Dual-Channel Shoulder Joint X-ray Bone Age Estimation in Chinese Han Ado-lescents Based on the Fusion of Segmentation Labels and Original Images
10.12116/j.issn.1004-5619.2025.250106
- VernacularTitle:基于分割标签与原始图像融合的双通道汉族青少年肩关节X线骨龄评估
- Author:
Hui-Ming ZHOU
1
;
Dan-Yang LI
;
Lei WAN
;
Tai-Ang LIU
;
Yuan-Zhe LI
;
Mao-Wen WANG
;
Ya-Hui WANG
Author Information
1. 山西医科大学法医学院,山西 晋中 030600;司法鉴定科学研究院 上海市法医学重点实验室 司法部司法鉴定重点实验室 上海市司法鉴定专业技术服务平台,上海 200063
- Keywords:
forensic anthropology;
age estimation;
X-ray image;
shoulder joint;
convolutional neural net-work;
segmentation network;
adolescents
- From:
Journal of Forensic Medicine
2025;41(3):208-216
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.
