Classifying pulmonary nodules using dynamic enhanced single slice and multi slice CT images

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説明

Pulmonary nodules are classified into three types such as solid, mixed GGO, and pure GGO types on the basis of the visual assessment of CT appearance. In our current study a quantitative classification algorithm has been developed by using volumetric data sets obtained from thin-section CT images. The algorithm can classify the pulmonary nodules into five types (α, β, γ, δ, and e) on the basis of internal features extracted from CT number histograms inside nodules. We applied dynamic enhanced single slice and multi slice CT images to this classification algorithm and we analyzed it in each type.

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詳細情報 詳細情報について

  • CRID
    1873116917500423296
  • DOI
    10.1117/12.654683
  • ISSN
    0277786X
  • データソース種別
    • OpenAIRE

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