Prof. Dr. Shadi Albarqouni (د. شادي البرقوني)

W2-Professor of Computational Imaging Research at the University Hospital Bonn | AI Young Investigator Group Leader at Helmholtz Munich | Senior Research Affiliate at TU Munich 

Contact Details

An up to date personal webpage can be found here.

Curriculum Vitae

Experience

2022 - 
W2 Professor of Computational Imaging Research, University Hospital Bonn, University of Bonn, Bonn, Germany
2020 -
AI Young Investigator Group LeaderHelmholtz AI, Helmholtz Center Munich, Munich, Germany
2020- Senior Reserach AffiliateChair for Artificial Intelligence in Healthcare and Medicine, Technical University Munich, Munich, Germany
2020 Visiting ScientistDepartment of Computing, Imperial College London, London, United Kingdom
2019- 2020 Visiting ScientistCVL - ETH Zurich, Zurich, Switzerland
2017- 2020 Postdoctoral Research AssociateCAMP - Technische Universität München (TUM), Munich, Germany
2013-2016 Visiting ScholarGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
2011-2012 Lecturer in Electrical and Computer Engineering Departments, The Islamic University of Gaza, Palestine
2007-2012 Lecturer in Information Technology Department, University College of Applied Science, Palestine
2006-2007 Teaching Assistant in Electrical Engineering Department, The Islamic University of Gaza, Palestine


Education

2013-2017 Ph.D. Informatics,Chair for Computer Aided Medical Procedures (CAMP), Technical University Munich, Germany
under the supervision of Prof. Dr. Nassir Navab
2005-2010 M.Sc. Electrical EngineeringThe Islamic University of Gaza, Palestine
Thesis: Re-evaluation and re-design of stand alone PV solar lighting projects: Gaza Strip, Palestine
under the supervision of Prof. Dr. Mohammed T. Hussein
2001-2005 B.Sc. Electrical EngineeringThe Islamic University of Gaza, Palestine
Finished within 4 years instead of the regular period of 5 years.

 

Scholarship & Awards

  • DAAD PRIME Fellowship 
  • Reviewer Commendation at MICCAI 2018, Granada, Spain
  • Best Paper Award at MIAR Conference 2016, Bern, Switzerland
  • 3rd rank in MICCAI-AMIDA13 challenge for Automatic Models for Mitosis Detection in Breast Cancer Histology Images
  • Ph.D. Fellowship
  • Best Master Thesis Award in Faculty of Engineering, Jun. 2010, The Islamic University of Gaza, Palestine.
  • Arab Bank Scholarship, Sept. 2001-Sept. 2002, Gaza, Palestine.

Publications

2021

  • Bdair, T.; Navab, N.; Albarqouni, S.: FedPerl: Semi-Supervised Peer Learning for Skin Lesion Classification. arXiv preprint arXiv:2103.03703, 2021 more…

