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Dual Arbitrary Scale Super-Resolution for Multi-Contrast MRI
Jiamiao Zhang, Yichen Chi, Jun Lyu +2
Limited by imaging systems, the reconstruction of Magnetic Resonance Imaging (MRI) images from partial measurement is essential to medical imaging research. Benefiting from the div…
Knowledge Distillation based Degradation Estimation for Blind Super-Resolution
Bin Xia, Yulun Zhang, Yitong Wang +4
Blind image super-resolution (Blind-SR) aims to recover a high-resolution (HR) image from its corresponding low-resolution (LR) input image with unknown degradations. Most of the e…
Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution
Guangyuan Li, Jun Lv, Yapeng Tian +4
Magnetic resonance imaging (MRI) can present multi-contrast images of the same anatomical structures, enabling multi-contrast super-resolution (SR) techniques. Compared with SR rec…
LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-Resolution
Wenming Yang, Xuechen Zhang, Yapeng Tian +3
In this paper, we develop a concise but efficient network architecture called linear compressing based skip-connecting network (LCSCNet) for image super-resolution. Compared with t…