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Contour Extraction of Skin Tumors Using Visual Attention and GVF-Snake Model

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DOI: 10.4236/eng.2013.510B099    4,331 Downloads   5,089 Views   Citations
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ABSTRACT

Contour extraction of skin tumors accurately is an important task for further feature generation of their borders and sur-faces to early diagnose melanomas. An integrated approach, combining visual attention model and GVF-snake, is pro-posed in the paper to provide a general framework for locating tumor boundaries in case of noise and boundaries with large concavity. For any skin image, the visual attention model is implemented to locate the Region of Interests (ROIs) based on saliency maps. Then an algorithm called GVF-snake is utilized to iteratively drive an initial contour, deriving from the extracted ROIs, towards real boundary of skin tumors by minimizing an energy function. It is shown from ex-periments that the proposed approach exceeds in two aspects compared with other contour-deforming methods: 1) ini-tial contours generated from saliency maps are definitely located at neighboring regions of real boundaries of skin tu-mors to speed up converges of contour deformation and achieve higher accuracy; 2) the method is not sensitive to nois-es on skins and initial contours extracted.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Ma, L. and Su, T. (2013) Contour Extraction of Skin Tumors Using Visual Attention and GVF-Snake Model. Engineering, 5, 482-486. doi: 10.4236/eng.2013.510B099.

References

[1] I. Maglogiannis, S. Pavlopoulos and D. Koutsouris, “An Integrated Computer Supported Acquisition, Handling and Characterization System for Pigmented Skin Lesions in Dermatological Images,” Information Technology in Biomedicine, Vol. 9, No. 1, 2005, pp. 86-98.
[2] M. Kass, A. Witkin and D. Terzopoulos, “Snakes: Active Contour Models,” International Journal of Computer Vision, Vol. 1, 1998, pp. 321-331. http://dx.doi.org/10.1007/BF00133570
[3] C. Xu and J. L. Prince, “Snakes, Shapes and Gradient Vector Flow,” IEEE Transactions on Image Processing, Vol. 7, 1998, pp. 359-369. http://dx.doi.org/10.1109/83.661186
[4] T. Cootes, “An Introduction to Active Shape Models,” Image Processing and Analysis, 2000, pp. 223-248.
[5] C.-C. Liu, C.-Y. Tsai, T.-S. Tsui and S.-S. Yu, “An Improved GVF Snake Based Breast Region Extrapolation Scheme for Digital Mammograms,” Expert Systems with Applications, 2011, pp. 1-6.
[6] B. R. Wu, M. Xie, G. Li and J. J. Gao, “Medical Image Segmentation Based on GVF Snake Model,” IEEE Conference on Second International Intelligent Computation Technology and Automation, Vol. 1, 2009, pp. 637-640.
[7] L. Itti, C. Koch and E. Niebur, “A Model for Saliency-Based Visual Attention for Rapid Scene Analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 11, 1998, pp. 1254-1259.
[8] J. L. Prince and C. Xu, “A New External Force Model for Snakes,” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997, pp. 66-71.

  
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