MRI图像中颅内栅格电极定位算法的研究

在癫痫的手术治疗中,往往需要在患者颅内植入电极,通过记录和分析颅内脑电来精确定位致痫病灶.通常情况下电极植入后,依靠MRI检查来定位这些电极的位置并找到它们和脑组织结构的空间位置关系.但是这些电极定位方法不是需要较多的人工参与就是计算效率较低.为此,本文开发了一种只需要用户很少参与,便可以自动高效地在MRI图像中定位颅内栅格电极的算法.本算法充分利用栅格电极的几何特征以及它在MRI图像中的成像表现来对其定位,之后利用一个光滑曲面模型对结果进行修正,最后在重建的三维人脑结构中标定这些电极的位置,从而帮助实现手术前的规划.应用本算法对数例患者的MRI脑图像进行了实验分析,证明了算法的有效性.

Study on the algorithm for locating implanted electrode grids in MR images

In epilepsy surgery,electrodes are often implanted between the skull and brain or inside the brain to record the EEG for locating the seizures onset zone. After the implantation, clinicians usually have to find out the positions of these electrodes with respect to brain structure according to MRI scans. However, the existing locating methods either need much user assistance or are low efficient. We developed an efficient automatic method that could locate the implanted electrodes efficiently with little user interaction. This method makes use of the geometrical character as well as the appearance of electrode grids in MRI images first, and then regularize the result using a smooth curved surface model. Finally these electrodes are visualized in a 3D reconstructed brain model to help the surgery planning. This method was applied on real MRI images and the results proved that the method was very effective for locating implanted electrode grids in MR images.