Improving an affine and non-linear image registration and/or segmentation task by incorporating characteristics of the displacement field

2009 ◽  
Author(s):  
Konstantin Ens ◽  
Stefan Heldmann ◽  
Jan Modersitzki ◽  
Bernd Fischer
Keyword(s):  
Image Registration ◽  
Displacement Field ◽  
Non Linear ◽  
Segmentation Task

Breast image registration by using non-linear local affine transformation

2013 ◽  
Author(s):  
Feiyu Chen ◽  
Peng Zheng ◽  
Penglong Xu ◽  
Andrew D. A. Maidment ◽  
Predrag R. Bakic ◽  
...  
Keyword(s):  
Image Registration ◽  
Affine Transformation ◽  
Breast Image ◽  
Non Linear

Sci-YIS Fri - 01: A protocol for the validation of non-linear image registration systems

2005 ◽  
Vol 32 (7Part2) ◽  
pp. 2418-2418
Author(s):  
R Rivest ◽  
T Riauka ◽  
A Murtha ◽  
B Fallone
Keyword(s):  
Image Registration ◽  
Non Linear

scholarly journals N-Dimensional Computation of Strain Tensor Images in the Insight Toolkit

2017 ◽  
Author(s):  
Matthew Mccormick
Keyword(s):  
Image Registration ◽  
Constitutive Model ◽  
Displacement Field ◽  
Input Data ◽  
Source Code ◽  
Strain Tensor ◽  
Fundamental Principle ◽  
Local Deformation ◽  
Output Data ◽  
Scientific Publications

Strain quantifies local deformation of a solid body. In medical imaging, strain reflects how tissue deforms under load. Or, it can quantify growth or atrophy of tissue, such as the growth of a tumor. Additionally, strain from the transformation that results from image-to-image registration can be applied as an input to a biomechanical constitutive model.This document describes N-dimensional computation of strain tensor images in the Insight Toolkit (ITK), www.itk.org. Two filters are described. The first filter computes a strain tensor image from a displacement field image. The second filter computes a strain tensor image from a general spatial transform. In both cases, infinitesimal, Green-Lagrangian, or Eulerian-Almansi strain can be generated.This paper is accompanied with the source code, input data, parameters and output data that the authors used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results.

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