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| ■論文No. |
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| ■ページ数 |
10ページ |
■発行日
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2021/09/01 |
| ■タイトル |
A Fast and Accurate Tube Diameter Visualization Method for Digestive System Medical Images |
| ■タイトル(英語) |
A Fast and Accurate Tube Diameter Visualization Method for Digestive System Medical Images |
| ■著者名 |
Mitsuru Ueda (Graduate School of Computer Science and Systems Engineering, Okayama Prefectural University), Masafumi Kondo (Faculty of Health Science and Technology, Kawasaki University of Medical Welfare), Isao Kayano (Faculty of Health Science and Techn |
| ■著者名(英語) |
Mitsuru Ueda (Graduate School of Computer Science and Systems Engineering, Okayama Prefectural University), Masafumi Kondo (Faculty of Health Science and Technology, Kawasaki University of Medical Welfare), Isao Kayano (Faculty of Health Science and Techn |
| ■価格 |
会員 ¥550 一般 ¥770 |
| ■書籍種類 |
論文誌(論文単位) |
| ■グループ名 |
【C】電子・情報・システム部門 |
| ■本誌 |
電気学会論文誌C（電子・情報・システム部門誌） Vol.141 No.9 （2021） 特集：知能メカトロニクス分野と連携する知覚情報技術
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| ■本誌掲載ページ |
982-991ページ |
| ■原稿種別 |
論文／英語 |
| ■電子版へのリンク |
https://www.jstage.jst.go.jp/article/ieejeiss/141/9/141_982/_article/-char/ja/
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| ■キーワード |
image processing，automated diameter measurement，dynamic centerline detection，color mapping |
| ■要約(日本語) |
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| ■要約(英語) |
Although the tube diameter and stenosis rate are important observations in the diagnosis using medical images of digestive organ, such as digestive systems, the diagnosis is based on the physician's subjective evaluation. On the other hand, automatic measurement of tube diameters by image processing has been used for blood vessels, which are tubular tissues similar to digestive systems, and it is also possible to visualize the vessel diameter by assigning pseudo-colors according to the length of the vessel. However, it is difficult to apply the existing diameter visualization methods directly to digestive system medical images due to the processing time and accuracy problems because the tubes are large and tortuous, unlike blood vessels. In this paper, we propose a method to measure the tube diameter quickly by dynamically calculating the next featured pixel using the history of the midpoints of the tube diameter line. Furthermore, we derive an approximate curve corresponding to the centerline of the tube from the history of the featured pixels and measure the tube diameter with high accuracy. We applied the proposed method to various types of digestive system medical images and confirmed that the proposed method could accurately measure and visualize the tube diameter along the shape of the tube and reduce the processing time by up to 99%. |
| ■版 型 |
A4 |
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