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dc.contributor.author
Misselwitz, Benjamin
dc.contributor.author
Strittmatter, Gerhard
dc.contributor.author
Periaswamy, Balamurugan
dc.contributor.author
Schlumberger, Markus C.
dc.contributor.author
Rout, Samuel
dc.contributor.author
Horvath, Peter
dc.contributor.author
Kozak, Karol
dc.contributor.author
Hardt, Wolf-Dietrich
dc.date.accessioned
2018-09-03T09:52:05Z
dc.date.available
2017-06-08T22:25:11Z
dc.date.available
2018-09-03T09:52:05Z
dc.date.issued
2010-01
dc.identifier.issn
1471-2105
dc.identifier.other
10.1186/1471-2105-11-30
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/17137
dc.identifier.doi
10.3929/ethz-b-000017137
dc.description.abstract
Background Light microscopy is of central importance in cell biology. The recent introduction of automated high content screening has expanded this technology towards automation of experiments and performing large scale perturbation assays. Nevertheless, evaluation of microscopy data continues to be a bottleneck in many projects. Currently, among open source software, CellProfiler and its extension Analyst are widely used in automated image processing. Even though revolutionizing image analysis in current biology, some routine and many advanced tasks are either not supported or require programming skills of the researcher. This represents a significant obstacle in many biology laboratories. Results We have developed a tool, Enhanced CellClassifier, which circumvents this obstacle. Enhanced CellClassifier starts from images analyzed by CellProfiler, and allows multi-class classification using a Support Vector Machine algorithm. Training of objects can be done by clicking directly "on the microscopy image" in several intuitive training modes. Many routine tasks like out-of focus exclusion and well summary are also supported. Classification results can be integrated with other object measurements including inter-object relationships. This makes a detailed interpretation of the image possible, allowing the differentiation of many complex phenotypes. For the generation of the output, image, well and plate data are dynamically extracted and summarized. The output can be generated as graphs, Excel-files, images with projections of the final analysis and exported as variables. Conclusion Here we describe Enhanced CellClassifier which allows multiple class classification, elucidating complex phenotypes. Our tool is designed for the biologist who wants both, simple and flexible analysis of images without requiring programming skills. This should facilitate the implementation of automated high-content screening.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/2.0/
dc.subject
Support Vector Machine
en_US
dc.subject
Hepatocyte Growth Factor
en_US
dc.subject
Mitotic Cell
en_US
dc.subject
Object Attribute
en_US
dc.subject
Decision Boundary
en_US
dc.title
Enhanced CellClassifier: a multi-class classification tool for microscopy images
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 2.0 Generic
ethz.journal.title
BMC Bioinformatics
ethz.journal.volume
11
en_US
ethz.journal.abbreviated
BMC bioinformatics
ethz.pages.start
30
en_US
ethz.size
13 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.nebis
004240301
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02030 - Dep. Biologie / Dep. of Biology::02520 - Institut für Mikrobiologie / Institute of Microbiology::03589 - Hardt, Wolf-Dietrich / Hardt, Wolf-Dietrich
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02030 - Dep. Biologie / Dep. of Biology::02520 - Institut für Mikrobiologie / Institute of Microbiology::03589 - Hardt, Wolf-Dietrich / Hardt, Wolf-Dietrich
ethz.date.deposited
2017-06-08T22:25:30Z
ethz.source
ECIT
ethz.identifier.importid
imp59364c7330e6a68156
ethz.ecitpid
pub:29092
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-12T11:11:21Z
ethz.rosetta.lastUpdated
2018-11-08T01:25:27Z
ethz.rosetta.versionExported
true
ethz.COinS
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