CT画像における早期虚血サイン検出アルゴリズムの開発

概要

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This paper describes an approach to automatically detect the parenchymal hypoattenuation of hyperacute stroke in nonenhanced computed tomography (CT) images. This technique is based on a comparison between the CT values histograms of right and left brains. A subtraction curve that was regarded as an output value was calculated by subtracting the right-hemispherical histogram from the left-hemispherical histogram obtained from one of the region-of-interest (ROI) sets on an image. The output value was used to assess whether hypoattenuation exists on CT images with a threshold value. If judged abnormal, a rectangular region including a whole or partial hypoattenuation area was detected from the ROI. Twenty-six cases with hypoattenuation and 30 cases without hypoattenuation were included in this study. As a result of our experiments, the sensitivity of this method in detecting hypoattenuation was found to be 92%, with approximately 0.16 false-positive per image. Our preliminary experimental results indicated that the proposed technique can be used for the automated detection of parenchymal hypoattenuation of hyperacute stroke on nonenhanced CT images.
社団法人日本放射線技術学会の論文
2007-08-20