Abstract
Recently the digital dental imaging system (DDIS) has been developed and its use has spread widely. Although it has several advantages, the image quality is not better than that of conventional dental radiographs. Particularly, the density distributions of DDIS images are often insufficient and inadequate. Therefore, the authors considered the density optimization of DDIS images. For this aim, we applied a fuzzy c-means clustering algorithm because the pattern of DDIS images has an extensive variety. Using our method, the denstity distribution of most DDIS images can be improved appropriately. In addition, this method provides a dose reduction for the patients. Consequently, 38.3% of the absorbed dose was decreased.