2020

  • Ali, S.; Zhou, F.; Braden, B.; Bailey, A.; Yang, S.; Cheng, G.; Zhang, P.; Li, X.; Kayser, M.; Soberanis-Mukul, R.D.; Albarqouni, S.; al., et: An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy. Scientific reports 10 (1), 2020, 1--15 more…
  • Ali, S.; Zhou, F.; Braden, B.; Bailey, A.; Yang, S.; Cheng, G.; Zhang, P.; Li, X.; Kayser, M.; Soberanis-Mukul, R.D.; Albarqouni, S.; al., et: An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy. Scientific reports 10 (1), 2020, 1--15 more…
  • Baur, C.; Graf, R.; Wiestler, B.; Albarqouni, S.; Navab, N.: SteGANomaly: Inhibiting CycleGAN Steganography for Unsupervised Anomaly Detection in Brain MRI. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020 more…
  • Baur, C.; Wiestler, B.; Albarqouni, S.; Navab, N.: Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI. arXiv preprint arXiv:2006.12852, 2020 more…
  • Bui, M.; Birdal, T.; Deng, H.; Albarqouni, S.; Guibas, L.; Ilic, S.; Navab, N.: 6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference. , 2020 more…
  • Sadafi, A.; Makhro, A.; Bogdanova, A.; Navab, N.; Peng, T.; Albarqouni, S.; Marr, C.: Attention based Multiple Instance Learning for Classification of Blood Cell Disorders. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020 more…
  • Soberanis-Mukul, R.D.; Navab, N.; Albarqouni, S.: An Uncertainty-Driven GCN Refinement Strategy for Organ Segmentation. Machine Learning for Biomedical Imaging (MELBA), 2020 more…
  • Soberanis-Mukul, R.D.; Navab, N.; Albarqouni, S.: Uncertainty-based graph convolutional networks for organ segmentation refinement. Medical Imaging with Deep Learning (MIDL), 2020 more…
  • Tran, A.; Weiss, J.; Albarqouni, S.; Faghihroohi, S.; Navab, N.: Retinal Layer Segmentation Reformulated as OCT Language Processing. Medical image Computing and Computer Assisted Interventions (MICCAI 2020), Springer Publishing, 2020 more…
  • Yeganeh, Y.; Farshad, A.; Navab, N.; Albarqouni, S.: Inverse Distance Aggregation for Federated Learning with Non-IID Data. arXiv preprint arXiv:2008.07665, 2020 more…
  • Yeganeh, Yousef; Farshad, Azade; Navab, Nassir; Albarqouni, Shadi: Inverse Distance Aggregation for Federated Learning with Non-IID Data. In: Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning. Springer International Publishing, 2020 more…
  • jimenez-sanchez; Kazi, A.; Albarqouni, S.; kirchhoff; Biberthaler, P.; Navab, N.; kirchhoff; Mateus, D.: Precise proximal femur fracture classification for interactive training and surgical planning. International journal of computer assisted radiology and surgery 15 (5), 2020, 847--857 more…

2019

  • Ayyad, A.; Navab, N.; Elhoseiny, M.; Albarqouni, S.: Semi-Supervised Few-Shot Learning with Local and Global Consistency. arXiv preprint arXiv:1903.02164, 2019 more…
  • Baur, C.; Albarqouni, S.; Navab, N.: Fusing Unsupervised and Supervised Deep Learning for White Matter Lesion Segmentation. International Conference on Medical Imaging with Deep Learning, 2019 more…
  • Bui, M.; Baur, C.; Navab, N.; Ilic, S.; Albarqouni, S.: Adversarial Networks for Camera Pose Regression and Refinement. , 2019 more…
  • Burwinkel, H.; Kazi, A.; Vivar, G.; Albarqouni, S.; Zahnd, G.; Navab, N.; Ahmadi, A.: Adaptive image-feature learning for disease classification using inductive graph networks. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019 more…
  • Hariharan, S.; Strobel, N.; Kaethner, C.; Kowarschik, M.; Albarqouni, S.; Fahrig, R.; Navab, N.: Learning-based X-ray Image Denoising utilizing Model-based Image Simulations. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019 more…
  • Jiménez-Sánchez, A.; Kazi, A.; Albarqouni, S.; Kirchhoff, C.; biberthaler; navab; Mateus, D.; Kirchhoff, C.: Towards an Interactive and Interpretable CAD System to Support Proximal Femur Fracture Classification. International journal of computer assisted radiology and surgery 15 (5), 2019, 847--857 more…
  • Kazi, A.; Krishna, S.; Shekarforoush, S.; Kortü m, K.; Albarqouni, S.; Navab, N.: Self-Attention Equipped Graph Convolutions for Disease Prediction (Oral). 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019 more…
  • Kazi, A.; Shekarforoush, S.; Krishna, S.; Burwinkel, H.; Vivar, G.; Kortü m, K.; Ahmadi, A.; Albarqouni, S.; Navab, N.: InceptionGCN : Receptive Field Aware Graph Convolutional Network for Disease Prediction (Oral). International Conference on Information Processing in Medical Imaging, 2019 more…
  • Kazi, A.; Shekarforoush, S.; Krishna, S.; Burwinkel, H.; Vivar, G.; Wiestler, B.; Kortü m, K.; Ahmadi, A.; Albarqouni, S.; Navab, N.: Graph convolution based attention model for personalized disease prediction. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019 more…
  • Khakzar, A.; Albarqouni, S.; Navab, N.: Learning Interpretable Features via Adversarially Robust Optimization. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019 more…
  • Lahiani, A.; Navab, N.; Albarqouni, S.; Klainman, E.: Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019 more…
  • Sarhan, M. H.; Albarqouni, S.; Navab, N.; Eslami, A.: Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019 more…
  • Shaban, M. T.; Baur, C.; Navab, N.; Albarqouni, S.: StainGAN: Stain Style Transfer for Digital Histological Images. arXiv e-prints, 2019, arXiv--1804 more…

