Wavelet-based Image Fusion for Enhancement of ROI in CT Image
Wavelet-based Image Fusion for Enhancement of ROI in CT Image
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DOI：
10.14738/jbemi.14.310
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发表时间：
2014-08
期刊：
影响因子：
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通讯作者：
N. Hai
中科院分区：
文献类型：
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作者：
N. Hai
提出了一种新的CT图像增强方法。在该方法中，利用基于熵的直方图算法来分离CT图像中的重要值，从而得到分离的图像。另外，对原始CT图像和分离后的图像进行小波变换，形成图像融合。因此，利用小波逆变换得到用于诊断的含有肿瘤区域的增强图像。结果是，增强后的图像中的处理区域比原始图像中显示出了更多的突出点。这一结果可以允许医生或医生更准确地诊断和预测增强CT图像中的肿瘤区域
This paper proposes a novel method for enhancing Computed Tomography (CT) image. In this proposed method, the entropy-based histogram algorithm was applied to detach significant values in CT image to produce a detached image. In addition, wavelet transforms were employed for both the original CT image and the detached image to create image fusion. Therefore, an enhanced image with tumor region was obtained for diagnosis using an inverse wavelet transform. The result is that the processed region in the enhanced image shows more prominent points than that in the original image. This result can allow physicians or doctors diagnose and predict more accurately tumor regions in the enhanced CT image