發明
日本
特願 2021-135019
特許 7142754
以超頻譜檢測物件影像之方法「畳み込みニューラルネットワークを使用して食道癌の画像を検出する方法」
國立中正大學
2022/09/15
本發明係有關一種以超頻譜檢測物件影像之方法,其先依據參考影像取得一超頻譜影像資訊,再藉此將輸入影像轉換出對應之超頻譜影像,以取得對應之特徵值,並進主成分分析,以簡化特徵值,然後透過卷積核取得特徵影像,再將特徵影像中以一預設框搭配一邊界框定位出一待測物件影像,經比對樣本影像,而將該待測物件影像分類為一目標物件影像或一非目標物件影像。藉此,透過卷積神經網路檢測影像擷取裝置所輸入之輸入影像是否為目標物件影像,因而輔助醫生判讀食道影像。 The invention related to a method for detecting image of esophageal cancer using hyperspectral imaging. Firstly, obtaining a hyperspectral imaging information according to a reference image, hereby, obtaining corresponded hyperspectral image from an input image and obtaining corresponded feature values for operating Principal components analysis to simplify feature values. Then, obtaining feature images by Convolution kernel, and then positioning an image of an object under detected by a default box and a boundary box from the feature image. By Comparing with the esophageal cancer sample image, the image of the object under detected is classifying to an esophageal cancer image or a non- esophageal cancer image. Thus, detecting an input image from the image capturing device by the convolutional neural network to judge if the input image is the esophageal cancer image for helping the doctor to interpret the image of the object under detected.
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