Quality control system based on artificial intelligence for improving imaging quality of chest CT / 中国医学影像技术

ABSTRACT

Objective To observe the value of quality control system based on artificial intelligence(AI)for improving imaging quality of chest CT.Methods Totally 1 726 CT images obtained from 415 patients were retrospectively collected,among which 1 414 images were used for convolutional neural network(CNN)training and the rest 312 images were used for validation.Precision,Recall,F1-Score,mean average precision(mAP)and intersection over union(IOU)of quality control system based on AI for chest CT scanning were calculated.Meanwhile,21 patients with unsatisfactory chest CT who would undergo re-examination were prospectively enrolled,and chest CT scanning with quality control system based on AI were performed.The results of 2 examinations were compared.Results Precision,Recall,F1-Score,mAP and IOU of quality control system based on AI for chest CT were all good.All 21 cases were diagnosed correctly with re-examination CT based on quality control system.Among 21 cases,the first CT misdiagnosed 19 cases,the displaying of the area,volume and display quality of pulmonary nodules were not significantly different,but the morphology,boundaries,spiny protrusions,vacuolar signs,inflatable bronchial signs of nodules as well as the thickened and twisted blood vessels were obviously different between 2 times examination.The first CT missed 1 case while correctly diagnosed 1 case.Conclusion The quality control system based on AI was helpful for improving imaging quality of chest CT and increasing diagnostic efficacy.