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Algorithms for cyto...
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Wählby, CarolinaUppsala universitet,Centrum för bildanalys,Datoriserad bildanalys
(författare)
Algorithms for cytoplasm segmentation of fluorescence labeled cells
- Artikel/kapitelEngelska2002
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LIBRIS-ID:oai:DiVA.org:uu-90086
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https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-90086URI
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Språk:engelska
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Sammanfattning på:engelska
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Ämneskategori:ref swepub-contenttype
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Ämneskategori:art swepub-publicationtype
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Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre-processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical analysis of a number of shape descriptive features. Objects that have features that differ to that of correctly segmented single cells can be further processed by a splitting step. By statistical analysis we therefore get a feedback system for separation of clustered cells. After the segmentation is completed, the quality of the final segmentation is evaluated. By training the algorithm on a representative set of training images, the algorithm is made fully automatic for subsequent images created under similar conditions. Automatic cytoplasm segmentation was tested on CHO-cells stained with calcein. The fully automatic method showed between 89% and 97% correct segmentation as compared to manual segmentation.
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Biuppslag (personer, institutioner, konferenser, titlar ...)
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Lindblad, JoakimUppsala universitet,Centrum för bildanalys,Datoriserad bildanalys(Swepub:uu)joali534
(författare)
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Vondrus, Mikael
(författare)
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Bengtsson, Ewert
(författare)
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Björkesten, Lennart
(författare)
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Uppsala universitetCentrum för bildanalys
(creator_code:org_t)
Sammanhörande titlar
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Ingår i:Analytical Cellular Pathology24:2-3, s. 101-1110921-89121878-3651
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