脳MR画像におけるラクナ梗塞の検出法の改良-AdaBoostテンプレートマッチングを用いた偽陽性削除-

DOI 機関リポジトリ HANDLE オープンアクセス
  • 谷河 文香
    岐阜大学工学部応用情報学科
  • 内山 良一
    熊本大学大学院生命科学研究部先端生命医療科学部門
  • 村松 千左子
    岐阜大学大学院医学系研究科知能イメージ情報分野
  • 原 武史
    岐阜大学大学院医学系研究科知能イメージ情報分野
  • 白石 順二
    熊本大学大学院生命科学研究部先端生命医療科学部門
  • 藤田 広志
    岐阜大学大学院医学系研究科知能イメージ情報分野

書誌事項

タイトル別名
  • Improvement of Automatic Detection Method of Lacunar Infarcts on MR Images: Reduction of False Positives By Using AdaBoost Template Matching

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抄録

The detection of lacunar infarcts is important because their presence indicates an increased risk of severe cerebral infarction. However, their accurate identification is often hard because of the difficulty in distinguishing between lacunar infarcts and enlarged Virchow-Robin spaces. Therefore, we developed computer-aided diagnosis scheme for the detection of lacunar infarcts. The performance of our previous method indicated that the sensitivity of 96.8% with 0.76 false positive(FP)per slice. However, further reduction of FPs was remained as an issue to be solved for the clinical application. In this paper, we proposed AdaBoost template matching. This classifier can distinguish between lacunar infarcts and FPs by selecting suitable templates in the template matching. By using this technique, 55.5% FPs were eliminated while keeping the same sensitivity. Thus the proposed method was found to be useful for the sophistication of the automatic detection of lacunar infarcts in MR images.

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