SENSE Algorithm: A Classic Approach to Parallel Magnetic Resonance Imaging

The SENSE algorithm, a classical method in parallel magnetic resonance imaging, demonstrates outstanding performance and provides substantial benefits for parallel MRI research. In the field of parallel MRI, the SENSE algorithm is widely employed as it utilizes parallel acquisition from multiple channels and reconstructs images using sensitivity encoding matrices, thereby enhancing imaging speed and spatial resolution. From an implementation perspective, the algorithm typically involves: 1. Acquiring undersampled k-space data from multiple receiver coils 2. Calculating coil sensitivity maps through calibration scans 3. Formulating the reconstruction problem as a linear equation: E × ρ = m, where E is the sensitivity encoding matrix, ρ represents the image to be reconstructed, and m contains the acquired k-space data 4. Solving the inverse problem using methods like least-squares optimization The research and application of this algorithm can significantly advance medical imaging development, providing more accurate information for clinical diagnosis and treatment. Additionally, parallel MRI research encompasses hardware and software optimization, as well as exploration of novel imaging techniques. In summary, in-depth investigation of parallel magnetic resonance imaging represents a highly significant research direction that promises substantial breakthroughs and advancements in medical and scientific fields.