AI 中文总结
研究提出 SIMPLE - 4D 工作流程，通过标准快速多层 2D MRI 重建切片实现便携式无替代 4D MRI，结合采集无关前端、无替代变分运动编码器和基于隐式神经表示的时空重建，在多数据集验证，有创新成果及性能提升。
AI 中文摘要
四维磁共振成像（4D MRI）用于表征呼吸器官运动，但现有重建流程与特定采集平台紧密相关，限制了其在不同临床和研究场景中的广泛应用。我们提出了 SIMPLE - 4D，这是一种完全基于标准快速多层 2D MRI 重建切片运行的软件优先便携式工作流程，无需修改脉冲序列、非笛卡尔轨迹、导航器或外部硬件。SIMPLE - 4D 结合了消耗标准 2D 协议的采集无关前端、直接从每个 2D 切片提取紧凑运动代码的无替代变分运动编码器，以及基于哈希编码隐式神经表示（INR）和 SIREN 变形网络的物理感知连续时空重建，产生双向循环一致的位移矢量场（DVFs）和运动相关的高斯 - 勒让德厚切片积分。我们在两个对比数据集上验证了该流程，结果表明这是首次仅从重建的 2D 笛卡尔切片在负重直立开放孔径低场扫描仪上进行每帧 4D 容积呼吸 MRI 重建，且在低场数据上 INR 模板还可作为隐式去噪器，使信噪比提高 132%。
英文摘要
Four-dimensional MRI (4D MRI) characterizes respiratory organ motion, yet existing reconstruction pipelines are tightly coupled to specific acquisition platforms (e.g., non-Cartesian trajectories with self-gating, vendor-specific navigators, or external respiratory hardware), limiting broad adoption across diverse clinical and research settings, including low-field, open-bore, and non-supine imaging. We present SIMPLE-4D (Surrogate-free, IMplicit, PortabLE 4D MRI), a software-first portable workflow that operates entirely on reconstructed slices from standard fast multi-slice 2D MRI and requires no pulse-sequence modification, no non-Cartesian trajectory, no navigator, and no external hardware. SIMPLE-4D combines an acquisition-agnostic front end consuming standard 2D protocols, a surrogate-free variational motion encoder that extracts a compact motion code directly from each 2D slice, and a physics-aware continuous spatio-temporal reconstruction based on a hash-encoded implicit neural representation (INR) with a SIREN deformation network producing bidirectional cycle-consistent DVFs and motion-dependent Gauss-Legendre thick-slice quadrature. Bidirectionality yields a complete inter-frame motion model by composition, supporting downstream tasks such as dose accumulation without retraining. We validate the identical pipeline on two contrasting datasets: a 1.5 T clinical bSSFP dataset (5 volunteers, 3 sessions each) and a 0.5 T open-bore HASTE dataset (5 volunteers, supine and upright). To our knowledge, this is the first per-frame 4D volumetric respiratory MRI reconstruction on a weight-bearing upright open-bore low-field scanner from reconstructed 2D Cartesian slices alone. On low-field data the INR template additionally acts as an implicit denoiser, yielding +132% SNR. Systematic ablations isolate each component's contribution.
Comments52 pages, 8 figures, 6 tables
