The thesis focuses on the development and application of advanced X-ray imaging techniques, specifically modulation-based dark-field imaging and X-ray scattering tensor tomography. Modulation-based imaging (MBI) exploits heterogeneous illumination patterns to encode locally the X-ray interaction with a sample. While a uniform illumination can normally reveal only the attenuating properties of the sample, a non-uniform X-ray illumination is also altered by refraction and ultra-small-angle scattering effects. MBI is commonly implemented using a periodic grating array (grating-based imaging or GBI) or a random diffuser (speckle-based imaging or SBI). MBI enables simultaneous access to attenuation, phase contrast, and small-angle scattering (or dark-field) signals from a single dataset, offering a multi-modal view of a sample’s internal structure. Combining high signal sensitivity with a simple experimental implementation, SBI is particularly suitable for biological soft tissues, where small density differences in the specimen are highlighted thanks to the differential-phase signal, enabling a higher contrast compared to absorption imaging without the need for a contrast agent. A multimodal study on ovarian and hepatic tissues is carried out in this thesis, providing insights into microstructural changes during follicular maturation of the ovaries and exploring hepatic tissue to reveal lipid aggregate distribution in the liver. The combination of phase contrast and transmission signals offered a detailed, non-destructive analysis of bovine ovaries and human liver samples. Samples with strongly oriented microstructural features often exhibit an anisotropic X-ray scattering profile. In these cases, the directionality of the scattering can also be extracted to reveal information about their orientation, e.g., of fibres in a composite material. In this thesis, we demonstrate the capability of speckle-based dark-field imaging to detect barely visible impact damage in carbon fibre reinforced polymers. This approach offers a valuable tool for non-destructive testing of composite structures. By collecting two-dimensional projection images with small-angle scattering signals at various orientations of the sample, two-dimensional directional scattering signals can be combined to reconstruct tomographically the local scattering tensor of the sample using X-ray tensor tomography (XTT). XTT provides information on the sub-structures' orientations in a macroscopic sample, even when their dimensions are smaller than the image pixel resolution, enabling the exploration of microstructural organisation in a macroscopic volume. A universal reconstruction method for XTT is presented in this thesis, which is compatible with different wavefront modulation techniques. In addition, we present a robust method for the extraction of the directional dark-field signal from data acquired with random diffusers. We demonstrate this approach on experimental measurements to obtain the first reconstruction of speckle-based tensor tomography. To optimise experimental parameters and predict the scattering behaviour, we developed a numerical wave-optics simulation model for SBI. We validate its effectiveness simulating a SBI measurement, a SAXS experiment, and an X-ray tensor tomography experiment. The work presented in this thesis aims to establish X-ray scattering tensor tomography with a random modulator, making it more accessible for a broader range of applications, from industrial non-destructive testing to advanced biomedical diagnostics, and cultural heritage. We show several application cases, ranging from aerospace-type carbon-epoxy materials, to human middle ear ossicles, to fossil human remains. These various applications demonstrate the versatility and power of the imaging techniques developed in this work, with significant potential to impact different fields of ongoing research.

The thesis focuses on the development and application of advanced X-ray imaging techniques, specifically modulation-based dark-field imaging and X-ray scattering tensor tomography. Modulation-based imaging (MBI) exploits heterogeneous illumination patterns to encode locally the X-ray interaction with a sample. While a uniform illumination can normally reveal only the attenuating properties of the sample, a non-uniform X-ray illumination is also altered by refraction and ultra-small-angle scattering effects. MBI is commonly implemented using a periodic grating array (grating-based imaging or GBI) or a random diffuser (speckle-based imaging or SBI). MBI enables simultaneous access to attenuation, phase contrast, and small-angle scattering (or dark-field) signals from a single dataset, offering a multi-modal view of a sample’s internal structure. Combining high signal sensitivity with a simple experimental implementation, SBI is particularly suitable for biological soft tissues, where small density differences in the specimen are highlighted thanks to the differential-phase signal, enabling a higher contrast compared to absorption imaging without the need for a contrast agent. A multimodal study on ovarian and hepatic tissues is carried out in this thesis, providing insights into microstructural changes during follicular maturation of the ovaries and exploring hepatic tissue to reveal lipid aggregate distribution in the liver. The combination of phase contrast and transmission signals offered a detailed, non-destructive analysis of bovine ovaries and human liver samples. Samples with strongly oriented microstructural features often exhibit an anisotropic X-ray scattering profile. In these cases, the directionality of the scattering can also be extracted to reveal information about their orientation, e.g., of fibres in a composite material. In this thesis, we demonstrate the capability of speckle-based dark-field imaging to detect barely visible impact damage in carbon fibre reinforced polymers. This approach offers a valuable tool for non-destructive testing of composite structures. By collecting two-dimensional projection images with small-angle scattering signals at various orientations of the sample, two-dimensional directional scattering signals can be combined to reconstruct tomographically the local scattering tensor of the sample using X-ray tensor tomography (XTT). XTT provides information on the sub-structures' orientations in a macroscopic sample, even when their dimensions are smaller than the image pixel resolution, enabling the exploration of microstructural organisation in a macroscopic volume. A universal reconstruction method for XTT is presented in this thesis, which is compatible with different wavefront modulation techniques. In addition, we present a robust method for the extraction of the directional dark-field signal from data acquired with random diffusers. We demonstrate this approach on experimental measurements to obtain the first reconstruction of speckle-based tensor tomography. To optimise experimental parameters and predict the scattering behaviour, we developed a numerical wave-optics simulation model for SBI. We validate its effectiveness simulating a SBI measurement, a SAXS experiment, and an X-ray tensor tomography experiment. The work presented in this thesis aims to establish X-ray scattering tensor tomography with a random modulator, making it more accessible for a broader range of applications, from industrial non-destructive testing to advanced biomedical diagnostics, and cultural heritage. We show several application cases, ranging from aerospace-type carbon-epoxy materials, to human middle ear ossicles, to fossil human remains. These various applications demonstrate the versatility and power of the imaging techniques developed in this work, with significant potential to impact different fields of ongoing research.

