Bjoern Menze

I am an assistant professor in computer science at TU München (W2 level), holding a Rudolf Moessbauer tenure-track professorship of the TUM Institute for Advanced Study (TUM-IAS). I am also a visiting research scientist of the Asclepios team at the Inria Sophia-Antipolis and of the computer vision lab at ETH Zurich, and a research affiliate of the medical computer vision group of CSAIL at MIT.

My research is in medical image computing, exploring topics at the interface of medical computer vision, image-based modeling and computational physiology. In this, I focus on applications in clinical neuroimaging and the modeling of tumor growth. My work strives towards transforming the descriptive interpretation of biomedical images into a model-driven analysis that infers properties of the underlying physiological and patho-physiological processes by using models from biophysics and computational physiology. I am also interested in how to apply such models to big data bases in order to learn about correlations between model features and disease patterns at a population scale.

I organized workshops at MICCAI, ISBI, NIPS and CVPR in the fields of medical computer vision and neuroimage processing, served as guest editor for Medical Image Analysis and as a member of the programm committee of MICCAI.

My work on translating computational methods from medical image analysis towards applications in Near Eastern Archaeology has been featured, for example, in Geo Magazin, Spiegel and Nature.

Bjoern Menze

Contact

Prof. Dr. Bjoern H. Menze

TU München
Computer Science
Boltzmannstr. 3
D-85748 Garching
Germany

Office: MI 03.13.053
Tel: +49 89 289 17081

bjoern.menze@tum.de
www.cs.tum.edu/~menze

Recent news
Paper accepted by Medical Image Analysis (on vessel segmentation) and by IEEE TMI (BRATS paper).
Best poster award at PASC conference (congrats Jana!).
Two papers accepted at MICCAI 2014 in Boston including one oral (congrats Markus!).
Paper accepted by IEEE JSTARS (on multitemporal fusion), and paper accepted by IEEE TIP (on longitudinal segmentation with growth constraint).
MSc thesis projects available: on longitudinal brain tumor image analysis and on computational blood flow modeling in stroke patients (in collaboration with J Bauer and T Boeckh-Behrens, TUM Neuroradiology, and N Thurey, TUM Computer Science). Please contact me via email if you are interested.
The preprint of the BRATS manuscript is now available from HAL.
The MICCAI-MCV proceedings are published by Springer (LNCS 8331).
Medical Computer Vision Workshop on big data (bigMCV), Multi-modal Brain Tumor Segmentation Challenge & Workshop (BRATS), and Interactive Medical Image Computing Workshop (iMIC) accepted at MICCAI 2014.
Our special issue on anatomy localization via classification and regression forests is published in Medical Image Analysis.
Medical Computer Vision Workshop (MCV) and Multi-modal Brain Tumor Segmentation Challenge (BRATS) accepted at MICCAI 2013.
The MICCAI-MCV proceedings are published by Springer (LNCS 7766).
10 workshop and challenge papers accepted at MICCAI 2012.
The PNAS paper is featured in Nature and CACM.
Menze et Ur. PNAS, accepted.
Medical Computer Vision Workshop (MCV) and Multi-modal Brain Tumor Segmentation Challenge (BRATS) accepted at MICCAI 2012.
The ECML talk on oblique random forests is available now through videolectures.net.
The MICCAI-MCV proceedings are published by Springer (LNCS 6533).


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