基于单次测量的潜空间运动跟踪的前瞻式动态3D MRI重建
Prospective Dynamic 3D MRI Reconstruction via Latent-Space Motion Tracking from Single Measurement
把形变矢量场（DVF）约束在离线学到的低维潜流形上，并用三平面编码实现几何感知、显存友好的3D运动表示，这一「低维运动流形+在线快速适配」思路可迁移到任何需要从稀疏观测快速估计稠密形变的视觉任务（如动态场景重建、非刚性配准、视频形变跟踪）。
原文依据 we parameterize the deformation vector fields (DVFs) on a low-dimensional manifold, effectively reducing the search space for fast online adaptation
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论前瞻式重建在许多临床应用中至关重要，例如MRI引导的放射治疗，它要求从当前采集的测量中实现准确的图像重建与快速运动估计。然而，超稀疏采样和严苛的延迟要求使前瞻式重建仍具挑战性。在本工作中，我们提出PDMR，一个带有潜空间运动跟踪的前瞻式动态3D MRI重建框架。我们的核心思想是离线学习一个高效且可泛化的运动场潜流形，从而支持面向前瞻式重建的快速在线适配。具体而言，我们将形变矢量场（DVF）参数化在低维流形上，有效缩小了快速在线适配的搜索空间，并采用三平面表示来实现对3D运动的几何感知且显存高效的编码。在XCAT数字体模与自建腹部MRI数据集上的实验表明，PDMR在多种前瞻式场景（即时与2分钟后）下均实现了高保真且时间一致的重建，优于最优的回顾式与在线方法。我们的结果指向了一条在临床实践中实现超快速、运动感知的前瞻式MRI重建的可行路径。
英文原文摘要 1307 字符
Prospective reconstruction is crucial in many clinical applications such as MRI-guided radiotherapy, which demands accurate image reconstruction and fast motion estimation from currently acquired measurements. However, prospective reconstruction remains challenging due to ultra-sparse sampling and stringent latency requirements. In this work, we propose PDMR, an Prospective Dynamic 3D MRI Reconstruction framework with latent-space motion tracking. Our core idea is to learn an efficient and generalizable latent manifold of motion fields offline, enabling rapid online adaptation for prospective reconstruction. Specifically, we parameterize the deformation vector fields (DVFs) on a low-dimensional manifold, effectively reducing the search space for fast online adaptation, and employ a tri-plane representation to achieve geometry-aware and memory-efficient encoding of 3D motion. Experiments on both XCAT digital phantoms and in-house abdominal MRI datasets demonstrate that PDMR achieves high-fidelity and temporally consistent reconstruction across multiple prospective scenarios (Immediate and After-2min), outperforming state-of-the-art retrospective and online methods. Our results suggest a promising pathway toward ultra-fast, motion-aware prospective MRI reconstruction in clinical practice.