View source for Publications:Automatic detection and morphological delineation of bacteriophages in electron microscopy images

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{{PublicationSetupTemplate|Author=Adas Gelzinis, Antanas Verikas, Evaldas Vaiciukynas, Marija Bacauskiene, Sigitas Šulčius, Juozas Staniulis, Ričardas Paškauskas
|PID=844113
|Name=Gelzinis, Adas (Kaunas University of Technology, Kaunas, Lithuania);Verikas, Antanas [av] [0000-0003-2185-8973] (Högskolan i Halmstad [2804], Akademin för informationsteknologi [16904], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], CAISR Centrum för tillämpade intelligenta system (IS-lab) [13650]) (Kaunas University of Technology, Kaunas, Lithuania);Vaiciukynas, Evaldas (Kaunas University of Technology, Kaunas, Lithuania);Bacauskiene, Marija (Kaunas University of Technology, Kaunas, Lithuania);Šulčius, Sigitas (Marine Science and Technology Center, Klaipeda University, Klaipeda, Lithuania & Open Access Centre for Nature Research, Nature Research Centre, Vilnius, Lithuania);Staniulis, Juozas (Laboratory of Plant Viruses, Nature Research Centre, Institute of Botany, Vilnius, Lithuania);Paškauskas, Ričardas (Marine Science and Technology Center, Klaipeda University, Klaipeda, Lithuania & Laboratory of Algology and Microbial Ecology, Nature Research Centre, Vilnius, Lithuania)
|Title=Automatic detection and morphological delineation of bacteriophages in electron microscopy images
|PublicationType=Journal Paper
|ContentType=Refereegranskat
|Language=eng
|Journal=Computers in Biology and Medicine
|JournalISSN=0010-4825
|Status=aheadofprint
|Volume=64
|Issue=
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|StartPage=101
|EndPage=116
|Year=2015
|Edition=
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|City=Kidlington
|Publisher=Pergamon Press
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|DOI=http://dx.doi.org/10.1016/j.compbiomed.2015.06.015
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|PMID=26164031
|ScopusId=2-s2.0-84936882280
|NBN=urn:nbn:se:hh:diva-29083
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|Keywords=Bacteriophage Vb-AphaS- CL131 Aphanizomenon flos-aquae Cyanophage Cyanobacteria Electron microscopy Pattern recognition Random forest Open active contours Bland–Altman
|Categories=Teknik och teknologier (2)
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|Notes=<p>Funding for this work was provided by a grant (No. LEK-09/2012) from the Research Council of Lithuania under National Research Programme “Ecosystems in Lithuania: Climate Change and Human Impact”.</p>
|Abstract=<p>Automatic detection, recognition and geometric characterization of bacteriophages in electron microscopy images was the main objective of this work. A novel technique, combining phase congruency-based image enhancement, Hough transform-, Radon transform- and open active contours with free boundary conditions-based object detection was developed to detect and recognize the bacteriophages associated with infection and lysis of cyanobacteria Aphanizomenon flos-aquae. A random forest classifier designed to recognize phage capsids provided higher than 99% accuracy, while measurable phage tails were detected and associated with a correct capsid with 81.35% accuracy. Automatically derived morphometric measurements of phage capsids and tails exhibited lower variability than the ones obtained manually. The technique allows performing precise and accurate quantitative (e.g. abundance estimation) and qualitative (e.g. diversity and capsid size) measurements for studying the interactions between host population and different phages that infect the same host. © 2015 Elsevier Ltd.</p>
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|CreatedDate=2015-08-03
|PublicationDate=2015-08-03
|LastUpdated=2015-08-04
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:844113}}
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