Alzheimer's disease (AD) is a neurodegenerative disorder that exerts a substantial influence
on individuals worldwide. Magnetic resonance imaging (MRI) can detect and track disease …

Super-resolution of brain magnetic resonance imaging (MRI) generates high resolution
brain images as opposed to low-resolution ones, thus providing more detailed anatomical …

Introduction Timely diagnosis and prognostication of Alzheimer's disease (AD) and mild
cognitive impairment (MCI) are pivotal for effective intervention. Artificial intelligence (AI) in …

Given the constraints posed by hardware capacity, scan duration, and patient cooperation,
the reconstruction of magnetic resonance imaging (MRI) images emerges as a pivotal …

Deep learning (DL) has shown great potential in medical image enhancement problems,
such as super-resolution or image synthesis. However, to date, most existing approaches …

Deep learning (DL) has shown great potential in medical image enhancement problems,
such as super-resolution or image synthesis. However, to date, little consideration has been …

Denoising diffusion probabilistic models (DDPMs) have achieved impressive performance
on various image generation tasks, including image super-resolution. By learning to reverse …

Multi-contrast magnetic resonance imaging (MRI) is the most common management tool
used to characterize neurological disorders based on brain tissue contrasts. However …

High-resolution (HR) MRI scans obtained from research-grade medical centers provide
precise information about imaged tissues. However, routine clinical MRI scans are typically …

In this work, we investigate the value of uncertainty modelling in 3D super-resolution with
convolutional neural networks (CNNs). Deep learning has shown success in a plethora of …