DocumentCode :
3512637
Title :
HMT Model and B-Spine Wavelet Based Intelligent Medical Image Edge Extraction Algorithm
Author :
Wang, Anna ; Gu, Zhaowei ; Bo, Wang ; Shen, Gongjian
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang
fYear :
2008
fDate :
1-3 Nov. 2008
Firstpage :
552
Lastpage :
555
Abstract :
A new medical image edge extraction algorithm is proposed to extract the significant edge of the medical image to avoid the interference of the internal noise and the external noise. The information measure combined with simulated annealing algorithm is used to remove the internal noise; then wavelet domain HMT model is used to denoise; at last we design quadratic B-spline wavelet to extract the edge feature information. The quadratic B-spline smoothing filter performing multi-scale filtering is designed using the characteristics of wavelet transform. The obtained multi-scale wavelet transform is combined to extract image edge at different scales. The experiment results of computer simulation show that the proposed edge extraction algorithm provides the best compromise between noise rejection and accurate edge localization.
Keywords :
edge detection; feature extraction; filtering theory; medical image processing; simulated annealing; smoothing methods; wavelet transforms; B-spine wavelet; B-spline smoothing filter; HMT model; edge feature information extraction; intelligent medical image edge extraction algorithm; multiscale filtering; multiscale wavelet transform; simulated annealing algorithm; Algorithm design and analysis; Biomedical imaging; Data mining; Interference; Medical simulation; Noise measurement; Simulated annealing; Spline; Wavelet domain; Wavelet transforms; edge extraction; hidden markov tree model; information measure; quadratic B-spline wavelet; simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3391-9
Electronic_ISBN :
978-0-7695-3391-9
Type :
conf
DOI :
10.1109/ICINIS.2008.138
Filename :
4683286
Link To Document :
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