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Landmark‐based multi‐region ensemble convolutional neural networks for bone age assessment

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References

2017Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs456 cited
2017Fully Automated Deep Learning System for Bone Age Assessment452 cited
2009The BoneXpert Method for Automated Determination of Skeletal Maturity438 cited
2016Deep learning for automated skeletal bone age assessment in X-ray images434 cited
1986Assessment of Skeletal Maturity and Prediction of Adult Height (TW2 Method)313 cited
2007Bone age assessment of children using a digital hand atlas214 cited
2009An Automated Method for Determination of Bone Age105 cited
2009Automatic determination of Greulich and Pyle bone age in healthy Dutch children96 cited
2001Effect of Knowledge of Chronologic Age on the Variability of Pediatric Bone Age Determined Using the Greulich and Pyle Standards86 cited
2013The applicability of Greulich and Pyle atlas to assess skeletal age for four ethnic groups77 cited
2010Validation of a New Method for Automated Determination of Bone Age in Japanese Children51 cited
2014Fully Automatic Bone Age Estimation from Left Hand MR Images34 cited
2013Automated Determination of Bone Age in a Modern Chinese Population31 cited
2015Validation of adult height prediction based on automated bone age determination in the Paris Longitudinal Study of healthy children

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2022SMANet: multi-region ensemble of convolutional neural network model for skeletal maturity assessment10 cited