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自适应光学技术和高分辨率视网膜成像
自适应光学 (AO) 是一种利用波前传感器测量观测目标和光学仪器内部的波前像差，并对其进行动态校正，从而直接提高成像质量的技术。此校正通常采用直接改变光路长度的可变形反射镜。然而，为了以更高的精度校正像差，我们正在研究一种使用相位调制器 (LCOS-SLM) 的技术，它能够通过改变液晶材料的折射率，以在局部精细地移动光波的相位。自适应光学技术目前主要应用于眼底成像领域，它可以获得人类视网膜的高分辨率图像，因此非常有望早期诊断眼部疾病。
通过将使用 LCOS-SLM 的自适应光学技术应用于视网膜观察，能够以几微米的空间分辨率测量视网膜（从而看到感光细胞）。图 1 给出了自适应光学视网膜成像系统的概览。人眼被非常弱但充分满足激光安全标准的光照射，从视网膜散射的光通过 LCOS-SLM 返回到波前传感器。波前传感器由微透镜阵列和高灵敏度视觉相机组成。该波前传感器可测量由眼睛光学和成像设备引起的波前畸变。负反馈控制器根据波前传感器测量的波前畸变控制 LCOS-SLM 的输入信号，使输出波前变成平面波（或具有所需曲率的球形波）。
图 1：自适应光学的波前校正原理
结果
图 2 给出了展示像差校正效果的人类视网膜图像示例。无像差校正时，仅获得模糊和带噪声的图像（左：无 AO 校正）。这不会为观测提供有用的信息。但是，当激活像差校正后，感光细胞（亮点）变得可解析（右：有 AO 校正）。人眼中最小的感光细胞只有 2 μm 至 3 μm；结果表明，自适应光学对于观察感光细胞至关重要。
图 2：结果
已知视网膜具有多层结构。通过使用 LCOS-SLM 控制焦点位置，可以将视网膜每一层的组织可视化。图 3 给出了通过控制感光细胞、血管和神经纤维层的焦点深度位置获得的视网膜图像示例。左图给出了感光细胞的分布，其中亮点是感光细胞。根据感光细胞图像，可以分析分布密度、细胞排列、是否存在缺陷等指标来检测视网膜异常。中间的血管和血细胞图像显示了分叉的血管，以及血管壁（黑线）和血管中的血细胞（两条黑线之间的明亮区域）。血流还可以通过视频录像来测量。在右侧的神经纤维图像中，可以看到神经纤维束从左上角延伸到右下角。通过对观察到的高分辨率眼底图像进行分析，有望推动先进医疗技术的发展。
图 3：聚焦于不同深度位置时的成像结果。
通过控制 LCOS-SLM 调整焦点来进行观察
出版物
- H. Huang, T. Inoue and H. Tanaka, “Stabilized high-accuracy correlation of ocular aberrations with liquid crystal on silicon spatial light modulator in adaptive optics retinal imaging system,” Optics Express 19(16), 15026-15040 (2011).
- H. Huang, T. Inoue, H. Toyota, and H. Tsutomu, “Long-term stable and high performance adaptive optics system using liquid crystal on silicon spatial light modulator for high resolution retinal imaging,” Proc. SPIE, 8200, 820002(2011).
- H. Huang, et. al., “Adaptive optics scanning laser ophthalmoscope using liquid crystal on silicon spatial light modulator: Performance study with involuntary eye movement,” Japanese Journal of Applied Physics, 56(9S), 09NB02(2017).
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