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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 Automated Recognition of Erector Spinae Muscles and Their Skeletal Attachment Region via Deep Learning in Torso CT Images
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    Chapter 2 Fully Automatic Teeth Segmentation in Adult OPG Images
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    Chapter 3 Fully Automatic Planning of Total Shoulder Arthroplasty Without Segmentation: A Deep Learning Based Approach
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    Chapter 4 Deep Volumetric Shape Learning for Semantic Segmentation of the Hip Joint from 3D MR Images
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    Chapter 5 Pelvis Segmentation Using Multi-pass U-Net and Iterative Shape Estimation
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    Chapter 6 Bone Adaptation as Level Set Motion
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    Chapter 7 Landmark Localisation in Radiographs Using Weighted Heatmap Displacement Voting
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    Chapter 8 Perthes Disease Classification Using Shape and Appearance Modelling
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    Chapter 9 Deep Learning Based Rib Centerline Extraction and Labeling
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    Chapter 10 Automatic Detection of Wrist Fractures From Posteroanterior and Lateral Radiographs: A Deep Learning-Based Approach
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    Chapter 11 Bone Reconstruction and Depth Control During Laser Ablation
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    Chapter 12 Automated Dynamic 3D Ultrasound Assessment of Developmental Dysplasia of the Infant Hip
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    Chapter 13 Automated Measurement of Pelvic Incidence from X-Ray Images
Attention for Chapter 1: Automated Recognition of Erector Spinae Muscles and Their Skeletal Attachment Region via Deep Learning in Torso CT Images
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