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METHOD FOR OPTIMIZING ULTRASONIC IMAGING SYSTEM PARAMETER BASED ON DEEP LEARNING

机译:基于深度学习优化超声成像系统参数的方法

摘要

A method for optimizing an ultrasonic imaging system parameter based on deep learning, comprising the following steps: step 1: collecting samples for training neural networks, the samples comprising ultrasound image samples i, and a corresponding ultrasonic imaging system parameter vector sample p used by an ultrasonic imaging system when the ultrasonic image samples are collected; step 2: establishing a neural network model and training the neural networks to convergence by using the samples collected = in step 1, so as to obtain a trained neural network system onn; and step 3: taking the original ultrasonic imaging system parameter vector p or the original ultrasonic image as an input to be input into the neural network system onn trained in step 2, at this moment, a parameter obtained from an output end of onn being an optimized ultrasonic imaging system parameter vector ep=onn(p). By means of the method, the purpose of improving the ultrasonic image quality is realized by optimizing the ultrasonic imaging system parameter.
机译:一种用于优化基于深度学习的超声成像系统参数的方法,包括以下步骤:步骤1:收集用于训练神经网络的样本,包括超声图像样本I的样本,以及由此使用的相应的超声成像系统参数矢量样本P.超声成像系统收集超声图像样品时;步骤2:建立神经网络模型并通过使用在步骤1中收集的样本训练神经网络以收敛,从而获得培训的神经网络系统ONN;和步骤3:以原始超声成像系统参数矢量p或原始超声图像作为输入到在步骤2中训练的神经网络系统ONN中,此时从ONN的输出端获得的参数优化超声成像系统参数矢量EP = ONN(P)。通过该方法,通过优化超声成像系统参数来实现改善超声图像质量的目的。

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