C206 マルチスライスCT画像に基づく3次元気道追跡と形態計測

• 三木 貴仁

  東北大学

• 和田 成生

  大阪大学

• 中村 匡徳

  東北大学

• 坪田 健一

  東北大学

• 山口 隆美

  東北大学

• 須田 祐司

  仙台オープン病院

• 田村 弦

  東北大学

書誌事項

タイトル別名

• Computer-aided Segmentation and Quantification of the Human Airway Tree on the Basis of Multi CT Images

抄録

We developed an algorithm for automated segmentation and quantification of the human airway tree from the CT images of the lung. The algorithm consists of segmentation of the airway tree, its skeletonization, identification of the airway generation, and measurement of volume, length and diameter of each airway. The airway lumen was extracted from CT images with the region growing method. For morphometric identification of airways' branching, the 3-D airway model was skeletonized. The results showed it was possible to extract up to the 14th generation of the airway tree whose diameter was 1.7mm. The airway diameters obtained were in good agreement with those reported in autopsy study, although the diameters on and after 8th generation were all larger than those in vivo measurement due probably to an insufficient resolution of CT images. These results addressed the potential of the algorithm developed in this study for quantification of the airway tree.

収録刊行物

• 可視化情報学会誌

  可視化情報学会誌 26 (Supplement1), 195-196, 2006

  社団法人 可視化情報学会

キーワード

• Computed Tomography
• Airway Segmentation
• Region Growing Method
• Skeletonization
• Airway Quantification

詳細情報

• CRID: 1390001204618568832
• NII論文ID: 10017995400
• NII論文ID: 130003443556
• NII書誌ID: AA11907562
• DOI: 10.3154/jvs.26.supplement1_195
• ISSN: 1884037X
• ISSN: 09164731
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可