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

Prof. Dr. Nassir Navab

Nassir Navab CAMP - Computer Aided Medical Procedures & Augmented Reality

Research Interests

CAMP Publications

Prof. Gudrun Klinker, Ph.D.

Gudrun Klinker FAR - Fachgebiet Augmented Reality

Research Interests

FAR Publications

Prof. Dr. Bjoern Menze

Bjoern Menze IBBM - Image-Based Biomedical Modelling

Research Interests

  • Computational Physiology
  • Image-based Modeling
  • Medical Computer Vision

Prof. Dr. Peter Struss

Peter Struss MQM - Model-Based Systems & Qualitative Reasoning

Research Interests

  • Qualitative REasoning
  • Model-based Diagnosis
  • Knowledge-based Configuration
  • Model-based Functional Safety
  • Model-based Support Systems

Teaching

Senior Research Scientists

Stefanie Demirci

Dr. Stefanie Demirci

  • Interventional image registration
  • Disocclusion in medical images
  • Medical device detection/navigation
  • Segmentation for medical treatment planning

Ulrich Eck

Dr. Ulrich Eck

  • Medical Augmented Reality for Surgery and Training
  • Intra-operative Navigation and Guidance
  • System Architectures for Realtime Interactive Systems
  • Haptic-Enabled Simulators

Christoph Hennersperger

Dr. Christoph Hennersperger

  • Ultrasound Imaging
  • Computer Assisted Neurosurgery
  • Cardiac Surgery and Imaging
  • Robotic Imaging

Tobias Lasser

PD Dr. Tobias Lasser

  • Mathematical Methods in Medical Imaging
  • Tomographic Reconstruction and Ill-posed Problems
  • Computer Assisted Surgery

Marie Piraud

Dr. Marie Piraud

  • Medical data analytics and modeling
  • Stochastic modeling and Bayesian inference
  • Machine learning and quantum artificial intelligence

Federico Tombari

Dr. Federico Tombari

  • Invariant representations for 2D, 3D and RGB-D data
  • 3D object recognition and pose estimation
  • Stereo vision and 3D reconstruction
  • Pattern matching and robust visual correspondence

Joint CAMP / Helmholtz Senior Research Group

Tingying Peng

Dr. Tingying Peng

  • Molecular imaging
  • Microscopic image processing
  • Machine learning for medical applications
  • Mathematical modeling for physiological understanding

Senior Affiliate Lecturers / Research Scientists

Ahmad Ahmadi

Dr. Ahmad Ahmadi

  • Neuroimaging
  • Multi-modal Imaging (US,MRI,etc.)
  • Clinical Applications

Maximilian Baust

Dr. Maximilian Baust

  • Variational methods
  • Medical image analysis
  • Machine learning

Benjamin Frisch

Dr. Benjamin Frisch

  • Nuclear Imaging Detectors
  • Interventional Imaging
  • Robotic Imaging

Slobodan Ilic

PD Dr. Slobodan Ilic

  • Deformable surface modeling and tracking
  • 3D reconstruction (multi-camera, stereo)
  • Real-time object detection and tracking
  • Object detection and localization in 3D data

Michael Friebe

Prof. Dr. Michael Friebe

  • Lecturer: "Medical Technology Entrepreneurship" and "Image Guided Surgery: From Bench to Bed and Back (IGSB3)"
  • Research: Translational research in medical imaging & image guided minimal invasive procedures

Markus Kowarschik

PD Dr. Markus Kowarschik

  • Lecturer: Interventional Imaging
  • Research: Interventional Imaging, Tomographic Image Reconstruction

Diana Mateus

Dr. Diana Mateus

  • Machine Learning for Medical Applications
  • 3D shape acquisition, modeling and registration
  • Computer Vision

Wolfgang Wein

Dr. Wolfgang Wein

  • Lecturer: conebeam CT and US Imaging
  • Research: Advanced Ultrasound Imaging

Joerg Traub

Dr. Joerg Traub

  • Lecturer: Image Guided Surgery: From Bench to Bed and Back (IGSB3)
  • Invited lecture in CAMP-I: Translation research in medical technology

Peter Noël

Dr. Peter Noël

  • Lecturer: Medical Imaging
  • Research: Tomographic reconstruction

Stephan Nekolla

PD Dr. Stephan Nekolla

  • Quantitative methods in medical imaging
  • Integration of multi modality data: PET, SPECT, CT, MRI
  • Going the full distance: from imaging physics to tracking therapeutical changes

