Ultrasound Doppler tissue image analysis based on neural network

Shukui Zhao; Deyu Li; Lixue Yin; Tianfu Wang; Changqiong Zheng; Yi Zheng

doi:10.1117/12.441694

20 September 2001 Ultrasound Doppler tissue image analysis based on neural network

Shukui Zhao, Deyu Li, Lixue Yin, Tianfu Wang, Changqiong Zheng, Yi Zheng

Proceedings Volume 4555, Neural Network and Distributed Processing; (2001) https://doi.org/10.1117/12.441694
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

A new method for quantitative analysis of ultrasound Doppler tissue images (DTI) has been developed based on a neural network. The method aims to extract numerical data of velocity or acceleration from DTI images and analyze them quantitatively. A three-layered back propagation (BP) neural network is used to accomplish this task. The input of the network is the differences between the red, green and blue components of pixels and the output is the acceleration or velocity values. The network is trained with the color bars in the DTI images. The result of analyzing the movement of the left ventricle anterior free wall (LVAW) from DTA (DTI acceleration mode) image sequences is presented. The result of time-acceleration curve is highly correlated with the electrocardiogram (ECG) curve and gives us a quantitative and graphic description of the ventricle movement in cardiac cycles. It shows the movement characteristics of the left ventricle in cardiac cycles and also shows the excitation differences among the three layers of the myocardium. It is demonstrated that the method has great potential to characterize myocardial movement, which may provide a new way to characterize cardiac activities.

Citation Download Citation

Shukui Zhao, Deyu Li, Lixue Yin, Tianfu Wang, Changqiong Zheng, and Yi Zheng "Ultrasound Doppler tissue image analysis based on neural network", Proc. SPIE 4555, Neural Network and Distributed Processing, (20 September 2001); https://doi.org/10.1117/12.441694

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