JP2019520885A - スペクトル及び非スペクトル物質分解を組み合わせることによる定量的撮像の精度及び分解能の向上 - Google Patents
スペクトル及び非スペクトル物質分解を組み合わせることによる定量的撮像の精度及び分解能の向上 Download PDFInfo
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Abstract
Description
Ienhanced=F−1(wspectral(f)F(Ispectral(x))+wnon−spectral(f)F(Inon−spectral(x)))
Ienhancedは、スペクトル画像データと非スペクトル画像データとを組み合わせて得られるエンハンスされた定量的画像データを示す。更に、Ispectralは、スペクトル画像データを示し、Inon−spectralは、非スペクトル画像を示す。関数wspectral及びwnon−spectralは、空間周波数に依存する重み関数を示し、F及びF−1は、それぞれ、フーリエ変換及び逆フーリエ変換である。上記式による重み付けは、空間領域における次の計算:
Ienhanced=vspectral(x)*Ispectral(x)+vnon−spectral(x)*Inon−spectral(x)
と数学的に等しい。後者の場合、vspectral(x)=F−1(wspectral(f))及びvnon−spectral(x)=F−1(wnon−spectral(f))は、フィルタカーネルであり、*は、畳み込み演算子を示す。なお、2つの上記計算は、数学的に等価である。最終結果の差は、ソフトウェアの実装の数値精度及び品質によるものであり、方法の選択は、ソフトウェアを実行する速度といった実用性に依存する。なお、例えばウェーブレット方法及びガウス/ラプラシアンピラミッド方法といった空間周波数及び構造サイズの関数として画像を処理する他の方法も存在する。本発明は、任意の特定の処理方法に限定されない。
Claims (13)
- 受信ユニットと、
処理ユニットと、
を含む定量的画像データを処理するための計算ユニットであって、
前記受信ユニットは、関心物体のスペクトル画像データを受信し、
前記受信ユニットは、前記関心物体の非スペクトル画像データを受信し、
前記処理ユニットは、前記スペクトル画像データから、位置の関数として物質特性を計算し、
前記処理ユニットは、前記非スペクトル画像データから、位置の関数として物質特性を計算し、
前記処理ユニットは、前記スペクトル画像データから計算された前記物質特性と、前記非スペクトル画像データから計算された前記物質特性とを、画像内の空間周波数に依存して、前記スペクトル画像データ及び前記非スペクトル画像データに重みを付けることによって、空間周波数の関数として組み合わせる、計算ユニット。 - 前記処理ユニットは、前記非スペクトル画像データの低空間周波部分と比べて、前記スペクトル画像データの低空間周波部分により強い重みを与え、
前記処理ユニットは、前記スペクトル画像データの高空間周波部分と比べて、前記非スペクトル画像データの高空間周波部分により強い重みを与える、請求項1に記載の計算ユニット。 - 請求項1又は2に記載の計算ユニットと、
撮像ユニットと、
を含み、
前記撮像ユニットは、前記計算ユニットに、スペクトル画像データ及び非スペクトル画像データを提供する、X線撮像システム。 - 前記スペクトル画像データ及び/又は前記非スペクトル画像データは、位相コントラスト画像データ、微分位相コントラスト画像データ、又は、暗視野画像データである、請求項3に記載のX線撮像システム。
- 関心物体のスペクトル画像データを取得するステップと、
前記スペクトル画像データから、位置の関数として物質特性を計算するステップと、
前記関心物体の非スペクトル画像データを取得するステップと、
前記非スペクトル画像データから、位置の関数として物質特性を計算するステップと、
画像の空間周波数に依存して、前記スペクトル画像データ及び前記非スペクトル画像データに重みを付けるステップを含む、前記スペクトル画像データから計算された前記物質特性と、前記非スペクトル画像データから計算された前記物質特性とを、空間周波数の関数として組み合わせるステップと、
を含む、定量的画像データ処理のための方法。 - 前記スペクトル画像データは、スペクトルトモシンセシスデータであり、及び/又は、前記非スペクトル画像データは、非スペクトルトモシンセシスデータである、請求項5に記載の方法。
- 前記非スペクトル画像データを取得する前記ステップは、追加的な先験的前提及び/又は追加データ入力を使用するステップを含む、請求項5又は6に記載の方法。
- 前記スペクトル画像データから計算された前記物質特性と、前記非スペクトル画像データから計算された前記物質特性とを、空間周波数の関数として組み合わせる前記ステップは、空間周波数領域において少なくとも部分的に行われる、請求項5乃至7の何れか一項に記載の方法。
- 前記スペクトル画像データから計算された前記物質特性と、前記非スペクトル画像データから計算された前記物質特性とを、空間周波数の関数として組み合わせる前記ステップは、空間領域において少なくとも部分的に行われ、ローパス、バンドパス若しくはハイパスフィルタリングによる及び/又はフィルタカーネルを用いた畳み込みのステップを含む、請求項5乃至7の何れか一項に記載の方法。
- 空間周波数の関数として重み付けする前記ステップは、前記非スペクトル画像データの低空間周波部分と比べて、前記スペクトル画像データの低空間周波部分により強い重みを与え、
空間周波数の関数として重み付けする前記ステップは、前記スペクトル画像データの高空間周波部分と比べて、前記非スペクトル画像データの高空間周波部分により強い重みを与える、請求項5に記載の方法。 - 前記スペクトル画像データ及び前記非スペクトル画像データから、位置の関数として物質特性を計算する前記ステップは、
嚢胞、腫瘍、又は、微小石灰化といった病変を特定する特性、
腺乳房組織及び脂肪乳房組織、又は、皮膚を特定する特性、
前記関心物体内の造影剤の濃度、
のうちの少なくとも1つを特定する又は特徴付けるステップを含む、請求項5乃至10の何れか一項に記載の方法。 - プロセッサによって実行されると、請求項5乃至11の何れか一項に記載の方法のステップを行うように適応される、コンピュータプログラム。
- 請求項12に記載のコンピュータプログラムを含む、コンピュータ可読媒体。
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WO2018015911A1 (en) * | 2016-07-19 | 2018-01-25 | Volpara Health Technologies Limited | System and apparatus for clinical decision optimisation |
JP7224115B2 (ja) * | 2018-06-12 | 2023-02-17 | キヤノンメディカルシステムズ株式会社 | 乳房用x線撮影装置及びプログラム |
FR3082945B1 (fr) * | 2018-06-22 | 2020-06-05 | Commissariat A L'energie Atomique Et Aux Energies Alternatives | Procede de caracterisation d'un objet par imagerie spectrale |
CN112334950A (zh) * | 2018-06-29 | 2021-02-05 | 皇家飞利浦有限公司 | 被配置为从kvp切换多能量采集中生成非谱体积图像数据的成像系统 |
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