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 03.13.053
Phone: +49 (89) 289-17081

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

Google ScholarScholar

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

List of Preprints and Publications

2020
H. Hase, MF. Azampour, M. Tirindelli, M. Paschali, W. Simson, E. Fatemizadeh, N. Navab
Ultrasound-Guided Robotic Navigation with Deep Reinforcement Learning
The original manuscript is available currently online on arXiv. (bib)
T. Czempiel, M. Paschali, M. Keicher, W. Simson, H. Feußner, S.T. Kim, N. Navab
TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks
International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Lima, Peru, 2020 (The pre-print is available currently online on arXiv) (bib)
S. Gasperini, M. Paschali, C. Hopke, D. Wittmann, N. Navab
Signal Clustering with Class-independent Segmentation
45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2020.
The original publication is available currently online on arXiv.
(bib)
2019
M. Paschali, F. Naeem, W. Simson, K. Steiger, M. Mollenhauer, N. Navab
Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks
The first two authors contributed equally.
The original manuscript is available currently online on arXiv.
(bib)
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)
W. Simson, R. Göbl, M. Paschali, M. Krönke, K. Scheidhauer, S. Weber, N. Navab
End-to-End Learning-Based Ultrasound Reconstruction
The first two authors contributed equally.
The original manuscript is available currently online on arXiv.
(bib)
2018
W. Simson, M. Paschali, N. Navab, G. Zahnd
Deep Learning Beamforming for Sub-Sampled Ultrasound Data
IEEE International Ultrasonics Symposium (IUS), 2018 Japan (bib)
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)

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


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Firstname: Magda
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Lastname: Paschali
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Nationality: Greece
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Groups: Machine Learning for Medical Applications, IFL
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Position: Scientific Staff
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Room: MI 03.13.039
Telephone: +49 89 289 19441
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