2018

  • Baur, C.; Albarqouni, S.; Navab, N.: MelanoGANs: High Resolution Skin Lesion Synthesis with GANs. arXiv preprint arXiv:1804.04338, 2018 more…
  • Baur, C.; Albarqouni, S.; Navab, N.: Generating Highly Realistic Images of Skin Lesions with GANs. International MICCAI Skin Image Analysis Workshop, 2018 more…
  • Baur, C.; Wiestler, B.; Albarqouni, S.; Navab, N.: Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images. International MICCAI Brainlesion Workshop, 2018 more…
  • Breininger, K.; Albarqouni, S.; Kurzendorfer, T.; Pfister, M.; Kowarschik, M.; Maier, A.: Intraoperative Stent Segmentation in X-ray Fluoroscopy for Endovascular Aortic Repair. International journal of computer assisted radiology and surgery 13 (8), 2018, 1221--1231 more…
  • Bui, M.; Albarqouni, S.; Ilic, S.; Navab, N.: Scene Coordinate and Correspondence Learning for Image-Based Localization. , 2018 more…
  • Bui, M.; Zakharov, S.; Albarqouni, S.; Ilic, S.; Navab, N.: When Regression meets Manifold Learning for Object Recognition and Pose Estimation. , 2018 more…
  • Degel, M.; Navab, N.; Albarqouni, S.: Domain and Geometry Agnostic CNNs for Left Atrium Segmentation in 3D Ultrasound. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2018 more…
  • Hariharan, S.; Strobel, N.; Kaethner, C.; Kowarschik, M.; Demirci, S.; Albarqouni, S.; Fahrig, R.; Navab, N.: A photon recycling approach to denoising of ultra-low dose X-ray sequences. International journal of computer assisted radiology and surgery 13 (6), 2018, 847--854 more…
  • Kazi, A.; Jiménez-Sánchez, A.; Albarqouni, S.; Kirchhoff, C.; sträter; Biberthaler, P.; Mateus, D.; Navab, N.: Weakly-Supervised Localization and Classificationof Proximal Femur Fractures. arXiv preprint arXiv:1809.10692, 2018 more…
  • Molina-Romero, M.; Gómez, PA.; Albarqouni, S.; Sperl, JI.; Menzel, MI.; Menze, B.: Deep learning with synthetic data for free water elimination in diffusion MRI. Proc Intl Soc Mag Reson Med, 2018 more…
  • Sanchez, A.; Albarqouni, S.; Mateus, D.: Capsule Networks against Medical Imaging Data Challenges. In: Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis. Springer, 2018, 150--160 more…
  • Stoyanov, D.; Taylor, R.; Balocco, S.; Sznitman, R.; Martel, A.; Maier-Hein, L.; Duong, L.; Zahnd, G.; Demirci, S.; Albarqouni, S.; Lee, J.; Moriconi, S.; Cheplygina, V.; Mateus, D.; Trucco, E.; Granger, E.; Jannin, P.: Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis. , 2018 more…

