Tubitak 108E162: Assessment of Fluid Tissue Interaction Using Multi-Modal Image Fusion for Characterization and Progression of Coronary Atherosclerosis
Assist. Prof. Gozde Unal (Principal Investigator),
Prof. Muzaffer Degertekin (Yeditepe University Hospital, Cardiology Department),
Gozde Gul Isguder (MSc Student)
Serhan Gurmeric (MSc Student, Jan 2008- Jan 2010)
Prof. Nassir Navab (Principal Investigator; Technical University of Munich, TUM),
Assoc. Dr. Johannes Rieber (Cardiology Department, Ludwig Maximillian University of Munich LMU Medical School),
Dr. Martin Groher (Post-doc, TUM),
Olivier Pauly (PhD student, TUM),
Steffi Demirci (PhD Student, TUM)
Tubitak-BMBF, TUBITAK- GERMAN BMBF Intense Cooperation Grant
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.
In the framework of the "Assessment of Fluid Tissue Interaction Using Multi-Modal Image Fusion for Characterization and Progression of Coronary Atherosclerosis" project, the following papers are published:
 - Cetin S, Demir A, Yezzi A, Degertekin M, Unal G., "Vessel tractography using an intensity based tensor model with branch detection," IEEE Trans Med Imaging. 2013 Feb;32(2):348-63. doi: 10.1109/TMI.2012.2227118. Epub 2012 Nov 15..
 - Aksoy, Timur and Demirci, Stefanie and Degertekin, Muzaffer and Navab, Nassir and Unal, Gozde, "Template-based CTA X-ray angio rigid registration of coronary arteries in frequency domain with automatic X-Ray segmentation," Medical Physics, vol:40, number:10, October 2013.