scholarly journals Tiling light sheet selective plane illumination microscopy using discontinuous light sheets

2018 ◽  
Author(s):  
Liang Gao

AbstractTiling light sheet selective plane illumination microscopy (TLS-SPIM) improves 3D imaging ability of SPIM by using a real-time optimized tiling light sheet. However, the imaging speed decreases, and size of the raw image data increases proportionally to the number of tiling positions in TLS-SPIM. The decreased imaging speed and the increased raw data size could cause significant problems when TLS-SPIM is used to image large specimens at high spatial resolution. Here, we present a novel method to solve the problem. Discontinuous light sheets created by scanning coaxial beam arrays synchronized with camera exposures are used for 3D imaging to decrease the number of tiling positions required at each image plane without sacrificing the spatial resolution. We investigate the performance of the method via numerical simulation and discuss the technical details of the method.

2019 ◽  
Author(s):  
Yanlu Chen ◽  
Xiaoliang Li ◽  
Dongdong Zhang ◽  
Chunhui Wang ◽  
Ruili Feng ◽  
...  

AbstractWe present a tiling light sheet microscope compatible with all tissue clearing methods for rapid multicolor 3D imaging of centimeter-scale cleared tissues with micron-scale (4×4×10 μm3) to nanometer-scale (70×70×200 nm3) spatial resolution. The microscope uses tiling light sheets to achieve a more advanced multicolor 3D imaging ability than conventional light sheet microscopes. The illumination light is phase modulated to adjust the 3D imaging ability of the microscope based on the tissue size and the desired spatial resolution and imaging speed, and also to keep the microscope aligned. The ability of the microscope to align via phase modulation alone also makes the microscope reliable and easy to operate. Here we describe the working principle and design of the microscope. We demonstrate its imaging ability by imaging various cleared tissues prepared by different tissue clearing and tissue expansion techniques.


Author(s):  
B. Liu ◽  
J. Chen ◽  
H. Xing ◽  
H. Wu ◽  
J. Zhang

The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. <br><br> A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial resolution images image by image. <br><br> Simulated experiment and remote sensing image downscaling experiment were conducted. In simulated experiment, the 30 meters class map dataset Globeland30 was adopted to investigate the effect on avoid the underdetermined problem in downscaling procedure and a comparison between spiral and window was conducted. Further, the MODIS NDVI and Landsat image data was adopted to generate the 30m time series NDVI in remote sensing image downscaling experiment. Simulated experiment results showed that the proposed method had a robust performance in downscaling pixel in heterogeneous region and indicated that it was superior to the traditional window-based methods. The high resolution time series generated may be a benefit to the mapping and updating of land cover data.


2017 ◽  
Author(s):  
Liang Gao

AbstractKeeping the excitation light sheet in focus is critical in selective plane illumination microscopy (SPIM) to ensure its 3D imaging ability. Unfortunately, an effective method that can be used in SPIM on general biological specimens to find the axial position of the excitation light sheet and keep it in focus is barely available. Here, we present a method to solve the problem. We investigate its mechanism and demonstrate its performance on a lattice light sheet microscope.


2021 ◽  
Author(s):  
Ali M. S. Alfosool ◽  
Yuanzhu Chen ◽  
Daniel Fuller

Abstract Walkability is a term that describes various aspects of the built and social environment and has been associated with physical activity and public health. Walkability is subjective and although multiple definitions of walkability exist, there is no single agreed upon definition. Road networks are integral parts of mobility and should be an important part of walkability. However, they are missing from existing methods. Most walkability measures only provide area-based scores with low spatial resolution, have a one-size-fits-all approach, and do not consider individuals opinion. Active Living Feature Score (ALF-Score) is a network-based walkability measure that incorporates road network structures as a core component. It also utilizes user opinion to build a high-confidence ground-truth that is used in our machine learning pipeline to generate models capable of estimating walkability. We found combination of network features with road embedding and POI features creates a complimentary feature set enabling us to train our models with an accuracy of over 87% while maintaining a conversion consistency of over 98%. Our proposed approach outperforms existing measures by introducing a novel method to estimate walkability scores that are representative of users opinion with a high spatial resolution, for any point on the map.


Sign in / Sign up

Export Citation Format

Share Document