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Brain cine MRI segmentation based on a multiagent algorithm for dynamic continuous optimization

机译:基于多智能体算法的脑电影MRI分割的动态连续优化

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In this paper, we propose a multiagent based evolution strategy algorithm, called CMADO, to evaluate the amplitudes of the deformations of the walls of the third cerebral ventricle on a brain cine-MR imaging. CMADO based segmentation technique is applied on a 2D+t dataset to detect the contours of the region of interest (i.e. lamina terminalis). Then, the successive segmented contours are matched using a procedure of global alignment. Finally, local measurements of deformations are derived from the previously determined matched contours. The validation step is realized by comparing our results to the measurements achieved on the same patients through a manual segmentation provided by an expert using Ethovision® software.
机译:在本文中,我们提出了一种基于多代理的进化策略算法,称为CMADO,用于在脑电影MR成像中评估第三脑室壁的变形幅度。将基于CMADO的分割技术应用于2D + t数据集,以检测感兴趣区域(即椎板末端)的轮廓。然后,使用整体对准的过程来匹配连续的分段轮廓。最后,从先前确定的匹配轮廓中得出变形的局部测量值。通过将我们的结果与通过使用Ethovision®软件的专家提供的手动分段在相同患者上获得的测量结果进行比较来实现验证步骤。

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