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Research
Minimally invasive surgery uses different imaging devices in order to visualize human anatomy before or during medical interventions. Angiographic imaging focuses on visualizing vessel systems in the human body. In many medical procedures, angiographic data sets are avaiable preoperatively for diagnosis / interventional planning (CT / MR), and intraoperatively for guidance of injected instruments (2D / 3D Angio). My main interest lies on processing, fusion, and visualization of angiographic images, in particular:- Vessel enhancement
- Vascular segmentation
- Vessel modeling
- Registration of vascular images
- Image-based tracking in fluoroscopic images
Active research projects
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Motion Compensation for CatheterizationsIn many minimally-invasive interventions, catheters are inserted into the body and guided to a region of interest with the help of fluoroscopic imaging (low-dose X-ray image sequences). Due to patient motion, the navigation can be disturbed, and the physician needs a longer time for treatment. This is hazardous in terms of radiation for both, physician and patient. In order to overcome these problems, suitable image-based compensation methods to resolve (non-) rigid motion can be applied. In this project, patient motion is analyzed and suitable compensation algorithms are developed. |
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Registration of Angiographic ImagesAngiographic 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. |
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Catheter Extraction in Abdominal Fluoroscopic Image SequencesThis work's focus lies in catheter and guide wire extraction from abdominal fluoroscopic sequences. Due to the fact that fluoroscopic X-ray images are of low quality and suffer from a lot of background clutter in the abdominal area the task we are working on is very difficult and not yet solved by the community. The detection process is very important since a properly detected catheter or guide wire is required by many applications that have been proposed in the last few years. One of the major goals is the enhancement of the navigation during abdominal cathterizations in order to reduce the time of interventions and thus the radiation exposure for the patient and especially the physician. |
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Assessment of Knee CartilageDegeneration 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 focusing on novel atlas-based segmentation methods for knee cartilage as well as improving the today's clinical routine of manual segmentation methods. In addition, we try 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. |
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Endovascular Stenting of Aortic AneurysmsEndovascular 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. |
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.
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M. Groher 2D-3D Registration of Angiographic Images Technische Universtät München, 2008 (bib) |
Publications
Teaching
Finished and Currently active Diploma Theses, SEPs, IDPs I (co-)supervised
Available:- Real-Time Respiratory Motion Tracking: Roadmap Correction for Endovascular Interventions by Selen Atasoy (DA/MA/BA 2007/06/15)
- Development and Implementation of a User-Friendly Tool for Analysis of the Patella Cartilage Using Magnetic Resonance Tomography by Lorenz König (IDP 2007/04/01)
- Rapid prototyping with Open Inventor for Medical Applications by Stephan v. Watzdorf (SEP 2007/01/01)
- Hepatic Vessel Extraction for 2D/3D Registration by Nicolas Padoy (DA/MA/BA 2005/09/15)
- Optimization Algorithms for 3D Computer Vision: by Moritz Blume (SEP )
- Implementation of a Fast Covariant Feature Detector by Stefan Hinterstoisser (SEP )
- Segmentation, Centerline Extraction, and Graph Creation of Angiographic Vessels in 2D by Josef Minde and Gefei Fu (SEP )
- 2D / 3D Pose Estimation by Christian Waechter (SEP )
Teaching Assistance
- Lecture 3D Computer Vision (2004SoSe)
- Programmierpraktikum Graphikprogrammierung in C++ (2004WiSe)
- Lecture 3D Computer Vision (2004WiSe)
- Hauptseminar Medical Image Registration (2004WiSe)
- Lecture 3D Computer Vision (2005WiSe)
- Hauptseminar Basics of Medical Image Segmentation and Registration (2005WiSe)
- Lecture Computer Aided Medical Procedures II (2006SoSe)
- Programmierpraktikum Graphikprogrammierung in C++ (2006SoSe)
- Lecture Computer Aided Medical Procedures (2006WiSe)
- Lecture 3D Computer Vision (2006WiSe)
- Hauptseminar Basics of Medical Image Formation, Segmentation and Registration (2006WiSe)
- Lecture Computer Aided Medical Procedures II (2007SoSe)
- Lecture Computer Aided Medical Procedures II (2008SoSe)
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
It's never good to have the biggest car at a chair...
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| Title: | Dr. |
| Firstname: | Martin |
| Middlename: | |
| Lastname: | Groher |
| Picture: |  |
| Birthday: | |
| Nationality: | Germany |
| Languages: | |
| Groups: | Registration/Visualization, Medical Imaging |
| Expertise: | |
| Position: | Scientific Staff |
| Status: | Active |
| Emailbefore: | groher |
| Emailafter: | cs.tum.edu |
| Room: | MI 03.13.061 |
| Telephone: | +49 89 289 19427 |
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