Real-time dispersion-compensated image reconstruction for compressive sensing spectral domain optical coherence tomography

The Development and Clinical Application of Innovative Optical Ophthalmic Imaging Techniques

The field of ophthalmic imaging has grown substantially over the last years. Massive improvements in image processing and computer hardware have allowed the emergence of multiple imaging techniques of the eye that can transform patient care. The purpose of this review is to describe the most recent advances in eye imaging and explain how new technologies and imaging methods can be utilized in a clinical setting. The introduction of optical coherence tomography (OCT) was a revolution in eye imaging and has since become the standard of care for a plethora of conditions. Its most recent iterations, OCT angiography, and visible light OCT, as well as imaging modalities, such as fluorescent lifetime imaging ophthalmoscopy, would allow a more thorough evaluation of patients and provide additional information on disease processes. Toward that goal, the application of adaptive optics (AO) and full-field scanning to a variety of eye imaging techniques has further allowed the histologic study of single cells in the retina and anterior segment. Toward the goal of remote eye care and more accessible eye imaging, methods such as handheld OCT devices and imaging through smartphones, have emerged. Finally, incorporating artificial intelligence (AI) in eye images has the potential to become a new milestone for eye imaging while also contributing in social aspects of eye care.

Brillouin optical time-domain analysis via compressed sensing

A compressed-sensing-technique-based Brillouin optical time-domain analysis is proposed. The Brillouin spectrum has a sparse representation in its discrete cosine transform domain, which can be successfully recovered from far fewer measurements with high probability through an orthogonal matching-pursuit algorithm. This work shows both empirically and experimentally that the amount of frequency acquisitions needed is only 30% of those required by a conventional distributed Brillouin fiber-optic sensing system with 1 MHz frequency increment in the acquisition process to obtain Brillouin spectra along an optical fiber; therefore, the number of acquisitions and the amount of data storage/transfer are greatly reduced. Moreover, the proposed method does not need any hardware modification in an existing sensing system and can also be adopted by Brillouin optical time-domain reflectometry.

Volumetric (3D) compressive sensing spectral domain optical coherence tomography

In this work, we proposed a novel three-dimensional compressive sensing (CS) approach for spectral domain optical coherence tomography (SD OCT) volumetric image acquisition and reconstruction. Instead of taking a spectral volume whose size is the same as that of the volumetric image, our method uses a sub set of the original spectral volume that is under-sampled in all three dimensions, which reduces the amount of spectral measurements to less than 20% of that required by the Shan-non/Nyquist theory. The 3D image is recovered from the under-sampled spectral data dimension-by-dimension using the proposed three-step CS reconstruction strategy. Experimental results show that our method can significantly reduce the sampling rate required for a volumetric SD OCT image while preserving the image quality.