Model-based iterative reconstruction for spectral-domain optical coherence tomography
Model-based iterative reconstruction for spectral-domain optical coherence tomography
复制标题
基于模型的谱域光学相干断层扫描迭代重建
DOI：
10.1117/12.2509424
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Bagnaninchi P
中科院分区：
文献类型：
--
作者：
Bagnaninchi P
光谱域光学相干层析成像(OCT)提供了高分辨率的多维成像，但通常会受到散焦、强度衰减和散粒噪声的影响，导致沿成像深度的伪影和图像退化。在这项工作中，我们发展了一种迭代统计重建技术，基于带有加性噪声的干涉合成孔径显微镜(ISAM)模型，以主动补偿这些影响。对于ISAM重采样，我们使用了带Kaiser-Bessel内插的非均匀FFT，提供了高效率和高精度。然后，我们使用基于加速梯度下降的算法来最小化模型的负对数似然，并包括基于空间或小波稀疏性的惩罚函数，以便为给定的图像结构提供适当的正则化。我们使用商用光谱域OCT系统，在不同的亚采样条件下，使用氧化钛微珠和黄瓜样本对我们的方法进行了评估，并显示出比传统的重建和ISAM方法更好的图像质量。
Spectral domain optical coherence tomography (OCT) offers high resolution multidimensional imaging, but generally suffers from defocussing, intensity falloff and shot noise, causing artifacts and image degradation along the imaging depth. In this work, we develop an iterative statistical reconstruction technique, based upon the interferometric synthetic aperture microscopy (ISAM) model with additive noise, to actively compensate for these effects. For the ISAM re-sampling, we use a non uniform FFT with Kaiser-Bessel interpolation, offering efficiency and high accuracy. We then employ an accelerated gradient descent based algorithm, to minimize the negative log-likelihood of the model, and include spatial or wavelet sparsity based penalty functions, to provide appropriate regularization for given image structures. We evaluate our approach with titanium oxide micro-bead and cucumber samples with a commercial spectral domain OCT system, under various subsampling regimes, and demonstrate superior image quality over traditional reconstruction and ISAM methods.
影响因子：
2.1
作者：
Beck, Amir;Teboulle, Marc
通讯作者：
Teboulle, Marc