To diagnose and test the orphan neuromuscular disease——Duchenne muscular dystrophy (DMD) in early stage,an experimental plan was designed.First,the magnetic resonance images (MRI) for DMD patients and healthy persons were decomposed into wavelets by using wavelet transform technique.Then,the dimension reduction was conducted with respect to the texture feature parameters extracted from the decomposed images.In the end,on the basis of the texture feature parameters,the classification and prediction of these images were carried out by using support vector machines (SVM).The results show that if the suitable combination of wavelet function,decomposed scale,kernel function and related parameters were selected,the classification sensitivity,specificity and overall correct classification rate of the MRI images can reach 96.9%, 97.3% and 97.1% respectively.This plan might provide an objective and effective auxiliary method for clinical diagnoses.