Proper evaluation of rectal cancer with MR imaging requires high resolution imaging of the rectal wall. The image quality demands are difficult to achieve due to the increasing risk of peristaltic motion with longer scan times. In this work, we apply a novel deep learning based reconstruction (DL recon) method to an accelerated sequence using reduced averages and increased acceleration. Radiologist scores indicate that the combined method provides superior SNR and definition with less motion degradation when compared to the routine sequence with conventional reconstruction. Thus improved motion robustness can be gained from applying DL Recon to an accelerated sequence.
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