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Segmentation of Cytoplasms of Cultured Cells
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
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2007 (Swedish)In: In Proceedings SSBA 2007, Symposium on image analysis, Linköping, 2007Conference paper, Published paper (Other academic)
Abstract [en]

Cell cultures as well as cells in tissue always display a certain degree of variability, and measurements based on cell averages will miss important information contained in a heterogeneous population. This paper presents automated methods for segmentation of cells and cytoplasms. The segmentation results are applied to image based measurements of mitochondiral DNA (mtDNA) mutations in individual cells. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%, compared to an inter observer variability of 79% at manual delineation.

Place, publisher, year, edition, pages
2007.
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Computer and Information Sciences
Identifiers
URN: urn:nbn:se:uu:diva-12454OAI: oai:DiVA.org:uu-12454DiVA: diva2:40223
Available from: 2007-12-21 Created: 2007-12-21 Last updated: 2018-01-12Bibliographically approved

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Allalou, AminWählby, Carolina

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