Biomedical image processing using FCM algorithm based on the wavelet transform

Abstract

An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated. By using hierarchical wavelet decomposition, an original image could be decomposed into one lower image and several detail images. The segmentation started at the lowest resolution with the FCM clustering algorithm and the texture feature extracted from various sub-bands. With the improvement of the FCM algorithm, FCM alternation frequency was decreased and the accuracy of segmentation was advanced.

Keywords

biomedical image processing / FCM algorithm / wavelet transform / texture feature

References

[1] Li shipu. Biomedical Material Guidance.Wuhan University of Technology Press, 2000, 8

[2] Reed T R, Reed J M H, Buf Du. A Review of Recent Texture Segmentation and Feature Extraction Techniques. Computer Vision Graphics and Image Processing, 1993, 57: 359-372.

[3] Chang T, Kuo Jay. Texture Analysis and Classification with Treestructural Wavelet Transform. IEEE Trans Image Process, 1993, 2(4): 429-440.

[4] Teuner Pichler A, Hosficka B J O. Unsupervised Texture Segmentation of Images Using Tuned Matched Gabor Filters. IEEE Trans. Image Process, 1995, 4(6): 863-870.

[5] Salari E, Ling Z. Texture Segmentation Using Hierarchical Wavelet Decomposition. Pattern Recognition, 1995, 28(12): 819-1824.

[6] Unser M. Texture Classification and Segmentation Using Wavelet Frames. IEEE Trans Image Process, 1995, 4(11): 1549-1560.

[7] Van De Wonwer Schanders G, Van Dyek D P. Statistical Texture Characterization from Discrete Wavelet Representation. IEEE Trans. Image Process, 1999, 8(4): 592-598.

[8] Brooks R R, Grewe Lynne, Iyengar S S. Recognition in the Wavelet Domain: A Survey. Journal of Electronic Image, 2001, 10(3): 757-784.

[9] Pal N R, Bezdek J C. On Cluster Validity for the Fuzzy C-means Model. IEEE Transactions on Fuzzy Systems, 1995, 3(3): 370-379.

[10] Mallat G. Multifrequency Channel Decompositions of Images and Wavelet Models. IEEE Transaction on Acoustics Speech and Processing, 1989, 37(12): 2091-2110.

[11] Chun S LU, Pau C Chuang, Chih F Chen. Unsupervised Texture Segmentationvia Wavelet Transform. Pattern Recognition, 1997, 30(5): 729-742.