The use of inverse phase Fourier image to accommodate intensity inhomogeneities in medical image registration

Tieng, Quang, Vegh, Viktor, Brereton, Ian M., Reutens, David and Yang, Zhengyi (2012). The use of inverse phase Fourier image to accommodate intensity inhomogeneities in medical image registration. In: Proceedings: CIMSiM 2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation. 2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation (CIMSiM), Kuantan, Malaysia, (276-281). 25 - 27 September 2012. doi:10.1109/CIMSim.2012.60

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Author Tieng, Quang
Vegh, Viktor
Brereton, Ian M.
Reutens, David
Yang, Zhengyi
Title of paper The use of inverse phase Fourier image to accommodate intensity inhomogeneities in medical image registration
Conference name 2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation (CIMSiM)
Conference location Kuantan, Malaysia
Conference dates 25 - 27 September 2012
Proceedings title Proceedings: CIMSiM 2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation
Journal name Proceedings of International Conference on Computational Intelligence, Modelling and Simulation
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2012
Sub-type Fully published paper
DOI 10.1109/CIMSim.2012.60
Open Access Status
ISBN 9781467331135
ISSN 2166-8531
Start page 276
End page 281
Total pages 6
Collection year 2013
Language eng
Abstract/Summary Medical image registration is generally faced with the confounding effect of spatially dependent intensity variations. This can be the case when images have been acquired using the same imaging modality, for example, in magnetic resonance imaging and also when using various histology and staining processes. We propose the application of an intensity-invariant dense feature extraction method through the use of phase Fourier transforms. The approach allows medical images containing intensity in homogeneities to be aligned and warped as part of a feature-based registration technique. Registration performance was evaluated on mono-modality and multi-modality data, namely magnetic resonance and histology images. Qualitative and quantitative validation was conducted with respect to two established image intensity correction methods.
Keyword Inverse phase Fourier image
Feature extraction
Image registration
Intensity inhomogeneity
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Tue, 30 Oct 2012, 17:13:43 EST by Sandrine Ducrot on behalf of Centre for Advanced Imaging