In this thesis, we investigate deep learning X-ray image reconstruction algorithms for exper- iments at large-scale X-ray facilities. Specially, we combine deep ...

May 20, 2024 · In this thesis, we show that combining the physical principles of X-ray imaging with deep learning greatly improves the performance and robustness of the ...

Nov 20, 2024 · Physics-driven deep learning (PD-DL) approaches have become popular for improved reconstruction of fast magnetic resonance imaging (MRI) scans.

In this thesis, we show that combining the physical principles of X-ray imaging with deep learning greatly improves the performance and robustness of the ...

Nov 23, 2024 · Physics-driven deep learning (PD-DL) approaches have become popular for improved reconstruction of fast magnetic resonance imaging (MRI) ...

A number of ideas inspired by deep learning techniques for computer vision and image processing have been successfully applied to nonlinear image reconstruction ...

Jul 23, 2024 · This review paper provides a comprehensive overview of recent advances in DL for MRI reconstruction, and focuses on various DL approaches and architectures.

Aug 15, 2022 · X ray phase-contrast imaging (PCI) is a powerful nondestructive imaging technique that can generate high contrasts in weakly attenuating samples ...

Different from previous works, they incorporate both an initial reconstruction of the object of interest and the scatter-corrupted measurements related to it, ...

Jul 15, 2024 · Physics-inspired generative models, in particular diffusion and Poisson flow models, enhance Bayesian methods and promise great utilities in medical imaging.