Spatial light interference microscopy (SLIM): principle and applications to biomedicine

TL;DR

SLIM is a highly sensitive, label-free phase imaging technique built on phase-contrast microscopy, enabling detailed biomedicine applications from cell dynamics to clinical diagnostics, enhanced by AI integration.

Contribution

This paper reviews the principles, instrumentation, and diverse biomedical applications of SLIM, highlighting its integration with AI for advanced cell and clinical studies.

Findings

SLIM provides sub-nanometer phase measurement stability.

SLIM enables high-throughput, whole slide imaging with color cameras.

AI-enhanced SLIM offers new solutions in cell biology and pathology.

Abstract

In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-shifting interferometer, built onto a phase-contrast microscope, with white-light illumination. As one of the most sensitive quantitative phase imaging (QPI) methods, SLIM allows for speckle-free phase reconstruction with sub-nanometer path-length stability. We first review image formation in QPI, scattering, holography, and microcopy. Then, we outline SLIM imaging from theory to instrumentation. Zernike phase-contrast microscopy, phase retrieval in SLIM, and halo removal algorithms are discussed. Next, we discuss the requirements for operation, with a focus on software developed in-house for SLIM that high-throughput acquisition, whole slide scanning, mosaic tile registration, and imaging with a color camera. Lastly, we review the applications of SLIM in basic science and clinical studies. SLIM can study cell dynamics, cell growth and proliferation, cell migration, and mass transport, etc. In clinical settings, SLIM can assist with cancer studies, reproductive technology, and blood testing, etc. Finally, we review an emerging trend, where SLIM imaging in conjunction with artificial intelligence (AI) brings computational specificity and, in turn, offers new solutions to outstanding challenges in cell biology and pathology.