Volume 8, Issue 1 (January & February 2017 -- 2017)                   BCN 2017, 8(1): 19-26 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Karami M A, Ansarian M. Neural Imaging Using Single-Photon Avalanche Diodes. BCN. 2017; 8 (1) :19-26
URL: http://bcn.iums.ac.ir/article-1-682-en.html
1- Department of Electronic Engineering, School of Electrical Engineering, University of Science and Technology, Tehran, Iran.

Introduction: This paper analyses the ability of single-photon avalanche diodes (SPADs) for neural imaging. The current trend in the production of SPADs moves toward the minimumdark count rate (DCR) and maximum photon detection probability (PDP). Moreover, the jitter response which is the main measurement characteristic for the timing uncertainty is progressing.
Methods: The neural imaging process using SPADs can be performed by means of florescence lifetime imaging (FLIM), time correlated single-photon counting (TCSPC), positron emission tomography (PET), and single-photon emission computed tomography (SPECT).
Results: This trend will result in more precise neural imaging cameras. While achieving low DCR SPADs is difficult in deep submicron technologies because of using higher doping profiles, higher PDPs are reported in green and blue part of light. Furthermore, the number of pixels integrated in the same chip is increasing with the technology progress which can result in the higher resolution of imaging.
Conclusion: This study proposes implemented SPADs in Deep-submicron technologies to be used in neural imaging cameras, due to the small size pixels and higher timing accuracies.

Type of Study: Methodological Notes | Subject: Computational Neuroscience
Received: 2016/05/6 | Accepted: 2016/09/1 | Published: 2017/01/1

Add your comments about this article : Your username or Email:

Send email to the article author

© 2019 All Rights Reserved | Basic and Clinical Neuroscience

Designed & Developed by : Yektaweb