Description

Multimodal medical image fusion based on Integer Wavelet Transform and Neuro-Fuzzy

                         In this project, Multimodal medical image fusion (MIF) is a method of extracting complementary information from different source images and combining them into a resultant image. The integration of multimodality medical images can provide more complete pathological information for doctors, which greatly helps their diagnosis and treatment. While acquiring the images from different imaging system the images will be affected by noise. Hence pre-processing technique has been carried out using Wavelet transform followed by Curvelet transform. . The fused image is obtained using Neuro fuzzy system.This paper proposes image fusion based on Integer Wavelet Transform (IWT) and Neuro-Fuzzy. The anatomical and functional images are decomposed using Integer Wavelet Transform. The wavelet coefficients are then fused using neuro-fuzzy algorithm. Then Inverse Integer Wavelet Transform (IIWT) is applied to the fused coefficients to get the fused Image. The performance of this algorithm is compared with image fusion based on Discrete Wavelet Transform (DWT) and neuro-fuzzy using entropy metric. Fusion Symmetry (FS) which quantifies the relative distance in terms of mutual information of the fused image with respect to input images is measured.

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