2006
DOI: 10.1016/j.jbiomech.2005.09.015
|View full text |Cite
|
Sign up to set email alerts
|

Abstract: In this study we investigate the use of splines and the ICP method [Besl, P., McKay, N., 1992. A method for registration of 3d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14, 239-256.] for calculating the transformation parameters for a rigid body undergoing planar motion parallel to the image plane. We demonstrate the efficacy of the method by estimating the finite centre of rotation and angle of rotation from lateral flexion/extension radiographs of the lumbar spine. In an in vitro… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
4
0

Year Published

2007
2007
2015
2015

Publication Types

Select...
4
2
2

Relationship

0
8

Authors

Journals

citations
Cited by 17 publications
(4 citation statements)
references
References 25 publications
0
4
0
Order By: Relevance
“…Although there is no perfect way to analyze instability, this method of measuring spinal stability has been previously referenced and deemed acceptable for this study. 16 The control group is referenced in Table 2 with the same information.…”
Section: Methodsmentioning
confidence: 99%
“…Although there is no perfect way to analyze instability, this method of measuring spinal stability has been previously referenced and deemed acceptable for this study. 16 The control group is referenced in Table 2 with the same information.…”
Section: Methodsmentioning
confidence: 99%
“…As the methods used in Leprince et al [44,50] and Borsa and Minster [51] involve gridding/smoothing of LiDAR data, biases or artifacts could be introduced in the results. To work with LiDAR point clouds directly, Nissen et al [46] introduced a new method for calculating 3-D coseismic surface displacements from preand post-earthquake LiDAR data based on the Iterative Closest Point (ICP) algorithm [52,53]. The method was also used to extract threedimensional displacements and rotations from pre-and postearthquake LiDAR data for the 2008 Iwate-Miyagi earthquake and the 2011 Fukushima-Hamadori earthquake in Japan [49].…”
Section: Surface Deformation Revealed By Differential Lidarmentioning
confidence: 99%
“…In this representation, the human body is subdivided into kinematic subchains (see Figure 2) that describe parts of the skeleton. Those kinematic chains are divided into three main types: r and the spine that is modeled by a spline (as suggested in biomechanics 31 ) whose advantage is that it can be easily subdivided into as many segments as the user wishes, depending on the character description. This spline is easily normalized by scaling the coefficients between 0 (close to pelvis) and 1 (close to the skull).…”
Section: Morphology-independent Representation Of Motionmentioning
confidence: 99%