mcLARO: Multi-Contrast Learned Acquisition and Reconstruction Optimization for simultaneous multi-contrast and multi-parametric mapping

We propose a unified framework for highly accelerated multi-contrast and multi-parametric imaging in a single scan. Our framework, named mcLARO, includes designing a novel multi-contrast pulse sequence, optimizing k-space sampling pattern and image reconstruction with a learning-based approach, and fitting T1, T2 T2* and QSM maps using the reconstructed multi-contrast images. mcLARO is compared with reference T1w, T2w, GRE, T1, T2, T2* and QSM mapping sequences and achieves comparable results.