In MR physics, there is a fundamental tradeoff between image spatial resolution, signal to noise ratio, and scan time. To acquire images with high resolution and SNR, signal averaging is the most common solution, but results in longer scan time. In this study, a Deep Learning Reconstruction method was employed to remove the noise from clinical images and improve SNR. This SNR improvement was devoted to increase the spatial resolution without the need of signal averaging and increased scan time. Hence, higher resolution images with high image quality can be obtained in shorter time in clinical practice.
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