Optical Coherence Tomography (OCT) has been widely used in many clinical apartments. The trade-off between Field-of-View (FOV) and transverse resolution has always become critical. High-Resolution (HR) image reconstruction of OCT has the potential to increase the resolution without reducing the FOV. Although it has been widely explored in these years, it is hard to find one-to-one paired high-resolution for reference. The SR methods are used to improve the cross-sectional OCT image only. Therefore, we build a custom-design, wide field-of-view, multi-scale optical coherence tomography that can allow us to produce excellent high- and low-resolution one-to-one mapping volumetric data set. With the SR methods, we can reduce the acquisition of synthetic high-resolution volumetric images by up to four times.
Several optical technologies have been demonstrated as potential diagnostic tools for skin imaging, such as reflectance confocal microscopy (RCM) and optical coherence tomography (OCT). Although RCM could support cellular-level imaging, OCT could provide a larger field of view and a longer imaging depth than RCM. To quantitatively evaluate the skin condition with OCT, it is essential to develop an algorithm extracting different features, for example, the epidermis thickness and the optical characteristic of the epidermis. Although various segmentation algorithms have been proposed, most of the golden standards used involve the delineation of the boundary manually, where the labeling is highly relied on clinicians' experience and might vary among different physicians and the physician him or herself. Therefore, in this study, we collected skin OCT images of different sites from 20 subjects using a portable spectral-domain OCT system. The contrast of the OCT images can be effectively improved by optical attenuation coefficient (OAC) computation. This enables the development of a fully automatic segmentation algorithm, providing the parameters such as the (i) epidermis thickness and the (ii, iii) roughness of the boundary between the epidermis and air as well as the epidermis and dermis. Also, the (iv, v) OAC coefficients of the epidermis and upper dermis layer are available. Collectively, the developed algorithm supports the quantitative analysis of the five parameters across the imaging site with volumetric OCT imaging. We believe the developed algorithm can facilitate the implementation of skin OCT imaging for aesthetic medicine as a modality for objective pre- and post-treatment evaluation.
Recently, the functional extension of optical coherence tomography (OCT) with OCT angiography (OCTA) allows
volumetric imaging of the subsurface microvasculature without requiring exogenous contrast agents like conventional
angiography techniques. However, performing OCTA requires intensive computation to extract the changes of OCT
signal due to moving red blood cells in the microvascular network. In this study, we have developed a graphic processing
unit (GPU)-accelerated framework to realize high speed OCTA imaging and the visualization of the microvascular
network after the data acquisition. In addition, we investigate the feasibility of providing real-time microvascular imaging
leveraging dynamic scattering OCT and GPU.
Optical coherence tomography (OCT) is non-invasive biomedical imaging technique, which can provide volumetric imaging of the tissue architectural information. In this talk, I will briefly discuss the preliminary results of several ongoing works in my lab, including the quantitative analysis of the microvasculature with the animal model and investigation of the mouse cochlear anatomy.
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