Reliability Detection System Of Stereotactic Radiotherapy Equipment Based On Video Analysis

Stereotactic radiotherapy has one of the main means of treating tumors and has an irreplaceable important role.However,China's radiotherapy technology started late,due to the immature technology,radiotherapy equipment will have various failures during use.Accurate recording and collection of equipment fault information can help equipment manufacturers to improve their own short board and improve the quality of stereotactic radiotherapy equipment.At present,the types of radiotherapy equipment used in domestic hospitals are various,which makes the data interface difficult to unify.Only manual methods can be used to record the fault information of the collection equipment,resulting in a large waste of human resources.Therefore,the development of a fully automatic fault detection system has a positive significance for ensuring the safety of stereotactic radiotherapy equipment.Due to the diverse brands of stereotactic radiotherapy equipment in China,the types of equipment failures of various models are different,which poses a huge challenge to the realization of the system.At present,the main problems are mainly reflected in: First,the diversity of devices to be tested requires the development of a system that supports fault detection for multiple devices.Second,the fault information of each device is diverse,and the location of the fault is uncertain.Problem,the system can accurately locate and classify faults of different types of equipment.In this system,TensorFlow is used to complete the fault classification model fault training,and OpenCV and C++ are used to complete the system function.The main function is to work on the stereotactic radiotherapy equipment for each type of radiotherapy equipment.Detect faults that occur during their work,save the fault image,record the fault occurrence time,end time,duration,count the total number of faults,and finally generate a test log.The advantages of this system are: first,support fault detection of multiple devices.For different radiotherapy devices,only need to enter each device information into the system as a configuration file.When detecting different devices,only need to replace the corresponding configuration file;Secondly,the SSD target detection algorithm based on deep learning can accurately determine the specific location of the fault,and then use KNN algorithm to accurately classify the fault.Finally,the system was tested by video images of 20 different types of devices.The system has accurate detection results and high recognition rate,which indicates that the system can meet the reliability detection requirements of stereotactic radiotherapy equipment.