DocumentCode
2086825
Title
Magnetic Resonance Images Edge Detection Based on Multi-scale Morphology
Author
Wang, Kun ; Wu, Jianhua ; Gao, Liqun ; Pian, Zhaoyu ; Guo, Li
Author_Institution
Northeastern Univ., Shenyang
fYear
2007
fDate
23-27 May 2007
Firstpage
744
Lastpage
747
Abstract
Medical image edge detection is the first and the most important steps in the process of extracting geometric features of the objects in medical image process. Conventionally, edge is detected according to some early brought forward algorithms such as gradient-based algorithm, but they are not so good for noise medical image edge detection. A method is proposed to detect the image edge with Gaussian and salt & pepper noise based on multi-scale morphology in this paper. The resource image is classified into two opposite classes by threshold: object and background. The part which is larger than the threshold uses large-scale structure element to detect the edge, and uses small-scale structure element for the part less than the threshold. Large-scale structure element gets through small-scale structure element´s dilation. The experimental results show that the proposed algorithm is more efficient than the usually used gradient-based edge detecting algorithms.
Keywords
biomedical MRI; edge detection; feature extraction; gradient methods; image classification; image denoising; medical image processing; Gaussian noise; edge detection; geometric features extraction; gradient-based algorithm; image classification; magnetic resonance images; medical image; multiscale image morphology; salt & pepper noise; Biomedical imaging; Educational institutions; Filters; Image edge detection; Information science; Large-scale systems; Magnetic resonance; Morphology; Multi-stage noise shaping; Noise shaping;
fLanguage
English
Publisher
ieee
Conference_Titel
Complex Medical Engineering, 2007. CME 2007. IEEE/ICME International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-1077-4
Electronic_ISBN
978-1-4244-1078-1
Type
conf
DOI
10.1109/ICCME.2007.4381837
Filename
4381837
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