A. R. Naderi Yaghouti DE
Portrait of Amir Reza Naderi Yaghouti

Marie Skłodowska-Curie Fellow · PhD Researcher in Visual Neuroscience

Amir Reza Naderi Yaghouti

I develop deep learning and computer vision methods for medical imaging, currently focused on detecting visual pathway anomalies in glaucoma and rare patient groups.

Joint PhD · Otto-von-Guericke University Magdeburg, Germany & University of Groningen, the Netherlands

Publications
4
Citations
58
h-index
3
i10-index
2

About

I'm Amir Reza Naderi Yaghouti, or Amir Naderi for short, a Marie Skłodowska-Curie Doctoral Candidate in the EGRET-AAA network, pursuing a joint PhD in visual neuroscience at Otto-von-Guericke University Magdeburg and the University of Groningen. In Magdeburg I work at the University Clinic for Ophthalmology under the supervision of Prof. Michael B. Hoffmann and Dr. Khaldoon O. Al-Nosairy; in Groningen I work with Prof. Nomdo M. Jansonius.

My research uses deep learning and computer vision to build intelligent, data-driven diagnostic tools. Before glaucoma, I worked on machine learning for liver disease: grading nonalcoholic fatty liver disease from ultrasound images and detecting non-alcoholic steatohepatitis from clinical and blood parameters. I was born and raised in Tehran, where I earned my BSc and MSc in Biomedical Engineering.

Research interests

News

  1. Oral presentation at CLINICCAI 2026 (MICCAI 2026 Clinical Day) in Strasbourg, France: “Glaucoma Biomarkers Beyond the Optic Disc: Vascular Signal Quantified via Anatomical Masking of a Retinal Foundation Model”. Read more (opens in new tab)

  2. Poster presentation at EVER 2026, the European Association for Vision and Eye Research conference, in Florence, Italy.

  3. Poster presentation at ECVP 2025, the European Conference on Visual Perception, in Mainz, Germany.

  4. New review in Archives of Computational Methods in Engineering: artificial intelligence for ovarian cancer detection with medical images over the last decade (2013–2023). Read more (opens in new tab)

  5. New paper in the Journal of Biomedical Physics and Engineering: classifying nonalcoholic fatty liver grades with pre-trained CNNs and a random forest on B-mode ultrasound. Read more (opens in new tab)

  6. Started a joint PhD in Visual Neuroscience at Otto-von-Guericke University Magdeburg and the University of Groningen as a Marie Skłodowska-Curie Doctoral Candidate (EGRET-AAA, Project 9), working on deep learning for visual pathway anomalies in glaucoma. Read more (opens in new tab)

Show earlier news

  1. New paper in Scientific Reports: machine learning approaches for early detection of non-alcoholic steatohepatitis (NASH) from clinical and blood parameters. Read more (opens in new tab)

Publications

Full list on Google Scholar

Under review

  1. Discrimination of benign and malignant ovarian tumors from routine laboratory biomarkers using a tabular foundation model

    AR Naderi Yaghouti, A Shalbaf

    Sci. Rep.Scientific Reports

2025

  1. Classification of Nonalcoholic Fatty Liver Grades using Pre-Trained Convolutional Neural Networks and a Random Forest Classifier on B-Mode Ultrasound Images

    AR Naderi Yaghouti, A Shalbaf

    J. Biomed. Phys. Eng.Journal of Biomedical Physics and EngineeringCited by 5

    PaperScholar
    Cite
    @article{naderiyaghouti2025classification,
  title = {{Classification of Nonalcoholic Fatty Liver Grades using Pre-Trained Convolutional Neural Networks and a Random Forest Classifier on B-Mode Ultrasound Images}},
  author = {Naderi Yaghouti, A. R. and Shalbaf, A.},
  journal = {Journal of Biomedical Physics and Engineering},
  year = {2025}
}
  2. Artificial intelligence for ovarian cancer detection with medical images: a review of the last decade (2013–2023)

    AR Naderi Yaghouti, A Shalbaf, R Alizadehsani, RS Tan, A Vijayananthan, ...

    Arch. Comput. Methods Eng.Archives of Computational Methods in Engineering 32 (7), 4093-4124Cited by 13

    PaperScholar
    Cite
    @article{naderiyaghouti2025artificial,
  title = {{Artificial intelligence for ovarian cancer detection with medical images: a review of the last decade (2013–2023)}},
  author = {Naderi Yaghouti, A. R. and Shalbaf, A. and Alizadehsani, R. and Tan, R. S. and Vijayananthan, A. and others},
  journal = {Archives of Computational Methods in Engineering},
  volume = {32},
  number = {7},
  pages = {4093--4124},
  year = {2025}
}

2024

  1. Machine learning approaches for early detection of non-alcoholic steatohepatitis based on clinical and blood parameters

    AR Naderi Yaghouti, H Zamanian, A Shalbaf

    Sci. Rep.Scientific Reports 14, 2442Cited by 37

    PaperDOIScholar
    Cite
    @article{naderiyaghouti2024machine,
  title = {{Machine learning approaches for early detection of non-alcoholic steatohepatitis based on clinical and blood parameters}},
  author = {Naderi Yaghouti, A. R. and Zamanian, H. and Shalbaf, A.},
  journal = {Scientific Reports},
  volume = {14},
  pages = {2442},
  year = {2024},
  doi = {10.1038/s41598-024-51741-0}
}

