At a glance
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Deep Learning Super Resolution Reconstruction for Fast and Motion Robust T2-weighted Prostate MRI
In Brief
A clinical study evaluating Deep learning based reconstruction of T2-TSE sequence for Prostate Cancer and Multiparametric MRI. Completed, enrolled 109 participants across 1 site.
Detailed Summary
The aim of this study was therefore to investigate a new unrolled DL super resolution reconstruction of an initially low-resolution Cartesian T2 turbo spin echo sequence (T2 TSE) and compare it qualitatively and quantitatively to standard high-resolution Cartesian and non-Cartesian T2 TSE sequences in the setting of prostate mpMRI with particular interest in image sharpness, conspicuity of lesions and acquisition time. Furthermore, the investigators assessed the agreement of assigned PI-RADS scores between deep learning super resolution and standard sequences.
Study Details
Timeline
Interventions
A newly developed deep-learning based reconstruction of a primarily low-resolved T2-TSE sequence is included in the imaging protocol for evaluation of prostate cancer.