MartinGroher

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

Me

  • Dr. rer. nat. Martin Groher



  • microDimensions
    Rupert-Mayer-Str. 44
    81379 München
    Germany

Research

My research is mainly focused on the validation, registration, and segmentation of medical images, in particular:

  • enhancement, segmentation, and registration of angiographic imagery
  • vessel modeling
  • estimation and analysis of the hemodynamics of blood

  • Image-based tracking in fluoroscopic images
  • breathing motion compensation in interventional procedures

  • analysis, reconstruction, and registration of histology slices
  • validation of new imaging technologies via registration to histology

  • dynamic analysis of microscopic image sequences

Active research projects

Registration of Angiographic Images

Registration of Angiographic Images

Angiographic images visualize vascular structure in different modalities like X-Ray, CT, or MR data sets. In many medical applications, a registration and proper visualization of the data sets, especially the vasculature is useful for a better navigation. The focus of this project lies on 2D/3D registration of angiographic data where intensity-based, feature-based, and hybrid approaches are evaluated, the latter two of them requiring an accurate 2D and 3D segmentation of the data. The main clinical partner is the radiology department of the Universitätsklinikum Großhadern (Ludwig-Maximilian Universität München) , industrial partner is Siemens Medical Solutions, Forchheim.
Assessment of Fluid Tissue Interaction Using Multi-Modal Image Fusion for Characterization and Progression of Coronary Atherosclerosis

Assessment of Fluid Tissue Interaction Using Multi-Modal Image Fusion for Characterization and Progression of Coronary Atherosclerosis

Coronary artery diseases such as atherosclerosis are the leading cause of death in the industrialized world. In this project, we develop computational tools for segmentation and registration problems on intravascular images including IVUS (Intravascular Ultrasound) and OCT (Optical Coherence Tomography). One sample component of this project is Automatic Stent Implant Follow-up from Intravascular OCT Pullbacks. The stents are automatically detected and their distribution is analyzed for monitoring of the stents: their malpositioning and/or tissue growth over stent struts.
Endovascular Stenting of Aortic Aneurysms

Endovascular Stenting of Aortic Aneurysms

Endovascular stenting is a minimally invasive treatment technique for aortic aneurysms or dissections. Thereby, a certain aortic prosthesis (stent graft) is placed inside the aortic aneurysm in order to prevent a life-threatening rupture of the aortic wall. Prior to the intervention, a computed tomography angiography (CTA) is acquired on which the surgical staff can measure the parameter of the desired stent graft and finalize the intervention workflow. The entire interventional catheter navigation is done under 2D angiography imaging where the physician is missing the important 3D information. The purpose of our project is two-fold:
1. In the planning phase, a modified graph cuts algorithm automatically segments the aorta and aneurysm, so the surgical staff can choose an appropriate type of stent to match the segmented location, length, and diameter of the aneurysm and aorta. By visualizing the defined stent graft next to the three-dimensionally reconstructed aneurysm, mismeasurements can be detected in an early stage. Our main goal is the creation of an interactive simulation system that predicts the behaviour of the aortic wall and the movement of the implanted stent graft.
2. During implantation of the stent graft, after an intensity based registration of CTA and angiography data, the current navigation can be visualized in the 3D CT data set at any time. This includes solutions for electro-magnetic tracking of catheters as well as guide wires and stent grafts. Eventually, Our main goal is the creation of solutions that enable the surgeon to enhance the accuracy of the navigation and positioning, along with a minimum use of angiography, leading to less radiation exposure and less contrast agent injection.
Semi-Automatic Patellar Cartilage Segmentation

Semi-Automatic Patellar Cartilage Segmentation

Development and refinement of a software system for semi-automatic segmentation of the patellar cartilage is the main goal of this project. By providing tools for sub-pixel accurate edge tracing, automatic contour completion, and adequate visualization, a remarkable speed-up of the physicians segmentation process can be achieved. Also, improved exactness can be reached for cartilage segmentation if expertise and automation are merged in a meaningful way.
Assessment of Knee Cartilage

