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首页> 外文期刊>International Journal of Applied Engineering Research >Wavelet based segmentation of Liver Tumors from CT Images
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Wavelet based segmentation of Liver Tumors from CT Images

机译:基于小波的CT图像肝肿瘤的分割

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摘要

Computer aided liver image analysis is of profound interest in recent years due to their faster, accurate and reliable characteristics. Qualitative methods include contrast stretching, smoothness, brightness, sharpness etc. Quantitative analysis, on the other hand make use of geometrical measurements such as area, perimeter, diagonal length, horizontal and vertical width etc. These methods of analysis have their own shortcomings due to the characteristics of tumors. Usually they are not in geometric shape which makes the analysis much more difficult and complex. In this work wavelet based image segmentation of liver tumor was performed. The computation time for segmentation is significantly reduced by using Wavelet decomposition method. The segmented results were further subjected to quantitative and qualitative analysis to compare the segmentation results obtained from three different wavelets such as Daubechies, Haar and Coiflet wavelets.
机译:由于其更快,准确可靠的特性,计算机辅助肝脏图像分析近年来兴趣。 定性方法包括对比度拉伸,光滑度,亮度,清晰度等定量分析,另一方面,使用诸如面积,周长,对角线长度,水平和垂直宽度等的几何测量。这些分析方法具有自身的缺点 肿瘤的特征。 通常它们不在几何形状,这使得分析更加困难和复杂。 在该工作中,进行了基于小波的肝肿瘤的图像分段。 通过使用小波分解方法显着降低分割的计算时间。 分段结果进一步进行定量和定性分析,以比较从三个不同小波获得的分段结果,例如Daubechies,Haar和Coiflet小波。

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