Medical Image Segmentation Based on Wavelet Analysis and Gradient Vector Flow


Medical image segmentation is one of the key technologies in computer aided diagnosis. Due to the complexity and diversity of medical images, the wavelet multi-scale analysis is introduced into GVF (gradient vector flow) snake model. The modulus values of each scale and phase angle values are calculated using wavelet transform, and the local maximum points of modulus values, which are the contours of the object edges, are obtained along phase angle direction at each scale. Then, location of the edges of the object and segmentation is implemented by GVF snake model. The experiments on some medical images show that the improved algorithm has small amount of computation, fast convergence and good robustness to noise.

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Zhao, J. , Zhang, L. and Yin, M. (2014) Medical Image Segmentation Based on Wavelet Analysis and Gradient Vector Flow. Journal of Software Engineering and Applications, 7, 1019-1030. doi: 10.4236/jsea.2014.712089.

Conflicts of Interest

The authors declare no conflicts of interest.


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