Abstract

Histopathology, while suffering from morbidity, cost and time associated with biopsy, plays a key role in detection and monitoring of disease. Optical technologies, with the capability to non-invasively image the cellular structures in real time, have the potential to revolutionize medicine. Gabor-domain optical coherence microscopy (GDOCM) is a noninvasive, high-definition, three-dimensional imaging technique leveraging concepts of low-coherence interferometry, liquid lens technology, confocal microscopy, high-speed imaging, and precision scanning. By operating at a high numerical aperture to improve transverse resolution and recovering the resulting loss in depth of focus by acquiring multiple volumes dynamically refocusing inside the sample with no moving parts, GDOCM breaks the cellular resolution limit of optical coherence tomography (OCT) and achieves isotropic 2 μm resolution in 3D. GDOCM enables optical biopsy capabilities that span both medical and industrial applications. In the past decade, GDOCM has been demonstrated for cellular imaging in 3D in a number of clinical applications, including dermatology, oncology and ophthalmology, as well as to characterize materials in industrial applications. The structural imaging capability of GDOCM has been enhanced by adding functional modalities and by incorporating machine learning techniques. In particular, convolutional neural networks were applied to automatically segment the endothelial cells in human cornea for quantitative, unbiased assessment of corneal health. A novel algorithm for optical coherence tomography angiography (OCTA), an attractive diagnostic tool for non-invasive, label-free vascular imaging in vivo, was demonstrated in conjunction with GDOCM to extract high-resolution cutaneous vasculature, significantly improving the visualization and characterization of micro-capillaries in vivo.

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