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Shanmugavel, S. C.

Publications and source records attributed to Shanmugavel, S. C..

2 recordsLinked to original sources

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

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 x 1.7 cm2) with micron-level resolution across various biological tissue sections.

bioengineering↗

Chromatix: a differentiable, GPU-accelerated wave-optics library

Modern microscopy methods incorporate computational modeling as an integral part of the imaging process, either to solve inverse problems or optimize the optical system design itself. These methods often depend on differentiable optics simulations, yet no standardized framework exists--forcing computational optics researchers to repeatedly and independently implement simulations with limited reusability and performance. These common problems limit the potential impact of computational optics as a field. Here we present Chromatix: an open-source, GPU-accelerated, differentiable wave optics simulation library. Chromatix builds on JAX to democratize fast, parallelized simulation of diverse optical systems and expand the design space in computational optics. Chromatix standardizes a growing collection of optical elements and propagation methods allowing a broad range of applications, which we demonstrate here for snapshot microscopy, holography, and phase retrieval. We demonstrate speed improvements of 2-6x on a single GPU and up to 22x on 8 GPUs.

bioinformatics↗