Performance of Registration Tools on High-Resolution 3D Brain Images

被引:0
|
作者
Nazib, Abdullah [1 ]
Galloway, James [1 ]
Fookes, Clinton [1 ]
Perrin, Dimitri [1 ]
机构
[1] Queensland Univ Technol, Sch Elect Engn & Comp Sci, Brisbane, Qld, Australia
关键词
WHOLE-BRAIN;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Recent progress in tissue clearing allows the imaging of entire organs at single-cell resolution. A necessary step in analysing these images is registration across samples. Existing methods of registration were developed for lower resolution image modalities (e.g. MRI) and it is unclear whether their performance and accuracy is satisfactory at this larger scale (several gigabytes for a whole mouse brain). In this study, we evaluated five freely available image registration tools. We used several performance metrics to assess accuracy, and completion time as a measure of efficiency. The results of this evaluation suggest that ANTS provides the best registration accuracy, while Elastix has the highest computational efficiency among the methods with an acceptable accuracy. The results also highlight the need to develop new registration methods optimised for these high-resolution 3D images.
引用
收藏
页码:566 / 569
页数:4
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