There are two well-known methods to assess bone age, the Greulich-Pyle method and the Tanner-Whitehouse method, which both utilize the hand radiogram to make bone-age assessment to assist medical doctors to identify the growth status of children. Basically, the morphology of bones could be evaluated to quantitatively describe the maturity. The study extracted the morphology of carpal bones and applied the fuzzy theory with principle component analysis to estimate the maturity of skeleton. Five geometric features of the carpals were extracted including the bone area, the area ratio, and the bone contour of the carpals. In order to analyze these features, the principle component analysis and the statistical correlation combined with three different types of procedure were used to construct a growth model of carpals. Eventually, the results of the three types of procedure with fuzzy rules can construct a bone-age assessment system to identify the maturity of children. The study shows that the proposed model based on fuzzy rule has an accuracy rate above 89% in Type-I and II, and above 87% in Type-III within a tolerance of 1.5 years.
GTA can efficiently simplify the complexity of the TW3 method, while maintaining almost the same accuracy. The relative accuracy between the assessment results of GTA and GP can also be marginal.
Precise and effective bony segmentation from soft tissues on hand radiograph is very critical in the bone age assessment, especially for separating phalanx and epiphyseal/metaphyseal region of interests (EMROIs) from the background and soft tissue. Our aim is to locate and segment the EMROIs based on children's hand radiographs, in which the images are with nonuniform background. Furthermore, a great destructive noise may suppress the segmentation process. The proposed approach combines a series of image preprocessing procedures to crop the left-hand radiograph and EMROIs. The experiments were conducted on different parts of knuckles, such as distal, middle, and proximal. Finally, the segmentation results demonstrate that the proposed schemes can segment the EMROIs automatically and effectively for the extraction of characteristics of bone age assessment.
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