An accurate 3D shape context based non-rigid registration method for mouse whole-body skeleton registration

2011 ◽  
Author(s):  
Di Xiao ◽  
David Zahra ◽  
Pierrick Bourgeat ◽  
Paula Berghofer ◽  
Oscar Acosta Tamayo ◽  
...  
Keyword(s):  
Whole Body ◽  
Shape Context ◽  
Registration Method ◽  
Rigid Registration ◽  
3D Shape

An improved 3D shape context based non-rigid registration method and its application to small animal skeletons registration

2010 ◽  
Vol 34 (4) ◽  
pp. 321-332 ◽  
Author(s):  
Di Xiao ◽  
David Zahra ◽  
Pierrick Bourgeat ◽  
Paula Berghofer ◽  
Oscar Acosta Tamayo ◽  
...  
Keyword(s):  
Small Animal ◽  
Shape Context ◽  
Registration Method ◽  
Rigid Registration ◽  
3D Shape

scholarly journals A non-rigid registration method for mouse whole body skeleton registration

2010 ◽  
Author(s):  
Di Xiao ◽  
David Zahra ◽  
Pierrick Bourgeat ◽  
Paula Berghofer ◽  
Oscar Acosta Tamayo ◽  
...  
Keyword(s):  
Whole Body ◽  
Registration Method ◽  
Rigid Registration

Non-rigid registration of small animal skeletons from micro-CT using 3D shape context

2009 ◽  
Author(s):  
Di Xiao ◽  
Pierrick Bourgeat ◽  
Jurgen Fripp ◽  
Oscar Acosta Tamayo ◽  
Marie Claude Gregoire ◽  
...  
Keyword(s):  
Small Animal ◽  
Micro Ct ◽  
Shape Context ◽  
Rigid Registration ◽  
3D Shape

Constrained non-rigid registration for whole body image registration: method and validation

2007 ◽  
Author(s):  
Xia Li ◽  
Thomas E. Yankeelov ◽  
Todd E. Peterson ◽  
John C. Gore ◽  
Benoit M. Dawant
Keyword(s):  
Body Image ◽  
Image Registration ◽  
Whole Body ◽  
Registration Method ◽  
Rigid Registration

scholarly journals An improved 3D shape context registration method for non-rigid surface registration

2010 ◽  
Author(s):  
Di Xiao ◽  
David Zahra ◽  
Pierrick Bourgeat ◽  
Paula Berghofer ◽  
Oscar Acosta Tamayo ◽  
...  
Keyword(s):  
Surface Registration ◽  
Rigid Surface ◽  
Shape Context ◽  
Registration Method ◽  
3D Shape

An Error-Adaptive, Non-Rigid Registration Method for the Analysis of Springback in Sheet Metal Forming

2015 ◽  
Vol 651-653 ◽  
pp. 1015-1020 ◽  
Author(s):  
Matthias Schweinoch ◽  
Alexei Sacharow ◽  
Dirk Biermann ◽  
Christoph Buchheim
Keyword(s):  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
Simulation Software ◽  
Registration Method ◽  
Rigid Registration ◽  
Reference Shape ◽  
Geometric Deviations ◽  
Error Metric ◽  
Test Shape

Springback effects, as occuring in sheet metal forming processes, pose a challenge to manufacturingplanning: the as-built part may deviate from the desired shape rendering it unusable forits intended purpose. A compensation can be achieved by modifying the forming tools to counteractthe shape deviations. A prerequisite to compensation is the knowledge of correspondences (ui; vj),between points ui on the desired and vj on the actual shape. FEM-based simulation software providesmeans to both virtually predict springback and directly obtain correspondences. In case of experimentalprototyping and validation, however, finding correspondences requires solving a registrationproblem: given a test shape Q (scan points of the as-built geometry) and a reference shape R (CADdata of the desired geometry), a transformation S has to be found to fit both objects. Correspondencesbetween S(Q) and R may then be computed based on a metric.If S is restricted to Euclidean transformations, then S(Q) results in a rigid transformation, whereevery point of Q is subject to the same translation and rotation. Local geometric deviations due tospringback are not considered, often resulting in invalid correspondences. In this contribution, a nonrigidregistration method for the efficient analysis of springback is therefore presented. The test shape Q is iteratively partitioned into segments with respect to an error metric. The segments are locally registeredusing rigid registration subject to regulatory conditions. Resulting discontinuities are addressedby minimization of the deformation energy. The error metric uses information about the deviationscomputed based on the correspondences of the previous iteration, e.g. maximum errors or changes ofthe sign. This adaptive per-segment registration allows appropriate correspondences to be determinedeven under local geometric deviations.

scholarly journals A non-rigid registration method for the analysis of local deformations in the wood cell wall

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Alessandra Patera ◽  
Stephan Carl ◽  
Marco Stampanoni ◽  
Dominique Derome ◽  
Jan Carmeliet
Keyword(s):  
Cell Wall ◽  
Wood Cell Wall ◽  
Registration Method ◽  
Rigid Registration ◽  
Local Deformations

A three-dimensional registration method for automated fusion of micro PET-CT-SPECT whole-body images

2005 ◽  
Vol 24 (7) ◽  
pp. 886-893 ◽  
Author(s):  
Meei-Ling Jan ◽  
Keh-Shih Chuang ◽  
Guo-Wei Chen ◽  
Yu-Ching Ni ◽  
S. Chen ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Whole Body ◽  
Body Images ◽  
Registration Method ◽  
Pet Ct
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