Skip to main content English


Amirreza Mahbod
Ass.-Prof Amirreza Mahbod, PhDAssistant Professor at Danube Private Univeristy

Center for Pathophysiology, Infectiology and Immunology (Institute of Pathophysiology and Allergy Research)
Position: Lecturer

ORCID: 0000-0001-5042-1442

Further Information


Artificial Intelligence; Pattern Recognition, Automated

Research interests

I got my bachelor's (2004-2009) and first master's degree (2009-2012) in Electrical Engineering from the School of Electrical Engineering at the Iran University of Science and Technology, Tehran, Iran, and my second master's degree in Medical Engineering from the Division of Biomedical Imaging at the KTH Royal Institute of Technology, Stockholm, Sweden (2014-2016). I did my PhD (2016-2020), entitled "Towards Improvement of Automated Segmentation and Classification of Tissues and Nuclei in Microscopic Images Using Deep Learning Approaches", within a Marie Skłodowska-Curie European training network called CaSR Biomedicine (Horizon 2020 Framework) as an industrial PhD fellow at the Institute of Pathophysiology and Allergy Research at the Medical University of Vienna and at the Department of Research and Development at TissueGnostics GmbH.

Through a successful FFG grant application, I did a postdoc (2020-2022) within a collaborative project between the Medical Univerity of Vienna and TissueGnostics (project title: Deep learning-based knowledge transfer methods for nuclei segmentation in microscopic images)

Currently, I am employed as an Assistant Professor at MIAAI reseach group at Danube Private University (DPU) and a part-time lecturer at the Medical University of Vienna.

Techniques, methods & infrastructure

Techniques and Methods:

  • Deep Convolutional Neural Networks
  • Classical Machine Learning Methods (ANN, SVM, MLP, ...)
  • Medical Image Analysis (Segmentation, Classification, Normalization, ...)
  • Medical Imaging (Histopathology, Microscopy, MRI, CT, ...)
  • Developing (Python, Keras, Tensorflow, PyTorch, Matlab)



  • LymphoidStructureMiner: AI-based exploration of the immunological contexture of lymphoid structures in translational research (2024)
    Source of Funding: WWTF (Vienna Science and Technology Fund), AI-based medical image analysis
    Principal Investigator

Selected publications

  1. Mahbod, A. et al. (2024) ‘NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images’, Scientific Data, 11(1). Available at:
  2. Mahbod, A. et al. (2024) ‘Improving generalization capability of deep learning-based nuclei instance segmentation by non-deterministic train time and deterministic test time stain normalization’, Computational and Structural Biotechnology Journal, 23, pp. 669–678. Available at:
  3. Mahbod, A. et al. (2022) ‘A dual decoder U-Net-based model for nuclei instance segmentation in hematoxylin and eosin-stained histological images’, Frontiers in Medicine, 9. Available at:
  4. Mahbod, A. et al. (2021) ‘CryoNuSeg: A dataset for nuclei instance segmentation of cryosectioned H&E-stained histological images’, Computers in Biology and Medicine, 132, p. 104349. Available at:
  5. Mahbod, A. et al. (2020) ‘Transfer learning using a multi-scale and multi-network ensemble for skin lesion classification’, Computer Methods and Programs in Biomedicine, 193, p. 105475. Available at: