Compressive SD-OCT: the application of compressed sensing in spectral domain optical coherence tomography.
Compressive SD-OCT: the application of compressed sensing in spectral domain optical coherence tomography.
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DOI：
10.1364/oe.18.022010
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发表时间：
2010-10-11
期刊：
影响因子：
3.8
通讯作者：
Kang JU
中科院分区：
文献类型：
--
作者：
Liu X;Kang JU
将压缩传感(CS)应用于光谱域光学相干层析成像(SD OCT)，并对其有效性进行了研究。我们通过对k空间SD OCT信号进行随机欠采样来测试CS重建。我们通过应用伪随机掩码对62.5%、50%和37.5%的CCD相机像素进行采样来实现这一点。通过求解一个优化问题来重建OCT图像，该优化问题最小化变换后图像的L 1范数，以在数据一致性约束下执行稀疏性。CS可以使像素较少的阵列探测器重建高分辨率OCT图像，同时减少处理图像所需的总数据量。
We applied compressed sensing (CS) to spectral domain optical coherence tomography (SD OCT) and studied its effectiveness. We tested the CS reconstruction by randomly undersampling the k-space SD OCT signal. We achieved this by applying pseudo-random masks to sample 62.5%, 50%, and 37.5% of the CCD camera pixels. OCT images are reconstructed by solving an optimization problem that minimizes the l 1 norm of a transformed image to enforce sparsity, subject to data consistency constraints. CS could allow an array detector with fewer pixels to reconstruct high resolution OCT images while reducing the total amount of data required to process the images.