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Data Fusion and Fuzzy Spatial Relationships for Locating Deep Brain Stimulation Targets in Magnetic Resonance Images

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4179))

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Abstract

Symptoms of Parkinson’s disease can be relieved through Deep Brain Stimulation. This neurosurgical technique relies on high precision positioning of electrodes in specific areas of the basal ganglia and the thalamus. In order to identify these anatomical targets, which are located deep within the brain, we developed a semi-automated method of image analysis, based on data fusion. Information provided by both anatomical magnetic resonance images and expert knowledge is managed in a common possibilistic frame, using a fuzzy logic approach. More specifically, a graph-based virtual atlas modeling theoretical anatomical knowledge is matched to the image data from each patient, through a research algorithm (or strategy) which simultaneously computes an estimation of the location of every structures, thus assisting the neurosurgeon in defining the optimal target. The method was tested on 10 images, with promising results. Location and segmentation results were statistically assessed, opening perspectives for enhancements.

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© 2006 Springer-Verlag Berlin Heidelberg

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Villéger, A., Ouchchane, L., Lemaire, JJ., Boire, JY. (2006). Data Fusion and Fuzzy Spatial Relationships for Locating Deep Brain Stimulation Targets in Magnetic Resonance Images. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_83

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  • DOI: https://doi.org/10.1007/11864349_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44630-9

  • Online ISBN: 978-3-540-44632-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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