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Computational Methods and Clinical Applications for Spine Imaging

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Cover of '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 Vertebral Fractures in CT Using 3D Convolutional Neural Networks
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    Chapter 2 Metastatic Vertebrae Segmentation for Use in a Clinical Pipeline
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    Chapter 3 Conditioned Variational Auto-encoder for Detecting Osteoporotic Vertebral Fractures
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    Chapter 4 Vertebral Labelling in Radiographs: Learning a Coordinate Corrector to Enforce Spinal Shape
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    Chapter 5 Semi-supervised Semantic Segmentation of Multiple Lumbosacral Structures on CT
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    Chapter 6 Accurate Automated Keypoint Detections for Spinal Curvature Estimation
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    Chapter 7 Seg4Reg Networks for Automated Spinal Curvature Estimation
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    Chapter 8 Automatic Spine Curvature Estimation by a Top-Down Approach
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    Chapter 9 Automatic Cobb Angle Detection Using Vertebra Detector and Vertebra Corners Regression
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    Chapter 10 Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks
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    Chapter 11 Automated Spinal Curvature Assessment from X-Ray Images Using Landmarks Estimation Network via Rotation Proposals
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    Chapter 12 A Coarse-to-Fine Deep Heatmap Regression Method for Adolescent Idiopathic Scoliosis Assessment
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    Chapter 13 Spinal Curve Guide Network (SCG-Net) for Accurate Automated Spinal Curvature Estimation
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    Chapter 14 A Multi-task Learning Method for Direct Estimation of Spinal Curvature
Attention for Chapter 13: Spinal Curve Guide Network (SCG-Net) for Accurate Automated Spinal Curvature Estimation
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Chapter title
Spinal Curve Guide Network (SCG-Net) for Accurate Automated Spinal Curvature Estimation
Chapter number 13
Book title
Computational Methods and Clinical Applications for Spine Imaging
Published by
Springer, Cham, October 2019
DOI 10.1007/978-3-030-39752-4_13
Book ISBNs
978-3-03-039751-7, 978-3-03-039752-4
Authors

Shuxin Wang, Shaohui Huang, Liansheng Wang, Wang, Shuxin, Huang, Shaohui, Wang, Liansheng

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 50%
Lecturer 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 1 25%
Engineering 1 25%
Unknown 2 50%