Significance: Full-field optical coherence tomography (FF-OCT) enables en face views of scattering samples at a given depth with subcellular resolution, similar to biopsy without the need of sample slicing or other complex preparation. This noninvasive, high-resolution, three-dimensional (3D) imaging method has the potential to become a powerful tool in biomedical research, clinical applications, and other microscopic detection.
Aim: Our review provides an overview of the disruptive innovations and key technologies to further improve FF-OCT performance, promoting FF-OCT technology in biomedical and other application scenarios.
Approach: A comprehensive review of state-of-the-art accomplishments in OCT has been performed. Methods to improve performance of FF-OCT systems are reviewed, including advanced phase-shift approaches for imaging speed improvement, methods of denoising, artifact reduction, and aberration correction for imaging quality optimization, innovations for imaging flux expansion (field-of-view enlargement and imaging-depth-limit extension), new implementations for multimodality systems, and deep learning enhanced FF-OCT for information mining, etc. Finally, we summarize the application status and prospects of FF-OCT in the fields of biomedicine, materials science, security, and identification.
Results: The most worth-expecting FF-OCT innovations include combining the technique of spatial modulation of optical field and computational optical imaging technology to obtain greater penetration depth, as well as exploiting endogenous contrast for functional imaging, e.g., dynamic FF-OCT, which enables noninvasive visualization of tissue dynamic properties or intracellular motility. Different dynamic imaging algorithms are compared using the same OCT data of the colorectal cancer organoid, which helps to understand the disadvantages and advantages of each. In addition, deep learning enhanced FF-OCT provides more valuable characteristic information, which is of great significance for auxiliary diagnosis and organoid detection.
Conclusions: FF-OCT has not been completely exploited and has substantial growth potential. By elaborating the key technologies, performance optimization methods, and application status of FF-OCT, we expect to accelerate the development of FF-OCT in both academic and industry fields. This renewed perspective on FF-OCT may also serve as a road map for future development of invasive 3D super-resolution imaging techniques to solve the problems of microscopic visualization detection.
Keywords: deep-learning enhanced FF-OCT; dynamic imaging; full-field optical coherence tomography; histological diagnosis.