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Segmentation and separation of point like fluorescent markers in digital images
Uppsala University.
2004 In: Proceedings of IEEE International Symposium on Biomedical Imaging, 2004, 2004- p.Chapter in book (Other academic) Published
Place, publisher, year, edition, pages
2004. 2004- p.
URN: urn:nbn:se:uu:diva-97426ISBN: 0-7803-8388-5OAI: oai:DiVA.org:uu-97426DiVA: diva2:172375
Available from: 2008-08-29 Created: 2008-08-29Bibliographically approved
In thesis
1. Methods and models for 2D and 3D image analysis in microscopy, in particular for the study of muscle cells
Open this publication in new window or tab >>Methods and models for 2D and 3D image analysis in microscopy, in particular for the study of muscle cells
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Metoder och modeller för två- och tredimensionell bildanalys inom mikroskopi, speciellt med inrikting mot muskelceller
Abstract [en]

Many research questions in biological research lead to numerous microscope images that need to be evaluated. Here digital image cytometry, i.e., quantitative, automated or semi-automated analysis of the images is an important rapidly growing discipline. This thesis presents contributions to that field. The work has been carried out in close cooperation with biomedical research partners, successfully solving real world problems.

The world is 3D and modern imaging methods such as confocal microscopy provide 3D images. Hence, a large part of the work has dealt with the development of new and improved methods for quantitative analysis of 3D images, in particular fluorescently labeled skeletal muscle cells.

A geometrical model for robust segmentation of skeletal muscle fibers was developed. Images of the multinucleated muscle cells were pre-processed using a novel spatially modulated transform, producing images with reduced complexity and facilitating easy nuclei segmentation. Fibers from several mammalian species were modeled and features were computed based on cell nuclei positions. Features such as myonuclear domain size and nearest neighbor distance, were shown to correlate with body mass, and femur length. Human muscle fibers from young and old males, and females, were related to fiber type and extracted features, where myonuclear domain size variations were shown to increase with age irrespectively of fiber type and gender.

A segmentation method for severely clustered point-like signals was developed and applied to images of fluorescent probes, quantifying the amount and location of mitochondrial DNA within cells. A synthetic cell model was developed, to provide a controllable golden standard for performance evaluation of both expert manual and fully automated segmentations. The proposed method matches the correctness achieved by manual quantification.

An interactive segmentation procedure was successfully applied to treated testicle sections of boar, showing how a common industrial plastic softener significantly affects testosterone concentrations.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2008. 76 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 544
medical image analysis, image segmentation, fluorescence microscopy, cytometry, human skeletal muscle
National Category
Natural Sciences
urn:nbn:se:uu:diva-9201 (URN)978-91-554-7255-9 (ISBN)
Public defence
2008-09-19, Polhemsalen, Ångströmlaboratoriet, Polacksbacken, Uppsala, 13:15
Available from: 2008-08-29 Created: 2008-08-29 Last updated: 2013-07-03Bibliographically approved

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