Image denoising is a prerequisite for downstream tasks in many fields. Low-dose and
photon-counting computed tomography (CT) denoising can optimize diagnostic …

Spectral computed tomography (CT) has recently emerged as an advanced version of
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …

Over the last decade, the number of digital images captured per day has increased
exponentially, due to the accessibility of imaging devices. The visual quality of photographs …

Purpose Computed tomography (CT) has played a vital role in medical diagnosis,
assessment, and therapy planning, etc. In clinical practice, concerns about the increase of x …

Objective. Self-supervised learning methods have been successfully applied for low-dose
computed tomography (LDCT) denoising, with the advantage of not requiring labeled data …

Purpose Supervised deep convolutional neural network (CNN)-based methods have been
actively used in clinical CT to reduce image noise. The networks of these methods are …

ABSTRACT CT image quality is largely reliant on radiation dose, which causes a trade-off
between image quality and dose, affecting the subsequent image-based diagnostic and …

These were the sociologists from the Frankfurt School, Theodor Adorno (1903–1969), and
Max Horkheimer (1895–1973)(Adorno & Horkheimer, 1944), who coined the term “cultural …

Although deep learning has witnessed great successes for low-dose CT (LDCT) denoising,
there still exist two significant problems: i) most LDCT denoising approaches require paired …

Image restoration refers to the process of inspecting a degraded image and recovering the
underlying artifact-free counterpart through discarding the artifacts. Medical image …