A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
Image processing and data analysis: the multiscale approach
Image processing and data analysis: the multiscale approach
Fingerprint verification by fusion of optical and capacitive sensors
Pattern Recognition Letters
Astronomical Image and Data Analysis (Astronomy and Astrophysics Library)
Astronomical Image and Data Analysis (Astronomy and Astrophysics Library)
The discrete wavelet transform: wedding the a trous and Mallatalgorithms
IEEE Transactions on Signal Processing
Biological image fusion using a NSCT based variable-weight method
Information Fusion
Computer Methods and Programs in Biomedicine
Human visual system inspired multi-modal medical image fusion framework
Expert Systems with Applications: An International Journal
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The display of image fusion is well accepted as a powerful tool in visual image analysis and comparison. In clinical practice, this is a mandatory step when studying images from a dual PET/CT scanner. However, the display methods that are implemented on most workstations simply show both images side by side, in separate and synchronized windows. Sometimes images are presented superimposed in a single window, preventing the user from doing quantitative analysis. In this article a new image fusion scheme is presented, allowing performing quantitative analysis directly on the fused images. Methods: The objective is to preserve the functional information provided by PET while incorporating details of higher resolution from the CT image. The process relies on a discrete wavelet-based image merging: both images are decomposed into successive details layers by using the ''a trous'' transform. This algorithm performs wavelet decomposition of images and provides coarser and coarser spatial resolution versions of them. The high-spatial frequencies of the CT, or details, can be easily obtained at any level of resolution. A simple model is then inferred to compute the lacking details of the PET scan from the high frequency detail layers of the CT. These details are then incorporated in the PET image on a voxel-to-voxel basis, giving the fused PET/CT image. Results: Aside from the expected visual enhancement, quantitative comparison of initial PET and CT images with fused images was performed in 12 patients. The obtained results were in accordance with the objectives of the study, in the sense that the organs' mean intensity in PET was preserved in the fused image. Conclusion: This alternative approach to PET/CT fusion display should be of interest for people interested in a more quantitative aspect of image fusion. The proposed method is actually complementary to more classical visualization tools.