Analysis and Visualization of Multi-Modal Computed Tomography Data: Neutron CT in combination with X-ray CT
Praktikum/BA/DA
Christoph Heinzl Artem Amirkhanov Radiograph of an analog camera: by neutrons (top) by X-rays (bottom). While X-rays are attenuated more effectively by heavier materials like metals, neutrons make it possible to image some light materials such as hydrogenous substances with high contrast: in the X-ray image, the metal parts of the photo apparatus are seen clearly, while the neutron radiograph shows details of the plastic parts. (This image is courtesy of PSI)Content:
Description
Neutron tomography (NCT) and X-ray computed tomography (XCT) are well established methods in medicine which have been increasingly used for industrial applications within recent years. Both methods are non destructive and mainly applied for three dimensional characterization of components in order to detect inhomogeneities (e.g., pores, cracks, voids, material interfaces and errors etc.) deep inside the component or to track changes of the component during processing.
Neutron tomography is an ideal complementary technique to conventional X-ray computed tomography. By its nature it is well suited for scanning metallic components, while X-ray radiation is strongly absorbed by metals and thus reaches its limits. Vice versa, X-rays penetrate plastic materials very well, while Neutron tomography has severe deficits due to the presence of hydrogen chains. To date there is no technique, which combines the advantages of each method in order to take advantage for visualization and analysis.Goals
- Together with us you will develop and evaluate algorithms for multimodal CT data visualization and analysis. More specifically techniques will be developed in order to combine the advantages of NCT and XCT
- You will collaborate in national and international research projects of the Computed Tomography research group and cooperate with our research partner Paul Scherrer Institute (PSI)
- Finally we intend to publish the generated results together to the scientific community.
Useful references
- General information on Neutron Imaging
- Martin Haidacher: Information-based Feature Enhancement in Scientific Visualization
- Johanna Beyer: GPU-based Multi-Volume Rendering of Complex Data in Neuroscience and Neurosurgery
- Christoph Heinzl: Analysis and Visualization of Industrial CT Data
What we offer
- Interesting topics, applied research on real world problems
- Cooperation with our company and research partners
- Supervision and mentoring together with the CG Institute
Requirements
- Good skills in C++ and software engineering
- Interested in scientific visualization
- Advantageous: experience in parallel programming, e.g., CUDA or OpenCL
Additional Information
If you are interested, just contact us:
Christoph Heinzl
christoph.heinzl@fh-wels.at
Artem Amirkhanov
artem@cg.tuwien.ac.at
