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Atlas-Based Segmentation of the Subthalamic Nucleus, Red Nucleus, and Substantia Nigra for Deep Brain Stimulation by Incorporating Multiple MRI Contrasts

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Information Processing in Computer-Assisted Interventions (IPCAI 2012)

Abstract

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy for drug-resistant Parkinson’s disease (PD). Pre-operative identification of the STN is an important step for this neurosurgical procedure, but is very challenging because of the accuracy necessary to stimulate only a sub-region of the small STN to achieve the maximum therapeutic benefits without serious side effects. Previously, a technique that automatically identified basal ganglia structures was proposed by registering a 3D histological atlas to a subject’s anatomy shown in the T1w MRI image. In this paper, we improve the accuracy of this technique for the segmentation of the STN, substantia nigra (SN), and red nucleus (RN). This is achieved by using additional MRI contrasts (i.e. T2*w and T2w images) that can better visualize these nuclei compared to the sole T1w contrast used previously. Through validation using the silver standard ground truth obtained for 6 subjects (3 healthy and 3 PD), we observe significant improvements for segmenting the STN, SN, and RN with the new technique when compared to the previous method that only uses T1w-T1w inter-subject registration.

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© 2012 Springer-Verlag Berlin Heidelberg

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Xiao, Y. et al. (2012). Atlas-Based Segmentation of the Subthalamic Nucleus, Red Nucleus, and Substantia Nigra for Deep Brain Stimulation by Incorporating Multiple MRI Contrasts. In: Abolmaesumi, P., Joskowicz, L., Navab, N., Jannin, P. (eds) Information Processing in Computer-Assisted Interventions. IPCAI 2012. Lecture Notes in Computer Science, vol 7330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30618-1_14

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  • DOI: https://doi.org/10.1007/978-3-642-30618-1_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30617-4

  • Online ISBN: 978-3-642-30618-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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