Super resolution problems are widely discussed in medical imaging. Spatial resolution of
medical images are not sufficient due to the constraints such as image acquisition time, low …

Magnetic resonance (MR) images with both high resolutions and high signal-to-noise ratios
(SNRs) are desired in many clinical and research applications. However, acquiring such …

The purpose of super-resolution approaches is to overcome the hardware limitations and
the clinical requirements of imaging procedures by reconstructing high-resolution images …

High resolution magnetic resonance (MR) images are desired in many clinical and research
applications. Acquiring such images with high signal-to-noise (SNR), however, can require a …

High resolution magnetic resonance (MR) imaging is desirable in many clinical applications
due to its contribution to more accurate subsequent analyses and early clinical diagnoses …

There is a growing demand for high-resolution (HR) medical images for both clinical and
research applications. Image quality is inevitably traded off with acquisition time, which in …

High-fidelity information, such as 4K quality videos and photographs, is increasing as high-
speed internet access becomes more widespread and less expensive. Even though camera …

Single image super-resolution (SISR) reconstruction for magnetic resonance imaging (MRI)
has generated significant interest because of its potential to not only speed up imaging but …

Deep learning-based super-resolution (SR) techniques have generally achieved excellent
performance in the computer vision field. Recently, it has been proven that three …

The use of MRI for prostate cancer diagnosis and treatment is increasing rapidly. However,
identifying the presence and extent of cancer on MRI remains challenging, leading to high …