| 基于小波变换的光声成像算法 |
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| 引用本文： | 谭毅,赵长水,姚军财. 基于小波变换的光声成像算法[J]. 陕西工学院学报, 2009, 0(4): 41-46 |
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| 作者姓名： | 谭毅 赵长水 姚军财 |
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| 作者单位： | 陕西理工学院物理系,陕西汉中723003 |
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| 基金项目： | 陕西理工学院科研资助项目（SLG0721）.致谢：在此衷心感谢华南师范大学激光生命科学研究所、激光生命科学教育部重点实验室的邢达教授及其研究团队对此文的悉心指导. |
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| 摘 要： | 为了进一步提高光声重建图像的质量,利用小波变换的多维多分辨率特性对光声图像进行消噪,将小波包的分解和重构理论与统计差值相结合对光声图像的细节部分进行增强。由仿真和实验结果表明,重建图像经过小波降噪和图像增强后,其对比度相对滤波反投影算法的光声像得到了明显的提高,其分辨率由0.55 mm提高到0.48 mm,该算法将为病变组织的正确诊断与治疗提供了更高的精度和准确度。
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| 关 键 词： | 光声成像 小波变换 降噪 图像增强 |
Photoacoustic imaging algorithm based on wavelet transform |
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| TAN Yi,ZHAO Chang-shui,YAO Jun-cai. Photoacoustic imaging algorithm based on wavelet transform[J]. Journal of Shaanxi Institute of Technology, 2009, 0(4): 41-46 |
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| Authors: | TAN Yi ZHAO Chang-shui YAO Jun-cai |
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| Affiliation: | (Department of Physical Sciences,Shaanxi University of Technology, Hanzhong 723003, China) |
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| Abstract: | In order to improve the quality of reconstructed photoacoustic image, a method of wavelet transformation was applied to process photoacoustic image. Multidimensions multiresolution analysis property of wavelet was used to denoise in the image,wavelet packets decomposition and reconstruction and statistic difference algorithm was used to enhance the image. The simulations and experiments demonstrated that the contrast of reconstructed image was greatly improved and resolution improved from 0.55mm to 0.48mm after wavelet denoise and image enhancement compared with the filtered back projection algorithm （FBPA）, the algorithm could improve the precision and accuracy of diagnosis and theraov of disease tissue. |
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| Keywords: | photoacoustic imaging wavelet transform denoise image enhancement |
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