Bjoern Menze

I am Professor for Machine Learning in Biomedical Imaging (W3 level) in the Department of Informatics at TU München, and a faculty member of the TUM School of Medicine. I am also a past Rudolf Moessbauer Professor of the TUM Institute for Advanced Study, and was a guest professor at Maastricht University in 2019. Since 2014, I am heading the Image-based Biomedical Modeling group at the Munich School of Bioengineering (MSB) and the Center for Translational Cancer Research (TranslaTUM). Before, I was member of the Asclepios team of the Inria Sophia-Antipolis, the Computer Vision Lab at ETHZ, and the CSAIL Medical Vision Group at MIT, after I had received a PhD from Heidelberg University.

My research is in medical image computing, exploring topics at the interface of machine learning, medical imaging, and image-based diagnostics. 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, computational physiology, and statistical learning. 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, NeurIPS, 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 program committee of MICCAI, and I am a member of the editorial board of Medical Image Analysis. I received the Medical Image Analysis Award for the best paper of MICCAI 2014, and the Young Scientist Publication Impact Award at MICCAI 2015.

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


Prof. Dr. Bjoern H. Menze

TU München
Computer Science
Boltzmannstr. 3
D-85748 Garching

Office: MSB (IMETUM) 1.102
Tel: +49 89 289 10930

Recent news
Anjany's paper adversarial learning of anatomical prior knowledge is out in Radiology AI. Congrats!
Our Schloss Dagstuhl seminar (co-organized with A Mang, G Biros, M Mehl) on 'Inverse Biophysical Modeling and Machine Learning in Personalized Oncology' has been accepted.
Our paper on extracting cerebrovascular networks in tissue-cleared mice has been accepted by Nature Methods. Congrats to Johannes, Oliver, Giles, Velizar, Marie, and the Ertuerk Lab!
Oliver's paper on detecting metastatic cells in tissue cleared mice has been accepted by Cell. Congratulations!
Marie's paper on modeling disease progression in Multiple Myeloma is accepted by Medical Image Analysis. Congrats!
Four papers at MICCAI 2019 in Shenzhen - congrats to Yu, Anjany, Ivan, and Bran!
The BRATS paper passed 1000 citations. is awarded EXIST funding. Congrats to Miguel and Pedro!
Jana's paper on image-based modeling of tumor growth is accepted by IEEE TMI. Congrats!
Miguel, Lina, and Markus defended their PhD. Congratulations!
Two papers out in Nature Neuroscience and Nature Communications.
Markus' paper on cell tracking is runner-up to the MICCAI Medical Image Analysis Best Paper Award 2018. Congrats!
5 papers accepted at MICCAI 2018.
Markus' MICCAI paper is invited to the MICCAI 2017 best paper issue of Medical Image Analysis!
Bran won the MICCAI White Matter Hyperintensities Segmentation Challenge. Congratulations!
Pedro, Marie, and Patrick defended their PhD. Congratulations!
Marie's paper on iterative trilateration is out in TMI, as is another paper in the Journal of Nuclear Medicine.
Ten abstracts accepted at ISMRM in Honolulu, including four orals and one Summa Cum Laude Award (to Pedro - congrats!).
Four papers accepted at MICCAI in Athens. Congrats - Dhritman, Markus, Patrick, and Pedro!
The generative tumor segmentation paper is published in IEEE TMI. Papers of the ISLES challenge and the VISCERAL challenge are accepted by Medical Image Analysis and IEEE TMI, respectivley.
Magna cum laude merit award for Pedro's ISMRM abstract: on MR fingerprinting - congrats!
The BRATS paper is the most downloaded and most cited IEEE TMI paper of 2014 and 2015. It is also one of five papers featured by IEEE TMI.
Events accepted at MICCAI 2016: BRATS challenge, mTOP challenge, BrainLes workshop, IMIC workshop, MCV workshop.
At MICCAI 2015 in Munich we won the MICCAI Young Scientist Publication Impact Award 2015 for our MICCAI 2010 paper on brain tumor segmentation. We also won the Medical Image Analysis Best Paper Award 2015 for the best paper presented at MICCAI 2014 Cambridge/USA.
Best poster award at PASC conference, again (congrats Jana!)
Events accepted at MICCAI 2015: BRATS challenge, ISLES challenge, BrainLes workshop, Tumor Precision Medicine workshop, IMIC workshop, MCV workshop.
Paper accepted by Medical Image Analysis (on vessel segmentation using Hough forests) 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).
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
The MICCAI-MCV proceedings are published by Springer (LNCS 6533).

text cloud