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Recent Advances in Computational Methods and Clinical Applications for Spine Imaging

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Cover of 'Recent Advances in Computational Methods and Clinical Applications for Spine Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications
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    Chapter 2 Stacked Auto-encoders for Classification of 3D Spine Models in Adolescent Idiopathic Scoliosis
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    Chapter 3 Recent Advances in Computational Methods and Clinical Applications for Spine Imaging
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    Chapter 4 Portable Optically Tracked Ultrasound System for Scoliosis Measurement
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    Chapter 5 Atlas-Based Registration for Accurate Segmentation of Thoracic and Lumbar Vertebrae in CT Data
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    Chapter 6 Recent Advances in Computational Methods and Clinical Applications for Spine Imaging
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    Chapter 7 Interpolation-Based Detection of Lumbar Vertebrae in CT Spine Images
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    Chapter 8 An Improved Shape-Constrained Deformable Model for Segmentation of Vertebrae from CT Lumbar Spine Images
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    Chapter 9 Recent Advances in Computational Methods and Clinical Applications for Spine Imaging
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    Chapter 10 Automatic Segmentation of the Spinal Cord Using Continuous Max Flow with Cross-sectional Similarity Prior and Tubularity Features
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    Chapter 11 Automated Radiological Grading of Spinal MRI
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    Chapter 12 Automated 3D Lumbar Intervertebral Disc Segmentation from MRI Data Sets
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    Chapter 13 Minimally Supervised Segmentation and Meshing of 3D Intervertebral Discs of the Lumbar Spine for Discectomy Simulation
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    Chapter 14 Recent Advances in Computational Methods and Clinical Applications for Spine Imaging
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    Chapter 15 Bone Profiles: Simple, Fast, and Reliable Spine Localization in CT Scans
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    Chapter 16 Area- and Angle-Preserving Parameterization for Vertebra Surface Mesh
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    Chapter 17 Contour Models for Descriptive Patient-Specific Neuro-Anatomical Modeling: Towards a Digital Brainstem Atlas
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    Chapter 18 Atlas-Based Segmentation of the Thoracic and Lumbar Vertebrae
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    Chapter 19 Lumbar and Thoracic Spine Segmentation Using a Statistical Multi-object Shape $$+$$ Pose Model
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    Chapter 20 Vertebrae Segmentation in 3D CT Images Based on a Variational Framework
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    Chapter 21 Interpolation-Based Shape-Constrained Deformable Model Approach for Segmentation of Vertebrae from CT Spine Images
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    Chapter 22 Recent Advances in Computational Methods and Clinical Applications for Spine Imaging
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    Chapter 23 Report of Vertebra Segmentation Challenge in 2014 MICCAI Workshop on Computational Spine Imaging
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Title
Recent Advances in Computational Methods and Clinical Applications for Spine Imaging
Published by
Springer International Publishing, January 2015
DOI 10.1007/978-3-319-14148-0
ISBNs
978-3-31-914147-3, 978-3-31-914148-0, 978-3-31-938599-0
Editors

Jianhua Yao, Ben Glocker, Tobias Klinder, Shuo Li

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Spain 1 2%
Germany 1 2%
Unknown 45 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 37%
Student > Master 11 22%
Researcher 7 14%
Student > Doctoral Student 5 10%
Student > Bachelor 3 6%
Other 3 6%
Unknown 2 4%
Readers by discipline Count As %
Engineering 18 37%
Computer Science 17 35%
Agricultural and Biological Sciences 3 6%
Medicine and Dentistry 2 4%
Physics and Astronomy 1 2%
Other 4 8%
Unknown 4 8%