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Predicted Microscopic Cortical Brain Images for Optimal Craniotomy Positioning and Visualization

Abstract : During a craniotomy, the skull is opened to allow surgeons to have access to the brain and perform the procedure. The position and size of this opening are chosen in a way to avoid critical structures, such as vessels, and facilitate the access to tumors. Planning the operation is done based on pre-operative images and does not account for intra-operative surgical events. We present a novel image-guided neurosurgical system to optimize the craniotomy opening. Using physics-based modeling we define a cortical deformation map that estimates the displacement field at candidate craniotomy locations. This deformation map is coupled with an image analogy algorithm that produces realistic synthetic images that can be used to predict both the geometry and the appearance of the brain surface before opening the skull. These images account for cortical vessel deformations that may occur after opening the skull and is rendered in a way that increases the surgeon's understanding and assimilation. Our method was tested retrospectively on patients data showing good results and demonstrating the feasibility of practical use of our system.
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https://hal.inria.fr/hal-03065619
Contributor : Nazim Haouchine <>
Submitted on : Monday, December 14, 2020 - 8:52:37 PM
Last modification on : Thursday, December 17, 2020 - 4:13:41 AM

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  • HAL Id : hal-03065619, version 1

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Nazim Haouchine, Pariskhit Juvekar, Alexandra Golby, Sarah Frisken. Predicted Microscopic Cortical Brain Images for Optimal Craniotomy Positioning and Visualization. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, Taylor & Francis, 2020. ⟨hal-03065619⟩

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