Iterative Reconstruction Optimization
Iterative Reconstruction Optimization is a computational methodology in signal and image processing that belongs to the class of reconstruction algorithms and is distinguished by its use of successive approximation cycles to refine solutions, thereby enhancing accuracy and convergence in underdetermined or noisy inverse problems.
136
Publications
5.6K
Citations
723
Authors
281
Institutions
Publications per year
2017–2026
46
Parents
136
Gordon Wetzstein, Douglas Lanman, Wolfgang Heidrich et al. · ACM Transactions on Graphics · 2011 · 162 citations
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Nanjing General Hospital of Nanjing Military Command, China
3 publications · 138 citations
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281
Heidelberg University
Heidelberg, Germany
6 h-index
34 publications
1.6K citations

University Hospital Heidelberg
Heidelberg, Germany
4 h-index
17 publications
498 citations
Medical University of South Carolina
Charleston, United States
4 h-index
19 publications
1.1K citations
Ludwig-Maximilians-Universität München
Munich, Germany
4 h-index
12 publications
491 citations
University of Lausanne
Lausanne, Switzerland
3 h-index
12 publications
641 citations
Inserm
Paris, France
3 h-index
9 publications
460 citations
Nanjing University
Nanjing, China
3 h-index
20 publications
1K citations
Nanjing General Hospital of Nanjing Military Command
Nanjing, China
3 h-index
19 publications
946 citations
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EJR · 16 publications · 495 citations
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10 publications · 431 citations
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5 publications · 144 citations
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5 publications · 151 citations
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5 publications · 498 citations
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