Deformable torso phantoms of Chinese adults for personalized anatomy modelling.

阅读:7
作者:Wang Hongkai, Sun Xiaobang, Wu Tongning, Li Congsheng, Chen Zhonghua, Liao Meiying, Li Mengci, Yan Wen, Huang Hui, Yang Jia, Tan Ziyu, Hui Libo, Liu Yue, Pan Hang, Qu Yue, Chen Zhaofeng, Tan Liwen, Yu Lijuan, Shi Hongcheng, Huo Li, Zhang Yanjun, Tang Xin, Zhang Shaoxiang, Liu Changjian
In recent years, there has been increasing demand for personalized anatomy modelling for medical and industrial applications, such as ergonomics device development, clinical radiological exposure simulation, biomechanics analysis, and 3D animation character design. In this study, we constructed deformable torso phantoms that can be deformed to match the personal anatomy of Chinese male and female adults. The phantoms were created based on a training set of 79 trunk computed tomography (CT) images (41 males and 38 females) from normal Chinese subjects. Major torso organs were segmented from the CT images, and the statistical shape model (SSM) approach was used to learn the inter-subject anatomical variations. To match the personal anatomy, the phantoms were registered to individual body surface scans or medical images using the active shape model method. The constructed SSM demonstrated anatomical variations in body height, fat quantity, respiratory status, organ geometry, male muscle size, and female breast size. The masses of the deformed phantom organs were consistent with Chinese population organ mass ranges. To validate the performance of personal anatomy modelling, the phantoms were registered to the body surface scan and CT images. The registration accuracy measured from 22 test CT images showed a median Dice coefficient over 0.85, a median volume recovery coefficient (RC(vlm) ) between 0.85 and 1.1, and a median averaged surface distance (ASD) < 1.5 mm. We hope these phantoms can serve as computational tools for personalized anatomy modelling for the research community.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。