Recognition of pulmonary nodules in thoracic CT scans using 3-D deformable object models of different classes

Hotaka Takizawa, Shinji Yamamoto, Tsuyoshi Shiina

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The present paper describes a novel recognition method of pulmonary nodules (i.e., cancer candidates) in thoracic computed tomography scans by use of three-dimensional spherical and cylindrical models that represent nodules and blood vessels, respectively. The anatomical validity of these object models and their fidelity to computed tomography scans are evaluated based on the Bayes theorem. The nodule recognition is employed by the maximum a posteriori estimation. The proposed method is applied to 26 actual computed tomography scans, and experimental results are shown.

Original languageEnglish
Pages (from-to)125-144
Number of pages20
JournalAlgorithms
Volume3
Issue number2
DOIs
Publication statusPublished - 2010 Jun
Externally publishedYes

Keywords

  • Bayes theorem
  • Maximum a posteriori estimation
  • Recognition of pulmonary nodules
  • Thoracic computed tomography scans
  • Three-dimensional deformable object models

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Numerical Analysis
  • Computational Theory and Mathematics
  • Computational Mathematics

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