Computer-aided diagnosis for pneumoconiosis using Neural Network is presented The rounded opacities on the pneumoconiosis X-ray photo ant picked up quickly through a lack propagation (BP) neural network with several typical training patterns. The naming patterns from 0.6 mmΦ to 4.0 mmΦ are made as simple circles. The neck problem for an automatic pneumoconiosis diagnosis has been to reject the unnecessary part like ribs and vessels shades. In this paper such unnecessary parts ant rejected well by the special technique called "moving normalization"... The new technique called moving 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. Mary simulation examples show that the proposed method gives much reliable result than traditional ones.
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