The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

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 …

Image reconstruction is an inverse problem that solves for a computational image based on
sampled sensor measurement. Sparsely sampled image reconstruction poses additional …

Current deep neural network based approaches to computed tomography (CT) metal artifact
reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training …

MRI with multiple protocols is commonly used for diagnosis, but it suffers from a long
acquisition time, which yields the image quality vulnerable to say motion artifacts. To …

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 …

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 …