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首页> 外文会议>Image Processing pt.3; Progress in Biomedical Optics and Imaging; vol.8,no.31; Proceedings of SPIE-The International Society for Optical Engineering; vol.6512 pt.3 >Automated Definition of Mid-Sagittal Planes for MRI Brain Scans
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Automated Definition of Mid-Sagittal Planes for MRI Brain Scans

机译：MRI脑部扫描的矢状中平面的自动定义

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摘要

In most magnetic resonance imaging (MRI) clinical examinations, the orientation and position of diagnostic scans are manually defined by MRI operators. To accelerate the workflow, algorithms have been proposed to automate the definition of the MRI scanning planes. A mid-sagittal plane (MSP), which separates the two cerebral hemispheres, is commonly used to align MRI neurological scans, since it standardizes the visualization of important anatomy. We propose an algorithm to define the MSP automatically based on lines separating the cerebral hemispheres in 2D coronal and transverse images. Challenges to the automatic definition of separation lines are disturbances from the inclusion of the shoulder, and the asymmetry of the brain. The proposed algorithm first detects the position of the head by fitting an ellipse that maximizes the image gradient magnitude in the boundary region of the ellipse. A symmetrical axis is then established which minimizes the difference between the image on either side of the axis. The pixels at the space between the hemispheres are located in the adjacent area of the symmetrical axis, and a linear regression with robust weights defines a line that best separates the two hemispheres. The geometry of MSP is calculated based on the separation lines in the coronal and transverse views. Experiments on 100 images indicate that the result of the proposed algorithm is consistent with the results obtained by domain experts and is significantly faster.
机译：在大多数磁共振成像（MRI）临床检查中，诊断扫描的方向和位置是由MRI操作员手动定义的。为了加快工作流程，已经提出了算法来自动定义MRI扫描平面。分开两个大脑半球的中矢状平面（MSP）通常用于对齐MRI神经扫描，因为它标准化了重要解剖结构的可视化。我们提出了一种基于二维冠状和横断面图像中分隔脑半球的线自动定义MSP的算法。自动定义分隔线的挑战是肩部夹杂物的干扰以及大脑的不对称性。提出的算法首先通过拟合一个椭圆来检测头部的位置，该椭圆使椭圆边界区域中的图像梯度幅度最大。然后建立一个对称轴，该轴使该轴两侧的图像之间的差异最小。半球之间的空间处的像素位于对称轴的相邻区域，具有稳健权重的线性回归定义了一条最能分隔两个半球的线。 MSP的几何形状是根据冠状视图和横向视图中的分隔线计算的。在100张图像上进行的实验表明，该算法的结果与领域专家获得的结果一致，并且速度更快。

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