JP2013518611A5 - - Google Patents

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JP2013518611A5
JP2013518611A5 JP2012550530A JP2012550530A JP2013518611A5 JP 2013518611 A5 JP2013518611 A5 JP 2013518611A5 JP 2012550530 A JP2012550530 A JP 2012550530A JP 2012550530 A JP2012550530 A JP 2012550530A JP 2013518611 A5 JP2013518611 A5 JP 2013518611A5
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Priority claimed from PCT/IB2011/000243 external-priority patent/WO2011092594A2/en
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Claims (7)

  1. 解剖学的構造の仮想モデルを三次元画像から作成するための方法であって:
    複数の二次元画像から作成される三次元画像を提供すること;
    撮像されたボクセルが組織を示していないことを示す値よりも高い閾値を設定すること;並びに、
    前記三次元画像における種子点ボクセルを、出発点として選択すること;
    複数の反復を実行することであって、各反復が:
    前記種子点にすぐ隣接し、所望するあらゆる方向にあるボクセルであって、前記閾値を満たすか、または、超える前記ボクセルをセグメント化すること;
    該反復においてセグメント化されたボクセル数を決定すること;
    前記ボクセル数がゼロより大きい場合、前記数が漏れを示すのに十分な大きさであるかどうかを決定すること;
    漏れとなったボクセルを削除し、後処理を行うために漏れとなったオブジェクトとして該漏れとなったボクセルを記憶すること;および、
    一つも漏れが示されない場合、次の反復のための種子点としてセグメント化されたボクセルを識別すること
    を含む、複数の反復を実行すること;
    セグメント化された前記ボクセル数がゼロに等しい時を検出すること;
    前記セグメント化されたボクセル数がゼロに等しくなるまで、漏れとなったオブジェクトがあれば該オブジェクトに第二の反復を実行することであって、前記第二の反復が:
    種子点として漏れとなった所与のボクセルにおける漏れを検出する最初の反復においてボクセルを選択すること;
    前記閾値を低減させること;
    すべての所望の方向に、前記種子点にすぐ隣接し、所望するあらゆる方向にあるボクセルであって、前記閾値を満たすか、または、超える前記ボクセルをセグメント化すること;
    該反復においてセグメント化されたボクセル数を決定すること;
    前記ボクセル数がゼロより大きい場合、前記数が漏れを示すのに十分な大きさであるかどうかを決定すること;
    漏れとなったボクセルを削除し、後処理を行うために漏れとなったオブジェクトとしてそれらを記憶すること;および、
    一つも漏れが示されない場合、次の反復のための種子点としてセグメント化されたボクセルを識別すること
    を含む、第二の反復を実行すること
    を含む、方法。
  2. 前記三次元画像における種子点を出発点として選択することは、高い閾値を有する種子点ボクセルを選択することを含む、請求項1に記載の方法。
  3. 前記高い閾値を有する種子点ボクセルを選択することは、空気を示す閾値を有する種子点ボクセルを選択することを含む、請求項2に記載の方法。
  4. コンピュータによって読み取る際に解剖学的構造の仮想モデルを三次元画像から作成するための方法を実行する命令を記憶するコンピュータ可読媒体であって:
    閾値として、流体を示す画像ボクセルの濃度を使用すること
    前記閾値を満たすボクセルのみをセグメント化し、それにより、前記解剖学的構造の内部空洞および/または内腔の仮想モデルを作成することであって、前記セグメント化は、種子点としてセグメント化されたボクセルを使用し、前記種子点に隣接する所望の方向にあるセグメント化されていないボクセルを分析する、一連の反復として行われること;および、
    前記種子点に隣接し、前記所望の方向にあるセグメント化されていないボクセルがなくなるまで、反復により新たにセグメント化されたボクセルを次の反復のための種子点として使用して、前記反復を繰り返すこと
    を含む、方法。
  5. 前記セグメント化の工程から、前記閾値を満たすが、漏れとなったオブジェクトとして識別され、公知の解剖学的構造に適合することに基づく基準を満たすことができないオブジェクトを形成するボクセルを分離すること
    をさらに含む、請求項4に記載の方法。
  6. 低減された閾値を使用して、前記漏れとなったオブジェクトを再セグメント化すること;
    前記再セグメント化の工程から、前記低減された閾値を満たすが、漏れとなったオブジェクトとして識別され、公知の解剖学的構造に適合することに基づく基準を満たすことができないオブジェクトを形成するボクセルを分離すること;および、
    分離されていない、再セグメント化ボクセルを前記仮想モデルに加えること
    をさらに含む、請求項5に記載の方法。
  7. 漏れとなったオブジェクトの一部として識別される最初にセグメント化されたボクセルの集まりを種子点として使用し、前記種子点に隣接し、所望の方向にあるセグメント化されていないボクセルを分析して、一連の反復として、前記再セグメント化の工程を行うこと;および、
    前記種子点に隣接し、前記所望の方向にあるセグメント化されていないボクセルがなくなるまで、反復により新たにセグメント化されたボクセルを次の反復のための種子点として使用して、前記反復を繰り返すこと
    を含む、請求項6に記載の方法。
JP2012550530A 2010-02-01 2011-02-01 領域拡張アルゴリズム Expired - Fee Related JP5650248B2 (ja)

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US30042310P 2010-02-01 2010-02-01
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EP (2) EP3407261A3 (ja)
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