Identification and Diagnosis of LDH Based on Medical Image Recognition
To realize fully automatic classification of herniation symptoms in lumbar MR images and improve the accuracy of lumbar disc herniation(LDH)diagnosis,an improved PSO-SVM classification algorithm is proposed.Particle swarm algorithm(PSO)is used to determine the optimal parameters of SVM,which improves the classification accuracy of SVM.Firstly,for the blurred image,preprocessing is carried out by the method of denoising and denoising.Then,according to the characteristics of verte-bral mass and intervertebral disc,shape,area features and thresholding are used for segmentation,respectively.The four points of the caudal vertebra are determined by means of contour poles,which improves the accuracy of positioning the caudal vertebra.Final-ly,the type of disc herniation is classified by using the improved PSO-SVM algorithm.Through the comparison experiments with tra-ditional SVM,WPA-SVM and unimproved PSO-SVM algorithms,it is proved that the improved algorithm in this paper has a good LDH classification effect,and the accuracy rates of the validation set and test set are 92.50%and 94.00%respectively.
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