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X-Ray Phase-Contrast

  • Early detection of cancer and angiography applications are just two examples that can directly benefit from an imaging modality with excellent soft-tissue contrast. X-ray grating interferometry is promising to achieve this while keeping radiation dose and examination costs low. Existing clinical X-ray systems can be retrofitted with a set of three gratings to form an interferometer. The measurement procedure yields three images: X-ray absorption, differential phase, and dark-field. The vision of phase-contrast X-ray is that these three complementary signals together enable highly sensitive tissue contrast for medical diagnosis and interventional applications.

    The X-ray phase contrast group at the Pattern Recognition Lab develops algorithms for processing these images, and for the 3-D reconstruction of tomographic acquisitions. We closely collaborate with the physicist at ECAP, who are maintaining the experimental setup.

Colloquium Timetable

11.07.2017Deep Learning Book Chapter 7, Part 1 / *
18.07.2017cancelled due to illness / *
25.07.2017no colloquium due to PRS
01.08.2017Brainstorming: Optimization of Talbot-Lau Setups / Deep Learning Book Chapter 7, Part 2 / *Shiyang (vacation)
08.08.2017Meeeting with ECAP (Wednesday 10:00) / *Christian, Shiyang (vacation)
15.08.2017In-vivo X-ray Dark-Field Chest Radiography of a Pig / *Shiyang (vacation)
05.09.2017*Christian, Sebastian (S3P)
12.09.2017Review paper: M. Endrizzi: X-ray phase contrast imagingSebastian (XNPIG)
26.09.2017*Sebastian (IMPRS)
03.10.2017Public holiday
10.10.2017Sebastian: Conference Review - XNPIG / *
17.10.2017Sebastian: Conference Review - XNPIG (postponed from last week) / *
24.10.2017*Christian, Lina, Shiyang
31.10.2017Public holiday
07.11.2017Sebastian: Raupach & Flohr: Analytical evaluation of the signal and noise propagation in x-ray differential phase-contrast computed tomographyShiyang


Sebastian: Raupach & Flohr: Analytical evaluation of the signal and noise propagation in x-ray differential phase-contrast computed tomography (continued)

21.11.2017Sebastian: Raupach & Flohr: Analytical evaluation of the signal and noise propagation in x-ray differential phase-contrast computed tomography (continued)
28.11.2017Shiyang - Koenig et al.: On the origin and nature of the grating interferometric dark-field contrast obtained with low-brilliance x-ray sources

All: Bevins et al.: Multicontrast x-ray computed tomography imaging using Talbot-Lau interferometry without phase stepping. (This time we start at 12:30) / *

******* 2018Kolloquium will take place at 13:30 *******
09.01.2018Johannes - Lim: Numerical Modeling and Experiment for Single Grid-Based Phase-Contrast X-Ray Imaging / *
16.01.2018short group meeting (This time we start at 15:00) / *
23.01.2018All: IMXP conference review / *Christian

Fabian Hofmann - Presentation of Master Thesis: Modeling and Correcting Moiré Artifacts in Grating-Based Phase-Contrast X-Ray Imaging

Shiyang - Projection Model Paper discussion

07.02.2018No colloquium
20.02.2018No colloquiumJohannes, Shiyang


Besides our colloquium, we regularly attend the colloquium of our collaborators at ECAP, every Wednesday, 10:00, at Erwin-Rommel-Str. 1


Papers to be schedueled:

- v.Teuffenbach: Single shot grating tomography

- Marschner: Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography 

- Lynch: Interpretation of Dark-field contrast and particle-size selectivity in grating interferometers

- Strobl: General solution for quantitative dark-field contrast imaging with grating interferometers

- Sharma: Design of Acquisition Schemes and Setup Geometry for Anisotropic X-ray Dark-Field Tomography (AXDT)


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Optimization of Setups of Talbot-Lau X-ray Phase Contrast Imaging Systems
Johannes Bopp
  • Grating-based Talbot-Lau X-ray Interferometry is a novel imaging modality. Compared to standard absorption X-ray imaging, it enables the acquisition of differential phase contrast images. These images correspond to the electron density of the scanned specimen. Furthermore, so-called dark-field images are obtained. These images can visualize density inhomogeneities at micrometer scale. The goal of the project is to improve the setup of Talbot-Lau X-ray Imaging systems. So far the correlation between the different variables of such a system especially with polychromatic X-ray spectra is not known yet. Thus, the setup should be simulated and optimized to find the ideal setup with respect to certain structures in the object and the resulting images.

    More details can be found on Johannes' Opens internal link in current windowproject page

3-D X-Ray Dark-field Reconstruction
Shiyang Hu
  • X-ray dark-field imaging (XDI) measures ultra-small angle scattering. It allows reconstruction of structural variation at length scales from hundreds nanometers to some micrometers, which is much smaller than the resolution of a conventional X-ray imaging system. The core idea of this project is to develop algorithms to fully recover information from XDI datasets. 

    More details can be found on Shiyang's Opens internal link in current windowproject page

Artifact Correction and Image Enhancement
Sebastian Käppler
  • The imaging performance of grating-based interferometers can be impacted by imperfections of the gratings and system miscalibration. The first goal of this project is to develop novel algorithms for correcting measurement artifacts in phase contrast images. The second goal is to investigate the problem of retrieving the X-ray phase shift from the differential projections by integration and its impact on object detectability.

    More details can be found on Sebastian's Opens internal link in current windowproject page.

Past Projects

Phase-contrast CT (PHACT)
Wilhelm Haas
  • The goal of this project is to build and investigate a system and algorithms for 2-D tomographic phase reconstruction using an X-ray grating interferometer. The system is built at Opens external link in new windowECAP. The system software was developed in large part by Opens external link in new windowWilhelm Haas, former member of the Pattern Recognition Lab.