Extended imaging depth of en-face optical coherence tomography based on fast measurement of a reflection matrix by wide-field heterodyne detection

Methods and applications of full-field optical coherence tomography: a review

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.

Enhance the delivery of light energy ultra-deep into turbid medium by controlling multiple scattering photons to travel in open channels

Multiple light scattering is considered as the major limitation for deep imaging and focusing in turbid media. In this paper, we present an innovative method to overcome this limitation and enhance the delivery of light energy ultra-deep into turbid media with significant improvement in focusing. Our method is based on a wide-field reflection matrix optical coherence tomography (RM-OCT). The time-reversal decomposition of the RM is calibrated with the Tikhonov regularization parameter in order to get more accurate reversal results deep inside the scattering sample. We propose a concept named model energy matrix, which provides a direct mapping of light energy distribution inside the scattering sample. To the best of our knowledge, it is the first time that a method to measure and quantify the distribution of beam intensity inside a scattering sample is demonstrated. By employing the inversion of RM to find the matched wavefront and shaping with a phase-only spatial light modulator, we succeeded in both focusing a beam deep (~9.6 times of scattering mean free path, SMFP) inside the sample and increasing the delivery of light energy by an order of magnitude at an ultra-deep (~14.4 SMFP) position. This technique provides a powerful tool to understand the propagation of photon in a scattering medium and opens a new way to focus light inside biological tissues.

Optimized number of the primary singular values for image reconstruction in reflection matrix based optical coherence tomography

A reflection matrix based optical coherence tomography (OCT) is recently proposed and expected to extend the imaging-depth limit twice. However, the imaging depth and hence the image quality heavily depend on the number of primary singular values considered for image reconstruction. To this regard, we propose a method based on correlation between image pairs reconstructed from different number of singular values and corresponding remainders. The obtained correlation curve and another feature curve fetched from the former are then fed to a long short-term memory (LSTM) network classifier to identify the optimized number of primary singular values for image reconstruction. Simulated targets with different combinations of filling fraction and signal-to-noise ratio (SNR) are reconstructed by the developed method as well as two current adopted methods for comparison. The results demonstrate that the proposed method is robust to recover the image with satisfactory similarity close to the reference one. To our knowledge, this is the first comprehensive study on the optimized number of the primary singular values considered for image reconstruction in reflection matrix based OCT.