多クラスAdaBoostを用いた3次元腹部CT像における腹部血管領域への血管名自動命名手法に関する研究 : 血管名識別器における検討

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  • タクラス AdaBoost オ モチイタ 3ジゲン フクブ CTゾウ ニ オケル フクブ ケッカン リョウイキ エ ノ ケッカンメイ ジドウ メイメイ シュホウ ニ カンスル ケンキュウ : ケッカンメイ シキベツキ ニ オケル ケントウ
  • A study on automated anatomical labeling to abdominal arteries in 3D abdominal CT images by using multil-class AdaBoost : Improvement of classifiers of the artery names

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We have developed an automated anatomical labeling method for the abdominal arteries to support understanding of the structure of the arteries for doctors in abdominal surgeries. This method labels artery names by using classifiers constructed with the multi-class AdaBoost. However, miss-labelings of the classifiers were caused in many cases. In this paper, we present a method to improve artery name labeling performance by adjusting weights of the classifiers of the AdaBoost. We also introduce new future values for the classifiers. We applied the proposed method to 38 cases of 3D contrasted abdominal CT images. The average recall and precision rates of the proposed method were 87.6% and 72.5%, respectively.

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