Analysis and Visualization of Images Overlapping: Automated Versus Expert Anatomical Mapping in Deep Brain Stimulation Targeting

Conference Paper · January 2006with3 Reads
DOI: 10.1007/978-3-540-71027-1_12 · Source: DBLP
Conference: Pixelization Paradigm, First Visual Information Expert Workshop, VIEW 2006, Paris, France, April 24-25, 2006, Revised Selected Papers

    Abstract

    In surgical treatment of Parkinson’s disease, deep brain stimulation requires high-precision positioning of electrodes, needing
    accurate localization and outlines of anatomical targets. Manual procedure of anatomical structures outlining on magnetic
    resonance images (MRI) takes about several hours. We proposed an automated localizing procedure aiming to shorten this task
    to some seconds. Different parameters were simultaneously assessed in our algorithm undertaking segmentation of anatomical
    structures. Intraclass correlation coefficients (ICCs) were computed for centers of gravity coordinates of structures between
    manual expert-mapped MRI and automated-mapped MRI. Tanimoto coefficients were computed accounting for pixels overlapping between
    these two procedures. Although ICCs showed almost perfect concordance, TC provided further information with a quite severe
    value about 35%. For both criteria, results were variable regarding each parameter in our process. With such complex results
    to relate, their presentations were enhanced using visualization methods resembling that of the generalized Case View method.