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Journal ArticleDOI

NSCT-based multimodal medical image fusion using pulse-coupled neural network and modified spatial frequency

Sudeb Das, +1 more
- 24 Jul 2012 - 
- Vol. 50, Iss: 10, pp 1105-1114
TLDR
A novel multimodal medical image fusion (MIF) method based on non-subsampled contourlet transform (NSCT) and pulse-coupled neural network (PCNN) is presented, which exploits the advantages of both the NSCT and the PCNN to obtain better fusion results.
Abstract
In this article, a novel multimodal medical image fusion (MIF) method based on non-subsampled contourlet transform (NSCT) and pulse-coupled neural network (PCNN) is presented. The proposed MIF scheme exploits the advantages of both the NSCT and the PCNN to obtain better fusion results. The source medical images are first decomposed by NSCT. The low-frequency subbands (LFSs) are fused using the ‘max selection’ rule. For fusing the high-frequency subbands (HFSs), a PCNN model is utilized. Modified spatial frequency in NSCT domain is input to motivate the PCNN, and coefficients in NSCT domain with large firing times are selected as coefficients of the fused image. Finally, inverse NSCT (INSCT) is applied to get the fused image. Subjective as well as objective analysis of the results and comparisons with state-of-the-art MIF techniques show the effectiveness of the proposed scheme in fusing multimodal medical images.

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Citations
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Journal ArticleDOI

A fusion algorithm for infrared and visible images based on adaptive dual-channel unit-linking PCNN in NSCT domain

TL;DR: Experimental results demonstrate that the proposed algorithm can significantly improve image fusion performance, accomplish notable target information and high contrast, simultaneously preserve rich details information, and excel other typical current methods in both objective evaluation criteria and visual effect.
Journal ArticleDOI

Multimodal Medical Image Sensor Fusion Framework Using Cascade of Wavelet and Contourlet Transform Domains

TL;DR: A two-stage multimodal fusion framework using the cascaded combination of stationary wavelet transform (SWT) and non sub-sampled Contourlet Transform (NSCT) domains for images acquired using two distinct medical imaging sensor modalities is presented.
Journal ArticleDOI

A new contrast based multimodal medical image fusion framework

TL;DR: A novel framework for spatially registered multimodal medical image fusion, which is primarily based on the non-subsampled contourlet transform (NSCT), is proposed that enables the decomposition of source medical images into low- and high-frequency bands in NSCT domain.
Journal ArticleDOI

A Neuro-Fuzzy Approach for Medical Image Fusion

TL;DR: This paper addresses a novel approach to the multimodal medical image fusion (MIF) problem, employing multiscale geometric analysis of the nonsubsampled contourlet transform and fuzzy-adaptive reduced pulse-coupled neural network (RPCNN).
Journal ArticleDOI

Nonsubsampled shearlet based CT and MR medical image fusion using biologically inspired spiking neural network

TL;DR: Experimental results demonstrate that the proposed method does not only produce better results by successfully fusing the different CT and MR images, but also ensures an improvement in the various quantitative parameters as compared to other existing methods.
References
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Journal ArticleDOI

The Nonsubsampled Contourlet Transform: Theory, Design, and Applications

TL;DR: This paper proposes a design framework based on the mapping approach, that allows for a fast implementation based on a lifting or ladder structure, and only uses one-dimensional filtering in some cases.
Journal ArticleDOI

Image quality measures and their performance

TL;DR: Although some numerical measures correlate well with the observers' response for a given compression technique, they are not reliable for an evaluation across different techniques, and a graphical measure called Hosaka plots can be used to appropriately specify not only the amount, but also the type of degradation in reconstructed images.
Journal ArticleDOI

Multisensor image fusion using the wavelet transform

TL;DR: In this article, an image fusion scheme based on the wavelet transform is presented, where wavelet transforms of the input images are appropriately combined, and the new image is obtained by taking the inverse wavelet transformation of the fused wavelet coefficients.
Journal ArticleDOI

Objective image fusion performance measure

TL;DR: Experimental results clearly indicate that this metric reflects the quality of visual information obtained from the fusion of input images and can be used to compare the performance of different image fusion algorithms.
Journal ArticleDOI

Feature linking via synchronization among distributed assemblies: Simulations of results from cat visual cortex

TL;DR: It is proposed that synchronization is a general principle for the coding of associations in and among sensory systems and that at least two distinct types of synchronization do exist: stimulus-forced (event-locked) synchronization support crude instantaneous associations and stimulus-induced (oscillatory) synchronizations support more complex iterative association processes.
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