ShaoSen Chueh

This paper enhances the spatial resolution of soft X-ray tomography using physics-aware learning, improving structural fidelity and reducing radiation exposure.

This paper introduces a self-supervised model to correct missing wedge artifacts in soft X-ray tomography, improving volume quantification and morphology accuracy in cellular structures.

This study compares denoising raw tilt series versus reconstructed tomograms in soft X-ray tomography, finding that denoising tilt series provides more reliable results and faster inference.