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Computer assisted lung cancer diagnosis based on helical images

  • K. Kanazawa
  • M. Kubo
  • N. Niki
  • H. Satoh
  • H. Ohmatsu
  • K. Eguchi
  • N. Moriyama
Session IA2b — Biomedical Imaging
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1024)

Abstract

In this paper, we describe a computer assisted automatic diagnosis system of lung cancer that detects tumor candidates in its early stage from the helical CT images. This automation of the process reduces the time complexity and increases the diagnosis confidence. Our algorithm consists of analysis part and diagnosis part. In the analysis part, we extract the lung regions and the pulmonary blood vessels regions and analyze the features of these regions using image processing technique. In the diagnosis part, we define diagnosis rules based on these features, and we detect the tumor candidates using these rules. We apply our algorithm to 224 patients data of mass screening. These results show that our algorithm detects lung cancer candidates successfully.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • K. Kanazawa
    • 1
  • M. Kubo
    • 1
  • N. Niki
    • 1
  • H. Satoh
    • 1
    • 2
  • H. Ohmatsu
    • 1
    • 3
  • K. Eguchi
    • 1
    • 3
  • N. Moriyama
    • 1
    • 3
  1. 1.Department of Information ScienceUniversity of TokushimaJapan
  2. 2.Medical Engineering LaboratoryToshiba CorporationJapan
  3. 3.National Cancer CenterJapan

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