ShadiAlbarqouni

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Shadi Albarqouni

Shadi Albarqouni

  • Postdoctoral Research Associate

  • Email: shadi.albarqouni [@] tum.de

  • Address:

Chair for Computer Aided Medical Procedures & Augmented Reality
Fakultät für Informatik
Technische Universität München
Boltzmannstr. 3
85748 Garching b. München

Hot Stuff

  • new.gif Our recent paper on X-ray In-Depth Decomposition: Revealing the latent structures got accepted at MICCAI 2017, Quebec, Canada.
  • new.gif Our recent paper on Semi-Supervised Learning for Fully Convolutional Networks got accepted at MICCAI 2017, Quebec, Canada.
  • Our IEEE-TMI paper, AggNet, is one of the top 50 popular papers at IEEEXplore (worldwide) sine May 2016!
  • List of Papers on Deep Learning for Medical Applications
  • Our recent X-ray PoseNet paper got accepted at IEEE WACV conference in Santa Rosa, CA, USA.

Short Curriculum Vitae

2017/ Postdoctoral Research Associate, CAMP - Technische Universität München (TUM), Munich, Germany
2013/16 Visiting Scholar, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
2010/12 Lecturer in Electrical and Computer Engineering Departments, The Islamic University of Gaza, Palestine
2007/12 Lecturer in Information Technology Department, University College of Applied Science, Palestine
2005/07 Teaching Assistant in Electrical Engineering Department, The Islamic University of Gaza, Palestine

Background

2013/16* Ph.D. Informatics,Chair for Computer Aided Medical Procedures (CAMP), Technical University Munich, Germany
under the supervision of Prof. Dr. Nassir Navab
2005/07 M.Sc. Electrical Engineering, The 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
2001/05 B.Sc. Electrical Engineering, The Islamic University of Gaza, Palestine
Finished within 4 years instead of the regular period of 5 years.

Scholarship & Awards

  • 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.

Professional Activities

Reviewer

Organizer

Member

Student Projects

Feel free to contact me to any of the following projects. open: drop by and ask!.

Available
IDPX-ray In-Depth Decomposition
(Shadi Albarqouni, Prof. Dr. Nassir Navab)
DA/MA/BAMedical Image Synthesis using Generative Adversarial Networks (GANs)
(Shadi Albarqouni, Prof. Dr. Nassir Navab)

Running
Master ThesisWeakly-Supervised Anomaly Detection assisted by Attention Models
(Shadi Albarqouni, Diana Mateus, Prof. Nassir Navab)
Bachelor ThesisMeta-Learning of Regularization Parameters in X-ray Computed Tomography
(Shadi Albarqouni, Tobias Lasser)
Master ThesisMultimodal Deep Learning
(Shadi Albarqouni, Prof. Dr. Nassir Navab)
Master ThesisSiemens AG: Detection of Complex Stents in Live Fluoroscopic Images for Endovascular Aneurysm Repair
(Shadi Albarqouni, Stefanie Demirci, Prof. Dr. Nassir Navab)

Finished
Master ThesisSiemens AG: X-ray PoseNet - Recovering the Poses of Portable X-Ray Device with Deep Learning
(Shadi Albarqouni, Slobodan Ilic, Prof. Nassir Navab)
Master ThesisA Deep Learning Approach to Synthesize Virtual CT based on Transmission Scan in hybrid PET/MR
(Sailesh Conjeti, Kuangyu Shi, Shadi Albarqouni, Prof. Dr. Nassir Navab)
ProjectCreating Diagnostic Model for Assessing the Success of Treatment for Eye Melanoma
(Shadi Albarqouni, Prof. Nassir Navab)
Master ThesisRohde & Schwarz: Deep feature representation with auxiliary embedding
(Shadi Albarqouni, Athanasios Karamalis, Prof. Nassir Navab)
Bachelor ThesisComparative Study on CNN Initialization
(Shadi Albarqouni, Prof. Nassir Navab)
IDPCancer Matestasis detection in Lymph nodes
(Shadi Albarqouni, Stefanie Demirci, Prof. Nassir Navab)
ProjectDepth Estimation for Catheters from Single-View Interventional X-ray Imaging
(Shadi Albarqouni, Stefanie Demirci, Pascal Fallavollita, Prof. Nassir Navab)
Bachelor ThesisGamification in the Medical Context
(Shadi Albarqouni,Stefanie Demirci, Maximilian Baust, Prof. Nassir Navab)
IDPCrowdsourcing in the Medical Context
(Shadi Albarqouni,Stefanie Demirci, Prof. Nassir Navab)
Master ThesisDepth Recovery from Single-View Interventional X-ray Imaging
(Shadi Albarqouni, Stefanie Demirci, Lichao Wang, Prof. Nassir Navab)

