用自产生和自组织神经网络对超声医学图像进行自动分割

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Abstract The automatic segmentation of ultrasonic heart image using self-creating and organizing neural network has been studied. This kind of unsupervised clustering method can search for the optimal number of output nodes automatically to get the number of textures in the image, and finish the automatic segmentation. Experimental results show that this method has significant benefits over self-organizing neural network method.

Key words： Self-organizing feature map Self-creating and organizing neural network Image segmentation Medical ultrasonic image

Received: 22 April 1997

PACS:	TN911.73
	TN-052

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	Wang Tianfu
	Li Deyu
	Zheng Changqiong
	Zheng Yi
	Ran Junguo

Cite this article:

Wang Tianfu,Li Deyu,Zheng Changqiong等. AUTOMATIC SEGMENTATION OF MEDICAL ULTRASONIC IMAGE USING SELF-CREATING AND ORGANIZING NEURAL NETWORK[J]. , 1999, 21(1): 124-127 .

URL:

http://jeit.ie.ac.cn/EN/ OR http://jeit.ie.ac.cn/EN/Y1999/V21/I1/124

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