SEPsPage

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

SEPs

Running SEPs

Optimization of a Positron Emission Tomography (PET) reconstruction algorithm

Iterative expectation-maximization algorithms are nowadays the most widespread choice of image reconstruction for tomographic medical scanners. However, due to the exceptional requirements in terms of memory and computation, these algorithms have often been implemented using certain simplifications in the underlying system model. Within the context of our MR/PET research project, our group is currently developing a modified version of the popular OSEM algorithm which does not rely on a simplified system model. This implementation should provide us with the required flexibility to perform an interesting set of experiments on dynamic, motion-compensated image reconstruction. The student will be in charge of analyzing the proposed reconstruction algorithm (C++) and writing an optimized version that minimizes convergence time. In a first stage the code must be studied and modified to reduce memory usage and improve cache reutilization. In a second stage, vectorization and/or GPU programming must be used to accelerate the algorithm. The resulting code will be benchmarked with real clinical data from PET/CT studies.
supervisor:Gaspar Delso
professor:Prof. Nassir Navab
student:
start-end: -
Stent Graft Detection in 2D Xray Images

In the current clinical workflow of endovascular abdominal aortic repairs (EVAR) a stent graft is inserted via an introducer system through one femoral artery into the aneurysmatic aorta under 2D angiographic imaging. Due to the missing depth information in the X-ray visualization, it is highly difficult in particular for junior physicians to place the stent graft in the preoperatively defined position within the aorta. Therefore, methods for accurate stent graft recognition or segmentation in fluoroscopy images are highly required.
supervisor:Stefanie Demirci, Ali Bigdelou
professor:Prof. Dr. Nassir Navab
student:Radhika Tibrewal
start-end: -
Implementation of an AR application for robust marker detection

The main task of this SEP is an implementation of a fiducal marker system, which can detect digital markers, encode them and estimate their correct pose with respect to the camera. This system must have very small inter-marker confusion, false positive- and false negative detection probabilities.
supervisor:Selim BenHimane
professor:Nassir Navab
student:Ivan Borisov
start-end:01.06.2006 - 15.12.2006

Finished SEPs



Edit | Attach | Refresh | Diffs | More | Revision r1.5 - 09 Jun 2005 - 11:55 - AxelMoeller

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