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Localization of deep brain stimulation electrodes via metal artifacts in CT images
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2014 (English)In: Proc. 36th International Conference of the IEEE Engineering in Medicine and Biology Society, Curran Associates, Inc., 2014, 1055-1058 p.Conference paper, Published paper (Refereed)
Abstract [en]

In Deep Brain Stimulation (DBS), the location of implanted electrodes in the brain has direct influence on the therapeutic effect of the treatment. This work deals with estimating the position of the implanted DBS electrodes from the images registered by X-ray Computed Tomography (CT) scanners. A technique named junction method that takes advantage of the streak artifacts created by the metal parts of the electrodes in CT images is proposed for this purpose. To start with, the brain image is extracted by defining a brain mask. Next, the edges are intensified by applying a Gaussian convolution operator followed by a measure of the second derivative of the image along all directions in the image plane. Criteria of adjacency and length are applied to the lines detected by the Hough transform to distinguish between tracks of streak artifacts and the brain structure. At some points, straight lines are distorted by noise. To handle this issue, all lines that fit same line equation are merged. The horizontal line connecting the two DBS electrodes (one in each cerebral hemisphere) is called electrode line. To specify the electrodes position, intersections of the electrode line with every other line are marked. Finally, to obtain the vertical position estimate, the above algorithm is applied to the image stack.

Place, publisher, year, edition, pages
Curran Associates, Inc., 2014. 1055-1058 p.
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-252476DOI: 10.1109/EMBC.2014.6943775ISI: 000350044701014ISBN: 978-1-4244-7929-0 (print)OAI: oai:DiVA.org:uu-252476DiVA: diva2:810805
Conference
EMBC 2014, August 26–30, Chicago, IL
Available from: 2014-08-30 Created: 2015-05-07 Last updated: 2015-05-13Bibliographically approved

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Medvedev, Alexander

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