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An extension of digital volume correlation for multimodality image registration

Tudisco, E. LU ; Jailin, C.; Mendoza, A. LU ; Tengattini, A.; Andò, E; Hall, Stephen A. LU ; Viggiani, Gioacchino; Hild, F. and Roux, Stephane (2017) In Measurement Science & Technology1991-01-01+01:00 28(9).
Abstract

The question of registering two images (or image volumes) acquired with different modalities, and thus exhibiting different contrast, at different positions is addressed based on an extension of global digital image (or volume) correlation. A specific comparison metric is introduced allowing the signature of the different phases to be related. A first solution consists of a Gaussian mixture to describe the joint distribution of gray levels, which not only provides a matching of both images, but also offers a natural segmentation indicator. A second 'self-adapting' solution does not include any postulated a priori model for the joint histogram and leads to a registration of the images based on their initial histograms. The algorithm is... (More)

The question of registering two images (or image volumes) acquired with different modalities, and thus exhibiting different contrast, at different positions is addressed based on an extension of global digital image (or volume) correlation. A specific comparison metric is introduced allowing the signature of the different phases to be related. A first solution consists of a Gaussian mixture to describe the joint distribution of gray levels, which not only provides a matching of both images, but also offers a natural segmentation indicator. A second 'self-adapting' solution does not include any postulated a priori model for the joint histogram and leads to a registration of the images based on their initial histograms. The algorithm is implemented with a pyramidal multiscale framework for the sake of robustness. The proposed multiscale technique is tested on two 3D images obtained from x-ray and neutron tomography respectively. The proposed approach brings the two images to coincidence with a sub-pixel accuracy and allows for a 'natural' segmentation of the different phases.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
digital image correlation, image fusion, image registration, neutron tomography, x-ray tomography
in
Measurement Science & Technology1991-01-01+01:00
volume
28
issue
9
publisher
IOP Publishing
external identifiers
  • scopus:85028420292
  • wos:000407864200001
ISSN
0957-0233
DOI
10.1088/1361-6501/aa7b48
language
English
LU publication?
yes
id
18d6e257-966e-489d-87aa-70b43ef1d33f
date added to LUP
2017-09-07 10:10:23
date last changed
2018-07-01 04:49:02
@article{18d6e257-966e-489d-87aa-70b43ef1d33f,
  abstract     = {<p>The question of registering two images (or image volumes) acquired with different modalities, and thus exhibiting different contrast, at different positions is addressed based on an extension of global digital image (or volume) correlation. A specific comparison metric is introduced allowing the signature of the different phases to be related. A first solution consists of a Gaussian mixture to describe the joint distribution of gray levels, which not only provides a matching of both images, but also offers a natural segmentation indicator. A second 'self-adapting' solution does not include any postulated a priori model for the joint histogram and leads to a registration of the images based on their initial histograms. The algorithm is implemented with a pyramidal multiscale framework for the sake of robustness. The proposed multiscale technique is tested on two 3D images obtained from x-ray and neutron tomography respectively. The proposed approach brings the two images to coincidence with a sub-pixel accuracy and allows for a 'natural' segmentation of the different phases.</p>},
  articleno    = {095401},
  author       = {Tudisco, E. and Jailin, C. and Mendoza, A. and Tengattini, A. and Andò, E and Hall, Stephen A. and Viggiani, Gioacchino and Hild, F. and Roux, Stephane},
  issn         = {0957-0233},
  keyword      = {digital image correlation,image fusion,image registration,neutron tomography,x-ray tomography},
  language     = {eng},
  month        = {08},
  number       = {9},
  publisher    = {IOP Publishing},
  series       = {Measurement Science & Technology1991-01-01+01:00},
  title        = {An extension of digital volume correlation for multimodality image registration},
  url          = {http://dx.doi.org/10.1088/1361-6501/aa7b48},
  volume       = {28},
  year         = {2017},
}