Computational Methods and Clinical Applications for Spine Imaging

Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings

AvTomaž Vrtovec,Jianhua Yao

Häftad, Engelska, 2016

Del 9402 i serien Lecture Notes in Computer Science

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2016-07-01
Mått:155 x 235 x 10 mm
Vikt:271 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:159
Förlag:Springer International Publishing AG
ISBN:9783319418261

Utforska kategorier

Systemvetenskap och AI inom Data och IT
3D-grafik och modellering inom Data och IT
Programmeringsböcker inom Data och IT

Innehållsförteckning

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.