Classification of CT examinations for COPD visual severity analysis

Jun Tan, Bin Zheng, Xingwei Wang, Jiantao Pu, David Gur, Frank C. Sciurba, J. Ken Leader

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this study we present a computational method of CT examination classification into visual assessed emphysema severity. The visual severity categories ranged from 0 to 5 and were rated by an experienced radiologist. The six categories were none, trace, mild, moderate, severe and very severe. Lung segmentation was performed for every input image and all image features are extracted from the segmented lung only. We adopted a two-level feature representation method for the classification. Five gray level distribution statistics, six gray level co-occurrence matrix (GLCM), and eleven gray level run-length (GLRL) features were computed for each CT image depicted segment lung. Then we used wavelets decomposition to obtain the low- and high-frequency components of the input image, and again extract from the lung region six GLCM features and eleven GLRL features. Therefore our feature vector length is 56. The CT examinations were classified using the support vector machine (SVM) and k-nearest neighbors (KNN) and the traditional threshold (density mask) approach. The SVM classifier had the highest classification performance of all the methods with an overall sensitivity of 54.4% and a 69.6% sensitivity to discriminate "no" and "trace visually assessed emphysema. We believe this work may lead to an automated, objective method to categorically classify emphysema severity on CT exam.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2012
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
DOIs
StatePublished - May 14 2012
EventMedical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging - San Diego, CA, United States
Duration: Feb 5 2012Feb 7 2012

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume8317
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CitySan Diego, CA
Period2/5/122/7/12

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Keywords

  • COPD
  • Classification
  • Texture analysis
  • Visual severity quantification

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Cite this

Tan, J., Zheng, B., Wang, X., Pu, J., Gur, D., Sciurba, F. C., & Leader, J. K. (2012). Classification of CT examinations for COPD visual severity analysis. In Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging [831723] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8317). https://doi.org/10.1117/12.911751