five

Coordinate selection data.

收藏
Figshare2024-10-07 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Coordinate_selection_data_/27181446
下载链接
链接失效反馈
官方服务:
资源简介:
PurposeThe position and orientation of the head is maintained to be relatively similar during the CT / MR imaging process. However, the position / orientation dissimilarities present in the resulting images between patients, or between different scans of the same patient, do not allow for direct comparison of the images themselves or features / metrics extracted from them. This paper introduces a method of defining a coordinate system which is consistent between patients and modalities (CT and MR) for images of the temporal bone, using easily identifiable landmarks within the semicircular canals.MethodsCone Beam CT and high resolution MRI (T2) images of the temporal bone from 20 patients with no cochlear or temporal bone pathology in either modality were obtained. Four landmarks within the semicircular canals were defined that can be identified in both modalities. A coordinate system was defined using these landmarks. Reproducibility of landmark selection was assessed using intra- and inter-rater reliability (for three expert raters and two repeats of the landmark selection). Accuracy of the coordinate system was determined by comparing the coordinates of two additional landmarks in CT and MR images after their conversion to the proposed coordinate system.ResultsIntraclass Correlation Coefficients at a 95% level of confidence showed significant agreement within and between raters as well as between modalities. The differences between selections, raters, and modalities (as measured using mean, standard deviation, and maximum) were low and acceptable for clinical applications.ConclusionThe proposed coordinate system is suited for use in images of the temporal bone and inner ear. Its multi-modal nature enables the coordinate system to be used in tasks such as image co-registration.
创建时间:
2024-10-07
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作