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用于厘米级相位成像的具有空间变化角度校准的无掩膜片上LED阵列显微镜。

Maskless and on-chip LED-array microscope with spatially-varying angle calibration for centimeter-scale phase imaging.

作者信息

Shanmugavel Sibi Chakravarthy, Senanayake Vindya, Suh Donghwa, Gross Jeffrey M, Chowdhury Shwetadwip

出版信息

bioRxiv. 2025 Sep 10:2025.09.05.674268. doi: 10.1101/2025.09.05.674268.

Abstract

On-chip imaging with LED-array-based angled illumination offers a cost-effective approach for large field-of-view (FOV) phase imaging. However, it faces two main challenges: (1) twin-image ambiguity can degrade phase reconstruction. While mask-based modulation can help, it adds system complexity due to fabrication and alignment requirements; and (2) the illumination angle from each LED varies across large FOVs, and can degrade centimeter-scale phase reconstruction without calibration. Here, we present a computational framework to jointly achieve mask-free on-chip phase imaging and adaptive calibration of spatially-varying illumination angles. The sensor FOV is divided into subregions within each of which LED illumination is approximated as planar. LED illumination angles for each subregion are initialized geometrically. Phase retrieval is then performed within each subregion by constraining the reconstruction with a soft optical transparency prior while simultaneously refining angle estimates. Reconstructed phase maps are merged to produce a high-quality, large-FOV phase image. We demonstrate this approach by achieving centimeter-scale on-chip phase imaging (up to 2.7 × 1.7 cm ) with micron-level resolution across various biological tissue sections.

摘要

基于LED阵列倾斜照明的片上成像为大视场(FOV)相位成像提供了一种经济高效的方法。然而,它面临两个主要挑战:(1)双像模糊会降低相位重建质量。虽然基于掩模的调制可以有所帮助,但由于制造和对准要求,它会增加系统复杂性;(2)每个LED的照明角度在大视场内会发生变化,并且在没有校准的情况下会降低厘米级的相位重建质量。在此,我们提出了一个计算框架,以共同实现无掩模的片上相位成像和空间变化照明角度的自适应校准。传感器视场被划分为多个子区域,在每个子区域内,LED照明近似为平面。每个子区域的LED照明角度通过几何方法初始化。然后在每个子区域内通过在软光学透明度先验约束下进行重建,同时细化角度估计来执行相位检索。将重建的相位图合并以生成高质量的大视场相位图像。我们通过在各种生物组织切片上实现厘米级的片上相位成像(最大2.7×1.7厘米)以及微米级分辨率来证明这种方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45d8/12439904/1e6322e74663/nihpp-2025.09.05.674268v1-f0001.jpg

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