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CLC number: TN911.73

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Received: 2007-04-28

Revision Accepted: 2007-08-13

Crosschecked: 0000-00-00

Cited: 6

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Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE A 2007 Vol.8 No.10 P.1624-1632


MRI and PET images fusion based on human retina model

Author(s):  DANESHVAR Sabalan, GHASSEMIAN Hassan

Affiliation(s):  Department of Electrical and Computer Engineering, Tarbiat Modares University, P.O.Box 14115-143, Tehran, Iran

Corresponding email(s):   ghassemi@modares.ac.ir

Key Words:  Image fusion, Retina based, Multiresolution, Multiresolution image (MRI), Positron emission tomography (PET)

DANESHVAR Sabalan, GHASSEMIAN Hassan. MRI and PET images fusion based on human retina model[J]. Journal of Zhejiang University Science A, 2007, 8(10): 1624-1632.

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author="DANESHVAR Sabalan, GHASSEMIAN Hassan",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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%I Zhejiang University Press & Springer
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T1 - MRI and PET images fusion based on human retina model
A1 - DANESHVAR Sabalan
J0 - Journal of Zhejiang University Science A
VL - 8
IS - 10
SP - 1624
EP - 1632
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2007.A1624

The diagnostic potential of brain positron emission tomography (PET) imaging is limited by low spatial resolution. For solving this problem we propose a technique for the fusion of PET and MRI images. This fusion is a trade-off between the spectral information extracted from PET images and the spatial information extracted from high spatial resolution MRI. The proposed method can control this trade-off. To achieve this goal, it is necessary to build a multiscale fusion model, based on the retinal cell photoreceptors model. This paper introduces general prospects of this model, and its application in multispectral medical image fusion. Results showed that the proposed method preserves more spectral features with less spatial distortion. Comparing with hue-intensity-saturation (HIS), discrete wavelet transform (DWT), wavelet-based sharpening and wavelet-à trous transform methods, the best spectral and spatial quality is only achieved simultaneously with the proposed feature-based data fusion method. This method does not require resampling images, which is an advantage over the other methods, and can perform in any aspect ratio between the pixels of MRI and PET images.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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