Reconstruction Kernel Selection
Reconstruction Kernel Selection is the systematic process of choosing a specific reconstruction kernel—a mathematical filter used in tomographic image reconstruction—to optimize the trade-off between image resolution, noise, and artifacts in computed tomography.
32
Publications
1.4K
Citations
141
Authors
73
Institutions
Publications per year
2017–2026
9
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141
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73

Tufts Medical Center
Boston, United States
2 h-index
7 publications
119 citations

Niigata University
Niigata, Japan
2 h-index
5 publications
221 citations
Applied Sciences Laboratory (United States)
Baldwin Park, United States
2 h-index
4 publications
112 citations
University of Wisconsin–Madison
Madison, United States
2 h-index
2 publications
54 citations
University Hospital of Zurich
Zurich, Switzerland
2 h-index
15 publications
446 citations
Tufts University
Medford, United States
2 h-index
7 publications
119 citations
Yonsei University
Seoul, South Korea
1 h-index
3 publications
45 citations
University of Zurich
Zurich, Switzerland
1 h-index
8 publications
320 citations
1–8 of 73
MRM · 4 publications · 116 citations
4
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3 publications · 94 citations
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1 publications · 61 citations
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CMIG · 1 publications · 13 citations
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JACMP · 1 publications · 46 citations
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