Fusion of PET and MRI brain images and comparison of fusion methods by image quality indicators in MATLAB

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عنوان دوره: اولین دوره بین المللی و بیست و هشتمین دوره ملی (1400)
Image fusion means merging the information of different images from different views of the image into a single image in order to create an improved image quality while maintaining the integrity and important features of the images. In medicine, image fusion has received a lot of attention for integrating structural information from imaging systems such as CT and MRI and metabolical information from PET and SPECT imaging systems, but achieving an optimal fusion algorithm is one of the challenges facing specialists. In this paper, 16 slides of PET and MRI images of the brain are integrated using two algorithms discrete wavelet and principal component analysis and then The performance of algorithms has been evaluated using image quality indicators such as signal to noise ratio, absolute mean error, structural similarity index and standard deviation., in which the principal component analysis algorithm has shown the best results in image quality evaluation indicators.
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