Active contour model driven by global and local intensity information for ultrasound image segmentation

2018 ◽  
Vol 75 (12) ◽  
pp. 4286-4299 ◽  
Author(s):  
Lingling Fang ◽  
Tianshuang Qiu ◽  
Yin Liu ◽  
Chaofeng Chen
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Active Contour Model ◽  
Ultrasound Image ◽  
Model Driven ◽  
Contour Model ◽  
Intensity Information ◽  
Ultrasound Image Segmentation ◽  
Local Intensity ◽  
Global And Local

TWO NOVEL ACM (ACTIVE CONTOUR MODEL) METHODS FOR INTRAVASCULAR ULTRASOUND IMAGE SEGMENTATION

2010 ◽  
Author(s):  
Chi Hau Chen ◽  
Labhesh Potdat ◽  
Rakesh Chittineni ◽  
Donald O. Thompson ◽  
Dale E. Chimenti
Keyword(s):  
Image Segmentation ◽  
Intravascular Ultrasound ◽  
Active Contour ◽  
Active Contour Model ◽  
Ultrasound Image ◽  
Contour Model ◽  
Ultrasound Image Segmentation

A hybrid active contour model for ultrasound image segmentation

2020 ◽  
Vol 24 (24) ◽  
pp. 18611-18625
Author(s):  
Lingling Fang ◽  
Xiaohang Pan ◽  
Yibo Yao ◽  
Lirong Zhang ◽  
Dongmei Guo
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Active Contour Model ◽  
Ultrasound Image ◽  
Contour Model ◽  
Ultrasound Image Segmentation

An Improved Image Segmentation Active Contour Model

2014 ◽  
Vol 513-517 ◽  
pp. 3463-3467
Author(s):  
Li Fen Zhou ◽  
Chang Xu Cai
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Image Segmentation ◽  
Active Contour ◽  
Active Contour Model ◽  
Local Region ◽  
Intensity Inhomogeneity ◽  
Contour Model ◽  
Global And Local ◽  
Region Information

The Chan-Vese (C-V) active contour model has low computational complexity, initialization and insensitive to noise advantagesand utilizes global region information of images, so it is difficult to handle images with intensity inhomogeneity. The Local binary fitting (LBF) model based on local region information has its certain advantages in mages segmentation of weak boundary or uneven greay.but , the segmentation results are very sensitive to the initial contours, In order to address this problem, this paper proposes a new active contour model with a partial differential equation, which integrates both global and local region information. Experimental results show that it has a distinctive advantage over C-V model for images with intensity inhomogeneity, and it is more efficient than LBF.

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