Fast volumetric imaging with line-scan confocal microscopy by an electro-tunable lens

In microscopic imaging of biological tissues, particularly real-time visualization of neuronal activities, rapid acquisition of volumetric images poses a prominent challenge. Typically, two-dimensional (2D) microscopy can be devised into an imaging system with 3D capability using any varifocal lens. Despite the conceptual simplicity, such an upgrade yet requires additional, complicated device components and suffers a reduced acquisition rate, which is critical to document neuronal dynamics properly. In this study, we implemented an electro-tunable lens (ETL) in the line-scan confocal microscopy, enabling the volumetric acquisition at the rate of 20 frames per second with the maximum volume of interest of 315 × 315 × 80 μm3. The axial extent of point-spread-function (PSF) was 17.6 ± 1.6 μm and 90.4 ± 2.1 μm with the ETL operating in either stationary or resonant mode, respectively, revealing significant depth elongation by the resonant mode ETL microscopy. We further demonstrated the utilities of the ETL system by volume imaging of cleared mouse brain ex vivo samples and in vivo brains. The current study foregrounds the successful application of resonant ETL for constructing a basis for a high-performance 3D line-scan confocal microscopy system, which will enhance our understanding of various dynamic biological processes.

Line Scan Spatial Speckle Contrast Imaging and Its Application in Blood Flow Imaging

Laser speckle imaging has been an indispensable tool for visualizing blood flow in biomedical applications. We proposed a novel design of the laser speckle imaging system, which combines confocal illumination and detection with various speckle analysis methods. The system can be operated by three imaging modes. One is surface illumination laser speckle contrast imaging (SI-LSCI) and the other two are line scan temporal speckle contrast imaging (LS-TSCI) and line scan spatial speckle contrast imaging (LS-SSCI). The experimental results of flow phantoms have validated the mixture model, which combines the Lorentzian and Gaussian models to describe the simultaneous existence of both Brownian motions and ordered flow. Our experimental results of in vivo chick embryos demonstrate that LS-SSCI maintains high temporal resolution and is less affected by motion artifacts. LS-SSCI can provide better image quality for in vivo imaging blood chick embryos than LS-TSCI. Furthermore, the experiential results present that LS-SSCI can detect and quantify the blood flow change during vascular clipping, and shows great potential in diagnosing vascular diseases, such as angiosclerosis, angiostenosis, or angiemphraxis.

A Multi-view Camera Model for Line-Scan Cameras with Telecentric Lenses

We propose a novel multi-view camera model for line-scan cameras with telecentric lenses. The camera model supports an arbitrary number of cameras and assumes a linear relative motion with constant velocity between the cameras and the object. We distinguish two motion configurations. In the first configuration, all cameras move with independent motion vectors. In the second configuration, the cameras are mounted rigidly with respect to each other and therefore share a common motion vector. The camera model can model arbitrary lens distortions by supporting arbitrary positions of the line sensor with respect to the optical axis. We propose an algorithm to calibrate a multi-view telecentric line-scan camera setup. To facilitate a 3D reconstruction, we prove that an image pair acquired with two telecentric line-scan cameras can always be rectified to the epipolar standard configuration, in contrast to line-scan cameras with entocentric lenses, for which this is possible only under very restricted conditions. The rectification allows an arbitrary stereo algorithm to be used to calculate disparity images. We propose an efficient algorithm to compute 3D coordinates from these disparities. Experiments on real images show the validity of the proposed multi-view telecentric line-scan camera model.