Medical Image Fusion Based on Wavelet Transform and Independent Component Analysis

被引：16

作者：

Cui, Zhiming ^{[1
]}

Zhang, Guangming ^{[1
]}

Wu, Jian ^{[1
]}

机构：

[1] Soochow Univ, Inst Intelligent Informat Proc & Applicat, Suzhou 215006, Peoples R China

来源：

FIRST IITA INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2009年

关键词：

CT medical image; fusion; wavelet transform; independent component analysis;

D O I：

10.1109/JCAI.2009.169

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

By analyzing the characters of CT medical image, this paper proposes a novel method for this particular image fusion, which is using discrete wavelet transform and independent component analysis. Firstly, each of CT images were decomposed by 2-D discrete wavelet transform. Then independent component analysis were used to analyse the wavelet coefficients in different level for acquiring independent component. At last, we use wavelet reconstruction to synthesize one CT medical image which could contain more integrated accurate detail information of different soft tissue such as muscles and blood vessels. By contrast, the efficiency of our method is better than weighted average, laplacian pyramid method in medical image fusion field.

引用

页码：480 / 483

页数：4

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