AIMC Topic: Lumbar Vertebrae

Clear Filters Showing 151 to 160 of 332 articles

Automated Magnetic Resonance Image Segmentation of Spinal Structures at the L4-5 Level with Deep Learning: 3D Reconstruction of Lumbar Intervertebral Foramen.

Orthopaedic surgery
OBJECTIVE: 3D reconstruction of lumbar intervertebral foramen (LIVF) has been beneficial in evaluating surgical trajectory. Still, the current methods of reconstructing the 3D LIVF model are mainly based on manual segmentation, which is laborious and...

Robotics is useful for less-experienced surgeons in spinal deformity surgery.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
PURPOSE: To verify whether robotics was useful for surgeons who had less experience with spinal deformity surgery.

Safety and risk factors of TINAVI robot-assisted percutaneous pedicle screw placement in spinal surgery.

Journal of orthopaedic surgery and research
OBJECTIVE: To determine the rates and risk factors of pedicle screw placement accuracy and the proximal facet joint violation (FJV) using TINAVI robot-assisted technique.

Predictors of accurate intrapedicular screw placement in single-level lumbar (L4-5) fusion: robot-assisted pedicle screw, traditional pedicle screw, and cortical bone trajectory screw insertion.

BMC surgery
BACKGROUND: The superiorities in proximal facet joint protection of robot-assisted (RA) pedicle screw placement and screw implantation via the cortical bone trajectory (CBT) have rarely been compared. Moreover, findings on the screw accuracy of both ...

External validation of the deep learning system "SpineNet" for grading radiological features of degeneration on MRIs of the lumbar spine.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
BACKGROUND: Magnetic resonance imaging (MRI) is used to detect degenerative changes of the lumbar spine. SpineNet (SN), a computer vision-based system, performs an automated analysis of degenerative features in MRI scans aiming to provide high accura...

Comparison of robot-assisted versus fluoroscopy-assisted minimally invasive transforaminal lumbar interbody fusion for degenerative lumbar spinal diseases: 2-year follow-up.

Journal of robotic surgery
This study was performed to prospectively compare the clinical and radiographic outcomes between robot-assisted minimally invasive transforaminal lumbar interbody fusion (RA MIS-TLIF) and fluoroscopy-assisted minimally invasive transforaminal lumbar ...

Improved Productivity Using Deep Learning-assisted Reporting for Lumbar Spine MRI.

Radiology
Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involves grading lumbar spinal stenosis, which is repetitive and time consuming. Deep learning (DL) could provide faster and more consistent interpretation. ...

A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: To propose a fully automated deep learning (DL) framework for the vertebral morphometry and Cobb angle measurement from three-dimensional (3D) computed tomography (CT) images of the spine, and validate the proposed framework on an external d...