Computational methods and clinical applications for spine imaging : 4th international workshop and challenge, CSI 2016 : held in conjunction with MICCAI 2016 Athens, Greece, October 17, 2016 ; revised selected papers

This book constitutes the refereed proceedings of the 4th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The 13 workshop papers were carefully reviewed and selected for inclusion in this volume. They aim at reviewing the state-of-the-art techniques, sharing the novel and emerging analysis and visualization techniques and discussing the clinical challenges and open problems in this rapidly growing field - including all major aspects of problems related to spine imaging, including clinical applications of spine imaging, computer aided diagnosis of spine conditions, computer aided detection of spine-related diseases, emerging computational imaging techniques for spinal diseases, fast 3D reconstruction of spine, feature extraction, multiscale analysis, pattern recognition, image enhancement of spine imaging, image-guided spine intervention and treatment, multimodal image registration and fusion for spine imaging, novel visualization techniques, segmentation techniques for spine imaging, statistical and geometric modeling for spine and vertebra, spine and vertebra localization. Front Matter....Pages I-X Front Matter....Pages 1-1 Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Vertebrae....Pages 3-15 Machine Learning Based Bone Segmentation in Ultrasound....Pages 16-25 Variational Segmentation of the White and Gray Matter in the Spinal Cord Using a Shape Prior....Pages 26-37 Automated Intervertebral Disc Segmentation Using Deep Convolutional Neural Networks....Pages 38-48 Front Matter....Pages 49-49 Fully Automatic Localisation of Vertebrae in CT Images Using Random Forest Regression Voting....Pages 51-63 Global Localization and Orientation of the Cervical Spine in X-ray Images....Pages 64-76 Accurate Intervertebral Disc Localisation and Segmentation in MRI Using Vantage Point Hough Forests and Multi-atlas Fusion....Pages 77-84 Multi-scale and Modality Dropout Learning for Intervertebral Disc Localization and Segmentation....Pages 85-91 Fully Automatic Localization and Segmentation of Intervertebral Disc from 3D Multi-modality MR Images by Regression Forest and CNN....Pages 92-101 Front Matter....Pages 103-103 Manual and Computer-Assisted Pedicle Screw Placement Plans: A Quantitative Comparison....Pages 105-115 Detection of Degenerative Osteophytes of the Spine on PET/CT Using Region-Based Convolutional Neural Networks....Pages 116-124 Reconstruction of 3D Lumvar Vertebra from Two X-ray Images Based on 2D/3D Registration....Pages 125-134 Classification of Progressive and Non-progressive Scoliosis Patients Using Discriminant Manifolds....Pages 135-145 Back Matter....Pages 147-147