Conventional reconstruction techniques, such as filtered back projection (FBP) and iterative
reconstruction (IR), which have been utilised widely in the image reconstruction process of …

Introduction Low-dose computed tomography tends to produce lower image quality than
normal dose computed tomography (CT) although it can help to reduce radiation hazards of …

In this paper, we present Neural Adaptive Tomography (NeAT), the first adaptive,
hierarchical neural rendering pipeline for tomography. Through a combination of neural …

Limited-angle CT is a challenging problem in real applications. Incomplete projection data
will lead to severe artifacts and distortions in reconstruction images. To tackle this problem …

This paper proposes a novel and fast self-supervised solution for sparse-view CBCT
reconstruction (Cone Beam Computed Tomography) that requires no external training data …

Computed tomography (CT) is increasingly essential for clinical diagnosis nowadays while
X-ray ionizing radiation is harmful and may increase the risk of cancers. Researchers have …

Deep learning (DL)-based methods show great potential in computed tomography (CT)
imaging field. The DL-based reconstruction methods are usually evaluated on the training …

To reduce the potential risk of radiation to the patient, low-dose computed tomography
(LDCT) has been widely adopted in clinical practice for reconstructing cross-sectional …

Noise is a definite degeneration of medical images that interferes with the diagnostic
process in clinical medicine. Although many denoising algorithms have been developed to …

In recent years, computed tomography (CT) has been widely used in various clinical
diagnosis. Given potential health risks bring by the X-ray radiation, the major objective of the …