Assessment of Knee Cartilage

Degeneration of knee joint cartilage is an important and early indicator of osteoarthritis (OA) which is one of the major socio-economic burdens nowadays. Accurate quantification of the articular cartilage degeneration in an early stage using MR images is a promising approach in diagnosis and therapy for this disease. Particularly, volume and thickness measurement of cartilage tissue has been shown to deliver significant parameters in assessment of pathologies. Here, accurate computer-aided diagnosis tools could improve the clinical routine where image segmentation plays a crucial role. In order to overcome the time-consuming and tedious work of manual segmentation, one tries to automate the segmentation as much as possible. We focus on novel atlas-based segmentation methods for knee cartilage as well as improve today’s clinical routine of manual segmentation methods. In addition, we try to evaluate different methods for the assessment of parameters such as volume and thickness which could allow computer-aided diagnosis of knee cartilage pathologies in an early stage.

Dissertation

Abstract: Angiographic imaging is a widely used monitoring tool for minimally invasive vascular treatment and pathology access. Especially in deforming abdominal areas, the registration of pre- and intraoperative image data is still an unsolved problem, but important in several aspects. In particular, treatment time and radiation exposure to patient and physician can be significantly reduced with the resulting 2D-3D data fusion. The focus of this work is to provide methods for the registration of 2D vascular images acquired by a stationary C-arm to preoperative 3D angiographic Computed Tomography (CT) volumes, in order to improve the workflow of catheterized liver tumor treatments. Fast and robust vessel segmentation techniques are used to prepare the necessary graph data structures for a successful alignment. Here, we introduce restricted correspondence selection and iterative feature space correction to drive the proposed rigid-body algorithms to global and accurate solutions. Moreover, it is shown for the first time that the assignment of natural constraints on vessel structures allows for a successful recovery of a 3D non-rigid transformation despite a single-view scenario. Based on these results, novel volumetric visualization and roadmapping techniques are developed in order to resolve interventional problems of reduced depth perception, blind navigation, and motion blur.

