Anti-Interference Study on Radiographic Bone Age Estimation Based on Artificial Intelligence Model  

作　　者：Songzheng Huang Jianfeng Chen Songzheng Huang;Jianfeng Chen(Zhejiang Kangyuan Medical Devices Incorporation, Hangzhou, China;Department of Radiology and Medical Imaging, Stritch School of Medicine, Loyola University Medical Center, Chicago, Illinois, USA)

机构地区：[1]Zhejiang Kangyuan Medical Devices Incorporation, Hangzhou, China [2]Department of Radiology and Medical Imaging, Stritch School of Medicine, Loyola University Medical Center, Chicago, Illinois, USA

出　　处：《Open Journal of Radiology》2023年第4期232-245,共14页放射学期刊(英文)

摘　　要：In this paper, the interferences of X-ray image noise on a bone age model, Xception model, were studied. We conduct a comparative experiment test according to the output performance of the neural network model using both the original image training and noise-added (Gaussian noise plus salt-pepper noise) training, and analyze the anti-interference ability of the Xception model, hoping to improve it through noise enhancement training and generalize the application ability of the model. The results show that the model trained with noise-added (Gaussian noise plussalt-pepper noise) images can make predictions that are more robust and less affected by the image disturbances, such as image noise.In this paper, the interferences of X-ray image noise on a bone age model, Xception model, were studied. We conduct a comparative experiment test according to the output performance of the neural network model using both the original image training and noise-added (Gaussian noise plus salt-pepper noise) training, and analyze the anti-interference ability of the Xception model, hoping to improve it through noise enhancement training and generalize the application ability of the model. The results show that the model trained with noise-added (Gaussian noise plussalt-pepper noise) images can make predictions that are more robust and less affected by the image disturbances, such as image noise.

关 键 词：Bone Age X-Ray Image Xception Model Gaussian Noise Salt-Pepper Noise 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]