Regularized Reconstruction

Regularized Reconstruction is a reconstruction method that incorporates additional constraints or penalties into the inversion process to stabilize solutions and mitigate ill-posedness in image reconstruction problems.

961

Publications

64.2K

Citations

2.4K

Authors

910

Institutions

Publications per year

2017–2026

260

Authors

2.4K

  1. JA
    Jeffrey A. Fessler

    University of Michigan, United States

    23 publications · 1.3K citations

    17

    h-index

  2. MU
    Michaël Unser

    École Polytechnique Fédérale de Lausanne, Switzerland

    15 publications · 587 citations

    13

    h-index

  3. AK
    Aggelos K. Katsaggelos

    Northwestern University, United States

    9 publications · 841 citations

    9

    h-index

  4. MN
    Mila Nikolova

    Centre National de la Recherche Scientifique, France

    8 publications · 751 citations

    8

    h-index

  5. TH
    Ting‐Zhu Huang

    University of Electronic Science and Technology of China, China

    7 publications · 317 citations

    7

    h-index

1–5 of 2.4K

Venues

  1. IEEE Transactions on Medical Imaging

    34 publications · 2.7K citations

    29

    h-index

  2. Inverse Problems

    50 publications · 2.3K citations

    28

    h-index

  3. IEEE Transactions on Image Processing

    37 publications · 6.4K citations

    27

    h-index

  4. Magnetic Resonance in Medicine

    MRM · 21 publications · 2.3K citations

    16

    h-index

  5. Journal of Mathematical Imaging and Vision

    14 publications · 776 citations

    14

    h-index

1–5