Research on Automatic Identification Technique of CT Image in Lung

Zhijie Zhao1, 2, Cong Ren1, 2, Huadong Sun1, 2, Zhipeng Fan1, 2 and Ze Gao1, 2

  1. School of Computer and Information Engineering, Harbin University of Commerce
    Harbin, 150028, China,,,,
  2. Key Laboratory of Electronic Commerce and Information Processing of Heilongjiang Province


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.

Key words

CT image, image segmentation, ROI extraction, feature extraction, support vector machine

Digital Object Identifier (DOI)

Publication information

Volume 15, Issue 3 (October 2018)
Year of Publication: 2018
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable in PDF
Portable Document Format

How to cite

Zhao, Z., Ren, C., Sun, H., Fan, Z., Gao, Z.: Research on Automatic Identification Technique of CT Image in Lung. Computer Science and Information Systems, Vol. 15, No. 3, 501–515. (2018),