Two-stage multi-modal MR images fusion method based on Parametric Logarithmic Image Processing (PLIP) Model

MRI is one of the most compliant technique that is used for the screening of Brain Tumor. MRI can be acquired in four available modalities which are MR-T1, MR-T2, MR-PD and MR-Gad; among these MR-T2 comprises of most of the detailed information of the tumorous tissues. However, the accuracy and reliability of the diagnosis may be affected due to lack of sufficient details in each modality (as different MRI modalities highlight different set of tissues). Therefore, MR Image(s) fusion is essential to obtain a more illustrative image containing the requisite complementary details of each modality. For this purpose, multi-modal fusion of MR-T2 with MR-T1, MR-PD and MR-Gad have been dealt in this work using the proposed fusion method. This paper presents a two-stage fusion method using Stationary Wavelet Transform (SWT) in combination with Parameterized Logarithmic Image Processing (PLIP) model. At Stage-I of sub-band decomposition: the first level SWT coefficients contain large amount of noise thus suppressing the necessary edge information. This aspect has been resolved at Stage-II by employing second level SWT decomposition along with Principal Component Analysis (PCA). The fusion coefficients from both the stages are finally fused using PLIP operators (prior to reconstruction). The obtained results are compared qualitatively as well as quantitatively using fusion metrics like Entropy, Fusion Factor, Standard Deviation and Edge Strength. Noteworthy visual response is obtained with PLIP fusion model in coherence with Human Visual System (HVS) characteristics. (C) 2020 Elsevier B.V. All rights reserved.