The fuzzy system consists of six subsystems referred to six ROIs. Each subsystem includes two classifiers: one, for younger children, uses the shape and size features and another one, for older children, applies the wavelet features. When both stages of development interfere and all features are available, the outputs of both subsystems are averaged.
The bone age is assessed in two stages. First, the age is assessed independently for each ROI. This yields fuzzy sets. Then, the results are combined into the fuzzy verdict of the system. Finally, the fuzzy output is defuzzified with a center of gravity method in order to give an exact classification of the bone age.
At the final aggregation step the classifier has to deal with a changing number of inputs and a tolerance to partially erroneous features. The former happens when an error in processing of a ROI is automatically detected and the features are not extracted. The latter problem is due to minor errors in the processing of a ROI that have passed undetected. It has been solved by applying an aggregation method that extracts a common kernel of the age assessment for all ROIs.

The accompanying figure shows the results of bone age assessment as they appear in the output window. The system displays:

• fuzzy bone age assessment for every ROI
• aggregated fuzzy bone age
• bone age as classical number calculated with a center-of-gravity method

The radiologist can accept the assessment of the system or choose another value on base of underlining fuzzy assessment. The shape of a fuzzy set yields information about the accuracy of the assessment.