Computational Methods and Clinical Applications for Spine Imaging

<div>Automated Pedicle Screw Size and Trajectory Planning by Maximization of Fastening Strength.-&nbsp;Automatic Modic Changes Classification in Spinal MRI.-&nbsp;Patient Registration via Topologically Encoded Depth Projection Images in Spine Surgery.-&nbsp;</div><div>Automatic Localisation of Vertebrae in DXA Images Using Random Forest Regression Voting.-&nbsp;Robust CT to US 3D-3D Registration by Using Principal Component Analysis and Kalman Filtering.-&nbsp;Cortical Bone Thickness Estimation in CT Images: A Model-Based Approach Without Profile Fitting.-&nbsp;Multi-Atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT.-&nbsp;Statistical Shape Model Construction of Lumbar Vertebrae and Intervertebral Discs in Segmentation for Discectomy Surgery Simulation.-&nbsp;Automatic Intervertebral Discs Localization and Segmentation: A Vertebral Approach.-&nbsp;Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-Atlas Based Registration.-&nbsp;Deformable Model-Based Segmentation of Intervertebral Discs from MR Spine Images by Using the SSC Descriptor.-&nbsp;3D Intervertebral Disc Segmentation from MRI Using Supervoxel-Based CRFs.-&nbsp;Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours.-&nbsp;Localization and Segmentation of 3D Intervertebral Discs from MR Images via a Learning Based Method: A Validation Framework.-&nbsp;Automated Intervertebral Disc Segmentation Using Probabilistic Shape Estimation and Active Shape Models.&nbsp;</div>