JP2019114262A - 医用画像処理装置、医用画像処理プログラム、学習装置及び学習プログラム - Google Patents
医用画像処理装置、医用画像処理プログラム、学習装置及び学習プログラム Download PDFInfo
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Abstract
Description
訓練の後、識別器76は、生成器66を残しながらシステムから除去される。訓練された生成器66は、その後、画像間の変換がまだ分かっていない新たな画像をレジストレーションするために、使用することができる。
1. 平均二乗誤差のみを使用し訓練された生成器(図2を参照し上で説明されたものと同様)
2. 平均二乗誤差及び識別器を使用し訓練された生成器(図5を参照し上で説明されたものと同様)
生成器は、2つの入力画像(参照画像と変換画像)が与えられて変位場を出力するよう訓練されたものである。
Claims (15)
- 第一の画像データと第二の画像データとを受け取る取得部と、
前記第一の画像データと前記第二の画像データとの間のレジストレーション処理を実行するための予測変位を生成する生成部と、
を具備し、
前記生成部は、前記予測変位の生成と識別部を用いた訓練とを繰り返し実行することで訓練されており、
前記識別部は、予め定めた変位と前記予測変位とを区別するように訓練されること、
を特徴とする医用画像処理装置。 - 前記生成部及び前記識別部のうちの少なくとも一方は、ニューラルネットワークを有することを特徴とする請求項1記載の医用画像処理装置。
- 前記生成部は、前記予測変位に基づいて、更なるレジストレーション、サブトラクション、セグメンテーション、アトラスベースを用いた処理、画像フュージョン、生体構造検出、病変検出、のうちの少なくとも一つを実行することを特徴とする請求項1又は2記載の医用画像処理装置。
- 前記第一の画像データ及び前記第二の画像データは、二次元画像データ又は三次元画像データであることを特徴とする請求項1乃至3のうちいずれか一項記載の医用画像処理装置。
- 識別部及び生成部を学習させる学習装置であって、
複数の訓練画像データセットと、前記複数の訓練画像データセットに対応する複数の予め定めた変位と、を受け取る取得部と、
前記生成部が前記複数の訓練画像データセットに基づいて予測変位を生成する生成処理と、前記識別部が前記予測変位と前記複数の予め定めた変位とを識別する識別処理と、を敵対的に繰り返し実行して前記生成部及び前記識別部を訓練する学習部と、
を特徴とする学習装置。 - 前記学習部は、前記生成部及び前記識別部の識別的損失を最大化する又は増加させ、前記複数の訓練画像データセットのレジストレーションに対する損失関数を最小化する又は減少させることを特徴とする請求項5記載の学習装置。
- 前記生成処理は、
前記複数の訓練画像データセットのそれぞれに対して、更なる画像データセットとの間の変換を表す前記予測変位を生成し、
前記識別部は、
前記予測変位が前記生成部により生成された前記予測変位か又は前記予め定めた変位かの識別結果を出力すること、
を特委長とする請求項5又は6記載の学習装置。 - 前記更なる画像データセットは、前記予め定めた変位のうちの1つを使用する前記訓練画像データセットから合成されたものである請求項7記載の学習装置。
- 前記学習部は、前記予め定めた変位及び前記予測変位の識別において、前記識別部のエラーを最小化する又は減少させることを特徴とする請求項5乃至7のうちいずれか一項記載の学習装置。
- 前記識別部は、前記予め定めた変位と前記生成部からの前記予測変位とを受け取り、
前記学習部は、前記予め定めた変位と前記予測変位を識別するように前記識別部を訓練すること、を特徴とする請求項5乃至9のうちいずれか一項記載の学習装置。 - 前記識別部は、前記予め定めた変位と前記予測変位との識別において、残差画像データ、差分画像データ、類似性計測、距離関数、のうちの少なくとも一つを用いて前記識別処理を実行する請求項5乃至10のうちいずれか一項記載の学習装置。
- 前記識別部は、多重識別部を有する請求項5乃至11のうちいずれか一項記載の学習装置。
- 前記複数の訓練画像データセットは、二次元画像データ又は三次元画像データであることを特徴とする請求項5乃至12のうちいずれか一項記載の学習装置。
- コンピュータに、
第一の画像データと第二の画像データとを取得させる取得機能と、
前記第一の画像データと前記第二の画像データとの間のレジストレーション処理を実行するための予測変位を生成させる生成機能と、
を実現させ、
前記生成機能は、前記予測変位の生成と識別機能を用いた訓練とを繰り返し実行することで訓練されており、
前記識別機能は、予め定めた変位と前記予測変位とを区別するように訓練されること、
を特徴とする医用画像処理プログラム。 - 生成部及び識別部を学習させる学習プログラムであって、
コンピュータに、
複数の訓練画像データセットと、前記複数の訓練画像データセットに対応する複数の予め定めた変位と、を取得させる取得機能と、
前記生成部が前記複数の訓練画像データセットに基づいて予測変位を生成する生成処理と、前記識別部が前記予測変位と前記複数の予め定めた変位とを識別する識別処理と、を敵対的に繰り返し実行させて前記生成部及び前記識別部を訓練する学習機能と、
を実現させることを特徴とする学習プログラム。
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US11699281B2 (en) | 2018-04-13 | 2023-07-11 | Elekta, Inc. | Image synthesis using adversarial networks such as for radiation therapy |
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JP2022547594A (ja) * | 2019-11-22 | 2022-11-14 | エヌイーシー ラボラトリーズ アメリカ インク | ジョイントローリングシャッター補正及び画像ぼけ除去 |
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US10878529B2 (en) | 2020-12-29 |
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