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Computational Methods and Clinical Applications in Musculoskeletal Imaging

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Cover of 'Computational Methods and Clinical Applications in Musculoskeletal Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Localization of Bone Surfaces from Ultrasound Data Using Local Phase Information and Signal Transmission Maps
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    Chapter 2 Shape-Aware Deep Convolutional Neural Network for Vertebrae Segmentation
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    Chapter 3 Automated Characterization of Body Composition and Frailty with Clinically Acquired CT
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    Chapter 4 Unfolded Cylindrical Projection for Rib Fracture Diagnosis
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    Chapter 5 3D Cobb Angle Measurements from Scoliotic Mesh Models with Varying Face-Vertex Density
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    Chapter 6 Automatic Localization of the Lumbar Vertebral Landmarks in CT Images with Context Features
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    Chapter 7 Joint Multimodal Segmentation of Clinical CT and MR from Hip Arthroplasty Patients
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    Chapter 8 Reconstruction of 3D Muscle Fiber Structure Using High Resolution Cryosectioned Volume
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    Chapter 9 Segmentation of Pathological Spines in CT Images Using a Two-Way CNN and a Collision-Based Model
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    Chapter 10 Attention-Driven Deep Learning for Pathological Spine Segmentation
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    Chapter 11 Automatic Full Femur Segmentation from Computed Tomography Datasets Using an Atlas-Based Approach
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    Chapter 12 Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling
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    Chapter 13 DSMS-FCN: A Deeply Supervised Multi-scale Fully Convolutional Network for Automatic Segmentation of Intervertebral Disc in 3D MR Images
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