计算机与数字工程2024，Vol.52Issue(10)：3084-3088,3106,6.DOI:10.3969/j.issn.1672-9722.2024.10.040
基于图像识别的腰椎间盘突出症的诊断
Identification and Diagnosis of LDH Based on Medical Image Recognition
摘要
Abstract
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.关键词
腰椎间盘突出症/图像识别/阈值分割/PSO-SVMKey words
lumbar disc herniation/image identification/image recognition/PSO-SVM分类
医药卫生引用本文复制引用
蒋正伟,杨化林,李向荣,王帅..基于图像识别的腰椎间盘突出症的诊断[J].计算机与数字工程,2024,52(10):3084-3088,3106,6.基金项目
国家自然科学基金项目(编号:52101401) （编号:52101401）
山东省自然科学基金项目(编号:ZR2019MEE102)资助. （编号:ZR2019MEE102）
