著者
長野 宣道 松尾 孝美 伊藤 隆志 友成 健一朗 白石 順二
出版者
公益社団法人 日本放射線技術学会
雑誌
日本放射線技術学会雑誌 (ISSN:03694305)
巻号頁・発行日
vol.68, no.11, pp.1474-1485, 2012-11-20 (Released:2012-11-21)
参考文献数
28

We proposed a method for a computer-aided diagnosis system that distinguishes between benign and malignant lesions in gastrointestinal digital radiography. To begin with, the level set method was applied in order to extract a tumor region from the image which was smoothed by the bilateral filter. Next, we selected four image features with the large SN ratio among various image features obtained from a tumor region using the Mahalanobis-Taguchi method, which has been employed mainly in quality engineering. The selected four image features—circularity, irregularity, size, and perimeter—were used as input data for the artificial neural network, which was employed for distinction between benign and malignant lesions. By using 43 regions of interest cropped from the 43 clinical cases, the area under the ROC curve (AUC) of diagnostic accuracy for the classification obtained with this proposed method was 0.970, whereas the average AUC obtained with 7 human observers (3 radiologists and 4 radiological technologist) was 0.941.

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《SCILABでガウシアンフィルタの「正規分布」を作ってみました(^^)》 今日は,ディジタル画像のノイズ除去でよく使用されている「ガウシアンフィルタ」を復讐するため,早速「SCILAB」を使用して「正規分布のグラフ」を作ってみました.MATLABは皆さんが個人で購入するのには金額が高すぎてたぶん無理ですから、このフリーソフトのSCILABを紹介します.さてガウシアンフィルタですが、このフィルタ ...

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