Nonmechanical parfocal and autofocus features based on wave propagation distribution in lensfree holographic microscopy

Agus Budi Dharmawan,Shinta Mariana,Andreas Waag,Gregor Scholz,Ingo Rustenbeck,Torben Schulze,Mayra Garcés-Schröder,Karsten Hiller,Hutomo Suryo Wasisto,Kuwat Triyana,Philipp Hörmann

doi:10.1038/s41598-021-81098-7

Abstract

Performing long-term cell observations is a non-trivial task for conventional optical microscopy, since it is usually not compatible with environments of an incubator and its temperature and humidity requirements. Lensless holographic microscopy, being entirely based on semiconductor chips without lenses and without any moving parts, has proven to be a very interesting alternative to conventional microscopy. Here, we report on the integration of a computational parfocal feature, which operates based on wave propagation distribution analysis, to perform a fast autofocusing process. This unique non-mechanical focusing approach was implemented to keep the imaged object staying in-focus during continuous long-term and real-time recordings. A light-emitting diode (LED) combined with pinhole setup was used to realize a point light source, leading to a resolution down to 2.76 μm. Our approach delivers not only in-focus sharp images of dynamic cells, but also three-dimensional (3D) information on their (x, y, z)-positions. System reliability tests were conducted inside a sealed incubator to monitor cultures of three different biological living cells (i.e., MIN6, neuroblastoma (SH-SY5Y), and Prorocentrum minimum). Altogether, this autofocusing framework enables new opportunities for highly integrated microscopic imaging and dynamic tracking of moving objects in harsh environments with large sample areas.

Highlights

Performing long-term cell observations is a non-trivial task for conventional optical microscopy, since it is usually not compatible with environments of an incubator and its temperature and humidity requirements
Different designs and approaches of lensless digital holographic microscopes have been reported to be used in a wide range of biomedical and environmental monitoring a pplications[14,17], they have not employed statistical approaches for analyzing the wave propagation distributions
We explored the usage of various light sources and statistical approaches to find the optimum image quality and obtain a faster processing speed of the information from the raw hologram images

Summary

Introduction

Performing long-term cell observations is a non-trivial task for conventional optical microscopy, since it is usually not compatible with environments of an incubator and its temperature and humidity requirements. System reliability tests were conducted inside a sealed incubator to monitor cultures of three different biological living cells (i.e., MIN6, neuroblastoma (SH-SY5Y), and Prorocentrum minimum) This autofocusing framework enables new opportunities for highly integrated microscopic imaging and dynamic tracking of moving objects in harsh environments with large sample areas. It can be customized to be used with standard sample slides, petri dishes or specific microfluidics, making this lensfree imaging system advantageous over conventional table-top optical microscopes[11,12], especially in terms of simultaneous parallel investigation and usage in harsh environment settings (i.e., incubators with high temperature and humidity) It creates a compact setup with a short sample-to-sensor distance and an sharp reconstructed image at all positions across a large field-of-view[13]. Attaching a pinhole structure on the LED is suitable method to yield an ideal light source for lensless holographic imaging

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