Abstract
This paper focuses on a Magnetic Resonance Imaging (MRI) reconstruction that gives brisk realization. This diminishes the scanning cost and image reconstructed in very fewer time. In this method, Generative Adversarial Network (GAN) designed a generator which gives the better enhancement like texture smoothness, and high resolution. In addition, it also finds the frequency province information to embed resemblance in both the images using parameter Structural Similarity Index (SSIM). Also performed radon transform to find the structural similarity of images with enhancement, accuracy and test whether the images are real or fake. Compared to other methods, the proposed GAN method provides superior reconstruction.
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Pawar, M., Kakde, S., Yadav, P.M. (2020). Implementation of MRI Images Reconstruction Using Generative Adversarial Network. In: Balas, V., Solanki, V., Kumar, R. (eds) Internet of Things and Big Data Applications. Intelligent Systems Reference Library, vol 180. Springer, Cham. https://doi.org/10.1007/978-3-030-39119-5_12
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DOI: https://doi.org/10.1007/978-3-030-39119-5_12
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