Resolution-enhanced parallel coded ptychography for high-throughput optical imaging

TL;DR

This paper introduces a high-throughput, resolution-enhanced parallel coded ptychography technique that significantly improves optical imaging resolution and speed, enabling detailed 3D phase imaging and applications like digital pathology.

Contribution

The authors develop a novel parallel coded ptychography platform with engineered surfaces and a new diffraction model, achieving higher resolution and throughput than previous methods.

Findings

Achieves 308-nm resolution without aperture synthesis.

Captures gigapixel images in 15 seconds over a large field of view.

Successfully reconstructs complex 3D phase objects and performs virtual staining.

Abstract

Ptychography is an enabling coherent diffraction imaging technique for both fundamental and applied sciences. Its applications in optical microscopy, however, fall short for its low imaging throughput and limited resolution. Here, we report a resolution-enhanced parallel coded ptychography technique achieving the highest numerical aperture and an imaging throughput orders of magnitude greater than previous demonstrations. In this platform, we translate the samples across the disorder-engineered surfaces for lensless diffraction data acquisition. The engineered surface consists of chemically etched micron-level phase scatters and printed sub-wavelength intensity absorbers. It is designed to unlock an optical space with spatial extent (x, y) and frequency content (kx, ky) that is inaccessible using conventional lens-based optics. To achieve the best resolution performance, we also report a new coherent diffraction imaging model by considering both the spatial and angular responses of the pixel readouts. Our low-cost prototype can directly resolve 308-nm linewidth on the resolution target without aperture synthesizing. Gigapixel high-resolution microscopic images with a 240-mm^2 effective field of view can be acquired in 15 seconds. For demonstrations, we recover slow-varying 3D phase objects with many 2{\pi} wraps, including optical prism and convex lens. The low-frequency phase contents of these objects are challenging to obtain using other existing lensless techniques. For digital pathology applications, we perform accurate virtual staining by using the recovered phase as attention guidance in a deep neural network. Parallel optical processing using the reported technique enables novel optical instruments with inherent quantitative nature and metrological versatility.