核磁共振和回声图像的神经居民分割心脏结构

R. Poli, G. Valli
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引用次数: 21

摘要

描述了医学成像中心脏结构分割问题的一种新方法。该方法基于繁殖和选择人工生物的想法,这些生物生活在这样的图像中,并被喂食要分割的结构的边界。作者的生物Gnets是基于循环神经网络的简单个体,它们可以看到,知道自己在环境中的位置,在环境中移动并进食。它们的行为是通过一种遗传算法发展起来的,这种算法可以保持一个种群,并与最优秀的个体交配。在一组已知分割的测试图像上评估性能。本文报道了该方法的初步结果
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Neural inhabitants of MR and echo images segment cardiac structures
Describes a new approach to the problem of the segmentation of cardiac structures in medical imaging. The approach is based on the idea of breeding and selecting artificial creatures who live in such images and are fed with the boundaries of the structures to be segmented. The authors' creatures, the Gnets, are simple individuals based on recurrent neural networks who can see, know their position in the environment, move inside it and eat. Their behavior is developed through a genetic algorithm which keeps a population of Gnets and mates the best individuals. Performance is evaluated on a set of test images of known segmentation. Preliminary results of this approach are reported.<>
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