Medical Image Fusion Based on Redundancy DWT and Mamdani Type Min-sum Mean-of-max Techniques with Quantitative Analysis- A Review
Volume: 4 - Issue: 08 - Date: 01-08-2015
Approved ISSN: 2278-1412
Published Id: IJAECESTU247 | Page No.: 560-563
Author: Gopal Kumar
Co- Author: Manish Trivedi
Abstract:-Medical image fusion has revolutionized medical analysis by improving the precision
and performance of computer assisted diagnosis. This fused image is more productive as
compared to its original input images. The fusion technique in medical images is useful for
resourceful disease diagnosis purpose. This paper illustrates different multimodality medical
image fusion techniques and their results assessed with various quantitative metrics. Firstly two
registered images CT (anatomical information) and MRI-T2 (functional information) are taken as
input. Then the fusion techniques are applied onto the input images such as Mamdani type
minimum-sum-mean of maximum (MIN-SUM-MOM) and Redundancy Discrete Wavelet
Transform (RDWT) and the resultant fused image is analyzed with quantitative metrics namely
Over all Cross Entropy(OCE), Peak Signal –to- Noise Ratio (PSNR), Signal to Noise Ratio (SNR),
Structural Similarity Index(SSIM), Mutual Information(MI). From the derived results it is inferred
that Mamdani type MIN-SUM-MOM is more productive than RDWT and also the proposed fusion
techniques provide more information compared to the input images as justified by all the metrics
Key Words:-Signal Processing Method, Precise Estimation of Leq , Roughly Observed Data,
Area:-Engineering
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