Multimodal 2D and 3D X-ray Directional Dark-Field Imaging: Development and Applications / Lautizi, Ginevra. - (2025 Jan 24).

Multimodal 2D and 3D X-ray Directional Dark-Field Imaging: Development and Applications

LAUTIZI, GINEVRA
2025-01-24

Abstract

The thesis focuses on the development and application of advanced X-ray imaging techniques, specifically modulation-based dark-field imaging and X-ray scattering tensor tomography. Modulation-based imaging (MBI) exploits heterogeneous illumination patterns to encode locally the X-ray interaction with a sample. While a uniform illumination can normally reveal only the attenuating properties of the sample, a non-uniform X-ray illumination is also altered by refraction and ultra-small-angle scattering effects. MBI is commonly implemented using a periodic grating array (grating-based imaging or GBI) or a random diffuser (speckle-based imaging or SBI). MBI enables simultaneous access to attenuation, phase contrast, and small-angle scattering (or dark-field) signals from a single dataset, offering a multi-modal view of a sample’s internal structure. Combining high signal sensitivity with a simple experimental implementation, SBI is particularly suitable for biological soft tissues, where small density differences in the specimen are highlighted thanks to the differential-phase signal, enabling a higher contrast compared to absorption imaging without the need for a contrast agent. A multimodal study on ovarian and hepatic tissues is carried out in this thesis, providing insights into microstructural changes during follicular maturation of the ovaries and exploring hepatic tissue to reveal lipid aggregate distribution in the liver. The combination of phase contrast and transmission signals offered a detailed, non-destructive analysis of bovine ovaries and human liver samples. Samples with strongly oriented microstructural features often exhibit an anisotropic X-ray scattering profile. In these cases, the directionality of the scattering can also be extracted to reveal information about their orientation, e.g., of fibres in a composite material. In this thesis, we demonstrate the capability of speckle-based dark-field imaging to detect barely visible impact damage in carbon fibre reinforced polymers. This approach offers a valuable tool for non-destructive testing of composite structures. By collecting two-dimensional projection images with small-angle scattering signals at various orientations of the sample, two-dimensional directional scattering signals can be combined to reconstruct tomographically the local scattering tensor of the sample using X-ray tensor tomography (XTT). XTT provides information on the sub-structures' orientations in a macroscopic sample, even when their dimensions are smaller than the image pixel resolution, enabling the exploration of microstructural organisation in a macroscopic volume. A universal reconstruction method for XTT is presented in this thesis, which is compatible with different wavefront modulation techniques. In addition, we present a robust method for the extraction of the directional dark-field signal from data acquired with random diffusers. We demonstrate this approach on experimental measurements to obtain the first reconstruction of speckle-based tensor tomography. To optimise experimental parameters and predict the scattering behaviour, we developed a numerical wave-optics simulation model for SBI. We validate its effectiveness simulating a SBI measurement, a SAXS experiment, and an X-ray tensor tomography experiment. The work presented in this thesis aims to establish X-ray scattering tensor tomography with a random modulator, making it more accessible for a broader range of applications, from industrial non-destructive testing to advanced biomedical diagnostics, and cultural heritage. We show several application cases, ranging from aerospace-type carbon-epoxy materials, to human middle ear ossicles, to fossil human remains. These various applications demonstrate the versatility and power of the imaging techniques developed in this work, with significant potential to impact different fields of ongoing research.
24-gen-2025
THIBAULT, PIERRE
37
2023/2024
Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
Università degli Studi di Trieste
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3104518
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