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An approach to lumbar vertebra CT image segmentation using contourlet transform and ANNs

机译：腰椎椎骨椎体椎体椎体椎体椎体椎体椎体椎体椎体椎体椎体骨折和ANN

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摘要

In this paper, we proposed a mathod for lumbar vertebra CT image segmentation based on the contourlet transform and artificial neural networks (ANNs). The proposed method consists of three portions. In the first part, contourlet transform is used to decompose the CT image to obtain the contourlet coefficients. In the second part, the self-organizing competitive artificial neural network is employed to optimize and extract the low frequency coefficients coefficients of contourlet transformation, reduce the number of coefficients greatly. The last part, the optimized coefficients are inverse contourlet transformed with the original coefficients, the segmented image is reconstructed. The experimental results show the accuracy of human lumbar vertebra CT image segmentation based on the proposed method is encouraged.
机译：在本文中，我们提出了一种基于轮廓曲线变换和人工神经网络（ANN）的腰椎椎骨CT图像分割Mathod。所提出的方法包括三个部分。在第一部分中，Contourlet变换用于分解CT图像以获得Contourlet系数。在第二部分中，采用自组织竞争性人工神经网络来优化和提取Contourlet变换的低频系数系数，大大减少系数的数量。最后部分，优化系数是用原始系数转换的逆轮廓，重建分段图像。实验结果表明，鼓励基于所提出的方法的人腰椎椎体椎体椎体椎骨图像分割的准确性。

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