Fast, volumetric multi-contrast and quantitative imaging has a broad range of applications, but applying them in 3D remains challenging. Most volumetric approaches rely on gradient-echo-based acquisitions to achieve high scan-efficiency, even though spin-echo imaging provides higher SNR. Here we explore a hybrid acquisition that combines a fast-spin-echo acquisition block with multiple spoiled gradient-echo blocks to acquire spin- and gradient-echo images. We use a shuffled acquisition ordering together with a global subspace constraint and local low rank regularization to accelerate the scan. Following reconstruction, we fit the time series of images to quantitative parameters directly in the subspace using dictionary matching.
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