Effect of Compressed SENSE on 3D T2-weighted sequence for Rectum Imaging with a deep learning constrained Compressed SENSE Reconstruction

Rectal MRI examination requires high resolution three-dimensional (3D) sequences to observe the morphology, structure and the location of the lesions. However, 3D sequences may lead to longer scan time ，patient discomfort and image quality problem. In this study, we investigated the use of a deep learning-based reconstruction algorithm (CS-AI) to highly accelerate 3D rectum MRI. The result showed that CS-AI reconstruction can use the same scan time with sufficient image quality compared to SENSE and might be clinically useful in assessment of rectum cancer.