人工智能在儿童骨龄影像检测中的应用

目的 研究对比证明解决人工判读骨龄存在耗时长、人为主观影响大、结果一致性稳定性差等问题.方法 使用G-P图谱法、TW计分法、中华05等方法对骨龄X光影像进行对照,开展人工智能和人工判读、以及人工智能辅助人工判读的研究,并进行多阅片者间差异性研究.结果 基于TW3标准,250份儿童骨龄片由人工智能系统与医生对比,TW3-...

Application of Artificial Intelligence in Evaluating the Bone Age Image of Children

Objective To study and compare the results to prove that it takes a long time to solve the problems of manual bone age interpretation,such as high human subjective influence,poor consistency and stability of results,etc.Methods G-P map,TW score method,Zhonghua 05 and other methods were used to compare bone age X-ray images.Artificial intelligence,artificial interpretation and artificial intelligence-assisted artificial interpretation were studied,and the differences among multiple readers were studied.Results Based on the standard TW3,250 bone age images of children were compared by artificial intelligence system and doctor,TW3-AI model interpretation efficiency on the average processing time was 1.5±0.2 s,significantly shorter than the doctor’s 525.6±55.5 s.In terms of accuracy and reliability,the root mean square of TW3-AI model and expert interpretation results was 0.50 years,indicating a high degree of consistency between the two.Based on G-P standard,the bone age of 745 patients with abnormal growth and development was estimated.The average time of doctors’interpretation was about 2 min,and the AI model only needed 1~2 s.In terms of accuracy,the average proportion of the AI system was less than one year from the gold standard,84.60%.Based on the Chinese 05 standard,the average time of manual group reading was significantly higher than that of AI conformance assisted assessment.Conclusion The intelligent detection system of children’s bone age can complete the imaging analysis of children’s bone age at the second level and provide quantitative results such as ossification center rating and bone age,so as to assist doctors in rapid disease diagnosis and efficacy evaluation,and provide decision-making basis for the diagnosis and treatment of children’s endocrine diseases.