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...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-a 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.展开更多
An application of multiresolution image analysis to turbulence was investigated in this paper, in order to visualize the coherent structure and the most essential scales governing turbulence. The digital imaging photo...An application of multiresolution image analysis to turbulence was investigated in this paper, in order to visualize the coherent structure and the most essential scales governing turbulence. The digital imaging photograph of jet slice was decomposed by two-dimensional discrete wavelet transform based on Daubechies, Coifman and Baylkin bases. The best choice of orthogonal wavelet basis for analyzing the image of the turbulent structures was first discussed. It is found that these orthonormal wavelet families with index N<10 were inappropriate for multiresolution image analysis of turbulent flow. The multiresolution images of turbulent structures were very similar when using the wavelet basis with the higher index number, even though wavelet bases are different functions. From the image components in orthogonal wavelet spaces with different scales, the further evident of the multi-scale structures in jet can be observed, and the edges of the vortices at different resolutions or scales and the coherent structure can be easily extracted.展开更多
基金Project (No. TMU 85-05-33) supported in part by the Iran Telecommunication Research Center (ITRC)
文摘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-a 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.
文摘An application of multiresolution image analysis to turbulence was investigated in this paper, in order to visualize the coherent structure and the most essential scales governing turbulence. The digital imaging photograph of jet slice was decomposed by two-dimensional discrete wavelet transform based on Daubechies, Coifman and Baylkin bases. The best choice of orthogonal wavelet basis for analyzing the image of the turbulent structures was first discussed. It is found that these orthonormal wavelet families with index N<10 were inappropriate for multiresolution image analysis of turbulent flow. The multiresolution images of turbulent structures were very similar when using the wavelet basis with the higher index number, even though wavelet bases are different functions. From the image components in orthogonal wavelet spaces with different scales, the further evident of the multi-scale structures in jet can be observed, and the edges of the vortices at different resolutions or scales and the coherent structure can be easily extracted.