Arash Taki

Dr. Arash Taki

  • Lecturer: Ultrasound Imaging
  • Scientific Advisor: BMC Master of TUM in Singapore

Selected Video

MeTaTop A Multi Sensory Table Top System for Medical Procedures (Video3)
Video Length: 00:02:53
Diploma Thesis: A Tabletop Display as a Multi-Modal and Multi-User Interface for Collaborative Patient Data Analysis

fullsize version

Hot Stuff

10 September 2017, Quebec City, Canada
CAMP Nominations and Awards at MICCAI 2017
Once again our students made the difference. Only 12 papers out of over 800 submissions to MICCAI 2017 where nominated for Young Investigator Awards (less than .02%). This list include 3 papers from CAMP.
10 February 2017,
TEDx talk on Medical Augmented Reality
Professor Navab gave a TEDx talk on Medical Augmented Reality.

News

8 September 2017,
PhD Defense by Loïc Peter
The task of semantic image segmentation, i.e. the simultaneous partitioning of an image into regions and the labeling of their content, is a fundamental objective in computer vision and medical image analysis. The need for segmentation algorithms can be encountered in diverse real-world scenarios. In some cases, the segmentation of a scene must be entirely automated, for example to act as a scene understanding tool to help the decision-making of an autonomous system. In other situations, a segmentation algorithm can assist a human user in annotating an image. In this case, the fully-automated aspect is no longer crucial and can be relaxed in favor of an improved flexibility via interactions with the user. In this thesis, we demonstrate how the statistical learning framework of decision forests can be exploited for these two scenarios and propose three contributions. First, we introduce an efficient and generic scale-adaptive forest training scheme for fully automated image understanding. In the context of large digital slides in histopathology, we propose an interactive and adaptive solution entangling segmentation with image exploration to facilitate the examination of these large images. Finally, we show how the segmentation task can be modeled as a Twenty Questions game towards hands-free human-computer interactions. Overall, we hope to demonstrate the effectiveness of decision forests for automated segmentation in diverse application domains. Moreover, we wish to emphasize the relevance of interactive settings and to introduce practical learning-based solutions in cases where standard interactive techniques are not directly applicable.
2 August 2017, FMI 00.13.009A
Talk on Sensitive Longitudinal Events.NeuroImaging and Morphometry
Structural magnetic resonance imaging data are frequently analyzed to reveal morphological changes of the human brain in dementia. Most contemporary imaging biomarkers are scalar values, such as the volume of a structure, and may miss the localized morphological variation of early presymptomatic disease progression. Neuroanatomical shape descriptors, however, can represent complex geometric information of individual anatomical regions and may demonstrate increased sensitivity in association studies. Yet, they remain largely unexplored. In this talk we will describe sensitive computational methods for the automated quantification of neuroanatomical morphometric estimates and their longitudinal changes. We will, furthermore, show that neuroanatomical shape features, such as lateral shape asymmetry, demonstrate increased sensitivity to detect early disease effects and can improve computer-aided diagnosis of dementia.

Recent Publications

8 August 2017,
One paper accepted at IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
5 August 2017, Vancouver, Canada
2 papers accepted at IROS 2017
25 July 2017, Venice, Italy
5 papers accepted at ICCV 2017
We are happy to announce that 5 papers of our chair have been accepted at ICCV
25 July 2017, Quebec City, Quebec, Canada
11 papers accepted at MICCAI 2017
We are happy to announce that 11 papers of our chair have been accepted at MICCAI
24 July 2017, Nantes, France
2 papers accepted at ISMAR 2017
We are happy to announce that 2 papers of our chair have been accepted at ISMAR

Alumni News

Address

Location Technische Universität München
Fakultät für Informatik / I16
Boltzmannstraße 3
85748 Garching bei München
Germany

Proud of our Alumni

Dr. Amin Katouzian


Master Juergen Sotke


Dr. Ali Bigdelou
Development Specialist and Software Architect at BMW Group, Forschungs- und Innovationszentrum.
Operating Room Specific Domain Model for Usability Evaluations and HCI Design
20 November 2012
-none- Fausto Milletari


Dipl.-Tech. Math. Univ. Richard Brosig




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