Compressed-sensing magnetic resonance image reconstruction using an iterative convolutional neural network approach

Keyphrases

• Magnetic Resonance Image Reconstruction 100%
• Compressed Sensing 100%
• K-Space Data 80%
• K-space 40%
• Zero-filling 20%
• State-of-the-art Techniques 20%
• Network Space 20%
• Reconstruction Approach 20%
• MR Image Quality 20%
• Space Images 20%
• Enhanced MR 20%
• Non-iterative Approach 20%
• Structural Similarity Index 20%
• Peak Signal to Noise Ratio 20%
• Artifact in the Reconstructed Image 20%

Engineering

• Neural Network Approach 100%
• Compressed Sensing 100%
• Space Data 80%
• Peak Signal 20%
• Similarity Index 20%
• State-of-the-Art Technique 20%
• Sampled Image 20%
• Priori Information 20%
• Brain Image 20%
• Image Space 20%
• Structural Similarity 20%