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

Address

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

Office MI 03.13.056







Research on Deep Learning for Medical Applications

  • Medical Image Segmentation
  • Unsupervised & Semi-Supervised Domain Adaptation
  • Generative Adversarial Networks
  • Variational Autoencoders
  • Anomaly Detection

Student Projects

Starting winter semester 2017 I will be available for supervising Theses and 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 winter semester 2017! Open projects will be announced here as well.

Projects & Interests

  • MS Lesion Segmentation in multimodal & multidomain MRI data
  • Catheter Detection in X-ray images
  • Mitotic figure detection in histology images of breast cancer

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

2017
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
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. (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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Edit | Attach | Refresh | Diffs | More | Revision r1.12 - 09 May 2017 - 11:10 - ChristophBaur

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