JP6327845B2 - 口腔内画像と体積画像の統合 - Google Patents
口腔内画像と体積画像の統合 Download PDFInfo
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Description
一般に、口腔内画像はCBCT画像と比べて大幅に精度が高い。さらに、CBCTデータには雑音が多い可能性がある。また、CBCTを用いると患者に電離放射することとなり、できるだけ少ない放射でCBCTシステムを使用するのがベストである。
図1は、特定の実施形態に従う、口腔内画像104とCBCT画像106を統合する計算装置102を備える計算環境および撮像環境100のブロック図を示す。計算装置102は、パーソナル・コンピュータ、サーバ・コンピュータ、ミニ・コンピュータ、メインフレーム・コンピュータ、ブレード・コンピュータ、タブレット・コンピュータ、タッチスクリーン・コンピューティング装置、テレフォニー装置、携帯電話、モバイル計算装置、プロセッサを有する歯科用機器等のような任意の適切な計算装置を備えてもよい。特定の実施形態では、計算装置102がウェブ・サービスまたはクラウド・コンピューティング・サービスを提供してもよい。特定の代替的な実施形態では、複数の計算装置をデータの格納、または、計算装置102により実施される動作の実施に使用してもよい。
体積データの表現では、高いコントラストの領域と低いコントラストの領域が存在しうる。閾値化を介した(例えば、放射線濃度を閾値化することによる)セグメント化を行うとき、歯根よりクラウンを閾値化する方が容易であることがある。これは、クラウンが軟組織に対して高密度で現れるからである。歯根は骨に対して低いコントラストで現れることに留意されたい。高いコントラストの分岐は、この方式で容易にセグメント化することができる。特定の実施形態では、クラウンを閾値化し、その境界を使用してセグメント化をシードし、歯根を分離してもよい。このように、体積データを使用して当該体積データ自体をセグメント化してもよい。これにより、クラウンの歯根オブジェクトを自動的に重ね合わせることができる。これをクラウンのサーフェス・データの重ね合わせに使用してもよい。
種々の図面で説明した動作を、ソフトウェア、ファームウェア、ハードウェア、またはそれらの任意の組合せを生成する技法を用いた方法、装置またはコンピュータ・プログラム製品として実装してもよい。さらに、特定の実施形態が、コンピュータ読取可能プログラム・コードを組み込んだ1つまたは複数のコンピュータ読取可能記憶媒体(複数可)で具体化されたコンピュータ・プログラム製品の形をとってもよい。
104 口腔内画像
106 CBCT画像
108 統合アプリケーション
110 無線接続または有線接続
112 口腔内撮像システム
114 CBCT撮像システム
116 ワンド
118 口腔内撮像センサ
120 回転式X線機器
Claims (11)
- 方法であって、
患者のクラウンの形状データと前記患者の歯の体積画像を受信するステップと、
前記形状データの中の1つまたは複数のクラウンを表現する要素を決定するステップと、
計算装置を使用して、前記要素を前記体積画像の対応するボクセルに重ね合わせるステップと、
を含み、前記方法は、
前記ボクセルに対応する体積座標と放射線濃度とを決定するステップと、
前記ボクセルの1つまたは複数の決定された体積座標と放射線濃度を含む位置から開始する領域成長を介して、前記患者の少なくとも1つの歯根を決定するステップと、
をさらに含む、方法。 - 前記領域成長は、前記患者の歯の長手方向に沿った相関放射線濃度を有する隣接ボクセルを特定することによって実施される、請求項1に記載の方法。
- 前記体積座標と前記放射線濃度の決定を用いて歯の形状が決定され、前記方法は前記形状データおよび/または前記体積画像の中の欠落データまたは劣化データを埋めるステップをさらに含み、前記歯の形状は受信した前記体積画像と比べてより高い精度で決定され、前記歯の形状は弱放射を用いてより高い精度で決定される、請求項1または2に記載の方法。
- 前記体積画像は第1の複数のボクセルにより表現され、
前記1つまたは複数のクラウンは第2の複数のボクセルにより表現され、
前記第1の複数のボクセルと前記第2の複数のボクセルが重ね合わされる、
請求項1乃至3の何れか1項に記載の方法。 - 前記要素はベクトルであり、
前記形状データ内の境界は前記1つまたは複数のクラウンに対応し、
前記1つまたは複数のクラウンは複数の有限長ベクトルにより表現され、
前記体積画像は複数のボクセルにより表現され、
前記複数の有限長ベクトルと前記複数のボクセルの交点は前記重ね合わせの後に決定される、
請求項1乃至3の何れか1項に記載の方法。 - 1つまたは複数のクラウンが、前記形状データのセグメント化を介して前記形状データの中で決定される、請求項1に記載の方法。
- 前記形状データは口腔内画像からのものであり、前記体積画像はCBCT(cone beam computed tomography)画像であり、
前記口腔内画像の精度は前記CBCT画像より高く、
前記体積画像は、歯の歯根とクラウンの両方を含み、
前記口腔内画像は、少なくとも前記歯のクラウンを含むが、前記歯の歯根の全体は含まない、
請求項1に記載の方法。 - 前記口腔内画像内の関心領域を決定するステップであって、前記関心領域は前記口腔内画像の中の決定された前記1つまたは複数のクラウンの位置に対応するステップと、
前記体積画像において前記関心領域を抽出して、前記体積画像のサイズを減らすステップと、
をさらに含む、請求項7に記載の方法。 - 前記患者のクラウンの前記形状データは圧痕、石膏模型または口腔内スキャンを介して取得され、
前記体積画像は、断層撮影画像、超音波画像、CBCT(cone beam computed tomography)画像およびMRI(magnetic resonance image)から成るグループから選択される、
請求項1乃至8の何れか1項に記載の方法。 - メモリと、
前記メモリに接続されたプロセッサであって、前記プロセッサは請求項1乃至9の何れか1項に記載の方法のステップを実施するプロセッサと、
を備える、システム。 - コンピュータ読取可能記憶媒体であって、前記コンピュータ読取可能記憶媒体に組み込んだコードが、プロセッサにより実行されたときに請求項1乃至9の何れか1項に記載の方法のステップを含む動作を実施する、コンピュータ読取可能記憶媒体。
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US13/715,968 US9135498B2 (en) | 2012-12-14 | 2012-12-14 | Integration of intra-oral imagery and volumetric imagery |
US13/715,968 | 2012-12-14 |
Publications (3)
Publication Number | Publication Date |
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JP2014117611A JP2014117611A (ja) | 2014-06-30 |
JP2014117611A5 JP2014117611A5 (ja) | 2018-02-22 |
JP6327845B2 true JP6327845B2 (ja) | 2018-05-23 |
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JP2013257971A Active JP6327845B2 (ja) | 2012-12-14 | 2013-12-13 | 口腔内画像と体積画像の統合 |
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EP (2) | EP2742857B1 (ja) |
JP (1) | JP6327845B2 (ja) |
CN (1) | CN103860191B (ja) |
DK (2) | DK3513712T3 (ja) |
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DK3513712T3 (da) | 2021-07-05 |
US9904999B2 (en) | 2018-02-27 |
EP3513712B1 (en) | 2021-03-31 |
CN103860191B (zh) | 2018-04-13 |
US20160042509A1 (en) | 2016-02-11 |
US20190172200A1 (en) | 2019-06-06 |
US20180182098A1 (en) | 2018-06-28 |
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