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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 1: Detection of Vertebral Fractures in CT Using 3D Convolutional Neural Networks
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Chapter title
Detection of Vertebral Fractures in CT Using 3D Convolutional Neural Networks
Chapter number 1
Book title
Computational Methods and Clinical Applications for Spine Imaging
Published by
Springer, Cham, October 2019
DOI 10.1007/978-3-030-39752-4_1
Book ISBNs
978-3-03-039751-7, 978-3-03-039752-4
Authors

Joeri Nicolaes, Steven Raeymaeckers, David Robben, Guido Wilms, Dirk Vandermeulen, Cesar Libanati, Marc Debois, Nicolaes, Joeri, Raeymaeckers, Steven, Robben, David, Wilms, Guido, Vandermeulen, Dirk, Libanati, Cesar, Debois, Marc

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 20%
Student > Master 2 5%
Lecturer 2 5%
Student > Doctoral Student 2 5%
Student > Bachelor 2 5%
Other 5 13%
Unknown 19 48%
Readers by discipline Count As %
Computer Science 8 20%
Medicine and Dentistry 4 10%
Engineering 3 8%
Arts and Humanities 2 5%
Agricultural and Biological Sciences 1 3%
Other 2 5%
Unknown 20 50%