StefanieDemirci

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

Siemens-Abschied_03_gross.png Akad. Rätin
Dr. Stefanie Demirci

Coordination Master program Biomedical Computing
Managing Director
Chair for Computer Aided Medical Procedures & Augmented Reality
Fakultät für Informatik
Technische Universität München
Boltzmannstr. 3
85748 Garching b. München

room: MI 03.13.056
phone: +49 89 289-19405
fax: +49 89 289-17059
e-mail:

office hours: Mon 10 - 11am / Wed 2 - 3pm (or by email arrangement)

Biography

  • Diploma Thesis: A comparison of discriminant analysis methods for optimizing high-dimensional feature spaces (in collaboration with Siemens Corporate Technology)
  • Dissertation: New Approaches to Computer Assistance for Endovascular Abdominal Aortic Repair (download link)

Research Interests

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

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.
Decision Support System for Treating Patients with Coronary Artery Disease

Decision Support System for Treating Patients with Coronary Artery Disease

Efficacious treatment and management of patient with the Coronary Artery Disease (CAD) has drawn a lot of attention especially because of the high prevalence and high mortality rate. Two major treatment options are Coronary Artery Bypass Grafting (CABG) and Percutaneous Coronary Intervention (PCI). CABG is more expensive and invasive, however, the overall prognosis is better than PCI, which is widely considered as a less expensive and minimally-invasive option. It is documented that a large percentage of patients (up to one third) undergoing PCI procedure require repeat procedure after several years. It is beneficial to both patients and payers to identify this high-risk patient group as early as possible based on a series of in-vitro and imaging tests and possibly choose an alternate treatment option. Moreover, the identification of this high-risk patient group within the early months of PCI intervention could also trigger better management of these patients through administering possibly invasive tests (e.g., optical coherence tomography-OCT) to characterize and quantify the disease process and the associated risk. Our project partner at German Heart Center has collected large amount of data from patient cohorts that includes results of commercially available in-vitro tests, imaging tests, and for subset of patients the plasma samples and the follow-up data with clinical outcomes. The goal of this project is to identify features such as blood biomarkers that are predictive of PCI prognosis, to devise an algorithm decision support system to aggregate the biomarker test (including imaging) results and optimize the correlation to the clinical outcome, characterize and validate the system built based on retrospective data.
Automatic thrombus segmentation in in vivo micoscopic video sequences under low contrast and highly dynamic conditions

Automatic thrombus segmentation in in vivo micoscopic video sequences under low contrast and highly dynamic conditions

The Bloodomics EU project aims are to identify the genetic risks factors of coronary heart diseases.
One of the most common methods is to study the thrombus formation in the dorsal aorta of mutant Zebrafish larvae. The developing thrombus is imaged in vivo through a microscope/camera setup. The derived time to attachment, growth speed, and time to occlusion permits the characterization of the thrombus formation.
However, this step presently remains manual. Our objective is to provide the geneticists in the Wellcome Trust Sanger Institute with an image processing tool to automatically detect and segment the growing thrombus. This will significantly speed up and improve the precision of this current analysis.
Prediction of Rupture Risk for Abdominal Aortic Aneurysms

Prediction of Rupture Risk for Abdominal Aortic Aneurysms

An abdominal aortic aneurysm (AAA) describes an enlarged aortic diameter in the abdominal part of the body. Due to weakening rupture of the inner aortic wall layer, blood cells accumulate inside the wall layers and lead to a thrombus. In order to choose a suitable individual treatment, a prediction of rupture risk would be helpful. However, it is not possible to predict the ruputure risk only with quantative parameters extracted out of CT-images such as size and diameter. It is important to also include qualitative predictors like characteristics of the aortic wall and fluid dynamics.
Together with our medical and academic partners, we are interested in creating a model of the aorta and its thrombus in order to do certain calculations on wall stress and fluid dynamic computations. A further integration of other medical imaging devices such as PET/CT and IVUS into the geometrical model can provide more information about biochemical activities inside the aneurysmatic walls.
CAMPCom

CAMPCom

To ease the development of a hybrid modality we have created a generic, portable, lightweight, and easily extensible, client-server based framework, implemented in C++, to control the communication between multiple imaging and tracking devices. Our framework Computer-Aided Medical Procedures Communication (CAMPCom), allows developers of hybrid systems to focus on the most important implementation aspects by freeing them from the more generic tasks of data serialization and exchange.

