This lecture covers the encoding of spatial information in MRI through the scanning of k-space sequentially, explaining the phase encoding, sampling signals, artifacts, effects of incomplete sampling, and spatial encoding with gradients.
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Covers the Fourier transform, its properties, applications in signal processing, and differential equations, emphasizing the concept of derivatives becoming multiplications in the frequency domain.
Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.