从斜率复原波前是夏克-哈特曼波前传感器这一类斜率采样探测器的核心流程。传统的复原算法中，区域法对局部波前的复原效果好，但易受斜率噪声的影响，同时空间分辨率较低；模式法抗噪能力强，但没有精确复原局部波前的能力。本文提出了基于B样条函数的快速复原算法，将波前展开为B样条曲面的线性组合，并将复原问题从斜率最小二乘问题转化为泊松方程，利用斜率的Taylor展开式估计散度，再通过超松驰迭代法进行快速求解。该方法将B样条函数的理论散度积分和实际散度估计分离，可以方便地扩展到不同阶次和不同节点数量的B样条基复原算法中。另外，通过改变散度估计的计算区域，可以灵活控制并平衡算法的局部复原能力和抗噪能力。对变形镜驱动器响应函数的测量实验表明，该方法具有较好的局部复原能力、抗噪能力和任意精度的空间分辨率。

针对三种不同空间分辨率的双压电片变形镜(Bimorph DM)，采用仿真实验分析其对3~35 项Zernike 静态像差和实际人眼(包括疾病人眼)像差的拟合能力。实验表明，Bimorph 变形镜特别适用于校正低阶像差，拟合误差小于0.15，随着空间分辨率的增加，Bimorph 变形镜对Zernike 像差和人眼像差的拟合能力总体表现为增强的趋势，其中，35 单元的Bimorph 变形镜的像差拟合能力最优，对前20 项Zernike 像差的拟合误差稍优于传统分立式压电变形镜。通过对Bimorph 变形镜像差拟合能力的实验分析，为人眼视网膜高分辨率系统的Bimorph 变形镜选型提供了分析方法，也为进一步提升Bimorph 变形镜的像差校正能力奠定了研究基础。

According to the speckle feature in Optical coherence tomography (OCT), images with speckle indicate not only noise but also signals, an improved wavelet hierarchical threshold filter (IWHTF) method is proposed. At first, a modified hierarchical threshold-selected algorithm is used to prevent signals from being removed by assessing suitable thresholds for different noise levels. Then, an improved wavelet threshold function based on two traditional threshold functions is proposed to trade-off between speckle removing and sharpness degradation. The de-noising results of an OCT finger skin image shows that the IWHTF method obtains better objective evaluation metrics and visual image quality improvement. When α=0.2, β=5.0 and K=1.2, the improved method can achieve 9.58 dB improvement in signal-to-noise ratio, with sharpness degraded by 3.81%.

基于变形镜的激光束整形系统，具有控制灵活、适应性好、破坏阈值高等优点。为了提升变形镜作为相位调制元件的激光束整形系统性能，提出一种以最小二乘法拟合的驱动器控制电压为初始值的随机并行梯度下降算法优化驱动器控制电压的方法。通过驱动器正六边形排列的37 单元变形镜对不同大小的方形与圆形平顶激光束进行整形。数值仿真结果表明，在最小二乘法的基础上引入优化算法后，远场光强的目标区域均匀性及与理论光强的相似度均获得了改善，激光束整形系统性能得到提升。

A multi-GPU system designed for high-speed, real-time signal processing of optical coherence tomography (OCT) is described herein. For the OCT data sampled in linear wave numbers, the maximum processing rates reached 2.95 MHz for 1024-OCT and 1.96 MHz for 2048-OCT. Data sampled using linear wavelengths were re-sampled using a time-domain interpolation method and zero-padding interpolation method to improve image quality. The maximum processing rates for 1024-OCT reached 2.16MHz for the time-domain method and 1.26MHz for the zero-padding method. The maximum processing rates for 2048-OCT reached 1.58 MHz, and 0.68MHz, respectively. This method is capable of high-speed, real-time processing for OCT systems.

青光眼是全球第二位的致盲疾病。青光眼的发病机理尚未完全明确，但是房水循环受阻引起的高眼压被认为是主要成因。而作为我国发病率最高的青光眼类型,开角型青光眼的其房水循环阻力点一直未能明确。大量的前期动物和离体解剖实验表明，前房角施氏管的形态改变，可能是引起房水受阻的因素。为此，本课题组已研制了专门用于眼前节房角成像的扫频光源光学想干层析成像系统，成功地实现了正常被测者和开角型青光眼患者的施氏管成像，并顺利地开展了一系列的形态学测量与比对研究。回顾了课题组在该方向的研究过程，并对未来的研究进行展望。

Sensitivity and data processing speed are important in spectral domain Optical Coherence Tomography (SD-OCT) system. To get a higher sensitivity, zero-padding interpolation together with linear interpolation is commonly used to re-sample the interference data in SD-OCT, which limits the data processing speed. Recently, a time-domain interpolation for SD-OCT was proposed. By eliminating the huge Fast Fourier Transform Algorithm (FFT) operations, the operation number of the time-domain interpolation is much less than that of the zero-padding interpolation. In this paper, a numerical simulation is performed to evaluate the computational complexity and the interpolation accuracy. More than six times acceleration is obtained. At the same time, the normalized mean square error (NMSE) results show that the time-domain interpolation method with cut-off length L = 21 and L = 31 can improve about 1.7 dB and 2.1 dB when the distance mismatch is 2.4mm than that of zero-padding interpolation method with padding times M = 4, respectively. Furthermore, this method can be applied the parallel arithmetic processing because only the data in the cut-off window is processed. By using Graphics Processing Unit (GPU) with compute unified device architecture (CUDA) program model, a frame (400 A-lines × 2048 pixels × 12 bits) data can be processed in 6 ms and the processing capability can be achieved 164,000 line/s for 1024-OCT and 71,000 line/s for 2048-OCT when the cut-off length is 21. Thus, a high-sensitivity and ultra-high data processing SD-OCT is realized.

The signal processing speed of spectral domain optical coherence tomography (SD-OCT) has become a bottleneck in a lot of medical applications. Recently, a time-domain interpolation method was proposed. This method can get better signal-to-noise ratio (SNR) but much-reduced signal processing time in SD-OCT data processing as compared with the commonly used zeropadding interpolation method. Additionally, the resampled data can be obtained by a few data and coefficients in the cutoff window. Thus, a lot of interpolations can be performed simultaneously. So, this interpolation method is suitable for parallel computing. By using graphics processing unit (GPU) and the compute unified device architecture (CUDA) program model, time-domain interpolation can be accelerated significantly. The computing capability can be achieved more than 250,000 A-lines, 200,000 A-lines, and 160,000 A-lines in a second for 2,048 pixel OCT when the cutoff length is L = 11, L = 21, and L = 31, respectively. A frame SD-OCT data (400A-lines×2,048 pixel per line) is acquired and processed on GPU in real time. The results show that signal processing time of SD-OCT can be finished in 6.223 ms when the cutoff length L = 21, which is much faster than that on central processing unit (CPU). Real-time signal processing of acquired data can be realized.