Using wavelet denoising and mathematical morphology in the segmentation technique applied to blood cells images.

Accurate image segmentation is used in medical diagnosis since this technique is a noninvasive pre-processing step for biomedical treatment. In this work we present an efficient segmentation method for medical image analysis. In particular, with this method blood cells can be segmented. For that, we combine the wavelet transform with morphological operations. Moreover, the wavelet thresholding technique is used to eliminate the noise and prepare the image for suitable segmentation. In wavelet denoising we determine the best wavelet that shows a segmentation with the largest area in the cell. We study different wavelet families and we conclude that the wavelet db1 is the best and it can serve for posterior works on blood pathologies. The proposed method generates goods results when it is applied on several images. Finally, the proposed algorithm made in MatLab environment is verified for a selected blood cells.

[1]  Yi-Ping Hung,et al.  A Learning State-Space Model for Image Retrieval , 2007, EURASIP J. Adv. Signal Process..

[2]  Larry S. Davis,et al.  Parallel algorithms for image enhancement and segmentation by region growing, with an experimental study , 2004, The Journal of Supercomputing.

[3]  Pierre Soille,et al.  Morphological Image Analysis: Principles and Applications , 2003 .

[4]  Bijoy K. Ghosh,et al.  Multiresolution filtering with application to image segmentation , 1996 .

[5]  Yuan Zhou,et al.  A novel color image segmentation method and its application to white blood cell image analysis , 2006, 2006 8th international Conference on Signal Processing.

[6]  Stéphane Mallat,et al.  Zero-crossings of a wavelet transform , 1991, IEEE Trans. Inf. Theory.

[7]  Tsuhan Chen,et al.  DISCOV: A Framework for Discovering Objects in Video , 2008, IEEE Transactions on Multimedia.

[8]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .

[9]  Kan Jiang,et al.  A novel white blood cell segmentation scheme using scale-space filtering and watershed clustering , 2003, Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).

[10]  Dwi Anoraganingrum,et al.  Cell segmentation with median filter and mathematical morphology operation , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[11]  Jiang Bo,et al.  Wavelet transform and morphology image segmentation algorism for blood cell , 2009, 2009 4th IEEE Conference on Industrial Electronics and Applications.

[12]  Stéphane Mallat,et al.  Singularity detection and processing with wavelets , 1992, IEEE Trans. Inf. Theory.

[13]  Chi Chung Ko,et al.  Video object segmentation and tracking for content-based video coding , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[14]  Ron Kikinis,et al.  Improved watershed transform for medical image segmentation using prior information , 2004, IEEE Transactions on Medical Imaging.

[15]  David L. Donoho,et al.  De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.

[16]  Jie Liang,et al.  Application of wavelet transform in travelling wave protection , 2000 .

[17]  Meng Wang,et al.  NOVEL CELL SEGMENTATION AND ONLINE LEARNING ALGORITHMS FOR CELL PHASE IDENTIFICATION IN AUTOMATED TIME-LAPSE MICROSCOPY , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[18]  Bi Ning,et al.  Image coding based on multiband wavelet and adaptive quad-tree partition , 2006 .

[19]  Boying Wu,et al.  A novel variational model for image segmentation , 2011, J. Comput. Appl. Math..

[20]  Pingyu Liu,et al.  Partial differential equations-based segmentation for radiotherapy treatment planning. , 2005, Mathematical biosciences and engineering : MBE.

[21]  Jasprit Singh,et al.  Color Image Segmentation and Multi-Level Thresholding by Maximization of Conditional Entropy , 2007 .

[22]  Hamid R. Arabnia,et al.  Parallel Edge-Region-Based Segmentation Algorithm Targeted at Reconfigurable MultiRing Network , 2003, The Journal of Supercomputing.