[Retracted] Multimodal Medical Image Fusion of Positron Emission Tomography and Magnetic Resonance Imaging Using Generative Adversarial Networks

Table 1

Medical image fusion—existing approaches.

Modality	Work	Organ	Fusion technique	Approach
PET and MRI	[24]	Brain	2D Intensity Hue Saturation and Hilbert transform	PET and MRI image fusion using 2D Hilbert transform and Intensity Hue Saturation Fourier Transform is calculated for each of the input signals.
PET and MRI	[25]	Brain	Dual ripplet II transform	The proposed approach uses dual ripplet II transform as it uses complex wavelet transform. The color and spatial information of the images are preserved using weight matrix.
PET and MRI	[27]	Brain	Intrinsic image decomposition	Model based on intrinsic image decomposition are proposed to extract structural information from MRI and for obtaining color details from PET.
PET and MRI	[26]	Brain	Non-subsamples shearlet transform	The input images are registered and normalized and then transformed into independent components. Pulse coupled neural network is used to obtain useful information from the image.
MRI and CT	[33]	Brain	Hybrid image fusion	The image fusion is performed using principal component analysis and independent component analysis.
MRI and CT	[34]	Brain	Adolescent Identity Search Algorithm	The proposed approach decomposes the input image into high and low frequency component using nonsubsampled shearlet transform.
MRI and PET	[35]	Brain	Spectral Total Variation Transform	The proposed method decomposes the source image into base components and then combined using spatial frequency dual channel model.