Fusion of multimodal medical images using Daubechies complex wavelet transform - A multiresolution approach

By Rajiv Singh, A. Khare. Information Fusion, 2014

319 citations recorded by the source corpus.

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DDcGAN: A Dual-Discriminator Conditional Generative Adversarial Network for Multi-Resolution Image Fusion (2020, methodology): “According to the theories applied, existing medical fusion methods can be summarized into different categories, such as substitution methods [40], [42], arithmetic combination methods [43], and multi-resolution methods [44], [45].”
Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation (2020, unknown): “In [225] , the authors proposed the Daubechies complex wavelet transform (DCxWT) to fuse multimodal medical image.”
A medical image fusion method based on convolutional neural networks (2017, background): “Multi-scale transforms which are frequently studied in image fusion include pyramids [17]–[19], wavelets [9], [20], [21], multi-scale geometrical transforms like contourlet and shearlet”
An overview of multi-modal medical image fusion (2016, methodology): “( (a) MRI, (b) SPECT, (c) IHS+PCA, (d) MoR+MR, (e) DWT+Entropy, (f) NSCT+PCNN, (g) JSP+AR, and (d) LES+DC ) Table 5.”
Deep Learning-based Image Segmentation on Multimodal Medical Imaging (2019, methodology): “Works in [31] (using features of contourlets), [32] (using feature of wavelet), [33] (using features of wavelets), and [34] (using features learned by linear discriminant analysis) perform the classifier-level fusion.”