2021

  1. Automatic classification of Non-alcoholic fatty liver using texture features from ultrasound images

    AR Naderi Yaghouti, A Shalbaf, A Maghsoudi

    Tehran Univ. Med. J.Tehran University Medical Journal 79 (1), 10–17Cited by 3

    PaperScholar
    Cite
    @article{naderiyaghouti2021automatic,
  title = {{Automatic classification of Non-alcoholic fatty liver using texture features from ultrasound images}},
  author = {Naderi Yaghouti, A. R. and Shalbaf, A. and Maghsoudi, A.},
  journal = {Tehran University Medical Journal},
  volume = {79},
  number = {1},
  pages = {10--17},
  year = {2021}
}

Research

My doctoral research is part of EGRET-AAA, a Marie Skłodowska-Curie Doctoral Network for advanced glaucoma research, and is shared between Magdeburg and Groningen.

PhD project · University Medical Center Groningen

Glaucomatous retinal changes beyond the optic disc, uncovered by deep learning on fundus images after targeted ablation of specific anatomical structures and regions

With Prof. Nomdo M. Jansonius

  • Fundus imaging
  • Deep learning
  • Explainable AI

PhD project · Otto-von-Guericke University Magdeburg

Deep learning segmentation of anatomical MRI quantifies optic chiasm degeneration in glaucoma

With Prof. Michael B. Hoffmann and Dr. Khaldoon O. Al-Nosairy

  • MRI
  • Segmentation
  • Visual pathway

Earlier research

  1. Tehran, Iran

    Machine learning for liver disease and ovarian cancer

    In collaboration with Dr. Ahmad Shalbaf, Shahid Beheshti University

    Deep learning and radiomics pipelines for grading fatty liver disease on ultrasound, early detection of non-alcoholic steatohepatitis from clinical and blood data, and a review of AI for ovarian cancer detection in medical images. Published in Scientific Reports, Archives of Computational Methods in Engineering, the Journal of Biomedical Physics and Engineering and the Tehran University Medical Journal.

Talks & posters

  1. 2026Oral

    CLINICCAI 2026, MICCAI 2026 Clinical Day · Strasbourg, FranceGlaucoma Biomarkers Beyond the Optic Disc: Vascular Signal Quantified via Anatomical Masking of a Retinal Foundation Model

  2. 2026Poster

    EVER 2026, European Association for Vision and Eye Research · Florence, Italy

  3. 2025Poster

    ECVP 2025, European Conference on Visual Perception · Mainz, Germany

Education

  1. Otto-von-Guericke University Magdeburg logoUniversity of Groningen logo

    Jun 2024 – 2027 (expected) · Joint doctorate

    Doctor of Philosophy (PhD), Visual Neuroscience

    Otto-von-Guericke University Magdeburg, Germany

    University of Groningen · University Medical Center Groningen, the Netherlands

    Marie Skłodowska-Curie Doctoral Fellow, EGRET-AAA

  2. Islamic Azad University logo

    Sep 2018 – Oct 2021

    Master of Science (MSc), Biomedical Engineering

    Islamic Azad University, Science and Research Branch, Tehran

    Thesis Transfer learning with deep convolutional neural networks for classification of liver steatosis: a comparison of radiomics and convolutional features

    GPA 18.43 / 20 (3.77 / 4.0)

  3. Islamic Azad University logo

    Sep 2014 – Jul 2018

    Bachelor of Science (BSc), Biomedical Engineering

    Islamic Azad University, Science and Research Branch, Tehran

    Thesis Automated breast lesion segmentation and classification in ultrasound imaging via texture analysis

    GPA 18.09 / 20 (final year)

Honors & awards

  1. 2024

    Marie Skłodowska-Curie Doctoral Fellowship, EGRET-AAA, EU Horizon Europe

  2. 2021

    Highest possible grade for the Master's thesis

  3. 2021

    Top student of the Master's program, with the highest grades in most courses

Skills & languages

Methods
Deep learning (CNNs, transfer learning, segmentation) · Medical image analysis (fundus, MRI, ultrasound) · Radiomics & texture analysis · Explainable AI · Machine learning on clinical data · Signal processing · Natural language processing
Programming
Python (PyTorch, TensorFlow, MONAI, scikit-learn, OpenCV) · MATLAB · R
Tools
LaTeX · Git · SPSS · Minitab · RapidMiner · Microsoft Office
Languages
Persian (native) · English (C1) · German (A1)

Contact

I'm happy to talk about research collaborations, medical imaging, and AI for ophthalmology.

amir.naderiyaghouti@med.ovgu.de naderi.bme@gmail.com Download CV (PDF)

Funded by the European Union. This project has received funding from the European Union's Horizon Europe research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101072435 (EGRET-AAA). Views and opinions expressed are those of the author only and do not necessarily reflect those of the European Union or the granting authority.