Aarnio Antti, Nykänen Olli, Kolehmainen Ville, Nissi Mikko J
Department of Technical Physics, University of Eastern Finland, Kuopio, Finland.
Magn Reson Med. 2025 Nov;94(5):2258-2267. doi: 10.1002/mrm.30610. Epub 2025 Jun 16.
To determine how various compressed sensing (CS) models can accelerate alternating Look-Locker mapping.
An alternating Look-Locker acquisition was retrospectively accelerated by factors of 1-12. The data was reconstructed into 12 images with multiple CS models, which utilized combinations of spatial total variation, locally low-rank regularization, and subspace constraints. Complex non-linear least squares signal fitting was performed to obtain the maps. The accelerated maps were compared against the map of a full data reference reconstruction.
A subspace-constrained reconstruction model with spatial total variation and locally low-rank regularization outperformed all other models as measured by map normalized root mean squared error, structural similarity index, and normalized mean absolute deviation. The subspace constraint benefited models utilizing spatial total variation but, conversely, did not benefit models utilizing only locally low-rank regularization.
The radial 3-D alternating Look-Locker mapping acquisition was successfully accelerated by up to a factor of 12 with various CS models. The best-performing model was a subspace-constrained reconstruction, which utilized spatial total variation and locally low-rank regularization.
确定各种压缩感知（CS）模型如何加速交替Look-Locker映射。
对交替Look-Locker采集的数据进行回顾性加速，加速因子为1至12。使用多种CS模型将数据重建为12幅图像，这些模型利用了空间总变差、局部低秩正则化和子空间约束的组合。进行复杂的非线性最小二乘信号拟合以获得映射图。将加速后的映射图与全数据参考重建的映射图进行比较。
通过映射图归一化均方根误差、结构相似性指数和归一化平均绝对偏差测量，具有空间总变差和局部低秩正则化的子空间约束重建模型优于所有其他模型。子空间约束对利用空间总变差的模型有益，但相反，对仅利用局部低秩正则化的模型无益。
使用各种CS模型成功将径向三维交替Look-Locker映射采集加速了高达12倍。性能最佳的模型是子空间约束重建模型，它利用了空间总变差和局部低秩正则化。
