Predicted Microscopic Cortical Brain Images for Optimal Craniotomy Positioning and Visualization.

IF 1.3 Q4 ENGINEERING, BIOMEDICAL Computer Methods in Biomechanics and Biomedical Engineering-Imaging and Visualization Pub Date : 2020-01-01 Epub Date: 2020-10-30 DOI:10.1080/21681163.2020.1834874
Nazim Haouchine, Pariskhit Juvekar, Alexandra Golby, Sarah Frisken
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引用次数: 1

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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预测显微脑皮质图像为最佳开颅定位和可视化。
在开颅手术中,颅骨被打开以允许外科医生进入大脑并进行手术。选择该开口的位置和大小,以避开关键结构,如血管,并便于进入肿瘤。手术计划是根据术前图像完成的,并不考虑术中手术事件。我们提出了一种新的图像引导神经外科系统,以优化开颅开口。使用基于物理的建模,我们定义了一个皮质变形图,用于估计候选开颅位置的位移场。这种变形图与图像类比算法相结合,产生逼真的合成图像,可用于在打开头骨之前预测大脑表面的几何形状和外观。这些图像解释了打开颅骨后可能发生的皮质血管变形,并以一种增加外科医生理解和同化的方式呈现。我们的方法在患者数据上进行了回顾性测试,显示出良好的结果,并证明了我们系统实际应用的可行性。
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来源期刊
CiteScore
2.80
自引率
6.20%
发文量
102
期刊介绍: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization is an international journal whose main goals are to promote solutions of excellence for both imaging and visualization of biomedical data, and establish links among researchers, clinicians, the medical technology sector and end-users. The journal provides a comprehensive forum for discussion of the current state-of-the-art in the scientific fields related to imaging and visualization, including, but not limited to: Applications of Imaging and Visualization Computational Bio- imaging and Visualization Computer Aided Diagnosis, Surgery, Therapy and Treatment Data Processing and Analysis Devices for Imaging and Visualization Grid and High Performance Computing for Imaging and Visualization Human Perception in Imaging and Visualization Image Processing and Analysis Image-based Geometric Modelling Imaging and Visualization in Biomechanics Imaging and Visualization in Biomedical Engineering Medical Clinics Medical Imaging and Visualization Multi-modal Imaging and Visualization Multiscale Imaging and Visualization Scientific Visualization Software Development for Imaging and Visualization Telemedicine Systems and Applications Virtual Reality Visual Data Mining and Knowledge Discovery.
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