Abstract
In medical imaging applications, it is often necessary to enhance the bone-background contrast to improve the visibility of anatomical landmarks. Because of the low contrast nature of these images, many classical image enhancement techniques have met with limited success. In this paper, the image enhancement problem is treated as a natural extension to the image segmentation. We make specific use of the energy dependency of the x-ray attenuation characteristics to establish the basis for classification. The inherent ambiguity or vagueness in the bone-background classification is handled nicely with the fuzzy logic approach. The membership grade is generated with a generalized adaptive median filter to achieve the noise suppression and edge preservation. The final image is obtained by a non-linear gray scale mapping. Phantom and clinical studies have demonstrated the effectiveness of this approach. Some limitations of the approach are also discussed in the paper.
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