Multi-modal Image Reconstruction
Multi-Modal Image Reconstruction is a computational methodology in hybrid imaging instrumentation that integrates and jointly processes complementary data from multiple imaging modalities to produce a single, enhanced image representation with improved accuracy, resolution, or diagnostic value compared to reconstructions from individual modalities alone.
55
Publications
2.2K
Citations
297
Authors
177
Institutions
Publications per year
2017–2026
37
55
Deep-Learning-Based Multi-Modal Fusion for Fast MR Reconstruction
Lei Xiang, Yong Chen, Wei‐Tang Chang et al. · IEEE Transactions on Biomedical Engineering · 2018 · 162 citations · Full text
Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer
Florian Knöll, Martin Höller, Thomas Koesters et al. · IEEE Transactions on Medical Imaging · 2016 · 130 citations · Full text
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Massachusetts Institute of Technology, United States
2 publications · 54 citations
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2
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1–5 of 297
177
Athinoula A. Martinos Center for Biomedical Imaging
Boston, United States
4 h-index
13 publications
779 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
6 publications
653 citations

Shanghai Jiao Tong University
Shanghai, China
4 h-index
9 publications
669 citations
Harvard University
Cambridge, United States
3 h-index
8 publications
669 citations
United Imaging Healthcare (China)
Shanghai, China
3 h-index
5 publications
165 citations
Heidelberg University
Heidelberg, Germany
3 h-index
6 publications
132 citations
University College London
London, United Kingdom
2 h-index
4 publications
114 citations
KU Leuven
Leuven, Belgium
2 h-index
4 publications
90 citations
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3 publications · 50 citations
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3 publications · 260 citations
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2 publications · 36 citations
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2 publications · 57 citations
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Repository · 2 publications · 29 citations
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