MagdaPaschali

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

Magda Paschali

Magda Paschali
PhD Student
Email: magda.paschali[@]tum.de

Chair for Computer Aided Medical Procedures & Augmented Reality
Fakultät für Informatik
Technische Universität München
Boltzmannstr. 3
85748 Garching b. München
Room: MI 03.13.039
Phone: +49 89 289 19441

Klinikum Rechts der Isar
Interdisziplinäres Forschungslabor
Ismaninger Str. 22
81675 München
Room: Building 501 - 01.01.3a-c
Phone: +49 89 4140 6457

Education

  • 2017: Master of Science in Informatics. Technical University of Munich, Germany
    Thesis: Security of Deep Learning Under Adversarial Settings
  • 2015: Bachelor in Informatics. Aristotle University of Thessaloniki, Greece
    Thesis: Distance Computation Between Videos Using Dynamic Time Warping

Research Interests

  • Machine Learning
  • Robustness of Neural Networks
  • Federated Learning
  • Interpretable Neural Networks
  • Medical imaging
    • Whole-Brain Segmentation
    • Ultrasound DeepForming
    • Skin Lesion Classification
    • Medical Image Retrieval

Teaching

Publications

2019
M. Paschali, S. Gasperini, A. Guha Roy, M.Y.-S. Fang, N. Navab
3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation
The first two authors contributed equally.
22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen 2019.
The original publication is available currently online on arXiv and will become available at link.springer.com
(bib)
M. Paschali, W. Simson, A. Guha Roy, R. Göbl, F. Naeem, C. Wachinger, N. Navab
Manifold Exploring Data Augmentation with Geometric Transformations for Increased Performance and Robustness
26th international conference on Information Processing in Medical Imaging (IPMI), Hong Kong 2019.
The original publication is available currently online on arXiv and will become available at link.springer.com
(bib)
2018
M. Paschali, S. Conjeti, F. Navarro, N. Navab
Generalizability vs. Robustness of medical imaging networks
21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Spain 2018.
The original publication is available online at link.springer.com
(bib)
S. Conjeti, M. Paschali, A. Guha Roy, N. Navab
Deep Hashing for Large-Scale Medical Image Retrieval
Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 11. bis 13. März 2018 in Erlangen
The original publication is available online at link.springer.com
(bib)
2017
S. Conjeti, M. Paschali, A. Katouzian, N. Navab
Deep Multiple Instance Hashing for Scalable Medical Image Retrieval
The first two authors contributed equally.
20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Canada 2017.
The original publication is available online at link.springer.com
(bib)

Preprints

P. Notaro, M. Paschali, C. Hopke, D. Wittmann, N. Navab
Radar Emitter Classification with Attribute-specific Recurrent Neural Networks
arXiv/1911.07683, 2019

S. Gasperini, M. Paschali, C. Hopke, D. Wittmann, N. Navab
Signal Clustering with Class-independent Segmentation
arXiv/1911.0759, 2019

M. Paschali*, M. F. Naeem*, W. Simson, K. Steiger, M. Mollenhauer, N. Navab
Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks,
arXiv/1904.03127, 2019 (* The authors contributed equally.)

W. Simson*, R. Göbl*, M. Paschali, M. Krönke, K. Scheidhauer, W. Weber, N. Navab
End-to-End Learning-Based Ultrasound Reconstruction,
arXiv/1904.04696, 2019 (* The authors contributed equally.)


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Firstname: Magda
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Groups: Machine Learning for Medical Applications, IFL
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Room: MI 03.13.039
Telephone: +49 89 289 19441
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Edit | Attach | Refresh | Diffs | More | Revision r1.42 - 20 Nov 2019 - 10:48 - MagdaPaschali

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