@Article{EAJAM-1-1,
author = {},
title = {A Comparative Method for Analysing Toponome Image Stacks},
journal = {East Asian Journal on Applied Mathematics},
year = {2011},
volume = {1},
number = {1},
pages = {35--48},
abstract = {<p style="text-align: justify;">We present a technique to find threshold values that allows the user to separate
signal from noise in fluorescence grey-level images. It can be classified as a purely
comparative method based upon the amount of “Mutual Information” between two or
more florescence images, and we apply it to stacks of such images produced using
the newly-developed MELK technology. Our results are compared to results obtained
by another research group using a quite different (completely independent and more
technology-based) approach; and also to results obtained using Otsu’s Thresholding
Method, yet another completely distinct approach invented to separate foreground and
background in a grey-level image, based on minimising “intra-class variance” [9, 10].
The remarkably good agreement found suggests that our proposed comparative information
based method not only accounts for the biological mechanisms governing cellular
protein networks very well, but also (and probably much more importantly) shows
that cells actually organise the spatial structure of their protein networks in a highly
non-random fashion as might be expected – and thereby try to optimise their “mutual
information content”, and thus most probably their efficiency.</p>},
issn = {2079-7370},
doi = {https://doi.org/10.4208/eajam.280909.270410a},
url = {https://global-sci.com/article/82858/a-comparative-method-for-analysing-toponome-image-stacks}
}