The computed tomography (CT) technique is extensively employed as an imaging modality
in clinical settings. The radiation dose of CT, however, is significantly high, thereby raising …

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 …

Fundus image quality serves a crucial asset for medical diagnosis and applications.
However, such images often suffer degradation during image acquisition where multiple …

Computed tomography (CT) is routinely used for three-dimensional non-invasive imaging.
Numerous data-driven image denoising algorithms were proposed to restore image quality …

While various deep learning methods were proposed for low-dose computed tomography
(CT) denoising, they often suffer from over-smoothing, blurring, and lack of explainability. To …

Recently, deep learning techniques have been used for low-dose CT (LDCT) reconstruction
to reduce the radiation risk for patients. Despite the improvement in performance, the …

Multiphase contrast-enhanced computed tomography (CECT) scan is clinically significant to
demonstrate the anatomy at different phases. But such multiphase scans inherently lead to …

Semantic scene understanding is beneficial for mobile robots. Semantic information
obtained through onboard cameras can improve robots' navigation performance. However …

In the medical field, the application of machine learning technology in the automatic
diagnosis and monitoring of osteoporosis often faces challenges related to domain …

Computed tomography (CT) is continuously becoming a valuable diagnostic technique in
clinical practice. However, the radiation dose exposure in the CT scanning process is a …