Multimodality medical image fusion based on multiscale geometric analysis of contourlet transform
By Liu Yang, B. Guo, Wei Ni. Neurocomputing, 2008
402 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/c2f0d6d11484cee774dd8200f022587b7e3f2dac
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In Computer Vision and Pattern Recognition
In Media Technology
Citations in the corpus
- Pixel-level image fusion: A survey of the state of the art (2017, background): “Due to its effectiveness in representing spatial structures, contourlet transform has been successfully applied in medical imaging [19], surveillance [20, 21], and remote sensing[22, 23] applications.”
- Medical Image Fusion: A survey of the state of the art (2013, methodology): “Transforms based methods are also applied for liver diagnosis [99], risk factor fusion [100], prediction of multifactorial diseases [100], parametric classification [100], local image analysis [101], multi-modality image fusion [102, 103, 95, 104, 96, 81].”
- DATFuse: Infrared and Visible Image Fusion via Dual Attention Transformer (2023, methodology): “Popular MST-based algorithms include pyramid-based algorithms [36], wavelet-based algorithms [37], curvelet-based algorithms [38], multiscale geometric representation-based algorithms [39], and their revised versions.”
- Directive Contrast Based Multimodal Medical Image Fusion in NSCT Domain (2013, background): “Therefore , these are not the highly suitable for medical image fusion [22].”
- An overview of multi-modal medical image fusion (2016, methodology): “It is of interest to look at a snapshot of five different key methodologies: 1) color space [3, 4], 2) pyramid [5, 6], 3) wavelet [7-16], 4) sparse representation [17-21] and 5) salient feature [22-24].”
- Performance comparison of different multi-resolution transforms for image fusion (2011, neutral): “…including the pyramid decomposition [4] [5] [13], discrete wavelet (DWT) [6–8,14], stationary wavelet (SWT) [15] [16], dual-tree complex wavelet (DTCWT) [18] [19] [20] [21], curvelet (CVT) [22– 28], contourlet (CT) [29] [30] [31], and nonsubsampled contourlet transform (NSCT) [32] [33] [34].”
- A medical image fusion method based on convolutional neural networks (2017, background): “In recent years, a variety of medical image fusion methods have been proposed [2]–[17].”