A Adaptive Segmentation Algorithms of Ultrasonic Image Based on Simplified PCNN

被引:0
|
作者
Liu, Yijie [1 ]
Zhang, Yanzhu [1 ]
Huang, Jingjing [1 ]
机构
[1] Shenyang Ligong Univ, Sch Automat & Elect Engn, Shenyang, Liaoning, Peoples R China
关键词
Ultrasound image; Pulsecoupled neural networks; The maximum entropy; Particle swarm optimization; Adaptive segmentation algorithm;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
the imaging characteristics of the ultrasound image, the segmentation research progress slowly. In this paper,a new segmentation algorithm based on PCNN to the ultrasonic image was provided. Aim at the problem which is hard to determine the parameters for the PCNN in the past segmentation algorithm, so the new image segmentation method was proposed that banded automatic optimization ability of PSO and used the improved maximum entropy function as the fitness function. Through the simulation experiments show that, the segmentation result diagram of this article represents a good robustness. When it is used in the segmentation of the primary liver cancer ultrasound ima ge, it can clearly separate the entity giant lesion area of the liver membrane area. It provides a reliable basis of the diagnosed type of the patient for the doctor and improves the diagnosis accuracy of the doctor.
引用
收藏
页码:784 / 788
页数:5
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