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Development of a convolutional neural network for the endoscopic classification of pouchitis in patients after restorative proctocolectomy.

The aim of this prospective single-center study is to train convolutional neural networks (CNNs) to detect the presence of pouchitis in two-dimensional (2D) images acquired during pouchoscopies and test its feasibility.
www.ncbi.nlm.nih.gov

Ultrafast deep learning super-resolution single-shot T2-weighted imaging for robust edema visualization in cardiovascular magnetic resonance.

To compare the diagnostic quality of deep learning (DL) super-resolution reconstructed breath-hold (BH) and free-breathing (FB) single-shot (SSH) black-blood T2-weighted short tau inversion recovery (STIR) imaging with standard BH T2-STIR in cardiovascular magnetic resonance (CMR).
www.ncbi.nlm.nih.gov