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

Affiliation/Institute
Institute of Semiconductor Technology (IHT), Technische Universität Braunschweig
Dharmawan, Agus Budi;
Affiliation/Institute
Institute of Semiconductor Technology (IHT), Technische Universität Braunschweig
Mariana, Shinta;
Affiliation/Institute
Institute of Semiconductor Technology (IHT), Technische Universität Braunschweig
Scholz, Gregor;
Affiliation/Institute
Institute for Biochemistry, Biotechnology and Bioinformatics, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig
Hörmann, Philipp;
Affiliation/Institute
Institute of Pharmacology, Toxicology and Clinical Pharmacy (IPT), Technische Universität Braunschweig
Schulze, Torben; Triyana, Kuwat;
Affiliation/Institute
Institute of Semiconductor Technology (IHT), Technische Universität Braunschweig
Garcés-Schröder, Mayra;
Affiliation/Institute
Institute of Pharmacology, Toxicology and Clinical Pharmacy (IPT), Technische Universität Braunschweig
Rustenbeck, Ingo;
Affiliation/Institute
Institute for Biochemistry, Biotechnology and Bioinformatics, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig
Hiller, Karsten;
Affiliation/Institute
Institute of Semiconductor Technology (IHT), Technische Universität Braunschweig
Wasisto, Hutomo Suryo;
Affiliation/Institute
Institute of Semiconductor Technology (IHT), Technische Universität Braunschweig
Waag, Andreas

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.

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