McLean James P, Hendon Christine P
Department of Electrical Engineering, Columbia University, New York, NY 10027, USA.
Biomed Opt Express. 2021 Mar 31;12(4):2531-2549. doi: 10.1364/BOE.421848. eCollection 2021 Apr 1.
We present a compressed sensing (CS) algorithm and sampling strategy for reconstructing 3-D Optical Coherence Tomography (OCT) image volumes from as little as 10% of the original data. Reconstruction using the proposed method, Denoising Predictive Coding (DN-PC), is demonstrated for five clinically relevant tissue types including human heart, retina, uterus, breast, and bovine ligament. DN-PC reconstructs the difference between adjacent b-scans in a volume and iteratively applies Gaussian filtering to improve image sparsity. An a-line sampling strategy was developed that can be easily implemented in existing Spectral-Domain OCT systems and reduce scan time by up to 90%.
我们提出了一种压缩感知（CS）算法和采样策略，用于从仅10%的原始数据重建三维光学相干断层扫描（OCT）图像体积。使用所提出的去噪预测编码（DN-PC）方法进行重建，已在包括人类心脏、视网膜、子宫、乳房和牛韧带在内的五种临床相关组织类型中得到验证。DN-PC重建体积中相邻b扫描之间的差异，并迭代应用高斯滤波以提高图像稀疏性。开发了一种a线采样策略，该策略可以在现有的谱域OCT系统中轻松实现，并将扫描时间减少多达90%。
