Accelerating sensitivity encoding using compressed sensing.

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Image Reconstruction
• Signal Processing

Background:

• Compressed Sensing (CS) and SENSitivity Encoding (SENSE) are advanced MRI techniques.
• Directly combining CS and SENSE may yield suboptimal encoding matrices.
• Improving MRI acquisition speed and robustness is crucial for clinical applications.

Purpose of the Study:

• To propose a novel sequential application of CS and SENSE for MRI.
• To evaluate the performance of the sequential CS-SENSE method against direct combination.
• To achieve a higher total acceleration factor in MRI acquisition.

Main Methods:

• A sequential approach applying CS first to reconstruct aliased coil images, followed by SENSE reconstruction.
• Utilizing the product of individual acceleration factors from CS and SENSE.
• Experimental validation comparing the proposed method with direct CS-SENSE combination.

Main Results:

• The proposed sequential CS-SENSE method demonstrates superior performance compared to direct combination.
• The sequential approach allows for a combined acceleration factor that is the product of individual factors.
• Reconstructed images show improved quality and robustness.

Conclusions:

• The sequential application of CS and SENSE offers a more effective strategy for accelerated MRI.
• This method enhances overall MRI performance, providing better image quality at higher acceleration factors.
• The proposed technique is a promising advancement for faster and more robust MRI acquisition.