Journal, Sub2Full: split spectrum to boost optical coherence tomography despeckling without clean data, JCR Q2
The paper- Sub2Full: split spectrum to boost optical coherence tomography despeckling without clean data was published in Optics Letters. 
Abstract, 2024 ARVO Imaging in the Eye, Seattle, US
Abstract Selected for Oral Presentation at 2024 ARVO Imaging in the Eye Conference!
Presentation Title: Reveal retinal ultra-structure with self-supervised denoising in vis-OCT
Presentation Number: PP009
Session Title: Artificial Intelligence & Hemodynamics
Session Date/Time: May 4, 2024 from 10:15 AM to 12:00 PM
Extramural Services, 2024 CVIPPR, Xiamen, China
Participation as a technical committee member in the 2024 CVIPPR Conference.
Grant, Axial super-resolution optical coherence tomography imaging by complex-valued enhanced deep residual network, San Francisco, CA, US
I received Travel Grant for SPIE Photonics West 2024 for my conference paper “Axial super-resolution optical coherence tomography imaging by complex-valued enhanced deep residual network” from SPIE and MKS Instruments, Inc. Thanks for their kind support!
Research Article, Axial super-resolution optical coherence tomography via complex-valued network, JCR Q2
Optical coherence tomography (OCT) is a fast and non-invasive optical interferometric imaging technique that can provide high-resolution cross-sectional images of biological tissues. OCT’s key strength is its depth resolving capability which remains invariant along the imaging depth and is determined by the axial resolution. The axial resolution is inversely proportional to the bandwidth of the OCT light source. Thus, the use of broadband light sources can effectively improve the axial resolution and however leads to an increased cost. In recent years, real-valued deep learning technique has been introduced to obtain super-resolution optical imaging. In this study, we proposed a complex-valued super-resolution network (CVSR-Net) to achieve an axial super-resolution for OCT by fully utilizing the amplitude and phase of OCT signal. The method was evaluated on three OCT datasets. The results show that the CVSR-Net outperforms its real-valued counterpart with a better depth resolving capability. Furthermore, comparisons were made between our network, six prevailing real-valued networks and their complex-valued counterparts. The results demonstrate that the complex-valued network exhibited a better super-resolution performance than its real-valued counterpart and our proposed CVSR-Net achieved the best performance. In addition, the CVSR-Net was tested on out-of-distribution domain datasets and its super-resolution performance was well maintained as compared to that on source domain datasets, indicating a good generalization capability.
Conference, Axial super-resolution optical coherence tomography imaging by complex-valued enhanced deep residual network, SPIE Conference
The high resolution of optical coherence tomography (OCT) allows for imaging micro-structure features in tissues. Broad-band light source is typically used to improve the axial resolution of OCT but leads to an increased cost. Many real-valued networks were employed to achieve OCT super-resolution. However, they ignore the phase which contains structural information. Therefore, we proposed a complex-valued enhanced deep super-resolution network (Cv-EDSR) based on EDSR to achieve axial super-resolution. The Cv-EDSR and EDSR were evaluated on two datasets. The results show that the SR images generated by the Cv-EDSR have more realistic structures and better image metrics.
CN Patent, OCT axial super-resolution method and system based on complex-valued neural network, CN116563116A
The Patent ‘OCT axial super-resolution method and system based on complex-valued neural network’ is granted by China National Intellectual Property Administration (CNIPA).
Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh
I received the PhD offer and will pursue my doctoral study in Bioengineering at UPitt. 
Research Article, Optical coherence tomography for in vivo longitudinal monitoring of artificial dermal scaffold, Lasers in Surgery and Medicine, JCR Q2
In this study, we propose to use optical coherence tomography (OCT) to monitor ADS in vivo through three‐dimensional imaging. A swept source OCT system with a handheld probe was developed for in vivo skin imaging. Moreover, a cell in‐growth, vascular regeneration, and scaffold degradation rate (IRDR) was defined with the volume reduction rate of the scaffold’s collagen sponge layer. To measure the IRDR, a semiautomatic image segmentation algorithm was designed based on U‐Net to segment the collagen sponge layer of the scaffold from OCT images.
Research Article, Compressive‐sensing swept‐source optical coherence tomography angiography with reduced noise, Journal of Biophotonics, JCR Q2
A method based on compressive sensing (CS) is proposed for reducing the acquisition time and noise of optical coherence tomography angiography (OCTA). It is aimed at making up for the disadvantages of OCTA including motion-induced artifact and noise. The results show that vasculature structures can be reconstructed well through CS on B-scans with a sampling rate of 70%. Moreover, the noise can be significantly eliminated by CGM filter.