Student projects

Available

Running

Finished

Teaching

Professional Activity

Editorial

  • Guest Editor for Computerized Medical Imaging and Graphics - Special Issue on Computation and Visualization for Intravascular Imaging

Reviewing

  • Journals: Medical Image Analysis, Medical Physics, Cardiovascular Imaging, IEEE Transactions on Medical Imaging
  • Conferences & Workshops: MICCAI, CVPR, ICCV, ECCV, ISBI, ICIP, MEDICON

Conferences & Workshops

Invited Talks

Dissertation

Abstract: This work presents new approaches to computer assistance for endovascular abdominal aortic repairs. In the current clinical workflow there is no technical guidance during the intervention except for two dimensional X-Ray images. Here, we introduce interventional registration methods that are able to handle such occlusions and further image dissimilarities. Thereby, contrast removal and disocclusion techniques are integrated within an image registration procedure. Furthermore, we show for the first time that a detection of the stent graft in the interventional image and a three dimensional recovery of its shape can be obtained at the same time. This allows image-based tracking of the prosthesis and simultaneous visualization within a volume rendering of the patient scan. All introduced methods are completely image based and do not require additional equipment to be introduced into the intervention room.

S. Demirci
New Approaches to Computer Assistance for Endovascular Abdominal Aortic Repairs
Technische Universtät München, 2011 (bib)

Publications

2013
T. Aksoy, S. Demirci, M. Degertekin, N. Navab, G. Unal
Template-based CTA X-ray Angio Rigid Registration of Coronary Arteries in Frequency Domain
SPIE Medical Imaging, Orlando, Florida, USA, February 2013 (bib)
S. Demirci, M. Baust, O. Kutter, F. Manstad-Hulaas, H-H. Eckstein, N. Navab
Disocclusion-based 2D-3D Registration for Aortic Interventions
Computers in Biology and Medicine, Volume 43, Issue 4, 1 May 2013, Pages 312-322 (bib)
2011
S. Demirci, A. Bigdelou, L. Wang, C. Wachinger, M. Baust, R. Tibrewal, R. Ghotbi, H-H. Eckstein, N. Navab
3D Stent Recovery from One X-ray Projection
14th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Toronto (CA), September 18-22, 2011 (bib)
D. Ugurlu, S. Demirci, N. Navab, M. S. Celebi
A Vessel Segmentation Method for MRA Images Based on Multi-scale Analysis and Level Set Framework
3rd International MICCAI-Workshop on Computation and Visualization on (Intra)Vascular Imaging, Toronto, Canada, September 18, 2011 (bib)
2010
F. Manstad-Hulaas, G. A. Tangen, S. Demirci, M. Pfister, S. Lydersen, T. A. Nagelhus Hernes
Endovascular Image-Guided Navigation - Validation of Two Volume-Volume Registration Algorithms
Minimally Invasive Therapy & Allied Technologies 20(5), pp. 282 - 289, 2011 (bib)
2009
S. Demirci, G. Lejeune, N. Navab
Hybrid Deformable Model for Aneurysm Segmentation
IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2009), Boston, Massachusetts, USA, June 28 - July 1, 2009 (bib)
M. Baust, S. Demirci, N. Navab
Stent Graft Removal for Improving 2D-3D Registration
IEEE International Symposium on Biomedical Imaging (ISBI), Boston, MA, USA, June 28-July 1 2009. (bib)
S. Demirci, F. Manstad-Hulaas, N. Navab
Extracting a Purely Non-Rigid Deformation Field of a Single Structure
Proceedings of Bildverarbeitung fuer die Medizin (BVM 2009), Heidelberg, Germany, March 2009 (bib)
S. Demirci, F. Manstad-Hulaas, N. Navab
Quantification of Abdominal Aortic Deformation after EVAR
SPIE Medical Imaging, Orlando, Florida, USA, 7-12 February 2009 (bib)
2008
S. Demirci, O. Kutter, F. Manstad-Hulaas, R. Bauernschmitt, N. Navab
Advanced 2D-3D Registration for Endovascular Aortic Interventions: Addressing Dissimilarity in Images
SPIE Medical Imaging, San Diego, California, USA, 16-21 February 2008 (bib)
2007
O. Kutter, S. Kettner (=Demirci), E.U. Braun, N. Navab, R. Lange, R. Bauernschmitt
Towards an Integrated Planning and Navigation System for Aortic Stent-Graft Placement
Proc. of Computer Assisted Radiology and Surgery (CARS), Berlin, Germany, June 2007. (bib)

Patents


UsersForm
Title: Dr.
Circumference of your head (in cm):  
Firstname: Stefanie
Middlename:  
Lastname: Demirci
Picture: Siemens-Abschied_03_icon.png
Birthday: 12.01.1981
Nationality: Bavaria
Languages: English, German, French, Turkish, Bavarian
Groups: Registration/Visualization, Segmentation, Medical Imaging, Computer-Aided Surgery
Expertise: Registration/Visualization, Segmentation, Medical Imaging, Computer-Aided Surgery, 3D Interaction
Position: Scientific Staff
Status: Active
Emailbefore: demirci
Emailafter: in.tum.de
Room: MI 03.13.056
Telephone: +49 89 289 19405
Alumniactivity:  
Defensedate: 12 April 2011
Thesistitle: New Approaches to Computer Assistance for Endovascular Abdominal Aortic Repairs
Alumnihomepage:  
Personalvideo01:  
Personalvideotext01:  
Personalvideopreview01:  
Personalvideo02:  
Personalvideotext02:  
Personalvideopreview02:  


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