Université Grenoble Alpes, CNRS, LIPhy, 38000 Grenoble, France.
Université Grenoble Alpes, CEA, Leti, 38000 Grenoble, France.
Proc Natl Acad Sci U S A. 2023 Jun 27;120(26):e2221407120. doi: 10.1073/pnas.2221407120. Epub 2023 Jun 21.
Speckle-correlation imaging techniques are widely used for noninvasive imaging through complex scattering media. While light propagation through multimode fibers and scattering media share many analogies, reconstructing images through multimode fibers from speckle correlations remains an unsolved challenge. Here, we exploit a kaleidoscopic memory effect emerging in square-core multimode fibers and demonstrate fluorescence imaging with no prior knowledge on the fiber. Experimentally, our approach simply requires to translate random speckle patterns at the input of a square-core fiber and to measure the resulting fluorescence intensity with a bucket detector. The image of the fluorescent object is then reconstructed from the autocorrelation of the measured signal by solving an inverse problem. This strategy does not require the knowledge of the fragile deterministic relation between input and output fields, which makes it promising for the development of flexible minimally invasive endoscopes.
散斑相关成像技术广泛应用于通过复杂散射介质进行非侵入式成像。虽然光在多模光纤中的传播与散射介质有许多相似之处，但从散斑相关中通过多模光纤重建图像仍然是一个尚未解决的挑战。在这里，我们利用方芯多模光纤中出现的万花筒记忆效应，展示了无需事先了解光纤即可进行荧光成像。在实验中，我们的方法只需将随机散斑图案在方芯光纤的输入端平移，并使用桶探测器测量得到的荧光强度。然后通过求解逆问题，从测量信号的自相关来重建荧光物体的图像。这种策略不需要了解输入和输出场之间脆弱的确定性关系，这使得它有望用于开发灵活的微创内窥镜。
