Fast acquisition of depth information is crucial for accurate 3D tracking of moving objects. Snapshot depth sensing can be achieved by wavefront coding, in which the point-spread function (PSF) is engineered to vary distinctively with scene depth by altering the detection optics. In low-light applications, such as 3D localization microscopy, the prevailing approach is to condense signal photons into a single imaging channel with phase-only wavefront modulation to achieve a high pixel-wise signal to noise ratio. Here we show that this paradigm is generally suboptimal and can be significantly improved upon by employing multi-channel wavefront coding, even in low-light applications. We demonstrate our multi-channel optimization scheme on 3D localization microscopy in densely labelled live cells where detectability is limited by overlap of modulated PSFs. At extreme densities, we show that a split-signal system, with end-to-end learned phase masks, doubles the detection rate and reaches improved precision compared to the current state-of-the-art, single-channel design. We implement our method using a bifurcated optical system, experimentally validating our approach by snapshot volumetric imaging and 3D tracking of fluorescently labelled subcellular elements in dense environments.

中文翻译：

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学习多通道成像的最佳波前整形


快速获取深度信息对于运动物体的精确 3D 跟踪至关重要。快照深度感测可以通过波前编码来实现，其中点扩散函数（PSF）被设计为通过改变检测光学器件来随场景深度而明显变化。在 3D 定位显微镜等低光应用中，普遍的方法是将信号光子压缩到具有纯相位波前调制的单个成像通道中，以实现高像素级信噪比。在这里，我们表明，这种范例通常不是最理想的，即使在低光应用中，也可以通过采用多通道波前编码来显着改进。我们在密集标记的活细胞中展示了我们在 3D 定位显微镜上的多通道优化方案，其中可检测性受到调制 PSF 重叠的限制。在极端密度下，我们表明，与当前最先进的单通道设计相比，具有端到端学习相位掩模的分离信号系统使检测率加倍，并达到更高的精度。我们使用分叉光学系统实施我们的方法，通过快照体积成像和密集环境中荧光标记的亚细胞元素的 3D 跟踪来实验验证我们的方法。