The method and efficacy of support vector machine classifiers based on texture features and multi-resolution histogram from (18)F-FDG PET-CT images for the evaluation of mediastinal lymph nodes in patients with lung cancer.

Journal: European journal of radiology
Published Date: Nov 18, 2014

Abstract

OBJECTIVES: In clinical practice, image analysis is dependent on simply visual perception and the diagnostic efficacy of this analysis pattern is limited for mediastinal lymph nodes in patients with lung cancer. In order to improve diagnostic efficacy, we developed a new computer-based algorithm and tested its diagnostic efficacy.

Authors

  • Xuan Gao
    College of Pharmacy, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
  • Chunyu Chu
    HIT-INSA Sino French Research Centre for Biomedical Imaging, Harbin Institute of Technology, Harbin, China.
  • Yingci Li
    Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China.
  • Peiou Lu
    Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China.
  • Wenzhi Wang
    Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China.
  • Wanyu Liu
    HIT-INSA Sino French Research Centre for Biomedical Imaging, Harbin Institute of Technology, Harbin, China.
  • Lijuan Yu
    Center of PET/CT, The Third Affiliated Hospital of Harbin Medical University, The Affiliated Tumor Hospital of Harbin Medical University, Harbin, China. Electronic address: yulijuan2003@126.com.

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