About

I am a Postdoctoral Researcher at Odyssey Digital Pathology, where I develop deep learning segmentation models for multi-cancer lymph node screening. By training I am a physicist, holding Bachelor's and Master's degrees in Physics. Over the years I have built deep expertise in optical and X-ray microscopy, as well as image analysis using both conventional and deep learning approaches. My research has focused primarily on the pathology domain, where I have developed a working knowledge of cancer biology and histopathology along the way.

Selected projects
  1. 2026
    Journal article Tomography of Materials and Structures

    DeepDeblur3D: A 3D U-Net for denoising and deblurring micro-CT data

    Kiarash Tajbakhsh, Robert Zboray

    10.1016/j.tmater.2026.100088
  2. 2026
    Journal article Scientific Reports

    3D radiomics profiling of thyroid tumors using micro-CT

    Kiarash Tajbakhsh, Olga Stanowska, Marija Buljan, Antonia Neels, Aurel Perren, Robert Zboray

    10.1038/s41598-026-57746-1
  3. 2025
    Journal article Endocrine Pathology

    Follicular Thyroid Carcinoma Relapse Cases - Revisited by X-ray 3D Virtual Histology

    Kiarash Tajbakhsh, Olga Stanowska, Jonas Bossart, Marija Buljan, Antonia Neels, Martina T. Mogl, Catarina Alisa Kunze, Guenther Klein, Wolfgang Hulla, Rene Brillmann, Sabine Kirchnawy, Michael Hermann, Reto Kaderli, Robert Zboray, Aurel Perren

    10.1007/s12022-025-09891-y
  4. 2025
    Thesis PhD thesis, University of Fribourg

    3D characterization of thyroid tumors using micro-CT and machine learning

    Kiarash Tajbakhsh

    10.51363/unifr.sth.2026.067
  5. 2024
    Journal article IEEE Access

    A Comprehensive Study of Laboratory-Based Micro-CT for 3D Virtual Histology of Human FFPE Tissue Blocks

    Kiarash Tajbakhsh, Antonia Neels, Elena Fadeeva, Jakob C. Larsson, Olga Stanowska, Aurel Perren, Robert Zboray

    10.1109/ACCESS.2024.3407733