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引用次数: 4

摘要

通过不同方式的图像融合可以增强医学图像提供的诊断疾病的重要信息。本文介绍了一种将不同模态图像的特征进行融合的方法。将离散小波变换(DWT)和基于主成分分析(PCA)的融合技术应用于多模态医学图像,实现了一种简单、可靠的图像融合检测技术。该系统涵盖了基于PCA和DWT的图像融合质量分析用于肿瘤检测,实验结果表明,基于主成分分析和离散小波变换的融合规则既保留了源图像的原始结构信息,又增强了源图像的相关信息。
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An enhancement in detection of brain cancer through image fusion
An important information provided by the medical image to diagnose the disease can be enhanced through image fusion using different modalities. This paper introduces the fusion process which allows combination of features of different modality images. It consists of application of Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) based fusion to multi-modality medical images, results in an easy and reliable technique to detect cancerous tissues through image fusion. The system defined below covers the PCA and DWT based image fusion quality analysis for detection of cancer tumour and the experimental results gives the effectiveness of fusion rule based on principal component analysis and discrete wavelet transform which preserves the original structural information from source image and also enhances the relevant information from the same.
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