Mitra Ekata, Guo Ruipeng, Nelson Soren, Nagarajan Naveen, Menon Rajesh
Department of Electrical & Computer Engineering, University of Utah, Salt Lake City, UT 84112, USA.
Department of Computer Science, Boston University, Boston, MA 02215, USA.
Opt Contin. 2022 Sep 15;1(9):2091-2099. doi: 10.1364/optcon.469219.
A solid-glass cannula serves as a micro-endoscope that can deliver excitation light deep inside tissue while also collecting emitted fluorescence. Then, we utilize deep neural networks to reconstruct images from the collected intensity distributions. By using a commercially available dual-cannula probe, and training a separate deep neural network for each cannula, we effectively double the field of view compared to prior work. We demonstrated ex vivo imaging of fluorescent beads and brain slices and in vivo imaging from whole brains. We clearly resolved 4 μm beads, with FOV from each cannula of 0.2 mm (diameter), and produced images from a depth of ~1.2 mm in the whole brain, currently limited primarily by the labeling. Since no scanning is required, fast widefield fluorescence imaging limited primarily by the brightness of the fluorophores, collection efficiency of our system, and the frame rate of the camera becomes possible.
实心玻璃插管用作微型内窥镜，它可以将激发光传输到组织深处，同时收集发射的荧光。然后，我们利用深度神经网络从收集到的强度分布重建图像。通过使用市售的双插管探头，并为每个插管训练单独的深度神经网络，与之前的工作相比，我们有效地将视野扩大了一倍。我们展示了荧光珠和脑切片的离体成像以及全脑的活体成像。我们清晰地分辨出了4μm的珠子，每个插管的视野为0.2mm（直径），并在全脑中从约1.2mm的深度生成了图像，目前主要受标记限制。由于无需扫描，主要受荧光团亮度、我们系统的收集效率和相机帧率限制的快速宽场荧光成像成为可能。
