Document Detail


Using wavelet denoising and mathematical morphology in the segmentation technique applied to blood cells images.
MedLine Citation:
PMID:  23458301     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
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.
Authors:
Macarena Boix; Begona Canto
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Mathematical biosciences and engineering : MBE     Volume:  10     ISSN:  1551-0018     ISO Abbreviation:  Math Biosci Eng     Publication Date:  2013 Apr 
Date Detail:
Created Date:  2013-03-05     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101197794     Medline TA:  Math Biosci Eng     Country:  United States    
Other Details:
Languages:  eng     Pagination:  279-94     Citation Subset:  IM    
Affiliation:
Universitat Politecnica de Valencia, Plaza Ferrandiz y Carbonell, n.2, Alcoy (Alicante), 03801, Spain. mboix@mat.upv.es.
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