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This book contains the full papers presented at the MICCAI 2014 workshop on Computational Methods and Clinical Applications for Spine Imaging. The workshop brought together scientists and clinicians in the field of computational spine imaging. The chapters included in this book present and discuss the new advances and challenges in these fields, using several methods and techniques in order to address more efficiently different and timely applications involving signal and image acquisition, image processing and analysis, image segmentation, image registration and fusion, computer simulation, image based modeling, simulation and surgical planning, image guided robot assisted surgical and image based diagnosis. The book also includes papers and reports from the first challenge on vertebra segmentation held at the workshop.
Preface.- Workshop Organization.- Computer Aided Diagnosis and Intervention.- Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications, by Holger Roth, Jianhua Yao, Le, James Stieger, Joseph Burns, Ronald Summers.- Stacked auto-encoders for classification of 3D spine models in adolescent idiopathic scoliosis, by William Thong, Hubert Labelle, Jesse Shen, Stefan Parent, Samuel Kadoury.- An Active Optical Flow Model for Dose Prediction in Spinal SBRT Plans, by Jianfei Liu, Jackie Wu, FangFang Yin, John Kirkpatrick, Alvin Cabrera, Yaorong Ge.- Portable optically tracked ultrasound system for scoliosis measurement, by Guillermo Carbajal, Álvaro Gómez, Gabor Fichtinger, Tamas Ungi.- Spine Segmentation.- Atlas-Based Registration for Accurate Segmentation of Thoracic and Lumbar Vertebrae in CT Data, by Daniel Forsberg.- Segmentation of Lumbar Vertebrae Slices from CT Images, by Hugo Hutt, Richard Everson, Judith Meakin.- Interpolation-Based Detection of Lumbar Vertebrae in CT Spine Images, by Bulat Ibragimov, Robert Korez, Bostjan Likar, Franjo Pernus, Tomaz Vrtovec.- An Improved Shape-Constrained Deformable Model for Segmentation of Vertebrae from CT Lumbar Spine Images, by Robert Korez, Bulat Ibragimov, Bostjan Likar, Franjo Pernus, Tomaz Vrtovec.- Detailed Vertebral Segmentation using Part-Based Decomposition and Conditional Shape Models, by Marco Pereañez, Karim Lekadir, Corné Hoogendoorn, Isaac Castro Mateos, Alejandro Frangi.- MR Image Processing.- Automatic Segmentation of the Spinal Cord using Continuous Max Flow with Cross-sectional Similarity Prior and Tubularity Features, by Simon Pezold, Ketut Fundana, Michael Amann, Michaela Andelova, Armanda Pfister, Till Sprenger, Philippe Cattin.- Automated Radiological Measurement of Spinal MRI, by Meelis Lootus, Timor Kadir, Andrew Zisserman.- Automated 3D Lumbar Intervertebral Disc Segmentation from MRI Images, by Xiao Dong, Guoyan Zheng.- Minimally Supervised Segmentation and Meshing of 3D Intervertebral Discs of the Lumbar Spine for Discectomy Simulation, by Rabia Haq, Rifat Aras, Roderick Borgie, David Besachio, Michel Audette.- Localization.- Localisation of Vertebrae on DXA Images using Constrained Local Models with Random Forest Regression Voting, by Paul Bromiley, Judith Adams, Tim Cootes.- Bone Profiles: Simple, Fast, and Reliable Spine Localization in CT Scans, by Jiri Hladuvka, David Major, Katja Bühler.- Modeling.- Area- and Angle-preserving Parametrization for Vertebra Surface Mesh, by Shoko Miyauchi, Ken'ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazame.- Contour models for descriptive patient-specific neuro-anatomical modeling: towards a digital brainstem atlas, by Nirmal Patel, Sharmin Sultana, Michel Audette.- Segmentation Challenge.- Atlas-Based Segmentation of the Thoracic and Lumbar Vertebrae, by Daniel Forsberg.- Lumbar and thoracic spine segmentation using a statistical multi-object shape+pose model, by Alexander Seitel, Abtin Rasoulian, Robert Rohling, Purang Abolmaesumi.- Vertebrae Segmentation in 3D CT Images based on a Variational Framework, by Kerstin Hammernik, Thomas Ebner, Darko Stern, Martin Urschler, Thomas Pock.- Interpolation-Based Shape-Constrained Deformable Model Approach for Segmentation of Vertebrae from CT Spine Images, by Robert Korez, Bulat Ibragimov, Bostjan Likar, Franjo, Tomaz Vrtovec.- 3D Vertebra segmentation by feature selection Active Shape Model, by Isaac Castro Mateos, Jose Pozo Soler, Alejandro Frangi.- Report of Vertebra Segmentation Challenge in 2014 MICCAI Workshop on Computational Spine Imaging, by Jianhua Yao, Shuo Li.