This research work explains a unique Multimodal Medical Image Fusion Technique (MIFT) in light-weight of MIFT-HDWRT, Non-subsampled Contourlet Transform (NSCT), and Pulse Coupled Neural Network (PCNN). The MIFT-DWNRT plot tells the benefits of each of the NSCT and PCNN to amass higher combination. The supply medical pictures are first decayed by NSCT. The low-recurrence sub bands (LFSs) are tangled utilizing the MIFT-HDWRT run the show. For melding the high-recurrence sub bands (HFSs), a NSCT-PCNN show is employed. Altered abstraction frequency (MSF) in NSCT area is contributed to propel the PCNN, and coefficients in NSCT space with expansive terminating times are chosen as coefficients of the tangled image. At long last, opposite of NSCT i.e. INSCT is connected to urge the tangled image. Abstract and target examination of the outcomes and correlations with leading edge MIF technique demonstrate the effectiveness of the MIFT-DWNRT plot in melding multimodal therapeutic picture.

Image fusion; Pulse-Coupled Neural Network; Multi scale Geometric Analysis; Medical Imaging, NSCT

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