JP6469838B2 - 生物組織の3次元ボリュームを表す画像データを分析する方法 - Google Patents
生物組織の3次元ボリュームを表す画像データを分析する方法 Download PDFInfo
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Description
a)局所的成長の評点の和、
b)局所的成長の評点の2乗和、
c)Moran’s I、及び、
d)Geary’s C
の4つの量によって構成される。
図面を用いて以下に各実施形態を説明する。
Claims (14)
- 生物組織の3次元ボリュームを表す画像データを分析する方法であって、
前記画像データは、第1の時点でのボリュームを表す第1の画像と、前記第1の時点とは異なる第2の時点でのボリュームを表す第2の画像と、を含み、
前記方法は、
a)予め定められた方向に主延長部を有する前記第1の画像が表す前記ボリュームの第1のサブボリュームと、前記予め定められた方向に主延長部を有する前記第2の画像が表す前記ボリュームの第2のサブボリュームと、を識別するステップであって、ただし、前記第1のサブボリュームと前記第2のサブボリュームとが前記3次元ボリュームの同一の領域を表すステップと、
b)前記予め定められた方向の前記第1のサブボリュームの一連のボクセルの画像データと前記予め定められた方向の前記第2のサブボリュームの一連のボクセルの画像データとから、距離マトリクスを形成するステップと、
c)前記予め定められた方向に沿って、前記第1のサブボリューム及び前記第2のサブボリュームが表す前記生物組織の層の成長確率に対する少なくとも1つの局所的尺度を取得するために、前記距離マトリクスを分析するステップと、
を含む方法。 - 前記距離マトリクスを分析するステップは、前記距離マトリクスによって与えられる距離の和が、前記距離マトリクスの予め定められた始点を予め定められた終点に接続する経路に沿って最小となるよう、前記経路に対応するワーピング関数を取得するサブステップを含む、
請求項1記載の方法。 - 前記距離マトリクスを分析するステップは、前記経路を基準経路と比較するさらなるサブステップを含み、
前記成長確率に対する前記局所的尺度は、前記経路と前記基準経路との間の全体差に対応する、
請求項2記載の方法。 - 前記成長確率に対する前記局所的尺度は、前記経路及び前記基準経路によって画定される領域の寸法に比例する、
請求項3記載の方法。 - 前記予め定められた方向に対して垂直な平面の所定位置に依存する前記成長確率に対する前記局所的尺度によって構成される成長マップを取得する、
請求項1から4までのいずれか1項記載の方法。 - 前記予め定められた方向に沿って、前記第1の画像及び前記第2の画像が表す前記生物組織の層の成長確率に対する大域的尺度を、機械学習アルゴリズムを前記成長マップに適用することにより取得する、
請求項5記載の方法。 - 前記成長マップから大域的成長特徴ベクトルを抽出し、サポートベクタマシンアルゴリズムを前記大域的成長特徴ベクトルに適用して大域的成長確率をクラス分類するステップを含む、
請求項6記載の方法。 - 前記大域的成長特徴ベクトルは、前記局所的尺度の少なくとも1つの平均と、前記局所的尺度の空間的自動補正の少なくとも1つの尺度と、を含む、
請求項7記載の方法。 - 前記第1のサブボリュームは、前記予め定められた方向に対して垂直な少なくとも1つの方向に、前記第2のサブボリュームの前記少なくとも1つの方向の延長部よりも大きな延長部を有し、
前記距離マトリクスは、前記第2のサブボリュームの、前記予め定められた方向に沿った所定位置に関する第1の次元と、前記第1のサブボリュームの、前記予め定められた方向及び前記予め定められた方向に対して垂直な前記少なくとも1つの方向に沿った所定位置に関する別の少なくとも2つの次元と、を含む、少なくとも3つの次元である、
請求項1から8までのいずれか1項記載の方法。 - 前記距離マトリクスを形成する前に、前記第1のサブボリューム及び前記第2のサブボリュームに関する画像データの輝度を正規化する、
請求項1から9までのいずれか1項記載の方法。 - 前記距離マトリクスを、前記予め定められた方向の前記第1のサブボリュームの一連のボクセルの画像データの輝度の局所的勾配と前記第2のサブボリュームの一連のボクセルの画像データの輝度の局所的勾配とに基づいて形成する、
請求項1から10までのいずれか1項記載の方法。 - 前記画像データは、光コヒーレンストモグラフィ画像データである、
請求項1から11までのいずれか1項記載の方法。 - 前記生物組織は、ヒトもしくは哺乳動物の網膜組織である、
請求項1から12までのいずれか1項記載の方法。 - 生物組織の3次元ボリュームを表す画像データを分析するためのコンピュータプログラムであって、
前記コンピュータプログラムは、コンピュータ上で実行される際に、請求項1から13までのいずれか1項記載の各ステップを実行するのに適したコンピュータプログラムコードを含む、
コンピュータプログラム。
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US6640124B2 (en) * | 1998-01-30 | 2003-10-28 | The Schepens Eye Research Institute | Imaging apparatus and methods for near simultaneous observation of directly scattered light and multiply scattered light |
US7042219B2 (en) * | 2004-08-12 | 2006-05-09 | Esaote S.P.A. | Method for determining the condition of an object by magnetic resonance imaging |
US7483572B2 (en) * | 2004-08-25 | 2009-01-27 | Mitsubishi Electric Research Laboratories, Inc. | Recovering a non-linear warping function from images |
EP1889111A2 (en) | 2005-05-25 | 2008-02-20 | Massachusetts Institute of Technology | Multifocal imaging systems and methods |
US8199994B2 (en) | 2009-03-13 | 2012-06-12 | International Business Machines Corporation | Automatic analysis of cardiac M-mode views |
US8332016B2 (en) * | 2009-08-04 | 2012-12-11 | Carl Zeiss Meditec, Inc. | Non-linear projections of 3-D medical imaging data |
US20110081055A1 (en) | 2009-10-02 | 2011-04-07 | Harris Corporation, Corporation Of The State Of Delaware | Medical image analysis system using n-way belief propagation for anatomical images subject to deformation and related methods |
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