Fast dynamic image segmentation using discrete-time nonlinear dynamics of chaotic neuronal network model

图像分割是医学图像计算机辅助诊断支持系统中必不可少的图像处理技术。提出了一种用于图像分割的混沌神经网络系统，并利用混沌神经网络模型固有的非线性特性研究了快速图像分割系统的开发。首先，我们分析了系统的非线性动力学特性，找到了适合图像分割的系统参数值。接下来，我们演示了该系统运行良好。我们还在一个数字大规模集成电路上实现了它。

Image segmentation is an essential image processing technique in computed aided diagnosis support systems for medical images. We proposed a system called chaotic neuronal network for image segmentation and studied on the development of a fast image segmentation system using the intrinsic nonlinear properties of our chaotic neuronal network model. At first, we analyzed the nonlinear dynamics of our system and found appropriate values of the system parameters for image segmentation. Next, we de-monstrated that the system worked well. We also implemented it on a digital LSI.