Stem cell microscopic image segmentation using supervised normalized cuts

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HUANG, Xinyu, Chen LI, Minmin SHEN, Kimiaki SHIRAHAMA, Johanna NYFFELER, Marcel LEIST, Marcin GRZEGORZEK, Oliver DEUSSEN, 2016. Stem cell microscopic image segmentation using supervised normalized cuts. 2016 IEEE International Conference on Image Processing (ICIP). Phoenix, Arizona, USA, 25. Aug 2016 - 28. Aug 2016. In: KARAM, Lina, ed.. 2016 IEEE International Conference on Image Processing : Proceedings. 2016 IEEE International Conference on Image Processing (ICIP). Phoenix, Arizona, USA, 25. Aug 2016 - 28. Aug 2016. Piscataway, NJ:IEEE, pp. 4140-4144. ISBN 978-1-4673-9961-6

@inproceedings{Huang2016micro-37235, title={Stem cell microscopic image segmentation using supervised normalized cuts}, year={2016}, doi={10.1109/ICIP.2016.7533139}, isbn={978-1-4673-9961-6}, address={Piscataway, NJ}, publisher={IEEE}, booktitle={2016 IEEE International Conference on Image Processing : Proceedings}, pages={4140--4144}, editor={Karam, Lina}, author={Huang, Xinyu and Li, Chen and Shen, Minmin and Shirahama, Kimiaki and Nyffeler, Johanna and Leist, Marcel and Grzegorzek, Marcin and Deussen, Oliver} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/37235"> <dc:creator>Li, Chen</dc:creator> <dc:creator>Grzegorzek, Marcin</dc:creator> <dc:creator>Shirahama, Kimiaki</dc:creator> <dc:creator>Nyffeler, Johanna</dc:creator> <dc:contributor>Leist, Marcel</dc:contributor> <dc:creator>Deussen, Oliver</dc:creator> <dc:creator>Huang, Xinyu</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-02-09T07:34:39Z</dcterms:available> <dc:contributor>Huang, Xinyu</dc:contributor> <dc:creator>Shen, Minmin</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-02-09T07:34:39Z</dc:date> <dcterms:abstract xml:lang="eng">A vast amount of toxicological data can be obtained from feature analysis of cells treated in vitro. However, this requires microscopic image segmentation of cells. To this end, we propose a new strategy, namely Supervised Normalized Cut Segmentation (SNCS), to segment cells that partially overlap and have a large amount of curved edges. SNCS approach is a machine learning based method, where loosely annotated images are used first to train and optimise parameters, and then the optimal parameters are inserted into a Normalized Cut segmentation process. Furthermore, we compare our segmentation results using SNCS to another four classical and two state-of-the-art methods. The overall experimental result shows the usefulness and effectiveness of our method over the six comparison methods.</dcterms:abstract> <dcterms:issued>2016</dcterms:issued> <dc:language>eng</dc:language> <dc:contributor>Deussen, Oliver</dc:contributor> <dc:contributor>Shen, Minmin</dc:contributor> <dc:contributor>Nyffeler, Johanna</dc:contributor> <dc:contributor>Shirahama, Kimiaki</dc:contributor> <dc:contributor>Li, Chen</dc:contributor> <dcterms:title>Stem cell microscopic image segmentation using supervised normalized cuts</dcterms:title> <dc:contributor>Grzegorzek, Marcin</dc:contributor> <dc:creator>Leist, Marcel</dc:creator> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/37235"/> </rdf:Description> </rdf:RDF>

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