Learning-based stochastic object models for characterizing anatomical variations

Keyphrases

• Learning-based 100%
• Anatomical Variation 100%
• Stochastic Object Model 100%
• Anatomic 60%
• Human Anatomy 60%
• Centroid 40%
• Phantom 40%
• Patient Demographics 40%
• Numerical Phantom 40%
• Accurately Model 40%
• Imaging Systems 20%
• Image Quality 20%
• Proposed Methodology 20%
• Simulation Study 20%
• Systems-based 20%
• Adult Male 20%
• Challenging Tasks 20%
• Task-oriented 20%
• Volumetric Images 20%
• Training Data 20%
• Statistical Variation 20%
• Model-driven Development 20%
• Inter-patient 20%
• Geometric Attributes 20%
• Randomly Sampling 20%
• Shape Similarity 20%
• Training Image 20%
• Attribute Distribution 20%
• Organ Shape 20%
• Anatomic Models 20%
• Inter-organ 20%
• Attribute Variation 20%
• Stochastic Objects 20%
• Male Pelvis 20%
• Image Dataset 20%
• Objective Tasks 20%

Computer Science

• Computational Simulation 100%
• Image Quality 50%
• Simulation Study 50%
• Imaging Systems 50%
• Training Data 50%
• Model Development 50%
• Training Image 50%