Abstract
Magnetic resonance imaging(MRI) is one of the most important non-invasive diagnostic tools in routine clinical examination.However,the temporal resolution is still low due to the limitation of Nyquist sampling theorem in k-space signal acquisition.Under the conditions of certain magnetic and gradient field,it takes a long time for signal acquisition to obtain a high resolution image with clinical value.In addition to enhancing the strength of main magnetic field and gradient as well speeding gradient field switch,some mathematical methods have been used to reduce the amount of k-space signal acquisition to shorten MR imaging time.Although under sparse sampling,the final reconstructed image data could be satisfied with Nyquist sampling theorem through these mathematical methods.Furthermore,many fast MRI methods based on data sharing and undersampling of k-space were proposed,such as half-Fourier imaging,keole imaging,parallel imaging,partially separable functions(PSF) and so on.In this review,several typical fast imaging methods were summarized and discussed based on k-space sampling techniques.
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