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  1. Date: 090227 
    Digital Image Analysis of Cells: Applications in 2D, 3D and Time 
    Student: Amalka Pinidiyaarachchi
    Supervisor: Carolina Wählby 
    Assistant Supervisor: Ewert Bengtsson 
    Opponent: Arvid Lundervold, Dept. of Biomedicine and Molecular Imaging Center, University of Bergen, Norway 
    Committee: Jos Buijs, Division of Biochemical Engineeering, Mälardalen University; Lennart Björkesten, GE Healthcare; Maria Magnusson Dept. of Electrical Engineering, Linköping University; Cris Luengo CBA; Ingela Nyström CBA 
    Publisher: Universitetsbiblioteket Uppsala, ISBN: 978-91-554-7398-3 
    Abstract: Light microscopes are essential research tools in biology and medicine. Cell and tissue staining methods have improved immensely over the years and microscopes are now equipped with digital image acquisition capabilities. The image data produced require development of specialized analysis methods. This thesis presents digital image analysis methods for cell image data in 2D, 3D and time sequences.

    Stem cells have the capability to differentiate into specific cell types. The mechanism behind differentiation can be studied by tracking cells over time. This thesis presents a combined segmentation and tracking algorithm for time sequence images of neural stem cells. The method handles splitting and merging of cells and the results are similar to those achieved by manual tracking.

    Methods for detecting and localizing signals from fluorescence stained biomolecules are essential when studying how they function and interact. A study of Smad proteins, that serve as transcription factors by forming complexes and enter the cell nucleus, is included in the thesis. Confocal microscopy images of cell nuclei are delineated using gradient information, and Smad complexes are localized using a novel method for 3D signal detection. Thus, the localization of Smad complexes in relation to the nuclear membrane can be analyzed. A detailed comparison between the proposed and previous methods for detection of point-source signals is presented, showing that the proposed method has better resolving power and is more robust to noise.

    In this thesis, it is also shown how cell confluence can be measured by classification of wavelet based texture features. Monitoring cell confluence is valuable for optimization of cell culture parameters and cell harvest. The results obtained agree with visual observations and provide an efficient approach to monitor cell confluence and detect necrosis.

    Quantitative measurements on cells are important in both cytology and histology. The color provided by Pap (Papanicolaou) staining increases the available image information. The thesis explores different color spaces of Pap smear images from thyroid nodules, with the aim of finding the representation that maximizes detection of malignancies using color information in addition to quantitative morphological parameters.

    The presented methods provide useful tools for cell image analysis, but they can of course also be used for other image analysis applications.

  2. Date: 090327
    Image Analysis for Volumetric Characterisation of Microstructure
    Student: Maria Axelsson 
    Affiliation: Faculty of Forest Sciences, SLU
    Supervisor: Gunilla Borgefors
    Assistant supervisor: Stina Svensson
    Opponent: Carl-Fredrik Westin, Laboratory of Mathematics in Imaging, Dept. of Radiology, Harvard Medical School, Brigham and Women's Hospital, Boston, USA
    Committee: Josef Bigun, Dept. of Information, Computer and Electrical, Högskolan Halmstad; Magnus Borga, Dept. of Biomedical Engineering, Linköpings University, Markku Kataja, Dept. of Physics, University of Jyväskylä, Finland
    Publisher: Acta Universitatis agriculturae Sueciae, ISBN: 978-91-86195-66-3
    Abstract: Digital image analysis provides methods for automatic, fast, and reproducible analysis of images. The main contribution of this thesis is new image analysis methods for volumetric characterisation of microstructure with application in the field of material science. The methods can be used as tools to characterise material microstructure, in particular the structure of fibre-based materials, such as paper, wood fibre composites, and press felts. More information about the material microstructure enables design of new materials with more specialised properties.

    Volume images have recently become available to characterise material microstructure. Manual inspection of material properties using volume images is both non-reproducible and expensive. The methods presented in this thesis are developed to meet the growing need for automated analysis. The focus has been on 3D methods for high-resolution volume images, such as X-ray microtomography images.

    New methods for characterisation of both the fibre structure and pore structure in fibre-based materials are presented. The fibre structure can be characterised by measuring either individual fibres or the local structure of the material. A method for tracking individual fibres in volume images is presented. The method is designed for wood fibres, but can also be applied to other types or fibres or in other areas where tubular or elongated structures are analysed in volume images. A method for estimating 3D fibre orientation of both tubular and solid fibres is also presented. Both methods have been evaluated on real volume images acquired using X-ray microtomography with good results. Two new pore structure representations and corresponding measurements are introduced. The usefulness of the methods is illustrated on real data. A method for estimating the pore volume at the interface between press felt and fibre web is presented. It has been applied in a case study of press felts under load using confocal microscopy images.

    In addition to the methods for fibre-based materials, a general method for reducing ring artifacts in X-ray microtomography images is presented. The method is evaluated on real data with good results. It is also applied as a preprocessing step before further analysis of the X-ray microtomography images.

  3. Date: 090925 
    Digital Lines, Sturmian Words, and Continued Fractions 
    Student: Hanna Uscka-Wehlou 
    Supervisor: Maciej Klimek, Dept. of Mathematics, UU 
    Assistant Supervisor: Christer Kiselman, Dept. of Mathematics UU; Gunilla Borgefors CBA; Mikael Passare, Dept. of Mathematics, Stockholm University 
    Opponent: Damien Jamet, Henri Poincaré University, Nancy, France 
    Committee: Petter Brändén, KTH and Stockholm University; Rikard Bøgvad, Dept. of Mathematics, Stockholm University; Isabelle Debled-Rennesson, Henri Poincaré University, Nancy, France; Anders Heyden, Centre for Mathematical Sciences, Lund University; Warwick Tucker, Dept. of Mathematics, UU 
    Publisher: Matematiska institutionen UU, ISBN: 978-91-86195-66-3 
    Abstract: How to construct a digitization of a straight line and be able to recognize a straight line in a set of pixels are very important topics in computer graphics. The aim of the present paper is to give a mathematically exact and consistent description of digital straight lines according to Rosenfeld's definition. The digitizations of the lines with slopes , where is irrational, are considered. We formulate a definition of digitization runs, formulate and prove theorems containing necessary and sufficient conditions for digital straightness. The proof was successfully constructed using only methods of elementary mathematics. The developed and proved theory can be used in the research into the theory of digital lines, their symmetries, translations etc.

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