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

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A. Hartl, T. Wendler, T. Lasser, J. Traub, S. I. Ziegler, N. Navab
Towards intra-operative 3D nuclear imaging: development and evaluation of ad hoc models
Proceedings of Jahrestagung der deutschen Gesselschaft für Computer- und Roboterassistierte Chirurgie e.V. (CURAC 2007), Karlsruhe, Germany, October 2007 (bib)

Nowadays surgical planning for cancer resection relies usually in systems that provide 3D functional images like PET. However, although such devices would be very useful in the operation cancer itself, in order to localize and characterize the tumor accurately and thus keep tracking of changes in the functional nature of the site, there are no comparable intra-operative tools available. The major reasons for this are limitations of these pre-operative imaging systems in terms of flexibility, resolution and the time required for acquisition. Lately a system based on tracked hand-held gamma-probes was introduced for 3D intra-operative imaging. The procedure follows a similar approach as in SPECT imaging. A tracer is injected into the patient and radiation is acquired by gamma-detector located at a certain position and orientation relative to the bed (i.e. in a certain 'relative pose') for a certain amount of time. Afterward the readings are used to reconstruct a 3D distribution in space. The major difference is, however, that instead of acquiring a multiple readings from a small set of relative poses in a grid, the novel system acquires single readings from a big arbitrary set of poses given by the tracked free movement of probe. This change in the acquisition nature brings also changes in the reconstruction due to the flexible geometry. This work has as objective to deal with the development of models that allow reconstruction of 3D radioactivity distributions in space for the introduced system. It further aims at evaluating these models in terms of quality of reconstruction and computational burden with the motivation of bringing this novel approach closer to the patient.
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