Plug and play truncated low rank optimization combined iterative soft thresholding (PNPT) for dynamic MRI reconstruction

Motivation: Try to obtaining high spatial and temporal resolution image in dynamic MRI. Goal(s): The plug and play truncated low rank optimization combined iterative soft thresholding(PNPT-) embedded method was proposed to reconstructe data and tested to accurately estimate the rank function for dMRI reconstruction. Approach: The PNPT- method uses truncated nuclear norm combined iterative soft thresholding to assign different shrink values to different singular vectors, enabling the preservation of essential image information while effectively eliminating noise. Results: The embedded method was proposed to reconstructe data and tested to accurately estimate the rank function for dMRI reconstruction. Impact: The proposed method demonstrated reduced aliasing artifacts compared to other methods and yielded better reconstruction images in cine and perfusion data. Consequently, it provided more accurate and efficient image information, benefiting the clinical diagnosis of heart-related diseases.