The x-ray computed tomography (CT) is essential for medical diagnosis and industrial
nondestructive testing. The aim of CT is to recover or reconstruct image from projection data …

Improve low-dose CT (LDCT) imaging quality is a hot research issue in the medical imaging
field. However, current image post-processing method mainly focus on denoising, ignoring …

Few-view or sparse-view computed tomography has been recently introduced as a great
potential to speed up data acquisition and alleviate the amount of patient radiation dose …

In recent years, the growing awareness of public health has brought attention to low-dose
computed tomography (LDCT) scans. However, the CT image generated in this way …

clinical low X-ray dose computed tomography (LDCT) scanner often induce high intensity
strip artifact and spot nosie, compromising diagnoses and intervention plans. Recently …

Objective. Deep learning-based methods have been widely used in medical imaging field
such as detection, segmentation and image restoration. For supervised learning methods in …

Sparse-view CT reconstruction is a fundamental task in computed tomography to overcome
undesired artifacts and recover the details of textual structure in degraded CT images …

Computed Tomography (CT) is a widely use medical image modality in clinical medicine,
because it produces excellent visualizations of fine structural details of the human body. In …

Convolutional neural network (CNN)-based deep learning techniques have enjoyed many
successful applications in the field of medical imaging. However, the complicated between …

The use of Low-dose Computed Tomography (LDCT) in clinical medicine for diagnosis and
treatment planning is widespread due to the minimal exposure of patients to radiation. Also …