Deep-learning-based tomographic imaging is an important application of artificial
intelligence and a new frontier of machine learning. Deep learning has been widely used in …

This review highlights recent efforts on applying electron microscopy (EM) to soft (including
biological) nanomaterials. We will show how developments of both the hardware and …

Abstract Recently, deep learning (DL)‐based methods for the generation of synthetic
computed tomography (sCT) have received significant research attention as an alternative to …

Computed tomography (CT) is an effective med-ical imaging modality, widely used in the
field of clinical medicine for the diagnosis of various pathologies. Advances in Multidetector …

To reduce the radiation dose, sparse-view computed tomography (CT) reconstruction has
been proposed, aiming to recover high-quality CT images from sparsely sampled sinogram …

X-ray computed tomography (CT) is of great clinical significance in medical practice
because it can provide anatomical information about the human body without invasion …

The use of deep learning (DL) to improve cone‐beam CT (CBCT) image quality has gained
popularity as computational resources and algorithmic sophistication have advanced in …

The Radon transform is widely used in physical and life sciences, and one of its major
applications is in medical X-ray computed tomography (CT), which is significantly important …

Low-dose computed tomography (LDCT) scans, which can effectively alleviate the radiation
problem, will degrade the imaging quality. In this paper, we propose a novel LDCT …

Sparse-view Computed Tomography (SVCT) has great potential for decreasing patient
radiation exposure dose during scanning. In this work, we propose a Self-supervised …