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  1. A500 情報学部/情報学研究科・情報文化学部・情報科学研究科
  2. A500a 雑誌掲載論文
  3. 学術雑誌

分岐パターン解析による腹部動脈および肝門脈系に対する解剖学的名称の自動対応付け

http://hdl.handle.net/2237/23725
059f61c8-859c-459a-92ca-61fbba91ee3e
名前 / ファイル ライセンス アクション
110009821230.pdf 110009821230.pdf (910.0 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2016-03-04
タイトル
タイトル 分岐パターン解析による腹部動脈および肝門脈系に対する解剖学的名称の自動対応付け
その他のタイトル
その他のタイトル Automated anatomical labeling of abdominal arteries and hepatic portal system by analyzing branching pattern
著者 松崎, 哲朗

× 松崎, 哲朗

WEKO 63410

松崎, 哲朗

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小田, 昌宏

× 小田, 昌宏

WEKO 63411

小田, 昌宏

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北坂, 孝幸

× 北坂, 孝幸

WEKO 63412

北坂, 孝幸

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林, 雄一郎

× 林, 雄一郎

WEKO 63413

林, 雄一郎

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三澤, 一成

× 三澤, 一成

WEKO 63414

三澤, 一成

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森, 健策

× 森, 健策

WEKO 63415

森, 健策

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MATSUZAKI, Tetsuro

× MATSUZAKI, Tetsuro

WEKO 63416

MATSUZAKI, Tetsuro

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ODA, Masahiro

× ODA, Masahiro

WEKO 63417

ODA, Masahiro

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KITASAKA, Takayuki

× KITASAKA, Takayuki

WEKO 63418

KITASAKA, Takayuki

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HAYASHI, Yuichiro

× HAYASHI, Yuichiro

WEKO 63419

HAYASHI, Yuichiro

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MISAWA, Kazunari

× MISAWA, Kazunari

WEKO 63420

MISAWA, Kazunari

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MORI, Kensaku

× MORI, Kensaku

WEKO 63421

MORI, Kensaku

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権利
権利情報 (c)一般社団法人電子情報通信学会 本文データは学協会の許諾に基づきCiNiiから複製したものである
キーワード
主題Scheme Other
主題 血管
キーワード
主題Scheme Other
主題 3次元CT像
キーワード
主題Scheme Other
主題 解剖学的名称認識
キーワード
主題Scheme Other
主題 血管構造解析
キーワード
主題Scheme Other
主題 blood vessel
キーワード
主題Scheme Other
主題 CT volume
キーワード
主題Scheme Other
主題 recognition of anatomical names
キーワード
主題Scheme Other
主題 analysis of blood vessel structures
抄録
内容記述 腹部血管は複雑な分岐構造を有するため,安全な外科手術を行う上でその構造把握は重要である.そこで,本稿では腹部動脈および肝門脈系の分岐構造を解析する手法を提案する.血管は木構造として表現され,機械学習を用いた手法によりそれぞれの枝が各血管である尤度を算出する.血管のとりうる分岐パターンはグラフとして表現され,そのグラフの各辺は尤度を基に重み付けられる.このグラフの全域木は1つの分岐パターンを表現しており,重みを最大化するものを求めることにより分岐パターンの判定を行うことができる.求めた分岐パターンを基に木構造の各枝に解剖学的名称を対応付ける.腹部CT像50例で実験を行ったところ,80.8%の分岐パターンを正しく判定できた. Since abdominal blood vessels have complicated branching structures, understanding them is important to perform abdominal surgeries. In this paper, we propose a method for automated analysis of branching structures of abdominal arteries and hepatic portal system. A blood vessel region is expressed as a tree structure. Likelihoods of candidate anatomical names for each branch in the tree structure is computed by utilizing a machine learning-based method. Possible branching patterns are expressed as a graph whose edges are assigned weights based on the likelihoods of the branches in the tree structure. The directed spanning tree of the graph represents a branching pattern. The optimum branching pattern is obtained by computing the directed maximum spanning tree. Each branch in the tree structure is labeled anatomical names based on the branching pattern. In an experiment using 50 cases of abdominal CT volumes, 80.8% of branching patterns are obtained correctly.
内容記述タイプ Abstract
出版者
出版者 一般社団法人電子情報通信学会
言語
言語 jpn
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
ISSN
収録物識別子タイプ ISSN
収録物識別子 0913-5685
書誌情報 電子情報通信学会技術研究報告. MI, 医用画像

巻 113, 号 410, p. 19-24, 発行日 2014-01
著者版フラグ
値 publisher
シリーズ
関連名称
関連名称 IEICE Technical Report;MI2013-59
URI
識別子 http://ci.nii.ac.jp/naid/110009821230/
識別子タイプ URI
URI
識別子 http://hdl.handle.net/2237/23725
識別子タイプ HDL
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