Comparison of two-dimensional with three-dimensional analyses for diffuse lung diseases from thoracic CT images

• SUGATA Yoshihiro

  Applied Medical Engineering Science, Graduate School of Medicine, Yamaguchi University

• KIDO Shoji

  Applied Medical Engineering Science, Graduate School of Medicine, Yamaguchi University

• SHOUNO Hayaru

  Department of Information and Communication Engineering, University of Electro-Communications

Bibliographic Information

Other Title

• 胸部CT画像を用いたびまん性肺疾患画像解析のための2次元と3次元特徴解析の比較

Abstract

For the diagnosis of diffuse lung diseases on CT images, we have used two-dimensional(2D)images. Now, we can easily obtain minute volume data of human body by use of multi-detector row CT, and can diagnose diffuse lung diseases by use of three-dimensional(3D)images. In this study, we focused attention on the patterns of diffuse lung diseases, and tried the computerized analysis method for the image features of the three-dimensional CT images. And we compared the classification results obtained from 3D feature analysis with those obtained from 2D feature analysis. Image patterns for the computerized analysis are as follows: consolidation, ground-glass opacity, reticular, honeycomb, cyst, nodular and normal. In order to evaluate these patterns, we used several features of texture analysis obtained from Fourier power spectrum, gray-level histogram, difference statistics, co-occurrence matrix, and run length matrix.

Journal

• Medical Imaging and Information Sciences

  Medical Imaging and Information Sciences 25 (3), 43-47, 2008

  MEDICAL IMAGING AND INFORMATION SCIENCES

Keywords

• Diffuse lung disease
• Texture analysis
• Baysian rule

Details

• CRID: 1390282679628863744
• NII Article ID: 130000097652
• DOI: 10.11318/mii.25.43
• ISSN: 18804977
• ISSN: 09101543
• Web Site: https://search.jamas.or.jp/link/ui/2009353209
• Text Lang: ja
• Data Source:
  • JaLC
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed