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加博尔光学相干断层扫描血管造影(GOCTA)(第一部分):人体视网膜成像

Gabor optical coherence tomographic angiography (GOCTA) (Part I): human retinal imaging .

作者信息

Chen Chaoliang, Yang Victor X D

机构信息

Biophotonics and Bioengineering Lab, Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada.

Division of Neurosurgery, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.

出版信息

Biomed Opt Express. 2017 Nov 20;8(12):5724-5734. doi: 10.1364/BOE.8.005724. eCollection 2017 Dec 1.

Abstract

Recently, parallel high A-line speed and wide field imaging for optical coherence tomography angiography (OCTA) has become more prevalent, resulting in a dramatic increase of data quantity which poses a challenge for real time imaging even for GPU in data processing. In this manuscript, we propose a new OCTA processing technique, Gabor optical coherence tomographic angiography (GOCTA), for label-free human retinal angiography imaging. In spectral domain optical coherence tomography (SDOCT), k-space resampling and Fourier transform (FFT) are required for the entire data set of interference fringes to calculate blood flow information in previous OCTA algorithms, which are computationally intensive. As adults' eye anterior-posterior radii are nearly constant, only 3 A-scan lines need to be processed to obtain the gross orientation of the retina by using a sphere model. Subsequently, the microvascular images can be obtained by using the GOCTA algorithm from interference fringes directly without the steps of k-space resampling, numerical dispersion compensation, FFT, and maximum (mean) projection, resulting in a significant improvement of the data processing speed by 4 to 20 times faster than the existing methods. GOCTA is potentially suitable for SDOCT systems in preview applications requiring real-time microvascular imaging.

摘要

最近,用于光学相干断层扫描血管造影(OCTA)的并行高A线速度和宽视野成像变得更加普遍,导致数据量急剧增加,这对即使是GPU进行数据处理的实时成像也构成了挑战。在本论文中,我们提出了一种新的OCTA处理技术,即加博尔光学相干断层扫描血管造影(GOCTA),用于无标记的人体视网膜血管造影成像。在光谱域光学相干断层扫描(SDOCT)中,先前的OCTA算法需要对整个干涉条纹数据集进行k空间重采样和傅里叶变换(FFT)来计算血流信息,这在计算上是密集的。由于成年人眼睛的前后半径几乎是恒定的,通过使用球体模型,只需要处理3条A扫描线就可以获得视网膜的大致方向。随后,通过GOCTA算法可以直接从干涉条纹中获得微血管图像,而无需进行k空间重采样、数值色散补偿、FFT和最大(平均)投影等步骤,从而使数据处理速度比现有方法显著提高4到20倍。GOCTA可能适用于需要实时微血管成像的SDOCT系统的预览应用。

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