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Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations.

Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations. Research Abstract Details 

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  • Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations. Abstract Text:

    In this article a comprehensive set of registration methods is utilized to provide image-to-physical space registration for image-guided neurosurgery in a clinical study. Central to all methods is the use of textured point clouds as provided by laser range scanning technology. The objective is to perform a systematic comparison of registration methods that include both extracranial (skin marker point-based registration (PBR), and face-based surface registration) and intracranial methods (feature PBR, cortical vessel-contour registration, a combined geometry/intensity surface registration method, and a constrained form of that method to improve robustness). The platform facilitates the selection of discrete soft-tissue landmarks that appear on the patient's intraoperative cortical surface and the preoperative gadolinium-enhanced magnetic resonance (MR) image volume, i.e., true corresponding novel targets. In an 11 patient study, data were taken to allow statistical comparison among registration methods within the context of registration error. The results indicate that intraoperative face-based surface registration is statistically equivalent to traditional skin marker registration. The four intracranial registration methods were investigated and the results demonstrated a target registration error of 1.6 +/- 0.5 mm, 1.7 +/- 0.5 mm, 3.9 +/- 3.4 mm, and 2.0 +/- 0.9 mm, for feature PBR, cortical vessel-contour registration, unconstrained geometric/intensity registration, and constrained geometric/intensity registration, respectively. When analyzing the results on a per case basis, the constrained geometric/intensity registration performed best, followed by feature PBR, and finally cortical vessel-contour registration. Interestingly, the best target registration errors are similar to targeting errors reported using bone-implanted markers within the context of rigid targets. The experience in this study as with others is that brain shift can compromise extracranial registration methods from the earliest stages. Based on the results reported here, organ-based approaches to registration would improve this, especially for shallow lesions.

    Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations. Publishing Authors By Initials

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    Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations. Journal Published:

    PUBLICATION TYPE: Research Support, N.I.H., Extr

    Journal: Medical physics

    VOLUME: 35

    Page Numbers: 1593-605

    Journal Abbreviation:

    ISSN: 0094-2405

    DAY: 21

    MONTH: Apr

    YEAR: 2008

    Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations. Information

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    LANGUAGE: eng

    NlmUniqueID: 425746

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    Grant and Affiliation Information for Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations.

    AFFILIATION: Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37235, USA.

    Country: United States

    United States Research PublicationUnited States Research Publication

    AGENCY: United States NINDS

    GRANT: R01 NS049251-01

    ACRONYM:

    MEDLINETA: Med Phys

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