Vascular image registration techniques: A living review.
Registration of vascular structures is crucial for preoperative planning, intraoperative navigation, and follow-up assessment. Typical applications include, but are not limited to, Trans-catheter Aortic Valve Implantation and monitoring of tumor vasculature or aneurysm growth. In order to achieve the aforementioned goals, a large number of various registration algorithms has been developed. With this review paper we provide a comprehensive overview over the plethora of existing techniques with a particular focus on the suitable classification criteria such as the involved modalities of the employed optimization methods. However, we wish to go beyond a static literature review which is naturally doomed to be outdated after a certain period of time due to the research progress. We augment this review paper with an extendable and interactive database in order to obtain a living review whose currency goes beyond the one of a printed paper. All papers in this database are labeled with one or multiple tags according to 13 carefully defined categories. The classification of all entries can then be visualized as one or multiple trees which are presented via a web-based interactive app (http://livingreview.in.tum.de) allowing the user to choose a unique perspective for literature review. In addition, the user can search the underlying database for specific tags or publications related to vessel registration. Many applications of this framework are conceivable, including the use for getting a general overview on the topic or the utilization by physicians for deciding about the best-suited algorithm for a specific application.
Computer Aided Medical Procedures, Technische Universität München, Munich, Germany. Electronic address: stefan.matl@tum.de.
Stefan
S
Matl
Computer Aided Medical Procedures, Technische Universität München, Munich, Germany. Electronic address: r.brosig@tum.de.
Richard
R
Brosig
Computer Aided Medical Procedures, Technische Universität München, Munich, Germany. Electronic address: maximilian.baust@tum.de.
Maximilian
M
Baust
Computer Aided Medical Procedures, Technische Universität München, Munich, Germany; Whiting School of Engineering, Johns Hopkins University, Baltimore MD, US. Electronic address: nassir.navab@tum.de.
Nassir
N
Navab
Computer Aided Medical Procedures, Technische Universität München, Munich, Germany. Electronic address: stefanie.demirci@tum.de.
Stefanie
S
Demirci
D000465:Algorithms; D001808:Blood Vessels / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000592:standards; D015203:Reproducibility of Results
Living review; Medical image registration; Vascular models; Vascular registration techniques