Teaching

List of Publications

2017
S. Albarqouni, J. Fotouhi, N. Navab
X-ray In-Depth Decomposition: Revealing The Latent Structures
Proceedings of the 20th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Quebec, Canada, September 2017 (bib)
M. Bui, S. Albarqouni, M. Schrapp, N. Navab, S. Ilic
X-ray PoseNet: 6 DoF Pose Estimation for Mobile X-ray Devices
Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), Mar 24, 2017 - Mar 31, 2017, Santa Rosa, USA (bib)
C. Baur, S. Albarqouni, N. Navab
Auxiliary Manifold Embedding for Fully Convolutional Networks
Proceedings of the 20th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Quebec, Canada, September 2017 (bib)
2016
S. Albarqouni, S. Matl, M. Baust, N. Navab, S. Demirci
Playsourcing: A Novel Concept for Knowledge Creation in Biomedical Research
Proceedings of MICCAI Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, Athens, Greece, October 2016 (bib)
C. Baur, S. Albarqouni, S. Demirci, N. Navab, P. Fallavollita
CathNets: Detection and Single-View Depth Prediction of Catheter Electrodes
7th International Conference on Medical Imaging and Augmented Reality (MIAR), 24-26 August, 2016, Bern, Switzerland. (Best Paper Award) (bib)
S. Albarqouni, U. Konrad, L. Wang, N. Navab, S. Demirci
Single-View X-Ray Depth Recovery: Towards a Novel Concept for Image-Guided Interventions
International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2016, June 2016, Volume 11, Issue 6, pp 873-880. (bib)
S. Albarqouni, C. Baur, F. Achilles, V. Belagiannis, S. Demirci, N. Navab
AggNet: Deep Learning from Crowds for Mitosis Detection in Breast Cancer Histology Images
IEEE Transactions on Medical Imaging (TMI), Special Issue on Deep Learning, vol. 35, no. 5, pp. 1313 - 1321, 2016. (bib)
A. Vahadane, T. Peng, A. Sethi, S. Albarqouni, L. Wang, M. Baust, K. Steiger, A. M. Schlitter, I. Esposito, N. Navab
Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images
IEEE Transactions on Medical Imaging (TMI), vol. 35, no. 8, pp. 1962 - 1971, 2016. (bib)
2015
S. Albarqouni, M. Baust, S. Conjeti, A. Al-Amoudi, N. Navab
Multi-scale Graph-based Guided Filter for De-noising Cryo-Electron Tomographic Data
Proceedings of the British Machine Vision Conference (BMVC), pages 17.1-17.10. BMVA Press, September 2015 (bib)
A. Vahadane, T. Peng, S. Albarqouni, M. Baust, K. Steiger, A. M. Schlitter, A. Sethi, I. Esposito, N. Navab
Structure-Preserved Color Normalization for Histological Images
International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, New York, USA, April 2015 (bib)
2014
S. Albarqouni, T. Lasser, W. Alkhaldi, A. Al-Amoudi, N. Navab
Gradient Projection for Regularized Cryo-Electron Tomographic Reconstruction
Proceedings of MICCAI Workshop on Computational Methods for Molecular Imaging, Boston, USA, September 2014. (bib)

Internship Offers

Collaboration

  • Rohde & Schwarz GmbH? & Co. KG.
  • Siemens AG, Corporate Technology Research & Technology Center
  • Augenklinik der Universität München

Conferences, Seminars and Courses

2017

2016

2015

2014

2013

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UsersForm
Title: M.Sc.
Circumference of your head (in cm):  
Firstname: Shadi
Middlename:  
Lastname: Albarqouni
Picture: 0d6e8f1.jpg
Birthday: 07.08.1984
Nationality: Palestine
Languages: English, German, Arab
Groups: Reconstruction, Medical Imaging, Molecular Imaging, Machine Learning for Medical Applications, Microscopic Image Analysis, Crowdsourcing
Expertise: Medical Imaging
Position: Scientific Staff
Status: Active
Emailbefore: Shadi.Albarqouni
Emailafter: tum.de
Room: MI 03.13.056
Telephone: +49 89 289 19405
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