… MRI scanning with higher-level accuracy will probably become more relevant. Therefore, we
… the feasibility of using deep learning algorithms for routine reporting in spine MRI with the …

… Deep learning (DL)–based MRI reconstructions can reduce examination times for turbo
spin-echo (… DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. …

… attempted to use deep learning methods to detect spinal cord compression in a … deep
learning model to detect cervical spinal cord compression in patients with DCM in T2 weighted MRI …

… assisted by deep learning for interpretation of lumbar spinal stenosis on MRI scans showed
… for all stenosis gradings compared with radiologists who were unassisted by deep learning. …

… To compare interobserver agreement and image quality of 3D T2-weighted fast spin
echo (T2w-FSE) L-spine MRI images processed with a deep learning reconstruction (DLRecon) …

… Data Characteristics Our initial cohort consisted of 7108 lumbar spine MRI examinations
reviewed by 57 different final-signing radiologists. For each study, the sagittal and axial T2-…

… , a pattern of deep learning, has … deep learning based program Spine Explorer for automated
detection and segmentation for major spinal components on T2W sagittal lumbar spine MRI…

… MRI protocol with deep learning (DL)-based image reconstruction for imaging degenerative
lumbar spine … in combination with an accelerated MRI protocol represents a promising …

… to detect MRI lumbar spine via a transfer learning method [15] without using annotated MRI
… neural network [16] with transfer learning to locate the lumbar spine from L1 to S1. The …

… This study included sagittal MRI images collected from 585 patients with spinal tumors (259
women, 326 men; mean age 48 ± 18 years, range 4–82 years), including 270 benign and …