RAMTaB: robust alignment of multi-tag bioimages.

<h4>Background</h4>In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located...

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Autores principales:	Shan-e-Ahmed Raza, Ahmad Humayun, Sylvie Abouna, Tim W Nattkemper, David B A Epstein, Michael Khan, Nasir M Rajpoot
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c4d83720222347f3af99743a161e18ec
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id	oai:doaj.org-article:c4d83720222347f3af99743a161e18ec
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spelling	oai:doaj.org-article:c4d83720222347f3af99743a161e18ec2021-11-18T07:28:36ZRAMTaB: robust alignment of multi-tag bioimages.1932-620310.1371/journal.pone.0030894https://doaj.org/article/c4d83720222347f3af99743a161e18ec2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22363510/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images.<h4>Methodology/principal findings</h4>We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies.<h4>Conclusions</h4>For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks.Shan-e-Ahmed RazaAhmad HumayunSylvie AbounaTim W NattkemperDavid B A EpsteinMichael KhanNasir M RajpootPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 2, p e30894 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Shan-e-Ahmed Raza Ahmad Humayun Sylvie Abouna Tim W Nattkemper David B A Epstein Michael Khan Nasir M Rajpoot RAMTaB: robust alignment of multi-tag bioimages.
description	<h4>Background</h4>In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images.<h4>Methodology/principal findings</h4>We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies.<h4>Conclusions</h4>For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks.
format	article
author	Shan-e-Ahmed Raza Ahmad Humayun Sylvie Abouna Tim W Nattkemper David B A Epstein Michael Khan Nasir M Rajpoot
author_facet	Shan-e-Ahmed Raza Ahmad Humayun Sylvie Abouna Tim W Nattkemper David B A Epstein Michael Khan Nasir M Rajpoot
author_sort	Shan-e-Ahmed Raza
title	RAMTaB: robust alignment of multi-tag bioimages.
title_short	RAMTaB: robust alignment of multi-tag bioimages.
title_full	RAMTaB: robust alignment of multi-tag bioimages.
title_fullStr	RAMTaB: robust alignment of multi-tag bioimages.
title_full_unstemmed	RAMTaB: robust alignment of multi-tag bioimages.
title_sort	ramtab: robust alignment of multi-tag bioimages.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/c4d83720222347f3af99743a161e18ec
work_keys_str_mv	AT shaneahmedraza ramtabrobustalignmentofmultitagbioimages AT ahmadhumayun ramtabrobustalignmentofmultitagbioimages AT sylvieabouna ramtabrobustalignmentofmultitagbioimages AT timwnattkemper ramtabrobustalignmentofmultitagbioimages AT davidbaepstein ramtabrobustalignmentofmultitagbioimages AT michaelkhan ramtabrobustalignmentofmultitagbioimages AT nasirmrajpoot ramtabrobustalignmentofmultitagbioimages
_version_	1718423437296271360

RAMTaB: robust alignment of multi-tag bioimages.

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