Oscillating Steady-State Imaging (OSSI) is a recently developed fMRI acquisition method that can provide 2 to 3 times higher SNR than standard fMRI approaches. However, because the OSSI signal exhibits a nonlinear oscillation pattern, one must acquire and combine ${n}_{c}$ (e.g., 10) OSSI images to get an image that is free of oscillation for fMRI, and fully sampled acquisitions would compromise temporal resolution. To improve temporal resolution and accurately model the nonlinearity of OSSI signals, instead of using subspace models that are not well suited for the data, we build the MR physics for OSSI signal generation as a regularizer for the undersampled reconstruction. Our proposed physics-based manifold model turns the disadvantages of OSSI acquisition into advantages and enables joint reconstruction and quantification. OSSI manifold model (OSSIMM) outperforms subspace models and reconstructs high-resolution fMRI images with a factor of 12 acceleration and without spatial or temporal smoothing. Furthermore, OSSIMM can dynamically quantify important physics parameters, including ${R}_{{2}}^{\ast}$ maps, with a temporal resolution of 150 ms.

中文翻译：

---

用于高分辨率 fMRI 联合重建和动态量化的流形正则化器


振荡稳态成像 (OSSI) 是一种最近开发的 fMRI 采集方法，其信噪比比标准 fMRI 方法高 2 至 3 倍。然而，由于 OSSI 信号表现出非线性振荡模式，因此必须获取并组合${n}_{c}$ （例如，10）个 OSSI 图像以获得 fMRI 没有振荡的图像，并且完全采样的采集会损害时间分辨率。为了提高时间分辨率并准确建模 OSSI 信号的非线性，我们没有使用不太适合数据的子空间模型，而是构建了用于 OSSI 信号生成的 MR 物理场，作为欠采样重建的正则器。我们提出的基于物理的流形模型将 OSSI 采集的缺点转化为优点，并实现联合重建和量化。 OSSI 流形模型 (OSSIMM) 的性能优于子空间模型，可以以 12 倍的加速度重建高分辨率 fMRI 图像，并且无需空间或时间平滑。此外，OSSIMM 可以动态量化重要的物理参数，包括${R}_{{2}}^{\ast}$地图，时间分辨率为 150 ms。