Bilde av Salomonsen, Christian
Bilde av Salomonsen, Christian
PhD Candidate / Machine Learning Department of Physics and Technology christian.salomonsen@uit.no Tromsø

Christian Salomonsen


Job description

Hi, I'm a PhD Candidate at the University of Tromsø in Norway, working in the Machine Learning Group and SFI Visual Intelligence. My research interest deal with the use of deep learning methods for complex spatial and temporal datasets, such as dynamic Positron Emission Tomography (PET) data.

Recently, I have been involved in methods for predicting the arterial input function (AIF) directly from the PET images with the use of an efficient in-house developed deep learning model, and extending this idea to incorporate physical (anatomical) information about the tracer kinetics during the learning phase of the model.

Reach me here!


  • Christian Salomonsen :
    Når datamaskiner lærer selv
    22. January 2026 ARKIV
  • Christian Salomonsen, Samuel Kuttner, Michael Kampffmeyer, Robert Jenssen, Kristoffer Wickstrøm, Jong Chul Ye et al.:
    Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN
    07. December 2025 ARKIV
  • Christian Salomonsen, Samuel Kuttner, Michael Kampffmeyer, Robert Jenssen, Kristoffer Wickstrøm, Jong Chul Ye et al.:
    Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN
    Medical imaging meets Eurips (MedEurIPS) 07. December 2025 DOI / ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Samuel Kuttner, Elisabeth Wetzer :
    Physics-Informed Deep Learning for Improved Input Function Estimation in Motion-Blurred Dynamic [18F]FDG PET Images
    16. October 2025 ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Samuel Kuttner, Elisabeth Wetzer :
    Physics-informed deep learning for improved input function estimation in motion-blurred dynamic [18F]FDG PET images
    24. September 2025 ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Samuel Kuttner, Elisabeth Wetzer :
    Physics-Informed Deep Learning for Improved Input Function Estimation in Motion-Blurred Dynamic [18F]FDG PET Images
    27. September 2025 ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Elisabeth Wetzer, Samuel Kuttner :
    Physics-Informed Machine Learning for dynamic PET modeling
    2025 ARKIV
  • Christian Salomonsen :
    KI i hvit frakk: Hvordan kunstig intelligens brukes i medisin
    2025 ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Elisabeth Wetzer, Samuel Kuttner :
    Physics-informed deep learning for improved input function estimation in motion-blurred dynamic [18F]FDG PET images
    2025 ARKIV
  • Christian Salomonsen, Samuel Kuttner, Elin Kile :
    Kunstig intelligens: Hvordan kan datamaskiner se?
    2024 ARKIV
  • Christian Salomonsen, Kristoffer Knutsen Wickstrøm, Elisabeth Wetzer, Samuel Kuttner :
    Kinetic modeling based compound loss for deep learning derived input function prediction in dynamic [18F]FDG PET images of mice
    2024 ARKIV
  • Christian Salomonsen, Kristoffer Knutsen Wickstrøm, Elisabeth Wetzer, Samuel Kuttner :
    Kinetic modeling based compound loss for deep learning derived input function prediction in dynamic [18F]FDG PET images of mice
    2024 ARKIV
  • Christian Salomonsen, Kristoffer Knutsen Wickstrøm, Elisabeth Wetzer, Samuel Kuttner :
    Kinetic modeling based compound loss for deep learning derived input function prediction in dynamic [18F]FDG PET images of mice
    2024 ARKIV

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    Research interests

    • Machine learning
    • Deep learning
    • Computer vision
    • Physics-informed machine learning
    • Generative models

    Member of research group