基于gpu高速并行计算实现逆信噪比‑复值退相关octa实时成像

Abstract

Objective Currently, most commercial optical coherence angiography (OCTA) systems lack a realtime display of en face OCTA images, which makes it difficult for operators to obtain intuitive feedback on data quality and adjust the system quickly and accurately in a single acquisition of OCTA volume data. In the process of dynamic acquisition of OCTA volume data, determining the state changes of the subjects is difficult, resulting in invalid data acquisition. In an experiment on flicker lightinduced functional retinal hyperemia, which provides a new perspective for the early screening of human diabetic retinopathy, the continuous collection of multiple groups of threedimensional data may be invalid because of the poor quality of one group, thereby wasting data processing time. Therefore, a realtime display of the experimental results is required. Although GPUbased OCTA data realtime processing methods have been proposed, the speed of the existing realtime processing methods still needs to be improved to adapt to highspeed 0907011 -11 封底文章•特邀论文 第 51 卷 第 9 期/2024 年 5 月/中国激光 scanning OCTA systems.Methods It is developed on a spectraldomain OCT (SD -OCT) system. Limited by the frame grabber, the maximum acquisition line speed of the system was 120 kHz in the highbitdepth mode and 250 kHz in the lowbitdepth mode. An optical coherence angiography algorithm based on the inverse signaltonoise ratio (SNR) and complexvalued decorrelation (ID -OCTA) was used to extract blood signals by adaptive SNR and achieve highquality angiography. The sum of absolute differences (SAD) algorithm was used to register OCT images, and the retinal OCT images were segmented by a vertical gradient distribution, which is convenient for fast parallel processing on a Graphics Processing Unit (GPU). This study proposes a realtime processing framework based on a GPU (Fig. 1), which uses texture memory to realize fast interpolation and filtering calculations and the CUDA stream to mask the time delay of data transmission between the host and GPU. We developed a realtime processing program using C++ and CUDA and a multithread system control program using the C++ and MFC libraries. To compare the guiding effect of the realtime data processing method in this study and the method using only a CPU, two realtime display modes were used for data acquisition: en face OCTA images and crosssectional OCT images. Moderately experienced operators collected multiple groups of data in these modes within 40 s. Three sets of data were collected continuously in 12 s to simulate the dynamic acquisition of OCTA volume data. The quality of the collected was evaluated using the en face OCTA image quality index. In the flicker lightinduced functional retinal hyperemia experiment in mice, the experimental success criteria and quantification parameters were set. Operators conducted multiple experiments to compare the experimental success rates of the two realtime display modes. Results and DiscussionsThe en face OCTA image realtime display was realized in the system with a 25...