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

Authors

723

  1. UJ
    U. Joseph Schoepf

    Medical University of South Carolina, United States

    4 publications · 246 citations

    4

    h-index

  2. CS
    Chang Sheng Zhou

    Nanjing General Hospital of Nanjing Military Command, China

    3 publications · 138 citations

    3

    h-index

  3. SO
    Seitaro Oda

    Kumamoto University, Japan

    3 publications · 72 citations

    3

    h-index

  4. DU
    Daisuke Utsunomiya

    Kumamoto University, Japan

    3 publications · 72 citations

    3

    h-index

  5. YY
    Yasuyuki Yamashita

    Kumamoto University, Japan

    3 publications · 72 citations

    3

    h-index

1–5 of 723

Venues

  1. European Journal of Radiology

    EJR · 16 publications · 495 citations

    13

    h-index

  2. European Radiology

    10 publications · 431 citations

    10

    h-index

  3. Clinical Radiology

    5 publications · 144 citations

    5

    h-index

  4. Journal of cardiovascular computed tomography

    5 publications · 151 citations

    5

    h-index

  5. Optics Express

    5 publications · 498 citations

    5

    h-index

1–5