JP6533147B2 - プロセッサ装置、内視鏡システム、及び画像処理方法 - Google Patents
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Description
式1: μs∝λ−b
図1に示すように、内視鏡システム10は、内視鏡12と、光源装置14と、プロセッサ装置16と、モニタ18(表示部)と、コンソール19とを有する。内視鏡12は光源装置14と光学的に接続されるとともに、プロセッサ装置16と電気的に接続される。内視鏡12は、被検体内に挿入される挿入部12aと、挿入部12aの基端部分に設けられた操作部12bと、挿入部12aの先端側に設けられた湾曲部12c及び先端部12dを有している。操作部12bのアングルノブ12eを操作することにより、湾曲部12cは湾曲動作する。この湾曲動作によって、先端部12dが所望の方向に向けられる。
上記第1実施形態では、散乱特徴量bを用いてベース画像81に色付けをして散乱特徴量画像82を生成しているが、散乱特徴量画像82を生成する際には、散乱特徴量b以外の生体情報等を加味してベース画像81に色付けをしてもよい。
16 プロセッサ装置
54 画像取得部
61 画像処理部
62 通常処理部
63 特殊処理部
71 散乱特徴量算出部
72 LUT記憶部
74 画像生成部
75 散乱特徴量LUT
271 酸素飽和度算出部
275 酸素飽和度LUT
700 カプセル内視鏡
Claims (10)
- 青色波長帯域、緑色波長帯域、及び赤色波長帯域の3波長帯域の画像を取得する画像取得部と、
前記3波長帯域の画像から色情報を取得し、前記色情報を用いて、観察対象の散乱特性を表す散乱特徴量を算出する散乱特徴量算出部と、
前記散乱特徴量の分布を表す散乱特徴量画像を生成する画像生成部と、
を備え、
前記散乱特徴量算出部は、前記赤色波長帯域の画像と前記緑色波長帯域の画像の比と、前記緑色波長帯域の画像と前記青色波長帯域の画像の比と、を前記色情報として算出し、算出した前記比を用いて前記散乱特徴量を算出するプロセッサ装置。 - 前記青色波長帯域、前記緑色波長帯域、及び前記赤色波長帯域は、酸化ヘモグロビンと還元ヘモグロビンの吸光係数が等しい等吸収波長帯域を含む請求項1に記載のプロセッサ装置。
- 前記散乱特徴量算出部は、前記散乱特徴量として、前記観察対象の散乱係数の波長依存性を表すパラメータを算出する請求項1または2に記載のプロセッサ装置。
- 前記色情報を軸にして形成され、波長「λ」と、前記観察対象の散乱係数μsと、前記散乱特徴量「b」との関係が式1で定義される色情報空間において、前記散乱特徴量算出部は前記色情報に対応する前記散乱特徴量「b」を算出する請求項3に記載のプロセッサ装置。
式1: μs∝λ-b - 前記画像取得部は、前記3波長帯域と比較して、ヘモグロビンの吸光係数と、還元ヘモグロビンの吸光係数に差がある第4の波長帯域の画像を取得し、
前記第4の波長帯域の画像を用いて前記観察対象の酸素飽和度を算出する酸素飽和度算出部を備え、
前記画像生成部は、前記散乱特徴量の分布に加え、酸素飽和度の分布も表す前記散乱特徴量画像を生成する請求項1〜4のいずれか1項に記載のプロセッサ装置。 - 前記画像生成部は、前記散乱特徴量と前記酸素飽和度にそれぞれ範囲を設定し、前記散乱特徴量が設定した範囲にあり、かつ、前記酸素飽和度が設定した範囲にある部分を強調した前記散乱特徴量画像を生成する請求項5に記載のプロセッサ装置。
- 前記画像生成部は、前記散乱特徴量を第1閾値と比較し、前記散乱特徴量が前記第1閾値以下の部分を強調した前記散乱特徴量画像を生成する請求項6に記載のプロセッサ装置。
- 前記画像生成部は、前記酸素飽和度を第2閾値と比較し、前記酸素飽和度が前記第2閾値以下の部分を強調した前記散乱特徴量画像を生成する請求項6または7に記載のプロセッサ装置。
- 照明光を発光する光源と、前記光源に接続された内視鏡とを備える内視鏡システムにおいて、
青色波長帯域、緑色波長帯域、及び赤色波長帯域の3波長帯域の画像を取得する画像取得部と、
前記3波長帯域の画像を用いて観察対象の散乱特性を表す散乱特徴量を算出する散乱特徴量算出部と、
前記散乱特徴量の分布を表す散乱特徴量画像を生成する画像生成部と、
を有するプロセッサ装置をさらに備え、
前記散乱特徴量算出部は、前記赤色波長帯域の画像と前記緑色波長帯域の画像の比と、前記緑色波長帯域の画像と前記青色波長帯域の画像の比と、を算出し、算出した前記比を用いて前記散乱特徴量を算出する内視鏡システム。 - 画像取得部が、青色波長帯域、緑色波長帯域、及び赤色波長帯域の3波長帯域の画像を取得するステップと、
散乱特徴量算出部が、前記3波長帯域の画像を用いて観察対象の散乱特性を表す散乱特徴量を算出するステップと、
画像生成部が、前記散乱特徴量の分布を表す散乱特徴量画像を生成するステップと、
を、内視鏡システムのプロセッサ装置が実行し、
前記散乱特徴量算出部は、前記赤色波長帯域の画像と前記緑色波長帯域の画像の比と、前記緑色波長帯域の画像と前記青色波長帯域の画像の比と、を算出し、算出した前記比を用いて前記散乱特徴量を算出する画像処理方法。
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JP2015218343A JP6533147B2 (ja) | 2015-11-06 | 2015-11-06 | プロセッサ装置、内視鏡システム、及び画像処理方法 |
EP16861841.1A EP3372142A4 (en) | 2015-11-06 | 2016-09-16 | Processor device, endoscope system, and image-processing method |
PCT/JP2016/077502 WO2017077772A1 (ja) | 2015-11-06 | 2016-09-16 | プロセッサ装置、内視鏡システム、及び画像処理方法 |
US15/969,779 US10939856B2 (en) | 2015-11-06 | 2018-05-03 | Processor device, endoscope system, and image processing method |
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WO2015093295A1 (ja) * | 2013-12-20 | 2015-06-25 | オリンパス株式会社 | 内視鏡装置 |
WO2018098465A1 (en) | 2016-11-28 | 2018-05-31 | Inventio, Inc. | Endoscope with separable, disposable shaft |
JP7090699B2 (ja) * | 2018-05-17 | 2022-06-24 | オリンパス株式会社 | 内視鏡装置及び内視鏡装置の作動方法 |
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US20080024868A1 (en) * | 2004-06-15 | 2008-01-31 | Olympus Corporation | Illuminating Unit and Imaging Apparatus |
JP2006003103A (ja) * | 2004-06-15 | 2006-01-05 | Olympus Corp | 照明ユニット及び撮像装置 |
JP4879374B2 (ja) * | 2010-05-19 | 2012-02-22 | オリンパスメディカルシステムズ株式会社 | 内視鏡及び内視鏡装置 |
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