Hypoperfusion Induced by Preconditioning Treadmill Training in Hyper-Early Reperfusion After Cerebral Ischemia: A Laser Speckle Imaging Study

2018 ◽  
Vol 65 (1) ◽  
pp. 219-223
Author(s):  
Zhijie He ◽  
Hongyang Lu ◽  
Xiaojiao Yang ◽  
Li Zhang ◽  
Yi Wu ◽  
...  
2020 ◽  
Vol 11 (8) ◽  
pp. 4150
Author(s):  
István Portörő ◽  
Péter Mukli ◽  
László Kocsis ◽  
Péter Hermán ◽  
Dario Caccia ◽  
...  

2014 ◽  
Vol 39 (3) ◽  
pp. 678 ◽  
Author(s):  
J. C. Ramirez-San-Juan ◽  
R. Ramos-Garcia ◽  
G. Martinez-Niconoff ◽  
B. Choi

2021 ◽  
Author(s):  
Ilya Balmages ◽  
Janis Liepins ◽  
Dmitrijs Bliznuks ◽  
Stivens Zolins ◽  
Ilze Lihacova ◽  
...  

2019 ◽  
Vol 122 ◽  
pp. 52-59 ◽  
Author(s):  
AmirHessam Aminfar ◽  
Nami Davoodzadeh ◽  
Guillermo Aguilar ◽  
Marko Princevac

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
J. Buijs ◽  
J. van der Gucht ◽  
J. Sprakel

Abstract Laser speckle imaging is a powerful imaging technique that visualizes microscopic motion within turbid materials. At current two methods are widely used to analyze speckle data: one is fast but qualitative, the other quantitative but computationally expensive. We have developed a new processing algorithm based on the fast Fourier transform, which converts raw speckle patterns into maps of microscopic motion and is both fast and quantitative, providing a dynamnic spectrum of the material over a frequency range spanning several decades. In this article we show how to apply this algorithm and how to measure a diffusion coefficient with it. We show that this method is quantitative and several orders of magnitude faster than the existing quantitative method. Finally we harness the potential of this new approach by constructing a portable laser speckle imaging setup that performs quantitative data processing in real-time on a tablet.


Sign in / Sign up

Export Citation Format

Share Document