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Computational Methods and Clinical Applications for Spine Imaging [electronic resource] : Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings /

Contributor(s): Material type: TextTextSeries: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 9402Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016Description: X, 159 p. 61 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319418278
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.37 23
LOC classification:
  • TA1634
Online resources:
Contents:
Automated Pedicle Screw Size and Trajectory Planning by Maximization of Fastening Strength -- Automatic Modic Changes Classification in Spinal MRI -- Patient Registration via Topologically Encoded Depth Projection Images in Spine Surgery -- Automatic Localisation of Vertebrae in DXA Images Using Random Forest Regression Voting -- Robust CT to US 3D-3D Registration by Using Principal Component Analysis and Kalman Filtering -- Cortical Bone Thickness Estimation in CT Images: A Model-Based Approach Without Profile Fitting -- Multi-Atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT -- Statistical Shape Model Construction of Lumbar Vertebrae and Intervertebral Discs in Segmentation for Discectomy Surgery Simulation -- Automatic Intervertebral Discs Localization and Segmentation: A Vertebral Approach -- Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-Atlas Based Registration -- Deformable Model-Based Segmentation of Intervertebral Discs from MR Spine Images by Using the SSC Descriptor -- 3D Intervertebral Disc Segmentation from MRI Using Supervoxel-Based CRFs -- Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours -- Localization and Segmentation of 3D Intervertebral Discs from MR Images via a Learning Based Method: A Validation Framework -- Automated Intervertebral Disc Segmentation Using Probabilistic Shape Estimation and Active Shape Models. .
In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the Third International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2015, held in conjunction with MICCAI 2015, in Munich, Germany, in October 2015. The 9 workshop papers and 6 challenge contributions were carefully reviewed and selected for inclusion in this volume. The papers cover all major aspects related to spine imaging.
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Automated Pedicle Screw Size and Trajectory Planning by Maximization of Fastening Strength -- Automatic Modic Changes Classification in Spinal MRI -- Patient Registration via Topologically Encoded Depth Projection Images in Spine Surgery -- Automatic Localisation of Vertebrae in DXA Images Using Random Forest Regression Voting -- Robust CT to US 3D-3D Registration by Using Principal Component Analysis and Kalman Filtering -- Cortical Bone Thickness Estimation in CT Images: A Model-Based Approach Without Profile Fitting -- Multi-Atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT -- Statistical Shape Model Construction of Lumbar Vertebrae and Intervertebral Discs in Segmentation for Discectomy Surgery Simulation -- Automatic Intervertebral Discs Localization and Segmentation: A Vertebral Approach -- Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-Atlas Based Registration -- Deformable Model-Based Segmentation of Intervertebral Discs from MR Spine Images by Using the SSC Descriptor -- 3D Intervertebral Disc Segmentation from MRI Using Supervoxel-Based CRFs -- Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours -- Localization and Segmentation of 3D Intervertebral Discs from MR Images via a Learning Based Method: A Validation Framework -- Automated Intervertebral Disc Segmentation Using Probabilistic Shape Estimation and Active Shape Models. .

This book constitutes the refereed proceedings of the Third International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2015, held in conjunction with MICCAI 2015, in Munich, Germany, in October 2015. The 9 workshop papers and 6 challenge contributions were carefully reviewed and selected for inclusion in this volume. The papers cover all major aspects related to spine imaging.

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