GPU-accelerated image registration algorithm in ophthalmic optical coherence tomography

Haiyi Bian; Jingtao Wang; Chengjian Hong; Lei Liu; Rendong Ji; Suqun Cao; Ahmed N Abdalla; Xinjian Chen

doi:10.1364/BOE.479343

GPU-accelerated image registration algorithm in ophthalmic optical coherence tomography

Biomed Opt Express. 2022 Dec 15;14(1):194-207. doi: 10.1364/BOE.479343. eCollection 2023 Jan 1.

Authors

Haiyi Bian¹, Jingtao Wang², Chengjian Hong², Lei Liu¹, Rendong Ji¹, Suqun Cao¹, Ahmed N Abdalla¹, Xinjian Chen^{1

2

3}

Affiliations

¹ Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai'an, Jiangsu, 223003, China.
² School of Electronic and Information Engineering, Soochow University, 215006, Suzhou, China.
³ State Key Laboratory of Radiation Medicine and Protection, Soochow University, 215123, Suzhou, China.

Abstract

Limited to the power of the light source in ophthalmic optical coherence tomography (OCT), the signal-to-noise ratio (SNR) of the reconstructed images is usually lower than OCT used in other fields. As a result, improvement of the SNR is required. The traditional method is averaging several images at the same lateral position. However, the image registration average costs too much time, which limits its real-time imaging application. In response to this problem, graphics processing unit (GPU)-side kernel functions are applied to accelerate the reconstruction of the OCT signals in this paper. The SNR of the images reconstructed from different numbers of A-scans and B-scans were compared. The results demonstrated that: 1) There is no need to realize the axial registration with every A-scan. The number of the A-scans used to realize axial registration is suitable to set as ∼25, when the A-line speed was set as ∼12.5kHz. 2) On the basis of ensuring the quality of the reconstructed images, the GPU can achieve 43× speedup compared with CPU.