Journey from Image Acquisition to Biological Insight: Handling and Analyzing Large Volumes of Light-Sheet Imaging Data.

Abstract

Recent advancements in imaging technologies have enabled the acquisition of high-quality, voluminous, multidimensional image data. Among these, light-sheet microscopy stands out for its ability to capture dynamic biological processes over extended periods and across large volumes, owing to its exceptional three-dimensional resolution and minimal invasiveness. However, handling and analyzing these vast datasets present significant challenges. Current computing environments struggle with the high storage and computational demands, while traditional analysis methods relying heavily on human intervention are proving inadequate. Consequently, there is a growing shift towards automated solutions using artificial intelligence, encompassing machine learning and other approaches. Although these technologies show promise, their application in extensive light-sheet imaging data analysis remains limited. This review explores the potential of light-sheet microscopy to revolutionize the life sciences through advanced imaging, addresses the primary challenges in data handling and analysis, and discusses potential solutions, including the integration of artificial intelligence and machine learning technologies.