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Segmentation methods and shape descriptions in digital images

applications in 2D and 3D microscopy

Sintorn, Ida-Maria (2005). Segmentation methods and shape descriptions in digital images. Diss. (sammanfattning/summary) Uppsala : Sveriges lantbruksuniv., Acta Universitatis agriculturae Sueciae, 1652-6880 ; 2005:20
ISBN 91-576-7019-6
[Doctoral thesis]

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Abstract

Digital image analysis enables creating objective, fast, and reproducible analysis methods of objects or situations that can be imaged. This thesis contains theoretical work regarding distance transforms for images digitized in elongated grids. Such images are the result of many, mainly 3D, imaging devices. Local weights appropriate for different elongation factors in 2D, as well as in 3D, are presented. Methods adapted to elongated grids save time and computer memory compared to increasing the image size by interpolating to a cubic grid. A number of segmentation methods for images in specific applications are also included in the thesis. Distance information is used to segment individual pores in paper volume images. This opens the possibility to investigate how the pore network affects the paper quality. Stable and reliable segmentation methods for cell nuclei are necessary to enable studies of tumor morphology, as well as amounts of fluorescence marked substances in individual nuclei. Intensity, gradient magnitude, and shape information is combined in a method to segment cell nuclei in 2D fluorescence and 3D confocal microscopy images of tissue sections. Two match based segmentation methods are also presented. Three types of viral capsids are identified and described based on their radial intensity distribution in transmission electron micrographs of infected cells. This can be used to measure how a potential drug affects the relative amounts of the three capsids, and possibly, the viral maturation pathway. Proteins of a specific kind in transmission electron volume images of a protein solution are identified using a shape based match method. This method reduces the amount of visual inspection needed to identify proteins of interest in the images. Two representation schemes, developed in order to simplify the analysis of individual proteins in volume images of proteins in solution, are presented. One divides a protein into subparts based on the internal intensity distribution and shape. The other represents the protein by the maximum intensity curve connecting the centers of the subparts of the protein. These representations can serve as tools for collecting information about how flexible a protein in solution is and how it interacts with other proteins or substances. This information is valuable for the pharmaceutical industry, when developing new drugs.

Authors/Creators:Sintorn, Ida-Maria
Title:Segmentation methods and shape descriptions in digital images
Subtitle:applications in 2D and 3D microscopy
Year of publishing :March 2005
Volume:2005:20
Number of Pages:58
Papers/manuscripts:
NumberReferences
ALLSintorn I-M., Borgefors G. (2001). Weighted distance transforms in rectangular grids. In Ardizzone, E. and Gesu`, V., editors, Proc. 11th International Conference on Image Analysis and Processing, Palermo, Italy, pages 322--326. IEEE Computer Society. Sintorn I-M., Borgefors G. (2004). Weighted distance transforms for images digitized in elongated voxel grids. Pattern Recognition Letters 25:571--580. Sintorn I-M., Axelsson M., Svensson S., Borgefors G. (2005). Segmentation of individual pores in paper volume images. Submitted for journal publication Sintorn I-M., Homman-Loudiyi M., Söderberg-Naucle'r C., Borgefors G. (2004). A refined circular template matching method for classification of human cytomegalovirus capsids in TEM images. Computer Methods and Programs in Biomedicine, 76(2):95--102. Wählby C., Sintorn I-M., Erlandsson F., Borgefors G., Bengtsson E. (2004). Combining intensity, edge, and shape information for 2D and 3D segmentation of cell nuclei in tissue sections, Journal of Microscopy 215:67--76. Sintorn, I-M., Mata, S. (2004). Using grey-level and shape information for decomposing proteins in 3D images. In Proc. IEEE International Symposium on Biomedical Imaging, Arlington, VA, USA, pages 800--803. Mira Digital Publishing. Sintorn, I-M., Gedda, M., Mata, S., Svensson S. (2005). Medial grey-level based representation for proteins in volume images. To appear in Proc. of Iberian Conference on Pattern Recognition and Image Analysis, Estoril, Portugal, Lecture Notes in Computer Science. Springer-Verlag. Sintorn, I-M., Borgefors, G. (2005). Shape based identification of proteins in volume images. Submitted for publication.
Place of Publication:Uppsala
ISBN for printed version:91-576-7019-6
ISSN:1652-6880
Language:English
Publication Type:Doctoral thesis
Full Text Status:Public
Agris subject categories.:U Auxiliary disciplines > U30 Research methods
Subjects:Not in use, please see Agris categories
Agrovoc terms:imagery, image analysis, methods, microscopy
Keywords:digital image analysis, volume images, microscopy images, elongated grid, distance transform, segmentation, shape description, grey-level, gradient magnitude, watershed, decomposition
URN:NBN:urn:nbn:se:slu:epsilon-574
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-574
ID Code:781
Department:(S) > Centrum för bildanalys (900701-031231?)
Deposited By: Ida-Maria Sintorn
Deposited On:14 Mar 2005 00:00
Metadata Last Modified:02 Dec 2014 10:07

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