3 citations · 3 across the 1 of their papers we have counts for
5 papers
MIASSR: An Approach for Medical Image Arbitrary Scale Super-Resolution
Jin Zhu, Chuan Tan, Junwei Yang +2
Single image super-resolution (SISR) aims to obtain a high-resolution output from one low-resolution image. Currently, deep learning-based SISR approaches have been widely discusse…
Generative Adversarial Networks (GAN) Powered Fast Magnetic Resonance Imaging -- Mini Review, Comparison and Perspectives
Guang Yang, Jun Lv, Yutong Chen +2
Magnetic Resonance Imaging (MRI) is a vital component of medical imaging. When compared to other image modalities, it has advantages such as the absence of radiation, superior soft…
Arbitrary Scale Super-Resolution for Brain MRI Images
Chuan Tan, Jin Zhu, Pietro Lio'
Recent attempts at Super-Resolution for medical images used deep learning techniques such as Generative Adversarial Networks (GANs) to achieve perceptually realistic single image S…
How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach
Jin Zhu, Guang Yang, Pietro Lio
Single image super-resolution (SISR) is of great importance as a low-level computer vision task. The fast development of Generative Adversarial Network (GAN) based deep learning ar…
Lesion Focused Super-Resolution
Jin Zhu, Guang Yang, Pietro Lio
Super-resolution (SR) for image enhancement has great importance in medical image applications. Broadly speaking, there are two types of SR, one requires multiple low resolution (L…