Portrait of Amir Reza Naderi Yaghouti

PhD Researcher · Biomedical AI & 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
3

About

I am 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. 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)

  2. 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)

  3. 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)

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

    Journal of Biomedical Physics and Engineering

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

    Scientific Reports 14, 2442

2021

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

    AR Naderi Yaghouti, A Shalbaf, A Maghsoudi

    Tehran University Medical Journal 79 (1), 10–17

Experience

  1. Doctoral Candidate (Marie Skłodowska-Curie, EGRET-AAA DC9)

    Otto-von-Guericke University Magdeburg · University Clinic for Ophthalmology

    Deep learning for detecting visual pathway anomalies in glaucoma and rare patient groups, supervised by Prof. Michael B. Hoffmann and Dr. Khaldoon O. Al-Nosairy.

  2. Doctoral Researcher (joint PhD)

    University of Groningen · University Medical Center Groningen

    Groningen side of the joint doctorate within EGRET-AAA, supervised by Prof. Nomdo M. Jansonius.

  3. Researcher, Machine Learning for Liver Disease

    In collaboration with Dr. Ahmad Shalbaf

    Built machine learning and CNN-based pipelines for grading nonalcoholic fatty liver disease from B-mode ultrasound and for early NASH detection from clinical and blood data, resulting in papers in Scientific Reports, the Journal of Biomedical Physics and Engineering, and the Tehran University Medical Journal.

Education

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

    Doctor of Philosophy (PhD), Visual Neuroscience

    Otto-von-Guericke University Magdeburg, Germany

    University of Groningen, the Netherlands

  2. Islamic Azad University logo

    Master of Science (MSc), Biomedical Engineering

    Islamic Azad University, Science and Research Branch, Tehran

  3. Islamic Azad University logo

    Bachelor's Degree (BSc), Biomedical Engineering

    Islamic Azad University, Science and Research Branch, Tehran

Skills

Languages & tools

  • Python
  • MATLAB
  • Git
  • Jupyter

Deep learning

  • PyTorch
  • TensorFlow
  • MONAI
  • scikit-learn

Imaging & vision

  • OpenCV
  • Fundus imaging
  • Ultrasound
  • Texture analysis

Methods

  • CNNs & transfer learning
  • Feature selection
  • Ensemble models
  • Explainable AI

Contact

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

naderi.bme@gmail.com