GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer

The image reconstruction for Fourier-domain optical coherence tomography (FD-OCT) could be achieved by iterative methods, which offer a more accurate estimation than the traditional inverse discrete Fourier transform (IDFT) reconstruction. However, the existing iterative methods are mostly A-line-ba...

Full description

Saved in:
Bibliographic Details
Main Authors: Wang, Mengyuan, Ling, Yuye, Dong, Zhenxing, Yao, Xinwen, Gan, Yu, Zhou, Chuanqing, Su, Yikai
Other Authors: School of Chemistry, Chemical Engineering and Biotechnology
Format: Article
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/171470
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-171470
record_format dspace
spelling sg-ntu-dr.10356-1714702023-10-27T15:31:47Z GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer Wang, Mengyuan Ling, Yuye Dong, Zhenxing Yao, Xinwen Gan, Yu Zhou, Chuanqing Su, Yikai School of Chemistry, Chemical Engineering and Biotechnology Engineering::Electrical and electronic engineering Optical-coherence Tomography Ultrahigh-resolution The image reconstruction for Fourier-domain optical coherence tomography (FD-OCT) could be achieved by iterative methods, which offer a more accurate estimation than the traditional inverse discrete Fourier transform (IDFT) reconstruction. However, the existing iterative methods are mostly A-line-based and are developed on CPU, which causes slow reconstruction. Besides, A-line-based reconstruction makes the iterative methods incompatible with most existing image-level image processing techniques. In this paper, we proposed an iterative method that enables B-scan-based OCT image reconstruction, which has three major advantages: (1) Large-scale parallelism of the OCT dataset is achieved by using GPU acceleration. (2) A novel image-level cross-domain regularizer was developed, such that the image processing could be performed simultaneously during the image reconstruction; an enhanced image could be directly generated from the OCT interferogram. (3) The scalability of the proposed method was demonstrated for 3D OCT image reconstruction. Compared with the state-of-the-art (SOTA) iterative approaches, the proposed method achieves higher image quality with reduced computational time by orders of magnitude. To further show the image enhancement ability, a comparison was conducted between the proposed method and the conventional workflow, in which an IDFT reconstructed OCT image is later processed by a total variation-regularized denoising algorithm. The proposed method can achieve a better performance evaluated by metrics such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), while the speed is improved by more than 30 times. Real-time image reconstruction at more than 20 B-scans per second was realized with a frame size of 4096 (axial) × 1000 (lateral), which showcases the great potential of the proposed method in real-world applications. Published version This work was funded by National Natural Science Foundation of China (61905141, 61875123); Open Research Fund Program of the State Key Laboratory of Low-Dimensional Quantum Physics (KF202107). 2023-10-26T01:00:59Z 2023-10-26T01:00:59Z 2023 Journal Article Wang, M., Ling, Y., Dong, Z., Yao, X., Gan, Y., Zhou, C. & Su, Y. (2023). GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer. Optics Express, 31(2), 1813-1831. https://dx.doi.org/10.1364/OE.478970 1094-4087 https://hdl.handle.net/10356/171470 10.1364/OE.478970 36785208 2-s2.0-85146086148 2 31 1813 1831 en Optics Express © 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Optical-coherence Tomography
Ultrahigh-resolution
spellingShingle Engineering::Electrical and electronic engineering
Optical-coherence Tomography
Ultrahigh-resolution
Wang, Mengyuan
Ling, Yuye
Dong, Zhenxing
Yao, Xinwen
Gan, Yu
Zhou, Chuanqing
Su, Yikai
GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer
description The image reconstruction for Fourier-domain optical coherence tomography (FD-OCT) could be achieved by iterative methods, which offer a more accurate estimation than the traditional inverse discrete Fourier transform (IDFT) reconstruction. However, the existing iterative methods are mostly A-line-based and are developed on CPU, which causes slow reconstruction. Besides, A-line-based reconstruction makes the iterative methods incompatible with most existing image-level image processing techniques. In this paper, we proposed an iterative method that enables B-scan-based OCT image reconstruction, which has three major advantages: (1) Large-scale parallelism of the OCT dataset is achieved by using GPU acceleration. (2) A novel image-level cross-domain regularizer was developed, such that the image processing could be performed simultaneously during the image reconstruction; an enhanced image could be directly generated from the OCT interferogram. (3) The scalability of the proposed method was demonstrated for 3D OCT image reconstruction. Compared with the state-of-the-art (SOTA) iterative approaches, the proposed method achieves higher image quality with reduced computational time by orders of magnitude. To further show the image enhancement ability, a comparison was conducted between the proposed method and the conventional workflow, in which an IDFT reconstructed OCT image is later processed by a total variation-regularized denoising algorithm. The proposed method can achieve a better performance evaluated by metrics such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), while the speed is improved by more than 30 times. Real-time image reconstruction at more than 20 B-scans per second was realized with a frame size of 4096 (axial) × 1000 (lateral), which showcases the great potential of the proposed method in real-world applications.
author2 School of Chemistry, Chemical Engineering and Biotechnology
author_facet School of Chemistry, Chemical Engineering and Biotechnology
Wang, Mengyuan
Ling, Yuye
Dong, Zhenxing
Yao, Xinwen
Gan, Yu
Zhou, Chuanqing
Su, Yikai
format Article
author Wang, Mengyuan
Ling, Yuye
Dong, Zhenxing
Yao, Xinwen
Gan, Yu
Zhou, Chuanqing
Su, Yikai
author_sort Wang, Mengyuan
title GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer
title_short GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer
title_full GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer
title_fullStr GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer
title_full_unstemmed GPU-accelerated iterative method for FD-OCT image reconstruction with an image-level cross-domain regularizer
title_sort gpu-accelerated iterative method for fd-oct image reconstruction with an image-level cross-domain regularizer
publishDate 2023
url https://hdl.handle.net/10356/171470
_version_ 1781793792169345024