The paper introduces Sensitivity Encoding (SENSE), a method to enhance the performance of Magnetic Resonance Imaging (MRI) using multiple receiver coils. SENSE leverages the complementary encoding effect of receiver sensitivity to Fourier preparation by linear field gradients, allowing for significant reduction in scan time without compromising image quality. The authors formulate the problem of image reconstruction from sensitivity-encoded data in a general manner and solve it for arbitrary coil configurations and k-space sampling patterns. They focus on the practical case of sampling a common Cartesian grid with reduced density, demonstrating the feasibility of the method through both in vitro and in vivo experiments. The scan time was reduced to half using a two-coil array in brain imaging and to one-third in double-oblique heart imaging with a five-coil array. The paper also discusses the theory and methods behind SENSE, including the reconstruction strategies, noise analysis, and sensitivity map determination. The results show that SENSE imaging is flexible and can produce artifact-free images, but the experimental setup significantly affects the Signal-to-Noise Ratio (SNR). The method is particularly suitable for applications requiring rapid imaging, such as real-time imaging and breath-hold examinations.The paper introduces Sensitivity Encoding (SENSE), a method to enhance the performance of Magnetic Resonance Imaging (MRI) using multiple receiver coils. SENSE leverages the complementary encoding effect of receiver sensitivity to Fourier preparation by linear field gradients, allowing for significant reduction in scan time without compromising image quality. The authors formulate the problem of image reconstruction from sensitivity-encoded data in a general manner and solve it for arbitrary coil configurations and k-space sampling patterns. They focus on the practical case of sampling a common Cartesian grid with reduced density, demonstrating the feasibility of the method through both in vitro and in vivo experiments. The scan time was reduced to half using a two-coil array in brain imaging and to one-third in double-oblique heart imaging with a five-coil array. The paper also discusses the theory and methods behind SENSE, including the reconstruction strategies, noise analysis, and sensitivity map determination. The results show that SENSE imaging is flexible and can produce artifact-free images, but the experimental setup significantly affects the Signal-to-Noise Ratio (SNR). The method is particularly suitable for applications requiring rapid imaging, such as real-time imaging and breath-hold examinations.