Department of Medical Informatics, RWTH Aachen University, Pauwels str. 30, 52057, Aachen, Germany.
Int J Comput Assist Radiol Surg. 2012 May;7(3):389-99. doi: 10.1007/s11548-011-0627-8. Epub 2011 Jun 14.
Maturity estimation by radiological bone age assessment (BAA) is a frequent task for pediatric radiologists. Following Greulich and Pyle, all hand bones are compared with a standard atlas, or a subset of bones is examined according to Tanner and Whitehouse. We support BAA comparing the epiphyses of a current case to similar cases with validated bone age by content-based image retrieval (CBIR).
A web-based prototype case-based retrieval system for BAA was developed and is publicly available. Hand radiographs from the USC database or user uploads may be retrieved by image-based query. The ten best matching cases for each epiphysis are retrieved by CBIR and displayed with their BAA, similarity score, and the derived age estimate. The similarity is approximated by cross-correlation. The USC hand database includes 1,101 cases comprising four ethnic groups of both genders between zero and 18 years of chronological age with radiographs and two annotated BAA. The USC image data have been enriched by marking the epiphyseal centers between metacarpals and distal phalanges.
Leave-one-out experiments yielded a mean error rate of 0.99 years and a standard deviation of 0.76 years in comparison with the mean USC-BAA. The research prototype enables radiologists to judge their agreement based on similarity of retrieved cases and the derived age.
CBIR provides support to the radiologist with a second opinion for BAA. Self-explanatory web applications can be established to support workflow integration. Enhancements in similarity computation and interface usability may further improve the system.
通过放射学骨龄评估（BAA）进行成熟度估计是儿科放射科医生的一项常见任务。按照 Greulich 和 Pyle 的方法，所有手部骨骼都与标准图谱进行比较，或者根据 Tanner 和 Whitehouse 的方法检查骨骼子集。我们通过基于内容的图像检索（CBIR）支持 BAA，即将当前病例的骨骺与具有验证骨龄的类似病例进行比较。
我们开发了一个基于网络的 BAA 基于病例的检索系统原型，并公开发布。可以通过图像查询检索来自 USC 数据库或用户上传的手部 X 光片。通过 CBIR 为每个骨骺检索十个最佳匹配的病例，并显示其 BAA、相似度得分和得出的年龄估计。相似度通过互相关近似。USC 手部数据库包含来自四个种族的 1101 例病例，这些病例包括零到 18 岁的男女，具有 X 光片和两个标注的 BAA。USC 图像数据通过标记掌骨和远节指骨之间的骨骺中心得到了丰富。
与 USC-BAA 的平均值相比，留一法实验的平均误差率为 0.99 岁，标准差为 0.76 岁。研究原型使放射科医生能够根据检索到的病例的相似性和得出的年龄来判断他们的一致性。
CBIR 为放射科医生提供了 BAA 的第二个意见支持。可以建立自解释的 Web 应用程序来支持工作流程集成。改进相似度计算和界面可用性可能会进一步改进该系统。