M. Groher
2D-3D Registration of Angiographic Images
Technische Universtät München, 2008 (bib)

Publications

2012
H. Heibel, B. Glocker, M. Groher, M. Pfister, N. Navab
Interventional Tool Tracking using Discrete Optimization
IEEE Transactions on Medical Imaging (TMI) (bib)
Y. Yagi, M. Groher, M. Feuerstein, M. Onozato, H. Heibel, N. Navab
Overcoming Challenges in Histology 3D Imaging
11th European Congress on Telepathology and 5th International Congress on Virtual Microscopy, Venice, Italy, June 2011. (bib)
A. Chekkoury, P. Khurd, Jie Ni, C. Bahlmann, , Amar Patel, L. Grady, M. Singh, M. Groher, N. Navab, , Jeffrey Johnson, Anna Graham, Ronald Weinstein
Automated Malignancy Detection in Breast Histopathological Images
SPIE Medical Imaging, 04-09 February 2012, San Diego, California, USA (bib)
N. Brieu, N. Navab, J. Serbanovic-Canic, W. Ouwehand , D. Stemple, A. Cvejic, M. Groher
Image-based Characterization of Thrombus Formation in Time-lapse DIC Microscopy
Medical Image Analysis 2012 (bib)
2011
N. Brieu, M. Groher, J. Serbanovic-Canic, A. Cvejic, W. Ouwehand , N. Navab
Joint Thrombus and Vessel Segmentation Using Dynamic Texture Likelihoods and Shape Prior
Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), Toronto, Canada, September 2011 (bib)
M. Feuerstein, H. Heibel, J. Gardiazabal, N. Navab, M. Groher
Reconstruction of 3-D Histology Images by Simultaneous Deformable Registration
Proceedings of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), Toronto, Canada, September 2011.
The original publication is available online at www.springerlink.com
(bib)
2010
N. Brieu, J. Serbanovic-Canic, A. Cvejic, D. Stemple, W. Ouwehand , N. Navab, M. Groher
Thrombus Segmentation by Texture Dynamics from Microscopic Image Sequences
SPIE Medical Imaging, 13-18 February 2010, San Diego, California, USA (bib)
N. Brieu, B. Glocker, N. Navab, M. Groher
MAP-MRF Optimal Partitioning for Dynamic Texture Segmentation of Thrombus in Time-Series Microscopic Images
MICCAI 2010 Workshop on Spatio Temporal Image Analysis for Longitudinal and Time-Series Image Data (STIA'10), 24 September 2010, Beijing, China (bib)
D. Zikic, B. Glocker, O. Kutter, M. Groher, N. Komodakis, A. Kamen, N. Paragios, N. Navab
Linear Intensity-based Image Registration by Markov Random Fields and Discrete Optimization
Medical Image Analysis, 22 April, 2010. (bib)
G.Gul-Isguder, G. Unal, M. Groher, N. Navab, A.K.Kalkan, M. Degertekin, H.Hetterich, J.Rieber
Manifold Learning for Image-Based Gating of Intravascular Ultrasound(IVUS) Pullback Sequences
5th International Workshop on Medical Imaging and Augmented Reality, Sep 2010, Beijing (bib)
M. Groher, M. Baust, D. Zikic, N. Navab
Monocular Deformable Model-to-Image Registration of Vascular Structures
International Workshop on Biomedical Image Registration (WBIR), in Lübeck, Germany, July 11-13 2010. (bib)
D. Zikic, B. Glocker, O. Kutter, M. Groher, N. Komodakis, A. Kamen, N. Paragios, N. Navab
Markov Random Field Optimization for Intensity-based 2D-3D Registration
SPIE Medical Imaging, San Diego, California, USA, 13-18 February 2010 (bib)
2009
N. Brieu, J. Serbanovic-Canic, A. Cvejic, D. Stemple, W. Ouwehand , N. Navab, M. Groher
A dynamic texture approach to semi-automatic thrombosis segmentation in in-vivo microscopic video-sequences
Workshop on Microscopic Image Analysis and Application in Biology, (MIAAB 2009), Bethesda, MD (US), 3-4 September 2009 (bib)
H. Heibel, B. Glocker, M. Groher, N. Paragios, N. Komodakis, N. Navab
Discrete Tracking of Parametrized Curves
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Miami, Florida (USA), June 2009. (bib)
M. Groher, D. Zikic, N. Navab
Deformable 2D-3D Registration of Vascular Structures in a One View Scenario
IEEE Trans. Med. Imag., 28 (6), pp. 847-860 (bib)
2008
F. Bender, M. Groher, A. Khamene, W. Wein, H. Heibel, N. Navab
3D Dynamic Roadmapping for Abdominal Catheterizations
Medical Image Computing and Computer-Assisted Intervention, MICCAI, 2008, New York, USA, September 6-10 2008 (bib)
C. Unger, M. Groher, N. Navab
Image Based Rendering for Motion Compensation in Angiographic Roadmapping
IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska (USA), June 24-26, 2008 (bib)
D. Zikic, M. Groher, A. Khamene, N. Navab
Deformable Registration of 3D Vessel Structures to a Single Projection Image.
SPIE Medical Imaging, San Diego, California, USA, 16-21 February 2008 (bib)
S. Atasoy, M. Groher, D. Zikic, B. Glocker, T. Waggershauser, M. Pfister, N. Navab
Real-Time Respiratory Motion Tracking: Roadmap Correction for Hepatic Artery Catheterizations
SPIE Medical Imaging, San Diego, California, USA, 16-21 February 2008 (bib)
N. Navab, M. Groher
Novel Navigation and Advanced Visualization Techniques for Abdominal Catheterization
Hospital Imaging and Radiology Europe, 2 (4), pp. 29-30, Feb. 2008 (bib)
2007
M. Groher, F. Bender, R.T. Hoffmann, N. Navab
Segmentation-driven 2D-3D Registration for Abdominal Catheter Interventions
Medical Image Computing and Computer-Assisted Intervention, MICCAI, 2007, Brisbane, Australia, October 29 - November 2 2007, LNCS 4792, pp. 527-535 (bib)
M. Groher, T. F. Jakobs, N. Padoy, N. Navab
Planning and Intraoperative Visualization of Liver Catheterizations: New CTA Protocol and 2D-3D Registration Method
Academic Radiology 14 (11), pp.1324-1339. Special issue of MICCAI 2006 (bib)
L. König, M. Groher, A. Keil, Ch. Glaser, M. Reiser, N. Navab
Semi-Automatic Segmentation of the Patellar Cartilage in MRI
Proc. of Bildverarbeitung für die Medizin (BVM 2007), Munich, Germany, March 2007. The original publication is available online at www.springerlink.com. (bib)
M. Groher, R.T. Hoffmann, C. J. Zech, M. Reiser, N. Navab
An Efficient Registration Algorithm for Advanced Fusion of 2D/3D Angiographic Data
in Proceedings of Bildverarbeitung fuer die Medizin (BVM 2007), Munich, Germany, March 2007 (bib)
2006
M. Groher, T. F. Jakobs, M. Reiser, N. Navab
Advanced 2D-3D Registration Method for Transarterial Chemoembolizations
5. Jahrestagung der Deutschen Gesellschaft für Computer-und Roboter-Assistierte Chirurgie (CURAC 2006), Hannover, Germany, September 2006 (bib)
M. Groher, N. Padoy, T. F. Jakobs, N. Navab
New CTA Protocol and 2D-3D Registration Method for Liver Catheterization
Proceedings of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2006), Copenhagen, Denmark, October 2006 (bib)
2005
M. Groher, T. F. Jakobs, N. Padoy, N. Navab
Towards a Feature-based 2D-3D Registration Method of CTA and 2D Angiograms for Liver Tumor Chemoembolizations
4. Jahrestagung der Deutschen Gesellschaft für Computer-und Roboter-Assistierte Chirurgie (CURAC 2005), Berlin, Germany, September 2005 (bib)
2004
R. Bauernschmitt, E.U. Schirmbeck, M. Groher, P. Keitler, M. Bauer, H. Najafi, G. Klinker, R. Lange
Navigierte Platzierung endovaskulärer Aortenstents
Z Kardiologie 2004 93 S3: 116 (bib)

