Deep learning enhanced NIR-Ⅱ volumetric imaging of whole mice vasculature

Fluorescence imaging through the second near-infrared window(NIR-Ⅱ,1000–1700 nm) allows in-depth imaging.However, current imaging systems use wide-field illumination and can only provide low-contrast 2D information, without depth resolution. Here, we systematically apply a light-sheet illumination, a time-gated detection, and a deep-learning algorithm to yield high-contrast high-resolution volumetric images. To achieve a large Fo V(field of view) and minimize the scattering effect, we generate a light sheet as thin as 100.5 μm with a Rayleigh length of 8 mm to yield an axial resolution of 220 μm. To further suppress the background, we time-gate to only detect long lifetime luminescence achieving a high contrast of up to 0.45 Icontrast. To enhance the resolution, we develop an algorithm based on profile protrusions detection and a deep neural network and distinguish vasculature from a low-contrast area of 0.07 Icontrast to resolve the 100μm small vessels. The system can rapidly scan a volume of view of 75 × 55 × 20 mm3and collect 750 images within 6mins. By adding a scattering-based modality to acquire the 3D surface profile of the mice skin, we reveal the whole volumetric vasculature network with clear depth resolution within more than 1 mm from the skin. High-contrast large-scale 3D animal imaging helps us expand a new dimension in NIR-Ⅱ imaging.

Dynamical analysis,circuit realization,and application in pseudorandom number generators of a fractional-order laser chaotic system

A new five-dimensional fractional-order laser chaotic system(FOLCS)is constructed by incorporating complex variables and fractional calculus into a Lorentz-Haken-type laser system.Dynamical behavior of the system,circuit realization and application in pseudorandom number generators are studied.Many types of multi-stable states are discovered in the system.Interestingly,there are two types of state transition phenomena in the system,one is the chaotic state degenerates to a periodical state,and the other is the intermittent chaotic oscillation.In addition,the complexity of the system when two parameters change simultaneously is measured by the spectral entropy algorithm.Moreover,a digital circuit is design and the chaotic oscillation behaviors of the system are verified on this circuit.Finally,a pseudo-random sequence generator is designed using the FOLCS,and the statistical characteristics of the generated pseudo-random sequence are tested with the NIST-800-22.This study enriches the research on the dynamics and applications of FOLCS.