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A Segmentation Algorithm for Lung Tumor CT Image

Jingjing Yang, Xiao Zhang, Zhanfu Wu, Benzhen Guo, Lun Yang


This paper introduces a method for lung tumor CT image segmentation .The resolution of lung tumor CT image due to many factors , the marginal area of the lesion and the surrounding normal tissue region have almost the same gray scale, which makes the detection of the tumor area harder. This paper first de-noises the lung CT image by image preprocessing, then enhances the de-noised image with improved Nonsub-sampled on contourlet transform algorithm for more accurate shape and figure of the lung tumor. Using newly upgraded chan-vese image segmentation algorithm to obtain the valid area of lung tumor, comparing the segmentation results under different preprocessing methods, the experimental data introduced by this thesis show that the joint of gray scale expansion and Fourier transform acts best among all the mentioned preprocessing methods.


lung tumor, image enhancement, NSCT transform , C-V segmentation.

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