MRI-CT Fusion Based on Phase Congruency of Intrinsic Functions and Laplacian of Residuals

• Published in: 2023 6th International Conference on Recent Trends in Advance Computing (ICRTAC) pp. 696 - 701
• Main Authors: Reddy, N. V. Maheswara, Gunnam, Suryanarayana, Jillelamudi, Prema Vani, Bhukya, Tejaswi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.12.2023
• Subjects: Computational efficiency; empirical mode decomposition; Intrinsic; Laplace equations; Local Laplacian energy; Measurement; Medical diagnosis; Multi-modality; Phase congruency; residue; Video surveillance; Visualization
• DOI: 10.1109/ICRTAC59277.2023.10480835

Multi-modality image fusion has become a valuable method in different fields like remote sensing, video surveillance and medical diagnosis. The study introduces an innovative approach for fusing multi-modality medical images using Phase Congruency and Local Laplacian Energy. Through this technique, we employ empirical mode decomposition to separate the input images into intrinsic and residual components. Intrinsic are combined by PC-based fusion rule to enhance fine details for medical diagnosis. For the residue components, we used the Local Laplacian Energy, which encompasses Weighted Local Energy and weighted sum of eight-neighborhood based modified Laplacian to capture structured and texture features from input. Consequently, this fusion rule integrates both key components of image. The fused intrinsic and residual components are transformed inversely to obtain final output fused image. Our approach demonstrates good performance in terms of image quality and also computational efficiency for the input images.