High-quality SiNx films with controllable low stress and low optical loss are deposited at ultra-low temperature (75 °C) using inductively coupled plasma chemical vapor deposition (ICP-CVD). Two kinds of integrated photonic structures have been demonstrated that exemplify its viability as a photonic integration platform. A microcavity consists of two distributed Bragg reflectors (DBR) formed by alternating a total of 49 layers of SiNx and SiO2 with a total thickness of about 11.5 μm is grown without any cracks, confirming the excellent stress control in the process. Microring resonators are also fabricated in as-deposited planar SiNx waveguide layer using electron-beam lithography (EBL) and plasma etching. Average waveguide loss of 0.79 ± 0.22 dB/cm has been achieved in the range of 1550-1600 nm for ring radii larger than 40 μm. The ultra-low temperature grown SiNx with properties of low loss and low stress is therefore a promising photonic integration platform for various photonic integration applications.
BackgroundPrecise identification, discrimination and assessment of central nervous system (CNS) tumors is of critical importance to brain neoplasm treatment. Due to the complexity and limited resolutions of the existing diagnostic tools, however, it is difficult to identify the tumors and their boundaries precisely in clinical practice, and thus, the conventional way of brain neoplasm treatment relies mainly on the experiences of neurosurgeons to make resection decisions in the surgery process. The purpose of this study is to explore the potential of Micro-optical coherence tomography (μOCT) as an intraoperative diagnostic imaging tool for identifying and discriminating glioma and meningioma with their microstructure imaging ex vivo, which thus may help neurosurgeons to perform precise surgery with low costs and reduced burdens.MethodsFresh glioma and meningioma samples were resected from patients, and then slices of such samples were excised and imaged instantly ex vivo with a lab-built μOCT, which achieves a spatial resolution of ~ 2.0 μm (μm). The acquired optical coherence tomography (OCT) images were pathologically evaluated and compared to their corresponding histology for both tumor type and tumor grade discriminations in different cases.ResultsBy using the lab-built μOCT, both the cross-sectional and en face images of glioma and meningioma were acquired ex vivo. Based upon the morphology results, both the glioma and meningioma types as well as the glioma grades were assessed and discriminated. Comparisons between OCT imaging results and histology showed that typical tissue microstructures of glioma and meningioma could be clearly identified and confirmed the type and grade discriminations with satisfactory accuracy.ConclusionsμOCT could provide high-resolution three-dimensional (3D) imaging of the glioma and meningioma tissue microstructures rapidly ex vivo. μOCT imaging results could help discriminate both tumor types and grades, which illustrates the potential of μOCT as an intraoperative diagnostic imaging tool to help neurosurgeons perform their surgery precisely in tumor treatment process.
Optical coherence tomography (OCT) is a noninvasive high-resolution diagnostic imaging modality that plays an increasingly important role in dermatology. Diagnosis of skin diseases using OCT requires both cellular-level high resolution and large area skin coverage. In practice, however, there exists a trade-off between the achievable spatial resolutions and the transverse scanning range. In this study, we report a Micro-OCT (µOCT) system that is capable of providing three-dimensional (3D) images of the skin at multiple spatial scales with both cellular-level resolution (1 ∼ 2 µm) mode and large area (∼ 20 × 20 mm 2 ) scanning mode. Specifically, in the cellular-level scanning mode, we achieve a transverse resolution of ∼ 1.5 µm and an axial resolution of 1.7 µm (n = 1.38) which enables the visualization of cellular-level skin microstructures. While in the large-area scanning mode, the system is capable of covering an en face imaging area reaching up to 20mm × 20 mm with a lateral resolution of ∼ 5.5 µm at a scanning speed of 60K Alines/s. We experimentally verify the imaging capabilities of such a multiscale µOCT system including in vivo visualization of epidermal cells in the cellular-level scanning mode as well as the internal fingerprints and sweat gland ducts in the large area scanning mode. Micro-anatomical imaging at multiple spatial scales could provide comprehensive information of the skin that is valuable to disease diagnosis.
As a crucial power amplifying component for electro-hydraulic servo valves, servo-valve spool valve largely determines the overall performances of an electro-hydraulic servo system. Due to the machining errors during servo-valve manufacturing process, however, there may exist certain nonlinearity between the flow rate and valve spool displacement caused by the overlap between the valve spool and valve sleeve. To accurately characterize the relationship between the flow rate and spool displacement to facilitate servo-valve production, an indirect flow measurement-based servo-valve spool valve grinding (FM-SVG) scheme is proposed in this study. Specifically, a valve spool overlap measurement mechanism is presented first based on the valve spool grinding principle, and then a data processing method is devised to eliminate the errors introduced by the fluctuations of differential pressure at the valve ports. Meanwhile, a closed-loop control system is also devised to maintain a constant differential pressure at the servo-valve ports. Finally, the FM-SVG scheme is embedded onto a lab-customized electro-hydraulic servo valve platform, and experiments are conducted to verify the feasibility and effectiveness of the FM-SVG scheme. Results show that, by utilizing the devised control scheme to maintain a differential pressure around 2.00MP, the proposed grinding scheme helps achieve a grinding accuracy of 2.0 μm. With only grinding process needed, such a grinding scheme helps improve both grinding accuracy and production efficiency in practice.
.PurposeOptical coherence tomography (OCT) is a noninvasive, high-resolution imaging modality capable of providing both cross-sectional and three-dimensional images of tissue microstructures. Owing to its low-coherence interferometry nature, however, OCT inevitably suffers from speckles, which diminish image quality and mitigate the precise disease diagnoses, and therefore, despeckling mechanisms are highly desired to alleviate the influences of speckles on OCT images.ApproachWe propose a multiscale denoising generative adversarial network (MDGAN) for speckle reductions in OCT images. A cascade multiscale module is adopted as MDGAN basic block first to raise the network learning capability and take advantage of the multiscale context, and then a spatial attention mechanism is proposed to refine the denoised images. For enormous feature learning in OCT images, a deep back-projection layer is finally introduced to alternatively upscale and downscale the features map of MDGAN.ResultsExperiments with two different OCT image datasets are conducted to verify the effectiveness of the proposed MDGAN scheme. Results compared those of the state-of-the-art existing methods show that MDGAN is able to improve both peak-single-to-noise ratio and signal-to-noise ratio by 3 dB at most, with its structural similarity index measurement and contrast-to-noise ratio being 1.4% and 1.3% lower than those of the best existing methods.ConclusionsResults demonstrate that MDGAN is effective and robust for OCT image speckle reductions and outperforms the best state-of-the-art denoising methods in different cases. It could help alleviate the influence of speckles in OCT images and improve OCT imaging-based diagnosis.
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