Scattering-Based X-ray Imaging and Tomography

Objective

This research project will create new ways of doing X-ray imaging based on scattering and data redundancy. Many X-ray imaging techniques are based on simple models that fail to capture important phenomena, such as small-angle or incoherent scattering. Far from being a nuisance, scattering signals often hold valuable information on the finest structure of the investigated sample. For instance X-ray scattering can reveal fibre orientations in a carbon-fibre composite or the early formation of cancerous tissues in mammography. To exploit scattering, adapting data acquisition is often necessary. Collecting diverse but partly redundant datasets is a powerful way to encode information so that it can be subsequently decoded with appropriate software. For this purpose one can, for instance, displace the sample in a non-uniform illumination profile. Another often overlooked source of redundancy is tomography itself, where projection images from different view angles are strongly correlated. The central achievements of this research project will be the introduction of a new formalism that offers a complete picture of scattering in the context of imaging, and the development of techniques that exploit explicitly measurement diversity - in particular tomographic redundancy - to extract complementary information. These new paradigms will be implemented and demonstrated with a range of X-ray imaging techniques: ptychography for high-resolution imaging, speckle-based imaging for lab-based phase-contrast and dark-field, and conventional transmission microCT, for scattering signal extraction. The expected results of this research project will leave a lasting impact on the research community. The full exploitation of data redundancy and scattering-aware models will create imaging modalities that can reveal features that could not be seen before for a broad range of applications, from advanced materials to fragile biological samples, to valuable heritage and archaeological artefacts.

Programme(s)

• H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)

Topic(s)

• ERC-2019-COG - ERC Consolidator Grant

Call for proposal

ERC-2019-COG
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Funding Scheme

Host institution

Beneficiaries (2)