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Classification and Identification of magnetic resonance image of neuromuscular disease DMD with wavelet transform and artificial neural network
Pages: 342-346
Year: Issue:  4
Journal: Optical Technique

Keyword:  duchenne muscular dystrophymagnetic resonance imagecomputer-aided detectionwavelet transformartificial neural network;
Abstract: Duchenne muscular dystrophy(DMD)is a severe orphan neuromuscular disease in the part of legs.The conventional treatment is invasive,which incurs great sufferings.Therefore,with the aid of computers,a non-invasive detection method is explored on the basis of magnetic resonance images(MRI)of the patients.Two wavelet basis function,sym4 and db4are used and wavelet decomposition is conducted for three levels of MRI from both the sick and the healthy.12 texture parameters are extracted from the decomposed images.In the end,classification and recognition of these images are carried out by using Artificial Neural Network on the basis of these texture feature parameters.Conclusions of the study are as follows:(1)In the two kinds of weighed images(T1and T2)of the sick,T1 is better in distinguishing the sick from the healthy.(2)The results of wavelet decomposition with db4 function are better than those with sym4 function,and in the three levels decomposed,the second level is the best.(3)With the optimal wavelet function and decomposition level,classification and recognition can produce very excellent outcomes.The sensitivity,specificity and accuracy rate might reach as high as 98.5%,97.3%,97.9% respectively.This method,as a pilot for non-invasive treatment of DMD,could be expected to provide an objective and effective auxiliary method for clinical diagnoses.
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