2017

  • Albarqouni, S.; Fotouhi, J.; Navab, N.: X-ray In-Depth Decomposition: Revealing The Latent Structures. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2017 more…
  • Baur, C.; Albarqouni, S.; Navab, N.: Semi-Supervised Learning for Fully Convolutional Networks. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2017 more…
  • Bui, M.; Albarqouni, S.; Schrapp, M.; Navab, N.; Ilic, S.: X-ray PoseNet: 6 DoF Pose Estimation for Mobile X-ray Devices. 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), 2017 more…
  • Cardoso, J.; Arbel, T.; Lee, J.; Cheplygina, V.; Balocco, S.; Mateus, D.; Zahnd, G.; Maier-Hein, L.; Demirci, S.; Granger, E.; Duong, L.; Carbonneau, M. A.; Albarqouni, S.; Carneiro, G.: Intravascular imaging and computer assisted stenting, and large-scale annotation of biomedical data and expert label synthesis. , 2017 more…
  • Kazi, A.; Albarqouni, S.; Sanchez, A.; Kirchhoff, C.; Biberthaler, P.; Navab, N.; Mateus, D.: Automatic Classification of Proximal Femur Fractures based on Attention Models. International Workshop on Machine Learning in Medical Imaging, 2017 more…
  • Wiestler, B.; Baur, C.; Eichinger, P.; hwiestler; Zhang, T.; Biberacher, V.; Zimmer, C.; muehlau; Kirschke, J.; Albarqouni, S.: Fully Automated Multiple Sclerosis lesion detection on multi-channel subtraction images through an integrated Computer Vision- Machine Learning pipeline. Clinical Neuroradiology 27 (1), 2017, 1--118 more…

2016

  • Albarqouni, S.; Baur, C.; Achilles, F.; Belagiannis, V.; Demirci, S.; Navab, N.: AggNet: Deep Learning from Crowds for Mitosis Detection in Breast Cancer Histology Images. IEEE Transactions on Medical Imaging 35 (5), 2016, 1313--1321 more…
  • Albarqouni, S.; Konrad, U.; Wang, L.; Navab, N.; Demirci, S.: Single-View X-Ray Depth Recovery: Towards a Novel Concept for Image-Guided Interventions. International Journal of Computer Assisted Radiology and Surgery 11 (6), 2016, 873--880 more…
  • Albarqouni, S.; Matl, S.; Baust, M.; Navab, N.; Demirci, S.: Playsourcing: A Novel Concept for Knowledge Creation in Biomedical Research. In: Deep Learning and Data Labeling for Medical Applications. Springer Nature, 2016, 269--277 more…
  • Baur, C.; Albarqouni, S.; Demirci, S.; Navab, N.; Fallavollita, P.: CathNets: Detection and Single-View Depth Prediction of Catheter Electrodes. In: Zheng, Guoyan; Liao, Hongen; Jannin, Pierre; Cattin, Philippe; Lee, Su-Lin (Ed.): Medical Imaging and Augmented Reality: 7th International Conference, MIAR 2016, Bern, Switzerland, August 24-26, 2016, Proceedings. Springer International Publishing, 2016, 38--49 more…
  • Vahadane, A.; Peng, T.; Sethi, A.; Albarqouni, S.; Wang, L.; Baust, M.; Steiger, K.; Schlitter, A. M.; Esposito, I.; Navab, N.: Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images. IEEE Transactions on Medical Imaging, 2016 more…

2015

  • Albarqouni, S.; Baust, M.; Conjeti, S.; Al-Amoudi, A.; Navab, N.: Multi-scale Graph-based Guided Filter for De-noising Cryo-Electron Tomographic Data. Proceedings of the British Machine Vision Conference (BMVC), BMVA Press, 2015 more…
  • Vahadane, A.; Peng, T.; Albarqouni, S.; Baust, M.; Steiger, K.; Schlitter, A. M.; Sethi, A.; Esposito, I.; Navab, N.: Structure-Preserved Color Normalization for Histological Images. Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on, 2015 more…

2014

  • Albarqouni, S.; Lasser, T.; Alkhaldi, W.; Al-Amoudi, A.; Navab, N.: Gradient Projection for Regularized Cryo-Electron Tomographic Reconstruction. In: Gao, Fei; Shi, Kuangyu; Li, Shuo (Ed.): Computational Methods for Molecular Imaging. Springer International Publishing, 2014, 43--51 more…

Teaching

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