Sparse classification with MRI based markers for neuromuscular disease categorization

Keyphrases

• Cardiac Magnetic Resonance Imaging (cMRI) 100%
• Image-based 100%
• Feature Selection 100%
• Neuromuscular Disease 100%
• Sparse Representation Classifier 100%
• Disease Categorization 100%
• Disease Classification 50%
• Structural Information 50%
• Area under the Curve 50%
• Diffusion Tensor Imaging 50%
• Patient Demographics 50%
• T1-weighted 50%
• Population-based 50%
• Myopathy 50%
• MR Diffusion 50%
• Machine Learning Algorithms 50%
• Myotonic Dystrophy 50%
• High Performance 50%
• Magnetic Resonance Imaging Data 50%
• Source Code 50%
• General Utility 50%
• Sparsity 50%
• MR Markers 50%
• Selection Property 50%
• Discriminative Value 50%
• Facioscapulohumeral muscular Dystrophy 50%
• T2-weighted MR Images 50%
• Feature Extraction 50%
• Image Dataset 50%
• Mean Area 50%
• Dystrophy Type 1 50%

Neuroscience

• Support Vector Machine 100%
• Magnetic Resonance Imaging 100%
• Neuromuscular Disorder 100%
• Muscular Dystrophy 66%
• Diffusion Tensor Imaging 33%
• Muscle Disorder 33%
• Machine Learning Algorithm 33%
• Follicle-Stimulating Hormone 33%

Computer Science

• Support Vector Machine 100%
• Feature Selection 66%
• Feature Extraction 66%
• Extracted Feature 33%
• Sparsity 33%
• Diffusion Tensor 33%
• Machine Learning Algorithm 33%
• Source Coding 33%