Smart Computational Light Microscopes (SCLMs) of Smart Computational Imaging Laboratory (SCILab)

Abstract

Computational microscopy, as a subfield of computational imaging, combines optical manipulation and image algorithmic reconstruction to recover multi-dimensional microscopic images or information of micro-objects. In recent years, the revolution in light-emitting diodes (LEDs), low-cost consumer image sensors, modern digital computers, and smartphones provide fertile opportunities for the rapid development of computational microscopy. Consequently, diverse forms of computational microscopy have been invented, including digital holographic microscopy (DHM), transport of intensity equation (TIE), differential phase contrast (DPC) microscopy, lens-free on-chip holography, and Fourier ptychographic microscopy (FPM). These computational microscopy techniques not only provide high-resolution, label-free, quantitative phase imaging capability but also decipher new and advanced biomedical research and industrial applications. Nevertheless, most computational microscopy techniques are still at an early stage of "proof of concept" or "proof of prototype" (based on commercially available microscope platforms). Translating those concepts to stand-alone optical instruments for practical use is an essential step for the promotion and adoption of computational microscopy by the wider bio-medicine, industry, and education community. In this paper, we present four smart computational light microscopes (SCLMs) developed by our laboratory, i.e., smart computational imaging laboratory (SCILab) of Nanjing University of Science and Technology (NJUST), China. These microscopes are empowered by advanced computational microscopy techniques, including digital holography, TIE, DPC, lensless holography, and FPM, which not only enables multi-modal contrast-enhanced observations for unstained specimens, but also can recover their three-dimensional profiles quantitatively. We introduce their basic principles, hardware configurations, reconstruction algorithms, and software design, quantify their imaging performance, and illustrate their typical applications for cell analysis, medical diagnosis, and microlens characterization.

Automatic correction method of optical microscope displacement stage based on Hough transform

“…The new concept of "computational optics" endows optical microscopes with powerful performance, provides specialized observation tools for diverse biological applications, and leads optical microscopes into a new era of intelligence, automation, and digitalization. 1,2 As a subfield of computational imaging, 3,4 computational optical microscopy extracts multi-dimensional microscopic sample images and information that cannot be observed by the naked eye through modulation methods (such as illumination control and aperture control) and post-processing algorithms. [5][6][7][8][9][10][11][12] The system's strict registration, precise correction and high-precision image processing algorithms are the basis for ensuring its subsequent imaging capabilities.…”

Single-shot iterative twin image removal method in partially coherent illumination in-line digital holography

“…Thanks to its large field of view, high throughput, low cost, and portability, lensless on-chip microscopy offers a promising solution for telemedicine and point-of-care diagnostics in resource-limited environments [1] . The development of lensless on-chip microscopy originated from Gabor's digital in-line holographic system [2] , where the interference between the scattered object wave and the unscattered reference wave forms a hologram (intensity map).…”