Consideration for Density Optimization and Dose Reduction of Digital Dental Imaging System Using Fuzzy Control

近年来，数字口腔成像系统（DDIS）得到了广泛的发展和推广。然而，由于密度分布不足，DDIS的图像并不总是那么好。因此，DDIS似乎需要以适当的方式进行密度优化。为此，作者采用了模糊推理和模糊c均值聚类算法。与传统的直方图均衡化方法相比，我们的方法可以更好地改善大多数DDIS图像的密度分布。此外，该方法还可用于降低患者的吸收剂量。如果曝光时间比标准曝光时间短，图像的密度不足，可以按照上述方法进行密度补偿。结果表明，吸收剂量可降低38.3%。

The digital dental imaging system (DDIS) has been developed and spread widely in recent years. The images of DDIS, however, aren't always so good, because of insufficient density distribution. Therefore, it seems that DDIS requires density optimization in an appropriate way. The authors applied the fuzzy reasoning and fuzzy c-means clustering algorithm for this purpose. According to our method, density distribution of most DDIS images could be improved better than the conventional histogram equalization method.Moreover, this method could be applied for the reduction of absorbed dose of the patients. If the exposure time is shorter than standard one and the density of the image is insufficient, the density can be compensated acoording to the method described as above. Consequently, it was suggested that the absorbed dose could be decreased 38.3%.