (bMASR2018) conference held in Beijing (China) from October 23rd till 27th 2018. He presented the latest results of his work, entitled Multiscale X-ray Phase Contrast Imaging for Assessing Cardiac Remodelling: towards in-vitro applications.
TOMCAT paper on hard X-ray multi-projection imaging published
The TOMCAT team in collaboration with scientists from CFEL, MaxIV and ESRF developed a method for hard X-ray multi-projection imaging, using a single crystal to split the beam into multiple beams with different directions.
Dr. Anne Bonnin gives an invited talk at SRI 2018
The 13th International Conference on Synchrotron Radiation Instrumentation (SRI 2018) was hosted by the National Synchrotron Radiation Research Center (NSRRC) from June 10 to 15, 2018. The 5-day conference was gathering scientists and engineers around the world involved in development of new concepts, techniques, and instruments related to synchrotron radiation and free electron laser research.
Arttu Miettinen joins the TOMCAT team as Post Doc
After his PhD at the University of Jyväskylä in Finnland in image analysis, Arttu will be working on the stitching and segmentation of large datasets in the framework of the Human Brain Project.