Algorithms for Applied Digital Image Cytometry

Image analysis can provide genetic as well as protein level information from fluorescence stained fixed or living cells without loosing tissue morphology. Analysis of spatial, spectral, and temporal distribution of fluorescence can reveal important information on the single cell level. This is in contrast to most other methods for cell analysis, which do not account for inter-cellular variation. Flow cytometry enables single-cell analysis, but tissue morphology is lost in the process, and temporal events cannot be observed.The need for reproducibility, speed and accuracy calls for computerized methods for cell image analysis, i.e., digital image cytometry, which is the topic of this thesis.Algorithms for cell-based screening are presented and applied to evaluate the effect of insulin on translocation events in single cells. This type of algorithms could be the basis for high-throughput drug screening systems, and have been developed in close cooperation with biomedical industry.Image based studies of cell cycle proteins in cultured cells and tissue sections show that cyclin A has a well preserved expression pattern while the expression pattern of cyclin E is disturbed in tumors…


1 Introduction and Objectives
1.1 Drugscreening
1.2 Cancer research
1.3 Segmentationandstaining
1.4 About this thesis
2 Background
2.1 Thecell
2.1.1 Thecellcycle
2.1.2 Cancer
2.2 Visualizingthecell
2.2.1 Fluorescence microscopy
2.2.2 Cellpreparation
2.2.3 Immunofluorescence staining
2.2.4 DNAstaining
2.2.5 GFPtagging
2.2.6 Other fluorescence staining techniques
2.3 Cytometry – the measurement of cell properties
2.3.1 Flowcytometry
2.3.2 Imagecytometry
2.3.3 Flowcytometryvs.imagecytometry
3 Digitalimagecytometry
3.1 Image acquisition:image quality vs. image quantity
3.2 Pre-processing
3.2.1 Reduction of intensity non-uniformities
3.2.2 Imageregistration
3.3 Segmentation
3.3.1 Thresholding
3.3.2 Watershedsegmentation
3.3.3 Shape-based watershed segmentation
3.3.4 Edge-based watershed segmentation
3.3.5 Merging

Author: Wählby, Carolina

Source: Uppsala University Library

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