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

Authors

141

  1. SW
    Shinichi Wada

    National Cerebral and Cardiovascular Center, Japan

    2 publications · 89 citations

    2

    h-index

  2. TF
    Thomas Flohr

    Siemens Healthineers (Germany), Germany

    2 publications · 113 citations

    2

    h-index

  3. AM
    Adel M. Malek

    Tufts Medical Center, United States

    2 publications · 34 citations

    2

    h-index

  4. AK
    Akihiro Kayugawa

    Niigata University, Japan

    2 publications · 89 citations

    2

    h-index

  5. AL
    Alexandra Lauric

    Tufts Medical Center, United States

    2 publications · 34 citations

    2

    h-index

1–5 of 141

Venues

  1. Magnetic Resonance in Medicine

    MRM · 4 publications · 116 citations

    4

    h-index

  2. Medical Physics

    3 publications · 94 citations

    3

    h-index

  3. Inverse Problems

    1 publications · 61 citations

    1

    h-index

  4. Computerized Medical Imaging and Graphics

    CMIG · 1 publications · 13 citations

    1

    h-index

  5. Journal of Applied Clinical Medical Physics

    JACMP · 1 publications · 46 citations

    1

    h-index

1–5