Retrospective Motion Correction
Retrospective Motion Correction is a computational method in neuroimaging that belongs to the class of motion correction techniques and is distinguished by its application of motion artifact reduction after data acquisition, typically through post-processing algorithms that realign or reconstruct corrupted image data based on estimated motion parameters.
186
Publications
13.2K
Citations
896
Authors
342
Institutions
Publications per year
2017–2026
73
Parents
186
1–5 of 186
896
Athinoula A. Martinos Center for Biomedical Imaging, United States
7 publications · 778 citations
7
h-index
6
h-index
Athinoula A. Martinos Center for Biomedical Imaging, United States
5 publications · 266 citations
5
h-index
5
h-index
5
h-index
1–5 of 896
342
Harvard University
Cambridge, United States
17 h-index
87 publications
6.5K citations
King's College London
London, United Kingdom
13 h-index
83 publications
9.3K citations
Siemens Healthineers (Germany)
Forchheim, Germany
12 h-index
23 publications
2.5K citations
Massachusetts General Hospital
Boston, United States
12 h-index
49 publications
5.2K citations
Athinoula A. Martinos Center for Biomedical Imaging
Boston, United States
12 h-index
48 publications
3.4K citations
Stanford University
Stanford, United States
11 h-index
40 publications
9.1K citations
University of California, Los Angeles
Los Angeles, United States
9 h-index
29 publications
1.5K citations
Friedrich-Alexander-Universität Erlangen-Nürnberg
Erlangen, Germany
8 h-index
24 publications
2.2K citations
1–8 of 342
MRM · 73 publications · 7.7K citations
39
h-index
15 publications · 909 citations
15
h-index
9 publications · 580 citations
9
h-index
7 publications · 197 citations
7
h-index
6 publications · 243 citations
6
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