AI 中文总结
本文提出特征域傅里叶叠层断层成像（FD-FPT），通过特征提取结合自动微分优化，实现了千兆体素级无标记体积成像，可解析常规方法无法识别的精细结构，兼具毫米级覆盖与细胞级对比度。
AI 中文摘要
傅里叶叠层断层成像（FPT）是强度衍射断层成像的一种实现方式，可从多角度强度测量数据中重建三维折射率（RI）分布。FPT结合暗场照明后，其优势凸显：可将空间带宽乘积扩展至千兆体素级的体积成像，但暗场测量对系统缺陷高度敏感，且信噪比通常较低。本文提出特征域FPT（FD-FPT），该方法在特征提取后评估数据保真度，并通过自动微分进行优化。数值与实验测试显示，FD-FPT相比空间域基线方法（SD-FPT），能更可靠地解析合成孔径截止附近的结构。在完整的鞘藻（Oedogonium）标本中，仅FD-FPT可解析网状叶绿体网络与横向隔膜。我们进一步展示了对小鼠肾上腺切片的1.81千兆体素RI重建，该样本视场为1.66×1.40平方毫米，证实FD-FPT是实现无标记体积成像的实用途径，兼具毫米级覆盖范围与细胞级结构对比度。
英文摘要
Fourier ptychographic tomography (FPT) is an implementation of intensity diffraction tomography that reconstructs three-dimensional (3D) refractive-index (RI) distributions from angle-varied intensity measurements. The distinctive advantage of FPT emerges when incorporating dark-field illumination, which extends the space-bandwidth product toward gigavoxel-scale volumetric imaging, yet dark-field measurements are highly sensitive to system imperfections and often have low signal-to-noise ratios. Here, we propose feature-domain FPT (FD-FPT), which evaluates data fidelity after feature extraction and is optimized using automatic differentiation. In numerical and experimental tests, FD-FPT resolves structures near the synthetic-aperture cutoff far more reliably than the spatial-domain baseline (SD-FPT). Notably, in a whole-mount Oedogonium specimen, the reticulate chloroplast network and transverse septa were resolved only by FD-FPT. We further demonstrate a 1.81-gigavoxel RI reconstruction of a mouse adrenal gland section across a 1.66 by 1.40 square millimeter field of view, establishing FD-FPT as a practical route to label-free volumetric imaging that combines millimeter-scale coverage with cellular-scale structural contrast.
