Titlebook: Digital Molecular Magnetic Resonance Imaging; Bamidele O. Awojoyogbe,Michael O. Dada Book 2024 The Editor(s) (if applicable) and The Autho

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https://doi.org/10.1007/978-981-97-6370-2Bloch NMR; Physics-informed neural networks (PINNs); Magnetic resonance relaxometry; Machine learning m

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Springer Series in Computational Mathematicsproblems solved in this chapter are described by a Bloch related equation based on close observation of how the system usually behaves in the presence of NMR magnetic fields. A few numbers of realistic assumptions have been made in order to obtain a solution to each differential equation that has be

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,Anregung von Quantensprüngen durch Stöße,s our understanding of the physical mechanisms behind medical interventions and opens the door to more effective and personalized clinical hyperthermia, which could lead to improved patient outcomes and advancements in medical management. The goal is to design and implement a Physics-Informed Neural

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https://doi.org/10.1007/978-3-642-60266-5nd thermal diffusivity. To streamline the analysis, metabolic heat generation was assumed to be zero in both tissues. The distribution of temperature in biological tissues offers several significant benefits across various fields including healthcare and medical research. The goal is to demonstrate