Study on imaging fault detection method of nursing scanner in thoracic surgery
Aiming at the problems of low detection accuracy and poor stability,a thoracic surgical nursing scanner imaging fault detection method based on SVR optimized depth certainty gradient algorithm is proposed.Firstly,the principle of depth deterministic strategy gradient algorithm is analyzed;then,support vector machine SVR is introduced into the depth deterministic strategy gradient algorithm to reduce the estimated gradient variance to achieve rapid convergence;finally,SVR optimization depth deterministic gradi-ent algorithm is applied to thoracic nursing scanner imaging to build a fault detection model to realize the accurate fault detection of the scanner.The experimental results show that the detection accuracy of deviation,offset,complete failure and precision failure is 95.42%,96.17%,94.09%and 98.33%respectively,stable at 90%or more,and all higher than the traditional DDPG model,EMD-MDT model and KPCA-SVM model.This shows that this model can realize the accurate detection of imaging faults of thoracic surgery nursing scanner,significantly improve the detection accuracy and stability,and meet the needs of practical application.