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We have developed a multi-scale OCM imaging system at a 1.7-μm regime enabling multi-scale imaging of the ex vivo oral precancerous tissue. The light source had a sweep rate of 90 kHz. Objectives with three different magnifications are mounted to a power turret, enabling seamless change of the OCT imaging resolution via the software control with up to 5.3 μm transverse resolution. Most importantly, we demonstrated the ability of our custom-developed volumetric mosaic stitching and processing algorithm applicable for aforementioned multi-scale OCM datasets in an fully automatic fashion without requiring manual adjustment of individual parameters.

 

In this study, we have developed a catheter-based OCT system with a polarization diversity detection apparatus allowing volumetric imaging of the cervix, including the endocervical canal. The rotary junction and catheter are custom-designed to tailor the aforementioned biomedical applications. Preliminary imaging results of the human fingertip and palm skin were shown to validate the imaging capability of the developed imaging system. In order to suppress the polarization artifact present in the volumetric OCT images, a custom-designed polarization diversity detection apparatus was designed and implemented to assure the optimum detection of OCT signals on the circumference as well.

 

Recently, the functional extension of optical coherence tomography (OCT) with the OCT angiography (OCTA) technique provides volumetric imaging of the subsurface microvasculature of the imaging tissue without requiring exogenous contrast agents. In this study, we have developed a small-footprint imaging platform with the MEMS scanning technologies, allowing volumetric imaging of the mouse brain microvasculature at different physiological states, including anesthesia, waking, and movement. In addition, in order to better examine the changes of microvasculature among different aforementioned states, we have employed three different OCTA algorithms, including decorrelation (DM-OCTA), speckle variance (SV-OCTA), and complex differential variation (CDV-OCTA).

 

In vivo cellular imaging has been highly desired for research use and practical diagnosis. Ultrahigh resolution optical coherence tomography (UHR-OCT), generally refers to 1–2 μm or even higher spatial resolution in tissue, has been considered a critical role on in vivo cellular or subcellular level imaging. In this study, we have developed an UHR-OCT system with a mode-locked laser pumped supercontinuum laser (ML-SCL), achieving ~1.8 μm on both axial and lateral resolution in biological tissues. This system is then implemented on mouse cornea and human skin imaging, demonstrating its feasibility of in vivo studies and clinical applications.



 

Neural canal opening (NCO) points are important landmarks of the retinal pigment epithelium (RPE) layer in the optic nerve head (ONH) region. How to identify the NCO points is a challenging issue by means of conventional image processing. In this study, we proposed a deep learning-based scenario for two purposes: one is to check the existence of NCO points as the binary classification task, and the other is to find the NCO location as the detection task. Proposed algorithm was validated to yield more stable NCO points detection under a series of testing OCT images.