Teaching

Finished and Currently active Diploma Theses, SEPs, IDPs I (co-)supervised

Available:

Current:
Finished:

Teaching Assistance

People I helped moving to a new flat while at the chair

3x Joerg Traub + one IKEA shopping...?
Tobias Sielhorst
Pierre Georgel And I live on the fifth floor without elevator, look how nice he is
Nicolas Padoy
Ben Glocker
Olivier Pauly
It's never good to have the biggest car at a chair...


UsersForm
Title: Dr.
Circumference of your head (in cm):  
Firstname: Martin
Middlename:  
Lastname: Groher
Picture: martin.jpg
Birthday:  
Nationality: Germany
Languages:  
Groups: Registration/Visualization, Medical Imaging
Expertise: Registration/Visualization, Segmentation, Medical Imaging, Computer Vision
Position: External Collaborator
Status: Alumni
Emailbefore: groher
Emailafter: cs.tum.edu
Room: microDimensions
Telephone: +49 89 289 10930
Alumniactivity: CEO of microDimensions
Defensedate: 8 April 2008
Thesistitle: 2D-3D Registration of Angiographic Images
Alumnihomepage:  
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Edit | Attach | Refresh | Diffs | More | Revision r1.56 - 20 Mar 2013 - 15:13 - MartinGroher

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