Automatic Color Segmentation Method Using a Neural Network Model for Stained Images

概要

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This paper describes a color segmentation method which is essential for automatic diagnosis of stained images. This method is applicable to the variance of input images using a three-layered neural network model. In this network, a back-propagation algorithm was used for learning, and the training data sets of RGB values were selected between the dark and bright images of normal mammary glands. Features of both normal mammary glands and breast cancer tissues stained with hematoxylin-eosin (HE) staining were segmented into three colors. Segmented results indicate that this network model can successfully extract features at various brightness levels and magnifications as long as HE staining is used. Thus, this color segmentation method can accommodate change in brightness levels as well as hue values of input images. Moreover, this method is effective to the variance of scaling and rotation of extracting targets.
社団法人電子情報通信学会の論文
1994-03-25