Hybrid iterating-averaging low photon budget Gabor holographic microscopy

TL;DR

This paper introduces a novel iterative Gabor averaging algorithm for low photon budget digital in-line holographic microscopy, significantly improving image reconstruction quality in high-noise conditions for live cell and dynamic biological sample imaging.

Contribution

The study presents an innovative IGA algorithm tailored for multi-frame DIHM under low photon conditions, outperforming traditional methods in accuracy and enabling high-speed, low-impact biological imaging.

Findings

IGA outperforms traditional algorithms in simulated high-noise data

Experimental validation shows successful imaging of sperm cells at low illumination

Effective reconstruction of optically thin samples with low SNR holograms

Abstract

One of the primary challenges in live cell culture observation is achieving high-contrast imaging with minimal impact on sample behavior. Quantitative phase imaging (QPI) techniques address this by providing label-free, high-contrast images of transparent samples. Measurement system influence may be further reduced by imaging samples under low illumination intensity (low photon budget - LPB), thereby minimizing photostimulation, phototoxicity, and photodamage, and enabling high-speed imaging. LPB imaging is challenging in QPI due to significant camera shot noise and quantification noise. Digital in-line holographic microscopy (DIHM), working with or without lenses, is a QPI technique known for its robustness to quantification noise. However, reducing simultaneously the camera shot noise and the inherent in-line holographic twin image disturbances remain a critical, yet unaddressed, challenge. This study introduces an innovative iterative Gabor averaging (IGA) algorithm designed specifically for filling this important scientific gap in multi-frame DIHM under LPB conditions. We evaluated the performance of the IGA on simulated data showing that it outperformed traditional algorithms in terms of reconstruction accuracy under high noise conditions. Those results were corroborated by experimental validation involving high-speed imaging of dynamic sperm cells and a phase test target under significantly reduced illumination power. Additionally, the IGA algorithm proved successful in reconstructing optically thin samples, which typically produce low signal-to-noise ratio holograms even under high photon budget conditions. These advancements facilitate photostimulation-free and high-speed imaging of dynamic biological samples and enhance the capability to image samples with extremely low optical thickness, potentially transforming various applications in biomedical and environmental imaging.