Medical Image Segmentation Using Improved Affinity Propagation
Affinity Propagation (AP) is an effective clustering method with a number of advantages over the commonly used k-means clustering. For example, it does not need to specify the number of clusters in advance, and can handle clusters with general topology, which makes it uniquely suitable for medical image segmentation as most of the objects in medical images are not roundly shaped. One factor hampering its applications is its relatively slow speed, especially for large-size images. To overcome this difficulty, we propose in this paper an Improved Affinity Propagation (IMAP) method with several improved features. Particularly, our IMAP method can adaptively select the key parameter p in AP according to the medical image gray histogram, and thus can greatly speed up convergence. Experimental results suggest that IMAP has a higher image entropy, lower class square error contrast, and shorter runtime than the AP algorithm.
KeywordsMedical image segmentation Affinity propagation Gray level histogram
- 8.Jia, S., Qian, Y., Ji, Z.: Band selection for hyperspectral imagery using affinity propagation. In: Proceedings of the 2008 Digital Image Computing: Techniques and Applications, Canberra, ACT, pp. 137–141. IEEE (2008)Google Scholar
- 9.Kelly, K.: Affinity program slashes computing times. Accessed 15 Dec 2007. http://www.news.utoronto.ca/bin6/070215–2952
- 10.Lee, L.K., Liew, S.C., Thong, W.J.: A review of image segmentation methodologies in medical image. In: Sulaiman, H.A., Othman, M.A., Othman, M.F.I., Rahim, Y.A., Pee, N.C. (eds.) Advanced Computer and Communication Engineering Technology. LNEE, vol. 315, pp. 1069–1080. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-07674-4_99 Google Scholar
- 12.Ravindraiah, R., Tejaswini, K.: A survey of image segmentation algorithms based on fuzzy clustering. IJCSMC 2, 200–206 (2013)Google Scholar
- 17.Zhen, D., Zhongshan, H., Jingyu, Y.: A image segmentation method base on Fuzzy c-means. Comput. Res. Dev. 7, 536–541 (1997)Google Scholar