Optimization of Scan Specific 3D Probabilistic Mask using Few Multi-Axial Slices Simulating Scout Scans for MRI Reconstruction

Motivation: Current MRI mask optimization methods require GT images or lack scan-adaptability. In 3D MRI, the optimal sampling pattern varies by axis, making existing methods challenging to apply effectively. Goal(s): To optimize a scan-specific 3D undersampling pattern using only sparse slices from multiple axes, similar to a scout scan (for calibration), to improve reconstruction quality. Approach: Using only a few slices, like scout scan, generate 2D probability maps, which is interpolated and refined with Fourier weights vectors to produce an optimized 3D probability map to sampling mask. Results: Ours achieved high PSNR, SSIM at an 8x reduction ratio, showing superior preservation of detailed structures. Impact: This study enables faster, high-quality 3D MRI with scan-specific undersampling patterns, potentially reducing scan times in clinical settings. It could improve patient experience, increase MRI accessibility, and enhance outcomes when combined with 3D MR reconstruction network research.