Geodesic
Research on Automatic Identification Technique of CT Image in Lung
Computer Science and Information Systems, Tome 15 (2018) no. 3.

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Lung cancer has become the world's human cancer disease in the "first killer." In this paper, three aspects of lung CT images were treated. Firstly, based on the CT image preprocessing, the lung parenchyma was segmented by random walk algorithm and the ROI was extracted from the pulmonary parenchyma; Secondly, the 10-dimensional feature vectors of pulmonary nodule ROI were extracted by the gray level co-occurrence matrix algorithm; Finally, support vector machine as a classifier is to identify the pulmonary nodules and the accuracy rate is more than 94%. The experimental results show that the study of automatic CT image recognition can provide some data reference for doctors and play a supporting role in the course of treatment.
Keywords: CT image, image segmentation, ROI extraction, feature extraction, support vector machine 
@article{CSIS_2018_15_3_a4,
     author = {Zhijie Zhao and Cong Ren and Huadong Sun and Zhipeng Fan and Ze Gao},
     title = {Research on {Automatic} {Identification} {Technique} of {CT} {Image} in {Lung}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {15},
     number = {3},
     year = {2018},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a4/}
}
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Zhijie Zhao; Cong Ren; Huadong Sun; Zhipeng Fan; Ze Gao. Research on Automatic Identification Technique of CT Image in Lung. Computer Science and Information Systems, Tome 15 (2018) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a4/