CONFOCALMICROSCOPY Archives

April 2013

CONFOCALMICROSCOPY@LISTS.UMN.EDU

Options: Use Monospaced Font
Show Text Part by Default
Show All Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Subject:
From:
Alessandro Esposito <[log in to unmask]>
Reply To:
Confocal Microscopy List <[log in to unmask]>
Date:
Fri, 26 Apr 2013 07:50:57 -0500
Content-Type:
text/plain
Parts/Attachments:
text/plain (45 lines)
*****
To join, leave or search the confocal microscopy listserv, go to:
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
*****

Dear Aleem, 
    perhaps it would help if you specify in more detail which is the issue you are 
trying to explain.

However, a general note of caution when using the "binning" option in 
SPCImage is necessary. 

First of all it is not technically binning. It is a convolution averaging filter. It is 
slower than binning, but a good idea as it permits to improve SNR with a better 
compromise in respect of loss in spatial resolution resolution. 

Second, the bin value you input in the GUI is not the dimension of the kernel. 
The kernel dimension is 2*x+1. 

Therefore, who does not read the manual, with x=2 may think to bin 2x2 pixel 
together, but actually this would be an averging filter with a kernel of 5x5 
pixel. 

Third, the default option of visualization in SPCImage is to overlay lifetime 
maps with intensity maps. Beautiful representation that provide the 
advantages of a smoother lifetime image (when using "binning") with the 
perception of higher resolution provided by the overlay with the non-binned 
intensity image.

All legit and described by B&H. However, users should always inspect the "raw" 
lifetime images in order to check for potential artefacts.

Edge artefacts are always possible. At the boundary between of fluorescent 
object and the background, you will have a decrease of signal-to-noise ratio 
and signal-to-background. This may concur to skew/bias your fitting results. 
Combine this with binning and you may get nice images but with edge 
artefacts.

Not sure if this is relevant to your issue though...

Cheers, 

Alessandro
www.quantitative-microscopy.org

ATOM RSS1 RSS2