arXiv subjects

Neng Xia

Publications and source records attributed to Neng Xia.

3 recordsLinked to original sources

arXiv2023

Liquid-shaped microlens for scalable production of ultrahigh-resolution OCT microendoscope

Endoscopic optical coherence tomography (OCT) is a valuable tool for providing diagnostic images of internal organs and guiding interventions in real time. Miniaturized OCT endoscopes are essential for imaging small and convoluted luminal organs while minimizing invasiveness. However, current methods for fabricating miniature fiber probes have limited ability to correct optical aberrations, leading to suboptimal imaging performance. In this study, we introduce a new paradigm of liquid shaping technique for the rapid and scalable fabrication of ultrathin and high-performance OCT microendoscopes suitable for minimally invasive clinical applications. This technique enables the flexible customization of freeform microlenses with sub-nanometer optical surface roughness by regulating the minimum energy state of curable optical liquid on a wettability-modified substrate and precisely controlling the liquid volume and physical boundary on a substrate. Using this technique, we simultaneously fabricated 800-nm OCT microendoscopes with a diameter of approximately 0.6 mm and evaluated their ultrahigh-resolution imaging performance in the esophagus of rats and the aorta and brain of mice.

physics.ins-det↗

arXiv2022

Swimming of the midge larva: principles and tricks of locomotion at intermediate Reynolds number

At the millimeter scale and in the intermediate Reynolds number (Re) regime, the midge and mosquito larvae can reach swimming speeds of more than one body length per cycle performing a "figure-of-8" gait, in which their elongated bodies periodically bend nearly into circles and then fully unfold. To elucidate the propulsion mechanism of this cycle of motion, we conducted a 3D numerical study which investigates the hydrodynamics of undergoing the prescribed kinematics. Novel propulsion mechanisms, such as modulating the body deformation rate to dynamically increase the maximum net propulsion force, using asymmetric kinematics to generate torque and the appropriate rotation, and controlling the radius of the curled body to manipulate the moment of inertia. The figure-of-8 gait is found to achieve propulsion at a wide range of Re, but is most effective at intermediate Re. The results were further validated experimentally, via the development of a soft millimeter-sized robot that can reach comparable speeds using the figure-of-8 gait.

physics.flu-dyn↗

arXiv2021

AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy

Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment outcome. Nowadays, the evaluation is performed in a manual manner, which is time-consuming, subjective, and error-prone. In this paper, we aim to automate this process by leveraging the advances in computer vision and artificial intelligence, to provide an objective and accurate method for root canal therapy result assessment. A novel anatomy-guided multi-branch Transformer (AGMB-Transformer) network is proposed, which first extracts a set of anatomy features and then uses them to guide a multi-branch Transformer network for evaluation. Specifically, we design a polynomial curve fitting segmentation strategy with the help of landmark detection to extract the anatomy features. Moreover, a branch fusion module and a multi-branch structure including our progressive Transformer and Group Multi-Head Self-Attention (GMHSA) are designed to focus on both global and local features for an accurate diagnosis. To facilitate the research, we have collected a large-scale root canal therapy evaluation dataset with 245 root canal therapy X-ray images, and the experiment results show that our AGMB-Transformer can improve the diagnosis accuracy from 57.96% to 90.20% compared with the baseline network. The proposed AGMB-Transformer can achieve a highly accurate evaluation of root canal therapy. To our best knowledge, our work is the first to perform automatic root canal therapy evaluation and has important clinical value to reduce the workload of endodontists.

cs.CV↗