Filtered back projection (FBP) has been the standard CT image reconstruction method for 4
decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in …

Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …

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 …

Medical imaging denoising faces great challenges, yet is in great demand. With its
distinctive characteristics, medical imaging denoising in the image domain requires …

Disentangled representation learning has been proposed as an approach to learning
general representations even in the absence of, or with limited, supervision. A good general …

Recently, the diffusion model has emerged as a superior generative model that can produce
high quality and realistic images. However, for medical image translation, the existing …

Unpaired medical image enhancement (UMIE) aims to transform a low-quality (LQ) medical
image into a high-quality (HQ) one without relying on paired images for training. While most …

Scoliosis is a common disease of the spine and requires regular monitoring due to its
progressive properties. A preferred indicator to assess scoliosis is by the Cobb angle, which …

Metal artifacts degrade CT image quality, hampering clinical assessment. Numerous metal
artifact reduction methods are available to improve the image quality of CT images with …

Computed tomography (CT) has been widely used for medical diagnosis, assessment, and
therapy planning and guidance. In reality, CT images may be affected adversely in the …