Objective To explore the automatic positioning method of ankle joint X-ray landmarks based on neural network deep learning model and its application value.Methods The normal left ankle joint anterior-lateral X-ray images of 360 adults between January 2019 and November 2022 were obtained from Shaanxi Provincial People's Hospital as research objects,and were randomly assigned to the training set(210 cases),validation set(90 cases)and test set(60 cases).With manual annotation as a reference,the prediction models of ankle joint landmarks based on neural network Unet architecture were established after image preprocessing,and the corresponding thermal maps were generated,and verified with the test set data.Results In the prediction of the 6 landmarks of the ankle joint X-ray anterior images,the average percentage of correct keypoints(PCK)of 2 mm threshold reached 99.7％,the total mean radial errors(MRE)was 0.411,and the total standard deviation(SD)was 0.290.The prediction accuracy of inner point at the top of talus(IPTT)among the 6 points was the highest,and the PCK of this point at 1 mm threshold reached 100％,and its MRE and SD were also the smallest among the 6 points of X-ray anterior images,which were 0.290 and 0.178 respectively.In the prediction of the 9 landmarks of the ankle joint X-ray lateral images,the PCK of this point at 1 mm threshold reached 95％,and the total MRE was 0.669,and the total SD was 0.710.The prediction accuracy of anterior point of lower tibia(APLT)among the 9 points was the highest,and the PCK of this point at 1 mm threshold reached 100％,and its MRE and SD were also the smallest among the 9 points of X-ray lateral images,which were 0.334 and 0.173 respectively.There was no statistical difference between the predicted position coordinates and the corresponding reference standard position coordinates of all the landmarks in the ankle joint X-ray anterior images and lateral images(P＞0.05).Conclusion The neural network deep learning model can realize the effective automatic positioning of ankle joint X-ray landmarks,which has application value in assisting the automatic measurement of ankle X-ray morphology and disease diagnosis and treatment.
维普
万方数据