Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
2016 · 6,903 citations
https://doi.org/10.1109/cvpr.2016.207
D
Daniel Rueckert
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Daniel Rueckert is an academic researcher from Munich Center for Machine Learning. The author has contributed to research in topics: Medical Image Segmentation Techniques & Advanced MRI Techniques and Applications & Medical Imaging Techniques and Applications. The author has an h-index of 132, co-authored 1311 publications.
ORCID: 0000-0002-5683-5889Papers by this author
worksTract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
2006 · NeuroImage · 6,534 citations
https://doi.org/10.1016/j.neuroimage.2006.02.024
Nonrigid registration using free-form deformations: application to breast MR images
1999 · IEEE Transactions on Medical Imaging · 5,226 citations
https://doi.org/10.1109/42.796284
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
2016 · Medical Image Analysis · 3,400 citations
https://doi.org/10.1016/j.media.2016.10.004
Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research
2017 · The Lancet Neurology · 2,449 citations
https://doi.org/10.1016/s1474-4422(17)30371-x
Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy
2009 · NeuroImage · 876 citations
https://doi.org/10.1016/j.neuroimage.2009.02.018
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