Abstract
In this article，it brings up an automatic procedure that combines the ways to assess the age of the carpal and the phalangeal. The procedure is made to assess the bone age of the growing children by analyzing their X-ray images of the palms. By comparing the bone age with the real age, doctors can find the problems of development early. In the preceding process, we segment the X-ray image of the left hand firstly, and according to the characteristic of morphology statistics in database, make an orientation in the carpal. Then, we find out the central point of the carpal, and segment carpal bone region of interest(CROI) from the intersection of the central point and the orientation. Lastly we use Gabor Filter smoothing image and two tools--- canny edge detector and local variance edge detector---which find the image’s edge to cut out the region of the carpal and the phalangeal from the needless parts such as the background. Feature extracts from the bone image we obtain after finishing the preceding process. We use the horizontal projection of phalangeal’s first joint to make one dimension discrete cosine transform(DCT) and one dimension discrete wavelet transform(DWT). And the carpal area ratio are considered the carpal feature vector. In order to assess the bone age more exactly, we use two different kind of ways---fuzzy and neural network---on the carpal and the phalangeal age assessment systems individually, then analyze the amount of error in each age of these two assessment systems and an integral system that combines both. The result of the experiment shows that the carpal age assessment system would be able to get a better accuracy than the phalangeal age assessment system. Furthermore, the system combines both would be more correct than only one of the age assessment systems. In the odds allowed range within two years of age, the age assessment system combines the ways to assess the age of the carpal and the phalangeal can reach about 85% of the correctness.