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  4. Helical 3-D X-ray Dark-field Imaging

Helical 3-D X-ray Dark-field Imaging

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  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users
  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users
  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users

Helical 3-D X-ray Dark-field Imaging

Helical 3-D X-ray Dark-field Imaging

(Third Party Funds Single)

Overall project:
Project leader: Andreas Maier
Project members:
Start date: April 1, 2015
End date: March 31, 2019
Acronym:
Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)
URL:

Abstract

The dark-field signal of an X-ray phase-contrast system captures the small-angle scattering of microscopic structures. It is acquired using Talbot-Lau interferometer, and a conventional X-ray source and a conventional X-ray detector. Interestingly, the measured intensity of the dark-field signal depends on the orientation of the microstructure. Using algorithms from tomographic image reconstruction, it is possible to recover these structure orientations. The size of the imaged structures can be considerably smaller than the resolution of the used X-ray detector. Hence, it is possible to investigate structural properties of - for example - bones or soft tissue at an unprecedented level of detail.Existing methods for 3-D dark-field reconstruction require sampling in all three spatial dimensions. For practical use, this procedure is infeasible.The goal of the proposed project is to develop a system and a method for 3-D reconstruction of structure orientations based on measurements from a practical imaging trajectory. To this end, we propose to use a helical trajectory, a concept that has been applied in conventional CT imaging with tremendous success. As a result, it will be possible for the first time to compute dark-field volumes from a practically feasible, continuous imaging trajectory. The trajectory does not require multiple rotations of the object or the patient and avoids unnecessarily long path lengths.The project will be conducted in cooperation between the experimental physics and the computer science department. The project is composed of six parts:- A: Development of a 3-D cone-beam scattering projection model- B: Development of reconstruction algorithms for a helical dark-field imaging system- C: Evaluation and optimization of the reconstruction methods towards clinical applications- D: Design of an experimental helical imaging system- E: Setup of the helical imaging system- F: Evaluation and optimization of the system performanceParts A to C will be performed by the computer science department. Parts D to E will be conducted by the experimental physics department.

Publications


    Friedrich-Alexander-Universität Erlangen-Nürnberg
    Lehrstuhl für Mustererkennung (Informatik 5)

    Martensstr. 3
    91058 Erlangen
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