Limits...
Convolutional virtual electric field for image segmentation using active contours.

Wang Y, Zhu C, Zhang J, Jian Y - PLoS ONE (2014)

Bottom Line: Gradient vector flow (GVF) is an effective external force for active contours; however, it suffers from heavy computation load.Meanwhile, the CONVEF model can also be implemented in real-time by using FFT.Experimental results illustrate these advantages of the CONVEF model on both synthetic and natural images.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science, Tianjin University of Technology, Tianjin, China.

ABSTRACT
Gradient vector flow (GVF) is an effective external force for active contours; however, it suffers from heavy computation load. The virtual electric field (VEF) model, which can be implemented in real time using fast Fourier transform (FFT), has been proposed later as a remedy for the GVF model. In this work, we present an extension of the VEF model, which is referred to as CONvolutional Virtual Electric Field, CONVEF for short. This proposed CONVEF model takes the VEF model as a convolution operation and employs a modified distance in the convolution kernel. The CONVEF model is also closely related to the vector field convolution (VFC) model. Compared with the GVF, VEF and VFC models, the CONVEF model possesses not only some desirable properties of these models, such as enlarged capture range, u-shape concavity convergence, subject contour convergence and initialization insensitivity, but also some other interesting properties such as G-shape concavity convergence, neighboring objects separation, and noise suppression and simultaneously weak edge preserving. Meanwhile, the CONVEF model can also be implemented in real-time by using FFT. Experimental results illustrate these advantages of the CONVEF model on both synthetic and natural images.

Show MeSH

Related in: MedlinePlus

Results on an ultrasound image.(a) Ultrasound heart image, (b) VEF field, (c) convergence of CONVEF snake and (d) its CONVEF field with n = 2.0, h = 10.0.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4216009&req=5

pone-0110032-g009: Results on an ultrasound image.(a) Ultrasound heart image, (b) VEF field, (c) convergence of CONVEF snake and (d) its CONVEF field with n = 2.0, h = 10.0.

Mentions: The CONVEF snake is also applied to real noisy medical images. The first example is an ultrasound heart image with weak edges on the upper-left region. The original image and the VEF field are shown in Figs. 9(a) and (b), respectively. It can be seen from Fig. 9(b) that the VEF field overwhelms the weak edge and flows into the blood pool. It is sure that the VEF snake cannot extract the endocardium correctly whatever is the initial contour. The evolution and the corresponding force field of the CONVEF snake are shown in Figs. 9(c) and (d), respectively. Although the speckle noise is troublesome, the CONVEF field within the blood pool is fairly regular and the CONVEF snake works well. This shows once again that the CONVEF snake provides a superior alternative to the VEF snake.


Convolutional virtual electric field for image segmentation using active contours.

Wang Y, Zhu C, Zhang J, Jian Y - PLoS ONE (2014)

Results on an ultrasound image.(a) Ultrasound heart image, (b) VEF field, (c) convergence of CONVEF snake and (d) its CONVEF field with n = 2.0, h = 10.0.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4216009&req=5

pone-0110032-g009: Results on an ultrasound image.(a) Ultrasound heart image, (b) VEF field, (c) convergence of CONVEF snake and (d) its CONVEF field with n = 2.0, h = 10.0.
Mentions: The CONVEF snake is also applied to real noisy medical images. The first example is an ultrasound heart image with weak edges on the upper-left region. The original image and the VEF field are shown in Figs. 9(a) and (b), respectively. It can be seen from Fig. 9(b) that the VEF field overwhelms the weak edge and flows into the blood pool. It is sure that the VEF snake cannot extract the endocardium correctly whatever is the initial contour. The evolution and the corresponding force field of the CONVEF snake are shown in Figs. 9(c) and (d), respectively. Although the speckle noise is troublesome, the CONVEF field within the blood pool is fairly regular and the CONVEF snake works well. This shows once again that the CONVEF snake provides a superior alternative to the VEF snake.

Bottom Line: Gradient vector flow (GVF) is an effective external force for active contours; however, it suffers from heavy computation load.Meanwhile, the CONVEF model can also be implemented in real-time by using FFT.Experimental results illustrate these advantages of the CONVEF model on both synthetic and natural images.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science, Tianjin University of Technology, Tianjin, China.

ABSTRACT
Gradient vector flow (GVF) is an effective external force for active contours; however, it suffers from heavy computation load. The virtual electric field (VEF) model, which can be implemented in real time using fast Fourier transform (FFT), has been proposed later as a remedy for the GVF model. In this work, we present an extension of the VEF model, which is referred to as CONvolutional Virtual Electric Field, CONVEF for short. This proposed CONVEF model takes the VEF model as a convolution operation and employs a modified distance in the convolution kernel. The CONVEF model is also closely related to the vector field convolution (VFC) model. Compared with the GVF, VEF and VFC models, the CONVEF model possesses not only some desirable properties of these models, such as enlarged capture range, u-shape concavity convergence, subject contour convergence and initialization insensitivity, but also some other interesting properties such as G-shape concavity convergence, neighboring objects separation, and noise suppression and simultaneously weak edge preserving. Meanwhile, the CONVEF model can also be implemented in real-time by using FFT. Experimental results illustrate these advantages of the CONVEF model on both synthetic and natural images.

Show MeSH
Related in: MedlinePlus