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Amirreza Mahbod

Profile picture of Amirreza Mahbod

About me

I am a research scientist with expertise in medical image analysis, machine learning, and computer vision.

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  Department of Biomedical Engineering and Health Systems 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, No. 675228) 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.  Currently,  I am involved in our recently FFG funded project (No. 872636) called "Deep learning-based knowledge transfer methods for nuclei segmentation in microscopic images" as a post-doctoral fellow at the Medical University of Vienna.

Research Interests: 

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

Curriculum Vitae: 

Journal Papers: 

  • Verma R, …, Mahbod A, …, Sethi A, MoNuSAC2020: A Multi-organ Nuclei Segmentation and Classification Challenge, IEEE Transactions on Medical Imaging, June 2021 (Paper Link)
  • Mahbod A, Schaefer G, Low C, Dorffner G, Ecker R, Ellinger I, Investigating the Impact of the Bit Depth of Fluorescence-Stained Images on the Performance of Deep Learning-Based Nuclei Instance Segmentation, Diagnostics, May 2021 (Paper Link)
  • Mahbod A, Schaefer G, Bancher B, Löw C, Dorffner G,  Ecker R, Ellinger I, CryoNuSeg: A Dataset for Nuclei Instance Segmentation of Cryosectioned H&E-Stained Histological Images,  Computers in Biology and Medicine, March 2021 (Paper Link)
  • Mahbod A, Tschandl P, Langs G, Ecker R, Ellinger I, The Effects of Skin Lesion Segmentation on the Performance of Dermatoscopic Image Classification, Computer Methods and Program in Biomedicine. August 2020 (Paper Link) 
  • Mahbod A, Schaefer G, Wang C, Ecker R, Dorffner G, Ellinger I. Transfer Learning Using a Multi-Scale and Multi-Network Ensemble for Skin Lesion Classification, Computer Methods and Program in Biomedicine Journal. March 2020  (Paper Link) (Preprint Link)
  • Kumar N, …, Mahbod A, …, Sethi A, A Multi-Organ Nucleus Segmentation Challenge, IEEE Transition on Medical Imaging. October 2019 (Paper Link)
  • Mahbod A, Schaefer G, Ellinger I, Ecker R, Pitiot A, Wang C. Fusing Fine-tuned Deep Features for Skin Lesion Classification. Computerized Medical Imaging and Graphics. January 2019. (Paper Link) (Preprint Link)
  • Commowick O, ..., Mahbod A, …, Barillot C. Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure. Nature Scientific Reports. September 2018. (Paper Link) (Preprint Link)
  • Mahbod A, Chowdhury M, Smedby Ö, Wang C. Automatic brain segmentation using artificial neural networks with shape context. Pattern Recognition Letters. January 2018 (Paper Link) (Preprint link) 

Peer-reviewed Conference Papers:

  • Bancher B, Mahbod A, Ellinger I, Ecker R, Dorffner G, Improving Mask R-CNN for Nuclei Instance Segmentation in Hematoxylin & Eosin-Stained Histological Images, accepted to the MICCAI COMPAY Workshop, August 2021 (Paper Link)
  • Mahbod A, Schaefer G, Wang C, Ecker R, Dorffner G and Ellinger I, Investigating and Exploiting Image Resolution for Transfer Learning-based Skin Lesion Classification, 25th IEEE International Conference on Pattern Recognition (ICPR), March 2021  (Paper Link) (Preprint Link)
  • Mahbod A, Schaefer G, Ecker R, Ellinger I, Pollen Grain Microscopic Image Classification Using an Ensemble of Fine-Tuned Deep Convolutional Neural Networks, Artificial Intelligence for Healthcare Applications workshop at the 25th International Conference on Pattern Recognition (ICPR), February 2021 (Paper Link) (Preprint Link)
  • Mahbod A, Schaefer G, Wang C, Ecker R, and Ellinger I. Skin Lesion Classification Using Hybrid Deep Neural Networks, 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2019 (Paper Link) (Preprint Link) (Poster Link)
  • Mahbod A, G Schaefer, Ellinger I, Ecker R, Smedby Ö, Wang C. A Two-Stage U-Net Algorithm for Segmentation of Nuclei in H&E-Stained Tissues. 15th European Congress on Digital Pathology (ECDP), January 2019 (Paper Link) (Preprint Link) (Poster Link)
  • Mahbod A, Ellinger I, Ecker R, Smedby Ö, Wang C. Breast Cancer Histological Image Classification Using Fine-Tuned Deep Network Fusion. 15th International Conference Image Analysis and Recognition (ICIAR), June 2018 (Paper Link) (Preprint Link)
  • Mahbod A, Wang C, Smedby Ö. Automatic Multiple Sclerosis Lesion Segmentation Using Hybrid Artificial Neural Networks. MSSEG Challenge Proceedings at 19th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). October 2016 (Paper Link)  (Poster Link)

Preprint & Poster: 

  • Mahbod A, Ecker R, Ellinger I,  Automatic Foot Ulcer segmentation Using an Ensemble of Convolutional Neural Networks, arXiv preprint, September 2021 (Preprint Link)
  • Mahbod A, Olesen M, Hannan F, Gelles K, Ecker R, Ellinger I. Deep Convolutional Neural Networks for Parathyroid Gland Classification in HE-Stained Microscopic Images, In Poster Presentation at the 13th YSA PhD symposium at Medical University of Vienna, 2017 June

Thesis: 

  • PhD thesis (Medical University of Vienna): Towards Improvement of Automated Segmentation and Classification of Tissues and Nuclei in Microscopic Images Using Deep Learning Approaches, 2020 Jan (Link)
  • Master thesis (KTH): Structural Brain MRI Segmentation Using Machine  Learning Technique, 2016 June (Link)

Scientific Reviewer (selected journals/conferences ): 

  • MICCAI 2020 and 2021 Conference 
  • ISIC Skin Image Analysis Workshop at CVPR 2020 and 2021
  • MIDL 2021 Conference 
  • Medical Image Analysis
  • IEEE Transaction in Medical Imaging
  • IEEE Journal of Biomedical and Health Informatics
  • Expert Systems with Applications
  • Computer Methods and Programs in Biomedicine
  • Artificial Intelligence Review
  • Artificial Intelligence in Medicine
  • IEEE Access
  • Diagnostics 
  • Sensors
  • Cancer Biomarkers
  • Annals of Biomedical Engineering
  • Computers & Electrical Engineering
  • IET Image Processing 
  • Biocybernetics and Biomedical Engineering 
  • Computer Assisted Surgery 
  • International Journal of Imaging Systems and Technology
  • Iranian Journal of Electrical and Computer Engineering

Certificates (courses):

Certificates (others):