Automatic Boundary Detection in Breast Ultrasound Images Based on Improved Pulse Coupled Neural Network and Active Contour Model

2011 ◽  
Author(s):  
Jing Jiao ◽  
Yuanyuan Wang
Keyword(s):  
Neural Network ◽  
Active Contour ◽  
Active Contour Model ◽  
Boundary Detection ◽  
Breast Ultrasound ◽  
Ultrasound Images ◽  
Pulse Coupled Neural Network ◽  
Contour Model

scholarly journals Active Contour Model for Ultrasound Images with Rayleigh Distribution

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Guodong Wang ◽  
Qian Dong ◽  
Zhenkuan Pan ◽  
Ximei Zhao ◽  
Jinbao Yang ◽  
...  
Keyword(s):  
Active Contour ◽  
Active Contour Model ◽  
Speckle Noise ◽  
Rayleigh Distribution ◽  
Ultrasound Images ◽  
Fast Method ◽  
Split Bregman Method ◽  
Split Bregman ◽  
Multiplicative Noises ◽  
Contour Model

Ultrasound images are often corrupted by multiplicative noises with Rayleigh distribution. The noises are strong and often called speckle noise, so segmentation is a hard work with this kind of noises. In this paper, we incorporate multiplicative noise removing model into active contour model for ultrasound images segmentation. To model gray level behavior of ultrasound images, the classic Rayleigh probability distribution is considered. Our model can segment the noisy ultrasound images very well. Finally, a fast method called Split-Bregman method is used for the easy implementation of segmentation. Experiments on a variety of synthetic and real ultrasound images validate the performance of our method.

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