期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2000
卷号：XXXIII Part B5/1
页码：453-458
出版社：Copernicus Publications
摘要：Computer aided diagnosis for pneumoconiosis using neural network is presented. The rounded opacities in the pneumoconiosis X-ray photo are picked up by a back propagation (BP) – neural network with several typical training patterns. The training patterns fro m 0.6 mm f to 30 mm f are made by simp le circles. The neck problem for an automatic pneumoconiosis diagnosis has been to reject the unnecessary part like ribs and vessel's shades. In this paper such an unnecessary part is rejected well b y adding several output neurons for own presenting neural network . These neurons are used only for picking unnecessary parts up. The input for the neural network is 30 ′ 30 pixel image which is quarried succeedingly from the bi-level ROI (region of interest) image with the size 500 ′ 500 pixel. The new technique called mo ving normalization is developed here in order to made an appropriate bi-level ROI image. The total evaluation is done from the size and figure categorization and density categorization. many simulation examples show that the proposed method gives much reliable results than traditional ones
