Computational Methods and Clinical Applications for Spine Imaging

Chapter 1 Detection of Vertebral Fractures in CT Using 3D Convolutional Neural Networks

Chapter 2 Metastatic Vertebrae Segmentation for Use in a Clinical Pipeline

Chapter 3 Conditioned Variational Auto-encoder for Detecting Osteoporotic Vertebral Fractures

Chapter 4 Vertebral Labelling in Radiographs: Learning a Coordinate Corrector to Enforce Spinal Shape

Chapter 5 Semi-supervised Semantic Segmentation of Multiple Lumbosacral Structures on CT

Chapter 6 Accurate Automated Keypoint Detections for Spinal Curvature Estimation

Chapter 7 Seg4Reg Networks for Automated Spinal Curvature Estimation

Chapter 8 Automatic Spine Curvature Estimation by a Top-Down Approach

Chapter 9 Automatic Cobb Angle Detection Using Vertebra Detector and Vertebra Corners Regression

Chapter 10 Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks

Chapter 11 Automated Spinal Curvature Assessment from X-Ray Images Using Landmarks Estimation Network via Rotation Proposals

Chapter 12 A Coarse-to-Fine Deep Heatmap Regression Method for Adolescent Idiopathic Scoliosis Assessment

Chapter 13 Spinal Curve Guide Network (SCG-Net) for Accurate Automated Spinal Curvature Estimation

Chapter 14 A Multi-task Learning Method for Direct Estimation of Spinal Curvature