Multi-modal Image Reconstruction

Multi-Modal Image Reconstruction is a computational methodology in hybrid imaging instrumentation that integrates and jointly processes complementary data from multiple imaging modalities to produce a single, enhanced image representation with improved accuracy, resolution, or diagnostic value compared to reconstructions from individual modalities alone.

55

Publications

2.2K

Citations

297

Authors

177

Institutions

Publications per year

2017–2026

37

Authors

297

  1. LX
    Lei Xiang

    University of North Carolina at Chapel Hill, United States

    2 publications · 205 citations

    2

    h-index

  2. JZ
    Jiangshe Zhang

    Xi'an Jiaotong University, China

    2 publications · 138 citations

    2

    h-index

  3. QW
    Qian Wang

    Shanghai Jiao Tong University, China

    2 publications · 205 citations

    2

    h-index

  4. KL
    Katherine L. Bouman

    Massachusetts Institute of Technology, United States

    2 publications · 54 citations

    2

    h-index

  5. ZZ
    Zixiang Zhao

    Xi'an Jiaotong University, China

    2 publications · 138 citations

    2

    h-index

1–5 of 297

Venues

  1. IEEE Access

    3 publications · 50 citations

    3

    h-index

  2. Physics in Medicine and Biology

    3 publications · 260 citations

    3

    h-index

  3. 2

    h-index

  4. 2

    h-index

  5. arXiv (Cornell University)

    Repository · 2 publications · 29 citations

    2

    h-index

1–5