Iterative Image Reconstruction

Iterative Image Reconstruction is a computational image formation method in computed tomography that, unlike analytical techniques, progressively refines the reconstructed image through successive approximations by minimizing a cost function that models the imaging physics and noise statistics.

2.1K

Publications

107.5K

Citations

7.3K

Authors

1.8K

Institutions

Publications per year

2017–2026

592

Authors

7.3K

  1. UJ
    U. Joseph Schoepf

    Medical University of South Carolina, United States

    29 publications · 2.6K citations

    24

    h-index

  2. CH
    Cynthia H. McCollough

    Mayo Clinic, United States

    24 publications · 2.2K citations

    20

    h-index

  3. JA
    Jeffrey A. Fessler

    University of Michigan, United States

    35 publications · 1.5K citations

    19

    h-index

  4. HA
    Hatem Alkadhi

    University Hospital of Zurich, Switzerland

    21 publications · 1.6K citations

    19

    h-index

  5. BS
    Bernhard Schmidt

    Siemens Healthineers (Germany), Germany

    20 publications · 2.4K citations

    18

    h-index

1–5 of 7.3K

Venues

  1. IEEE Transactions on Medical Imaging

    107 publications · 14.3K citations

    54

    h-index

  2. Physics in Medicine and Biology

    130 publications · 7.7K citations

    49

    h-index

  3. Medical Physics

    125 publications · 6.2K citations

    42

    h-index

  4. Radiology

    42 publications · 5.5K citations

    35

    h-index

  5. European Radiology

    74 publications · 4.4K citations

    34

    h-index

1–5