Near infrared‐II light‐sheet microscopy: Basic principle, intellectualization, and medical application

Abstract Fluorescence microscopy has emerged as a pivotal tool in biological and medical research, wherein the assessment of penetration depth and imaging resolution serves as crucial indicators of a microscope's efficacy. However, the intricate interaction between photons and biological tissues gives rise to substantial background noise, presenting a formidable challenge. Fortunately, the near‐infrared window (NIR), particularly the NIR‐II range (1000–1700 nm), has emerged as a viable solution to mitigate these challenges and attain optimal imaging outcomes. This review centers on the progressive developments in light‐sheet microscopy techniques, elucidating their distinctive characteristics and applications in the field of biological imaging. Furthermore, the incorporation of optical design enhancements, encompassing light‐sheet microscopy is discussed as a pivotal strategy to augment imaging quality. The discussion extends to include refinements in imaging precision and the integration of deep learning methodologies with NIR imaging, especially for unique applications in NIR clinical exploration. The ensuing discourse endeavors to furnish a comprehensive synthesis of advancements in fluorescence microscopy, emphasizing the significance of the NIR windows, while also elucidating the role of sophisticated optical design and machine learning methodologies in enhancing overall imaging capabilities.