Title :
Ultrasound Ventricular Contour Extraction Based on an Adaptive GVF Snake Model
Author :
Gong Xiaohong ; Zheng Yinfei
Author_Institution :
Dept. of Biomed. Eng., Zhejiang Univ., Hangzhou, China
Abstract :
In order to accurately extract the ultrasound ventricular contour, an adaptive contour extraction algorithm based on a kind of active contour model was put forward against the shortcomings of the traditional GVF snake model that was difficult to converge to the deep concave edges and noise sensitivity. The algorithm was based on the traditional GGVF snake, which added a pressure pointing to the normal direction of snake contour in the part of external force, and the value of the force was adaptive to the mean gradients of the neighbor contour points. The experimental results show that the algorithm can make the contour converge to the deep cavity border fleetly and improve the robustness to noise. Furthermore, it also can maintain the ability of weak edge extraction which has a good performance of the ultrasound ventricular contour extraction.
Keywords :
biomedical ultrasonics; convergence; edge detection; feature extraction; medical image processing; ultrasonic imaging; GGVF snake; active contour model; adaptive GVF snake model; adaptive contour extraction algorithm; concave edge convergence; contour convergence; edge extraction; neighbor contour point gradient; noise sensitivity; pressure pointing; ultrasound ventricular contour extraction; Convergence; Force; Image edge detection; Image segmentation; Noise; Ultrasonic imaging; Vectors; GGVF snake; adaptive; contour extraction; pressure;
Conference_Titel :
Image and Graphics (ICIG), 2013 Seventh International Conference on
Conference_Location :
Qingdao
DOI :
10.1109/ICIG.2013.52