A study on the characteristics of the Analog Mean Delay (AMD) method for high-speed Fluorescence Lifetime Imaging Microscopy (FLIM)

Byungyeon Kim; Byungjun Park; Seungrag Lee; Youngjae Won

doi:10.1117/12.2209468

7 March 2016 A study on the characteristics of the Analog Mean Delay (AMD) method for high-speed Fluorescence Lifetime Imaging Microscopy (FLIM)

Byungyeon Kim, Byungjun Park, Seungrag Lee, Youngjae Won

Author Affiliations +

Proceedings Volume 9720, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management; 972014 (2016) https://doi.org/10.1117/12.2209468
Event: SPIE BiOS, 2016, San Francisco, California, United States

Abstract

We present a study on the characteristics of the AMD method. We have demonstrated that the photon economy of the AMD method is not degraded for longer lifetimes even when the applied integration window size is increased. By an extension of MCS, the photon economy with respect to different designs of the Gaussian low-pass filter (GLPF) used in the AMD setup was also studied. When a GLPF with the highest cutoff frequency of 100 MHz is applied, the most effective photon economy performance is achieved for lifetimes of 1, 3.2, 5, and 8 ns.

Citation Download Citation

Byungyeon Kim, Byungjun Park, Seungrag Lee, and Youngjae Won "A study on the characteristics of the Analog Mean Delay (AMD) method for high-speed Fluorescence Lifetime Imaging Microscopy (FLIM)", Proc. SPIE 9720, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management, 972014 (7 March 2016); https://doi.org/10.1117/12.2209468

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available