ChristophBaur

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

Christoph Baur

Christoph Baur, M.Sc.
PhD Candidate
c.baur [@] tum.de

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

Office MI 03.13.042







Research on Deep Learning for Medical Applications

  • Medical Image Segmentation
  • Multiple Sclerosis Lesion Segmentation and Classification
  • Unsupervised Anomaly Detection
  • Unsupervised & Semi-Supervised Domain Adaptation
  • Deep Directed Generative Models (Generative Adversarial Networks, Variational Auto-Encoders, VAE-GANs, Adversarial Auto-Encoders) for Medical Image Synthesis
  • Catheter Detection in X-ray images
  • Mitotic figure detection in histology images of breast cancer
  • Crowdsourcing for Deep-Learning

Student Projects

Feel free to contact me or drop by at my office if you are looking for a Bachelor Thesis, Master Thesis, IDP or Guided Research Project in summer semester 2017! Open projects will be announced here as well.

Collaboration with the Neuroradiology at Klinikum Rechts der Isar

Together with the Department for Neuroradiology located at Klinikum Rechts der Isar I am working on exciting Computational Imaging projects. More information is provided at http://www.neurokopfzentrum.med.tum.de/neuroradiologie/forschung_projekt_computational_imaging.html

Teaching

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
  • 3rd rank at the Intel Leibniz Challenge 2009
  • 1st rank at the Neoflash Coding Competition 2009

Publications

2018
C. Baur, B. Wiestler, S. Albarqouni, N. Navab
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images
Submitted to the 21st International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Granada, Spain, September 2018
A pre-print version is available online at arXiv.
(bib)
C. Baur, S. Albarqouni, N. Navab
MelanoGANs: High Resolution Skin Lesion Synthesis with GANs
Submitted to the 1st International conference on Medical Imaging with Deep Learning (MIDL), Amsterdam, Netherlands, July 2018
A pre-print version is available online at arXiv.
(bib)
M. Bui, F. Bourier, C. Baur, F. Milletari, N. Navab, S. Demirci
Robust Navigation Support in Lowest Dose Image Setting
International Journal of Computer Assisted Radiology and Surgery, In Press (bib)
M. T. Shaban, C. Baur, N. Navab, S. Albarqouni
StainGAN: Stain Style Transfer for Digital Histological Images
Submitted to the 21st International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Spain, September 2018
A pre-print version is available online at arXiv.
(bib)
2017
B. Wiestler, C. Baur, P. Eichinger, , T. Zhang, V. Biberacher, C. Zimmer, , J. Kirschke, S. Albarqouni
Fully Automated Multiple Sclerosis lesion detection on multi-channel subtraction images through an integrated Computer Vision- Machine Learning pipeline
Clinical Neuroradiolgy (2017) 27:S1-S118 (bib)
C. Baur, S. Albarqouni, N. Navab
Semi-Supervised Learning for Fully Convolutional Networks
Accepted to Proceedings of the 20th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Quebec, Canada, September 2017
A pre-print version is available online at arXiv.
The first two authors contribute equally to this paper.
(bib)
2016
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, 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.
The first two authors contribute equally to this paper.
(bib)
2015
C. Baur, F. Milletari, V. Belagiannis, N. Navab, P. Fallavollita
Automatic 3D reconstruction of electrophysiology catheters from two-view monoplane C-arm image sequences
The 6th International Conference on Information Processing in Computer-Assisted Interventions (IPCAI) (bib)

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Firstname: Christoph
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Groups: Registration/Visualization, Segmentation, Medical Imaging, Computer Vision, Machine Learning for Medical Applications, Crowdsourcing
Expertise: Segmentation, Medical Imaging, Computer Vision
Position: Scientific Staff
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Room: MI 03.13.042
Telephone: +49 (89) 289-17079
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