Three-Dimensional Virtual Optical Clearing With Cycle-Consistent Generative Adversarial Network

High-throughput deep tissue imaging and chemical tissue clearing protocols have brought out great promotion in biological research. However, due to uneven transparency introduced by tissue anisotropy in imperfectly cleared tissues, fluorescence imaging based on direct chemical tissue clearing still encounters great challenges, such as image blurring, low contrast, artifacts and so on. Here we reported a three-dimensional virtual optical clearing method based on unsupervised cycle-consistent generative adversarial network, termed 3D-VoCycleGAN, to digitally improve image quality and tissue transparency of biological samples. We demonstrated the good image deblurring and denoising capability of our method on imperfectly cleared mouse brain and kidney tissues. With 3D-VoCycleGAN prediction, the signal-to-background ratio (SBR) of images in imperfectly cleared brain tissue areas also showed above 40% improvement. Compared to other deconvolution methods, our method could evidently eliminate the tissue opaqueness and restore the image quality of the larger 3D images deep inside the imperfect cleared biological tissues with higher efficiency. And after virtually cleared, the transparency and clearing depth of mouse kidney tissues were increased by up to 30%. To our knowledge, it is the first interdisciplinary application of the CycleGAN deep learning model in the 3D fluorescence imaging and tissue clearing fields, promoting the development of high-throughput volumetric fluorescence imaging and deep learning techniques

Directional Tykhonov well-posedness for optimization problems and variational inequalities

By using the so-called minimal time function, we propose and study a novel notion of directional Tykhonov well-posedness for optimization problems, which is an extension of the widely acknowledged notion of Tykhonov. In this way, we first provide some characterizations of this notion in terms of the diameter of level sets and admissible functions. Then, we investigate relationships between the level sets and admissible functions mentioned above. Finally, we apply the technology developed before to study directional Tykhonov well-posedness for variational inequalities. Several examples are presented as well to illustrate the applicability of our results.Comment: 2

Angular Gating and Biological Scattering in Optical Microscopy

Ph.DDOCTOR OF PHILOSOPH

Determinant representations for scalar products of the XXZ Gaudin model with general boundary terms

We obtain the determinant representations of the scalar products for the XXZ Gaudin model with generic non-diagonal boundary terms.Comment: Latex file, 17 page