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most citedAn Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural Representation

104 citations · 203 across the 25 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

eess.IV2022

Joint Rigid Motion Correction and Sparse-View CT via Self-Calibrating Neural Field

Qing Wu, Xin Li, Hongjiang Wei +2

Neural Radiance Field (NeRF) has widely received attention in Sparse-View Computed Tomography (SVCT) reconstruction tasks as a self-supervised deep learning framework. NeRF-based S…

eess.IV2022

A scan-specific unsupervised method for parallel MRI reconstruction via implicit neural representation

Ruimin Feng, Qing Wu, Yuyao Zhang +1

Parallel imaging is a widely-used technique to accelerate magnetic resonance imaging (MRI). However, current methods still perform poorly in reconstructing artifact-free MRI images…

eess.IV2022

Continuous longitudinal fetus brain atlas construction via implicit neural representation

Lixuan Chen, Jiangjie Wu, Qing Wu +2

Longitudinal fetal brain atlas is a powerful tool for understanding and characterizing the complex process of fetus brain development. Existing fetus brain atlases are typically co…

eess.IV2022

Noise2SR: Learning to Denoise from Super-Resolved Single Noisy Fluorescence Image

Xuanyu Tian, Qing Wu, Hongjiang Wei +1

Fluorescence microscopy is a key driver to promote discoveries of biomedical research. However, with the limitation of microscope hardware and characteristics of the observed sampl…

eess.IV2022★ 50 cited

Self-Supervised Coordinate Projection Network for Sparse-View Computed Tomography

Qing Wu, Ruimin Feng, Hongjiang Wei +2

In the present work, we propose a Self-supervised COordinate Projection nEtwork (SCOPE) to reconstruct the artifacts-free CT image from a single SV sinogram by solving the inverse…