Lingyun Wang

Lingyun Wang

PhD student at the University of Pittsburgh BioE & UPMC, interested in advanced Optical Coherence Tomography

Publications

Sub2Full: split spectrum to boost optical coherence tomography despeckling without clean data

Published in Optics Letters, 2024

Optical coherence tomography (OCT) suffers from speckle noise, causing the deterioration of image quality, especially in high-resolution modalities such as visible light OCT (vis-OCT). Here, we proposed an innovative self-supervised strategy called Sub2Full (S2F) for OCT despeckling without clean data. This approach works by acquiring two repeated B-scans, splitting the spectrum of the first repeat as a low-resolution input, and utilizing the full spectrum of the second repeat as the high-resolution target. The proposed method was validated on vis-OCT retinal images visualizing sublaminar structures in the outer retina and demonstrated superior performance over state-of-the-art Noise2Noise (N2N) and Noise2Void (N2V) schemes.

Recommended citation: Wang, L., Sahel, J., Pi, S., Sub2Full: split spectrum to boost optical coherence tomography despeckling without clean data. Optics Letters. 2024. https://doi.org/10.1364/OL.518906

Axial super-resolution optical coherence tomography via complex-valued network

Published in Physics in Medicine & Biology, 2023

Objectives. 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. This study is aimed to achieve axial super-resolution OCT imaging with complex-valued deep learning technique. Approach. A complex-valued super-resolution network (CVSR-Net) was designed to fully utilize the amplitude and phase of OCT signal to reconstruct an OCT image with an improved axial resolution. Main results. 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. Significance. The good performance of the CVSR-Net in both axial super-resolution and generalization indicate that this method has a good potential to reduce OCT system cost by utilizing narrow-band light source while retaining the axial resolution.

Recommended citation: Wang, L., Si, C., Liu, L., Yin, X., Shi, G., Mo, J., Axial super-resolution optical coherence tomography via complex-valued network. Physics in Medicine & Biology. 2023. https://doi.org/10.1088/1361-6560/ad0997

Optical coherence tomography for in vivo longitudinal monitoring of artificial dermal scaffold

Published in Lasers in Surgery and Medicine, 2023

Objectives. Artificial dermal scaffold (ADS) has undergone rapid development and been increasingly used for treating skin wound in clinics due to its good biocompatibility, controllable degradation, and low risk of disease infection. To obtain a good treatment efficacy, ADS needs to be monitored longitudinally during the treatment process. For example, scaffold-tissue fit, cell in-growth, vascular regeneration and scaffold degradation are the key properties to be inspected. However, to date, there are no effective, real-time and noninvasive techniques to meet the requirement of the scaffold monitoring above. Materials and Methods. 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 semi-automatic image segmentation algorithm was designed based on U-Net to segment the collagen sponge layer of the scaffold from OCT images. Results. The results show that the scaffold-tissue fit can be clearly visualized under OCT imaging. The IRDR can be computed based on the volume of the segmented collagen sponge layer. It is observed that the IRDR appeared to a linear function of the time and in addition the IRDR varied among different skin parts. Conclusion. Overall, it can be concluded that OCT has a good potential to monitor ADS in vivo. This can help guide the clinicians to control the treatment with ADS to improve the therapy.

Recommended citation: Chen, Z., Cheng, Q., Wang, L., Mo, Y., Li, K., Mo, J., Optical coherence tomography for in vivo longitudinal monitoring of artificial dermal scaffold. Lasers Surg Med. 2023; 1– 11. https://doi.org/10.1002/lsm.23645

Compressive‐sensing swept‐source optical coherence tomography angiography with reduced noise

Published in Journal of Biophotonics, 2022

Optical coherence tomography angiography (OCTA), as a functional extension of optical coherence tomography (OCT), has exhibited a great potential to aid in clinical diagnostics. Currently, OCTA still suffers from motion artifact and noise. Therefore, in this article, we propose to implement compressive sensing (CS) on B-scans to reduce motion artifact by increasing B-scan rate. Meanwhile, a noise reduction filter is specially designed by combining CS, Gaussian filter and median filter. Specially, CS filtering is realized by averaging multiple CS repetitions on en-face OCTA images with varied sampling functions. The method is evaluated on in vivo OCTA images of human skin. 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 the developed filter. This implies that our method has a good potential to expedite OCTA imaging and improve the image quality.

Recommended citation: Wang, L., Chen, Z., Zhu, Z., Yu, X., Mo, J., Compressive-sensing swept-source optical coherence tomography angiography with reduced noise. J. Biophotonics 2022, 15(8), e202200087. https://doi.org/10.1002/jbio.202200087