用神经场实现每秒20.8亿像素的超大视野高速显微成像
Video-rate gigapixel ptychography via space-time neural field representations
- 用时空神经场分解图像，从串行采集转为相关性高效提取
- 实现每秒20.8亿像素、厘米级视场、308纳米分辨的视频级成像
- 无需透镜，适用于晶体、细菌等多类动态样本观测
在成像科学中，以视频速率实现吉像素级空间-带宽积（SBP）是根本性挑战。本文通过神经场表示利用时空相关性，实现了突破该瓶颈的视频率全息成像。方法将时空体积分解为低秩空间与时间特征，使SBP扩展从逐次测量转变为高效相关性提取。采用双网络解码实部与虚部场分量，避免幅度-相位表示中的相位跳跃问题。在空间导数上使用梯度域损失，确保收敛稳定性。实验展示在厘米级覆盖范围内实现视频速率吉像素成像，可分辨308纳米线宽。验证涵盖晶体、细菌、干细胞、微针等样品动态监测，以及极端紫外实验中时变探针表征，展现跨波长适用性。通过将时间变化从约束转化为可利用的相关性，证明仅用单传感器测量即可实现吉像素视频成像，使全息术成为无透镜高通量传感工具，用于监测介观尺度动态过程。
原文摘要 · Abstract (English)
Achieving gigapixel space-bandwidth products (SBP) at video rates represents a fundamental challenge in imaging science. Here we demonstrate video-rate ptychography that overcomes this barrier by exploiting spatiotemporal correlations through neural field representations. Our approach factorizes the space-time volume into low-rank spatial and temporal features, transforming SBP scaling from sequential measurements to efficient correlation extraction. The architecture employs dual networks for decoding real and imaginary field components, avoiding phase-wrapping discontinuities plagued in amplitude-phase representations. A gradient-domain loss on spatial derivatives ensures robust convergence. We demonstrate video-rate gigapixel imaging with centimeter-scale coverage while resolving 308-nm linewidths. Validations span from monitoring sample dynamics of crystals, bacteria, stem cells, microneedle to characterizing time-varying probes in extreme ultraviolet experiments, demonstrating versatility across wavelengths. By transforming temporal variations from a constraint into exploitable correlations, we establish that gigapixel video is tractable with single-sensor measurements, making ptychography a high-throughput sensing tool for monitoring mesoscale dynamics without lenses.
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