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Artificial Intelligence for Image Enhancement and Reconstruction in Magnetic Resonance Imaging

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Artificial Intelligence in Cardiothoracic Imaging

Part of the book series: Contemporary Medical Imaging ((CMI))

Abstract

Artificial intelligence has evolved tremendously in the field of MRI reconstruction. In this chapter, we introduce common concepts of deep learning, a subbranch of artificial intelligence, for the development of successful enhancement and reconstruction methods. We discuss differences between enhancement and reconstruction strategies, and highlight the benefits from physics-aware processing. Application of deep learning to cardiac MRI faces several challenges specific to cardiac imaging, including the large size of the imaging datasets and the lack of fully sampled data for training in many acquisitions. Furthermore, for dynamic/quantitative cardiac MRI, an image series is processed, and various sources of motion have to be considered in acquisition and reconstruction. We discuss these new challenges and provide insights in advanced topics and future opportunities. Throughout the chapter, we outline important applications of deep learning enhancement and reconstruction for static and dynamic applications.

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Hammernik, K., Akçakaya, M. (2022). Artificial Intelligence for Image Enhancement and Reconstruction in Magnetic Resonance Imaging. In: De Cecco, C.N., van Assen, M., Leiner, T. (eds) Artificial Intelligence in Cardiothoracic Imaging. Contemporary Medical Imaging. Humana, Cham. https://doi.org/10.1007/978-3-030-92087-6_13

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