Point-cloud registration using adaptive radial basis functions

被引：19

作者：

Zhang, Ju ^{[1
]}

Ackland, David ^{[2
]}

Fernandez, Justin ^{[1
,3
]}

机构：

[1] Univ Auckland, Auckland Bioengn Inst, Level G,Uniserv House,70 Symonds St, Auckland 1010, New Zealand

[2] Univ Melbourne, Dept Biomed Engn, Parkville, Vic, Australia

[3] Univ Auckland, Dept Engn Sci, Auckland, New Zealand

来源：

COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING | 2018年 / 21卷 / 07期

关键词：

Non-rigid registration; registration; radial basis function; morphing; model generation;

D O I：

10.1080/10255842.2018.1484914

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Non-rigid registration is a common part of bioengineering model-generation workflows. Compared to common mesh-based methods, radial basis functions can provide more flexible deformation fields due to their meshless nature. We introduce an implementation of RBF non-rigid registration with iterative knot-placement to adaptively reduce registration error. The implementation is validated on surface meshes of the femur, hemi-pelvis, mandible, and lumbar spine. Mean registration surface errors ranged from 0.37 to 0.99mm, Hausdorff distance from 1.84 to 2.47mm, and DICE coefficients from 0.97 to 0.99. The implementation is available for use in the free and open-source GIAS2 library.

引用

页码：498 / 502

页数：5

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