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  • 1. Acosta, Oscar
    et al.
    Frimmel, Hans
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Fenster, Aaron
    Ourselin, Sébastien
    Filtering and restoration of structures in 3D ultrasound images2007In: Proc. 4th International Symposium on Biomedical Imaging, Piscataway, NJ: IEEE , 2007, p. 888-891Conference paper (Refereed)
  • 2. Acosta, Oscar
    et al.
    Frimmel, Hans
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Fenster, Aaron
    Salvado, Olivier
    Ourselin, Sébastien
    Pyramidal flux in an anisotropic diffusion scheme for enhancing structures in 3D images2008In: Medical Imaging 2008: Image Processing, Bellingham, WA, 2008, p. 691429:1-12Conference paper (Refereed)
  • 3.
    Allalou, Amin
    et al.
    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.
    Pinidiyaarachchi, Amalka
    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.
    Wählby, Carolina
    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.
    Robust signal detection in 3D fluorescence microscopy2010In: Cytometry. Part A, ISSN 1552-4922, Vol. 77A, no 1, p. 86-96Article in journal (Refereed)
    Abstract [en]

    Robust detection and localization of biomolecules inside cells is of great importance to better understand the functions related to them. Fluorescence microscopy and specific staining methods make biomolecules appear as point-like signals on image data, often acquired in 3D. Visual detection of such point-like signals can be time consuming and problematic if the 3D images are large, containing many, sometimes overlapping, signals. This sets a demand for robust automated methods for accurate detection of signals in 3D fluorescence microscopy. We propose a new 3D point-source signal detection method that is based on Fourier series. The method consists of two parts, a detector, which is a cosine filter to enhance the point-like signals, and a verifier, which is a sine filter to validate the result from the detector. Compared to conventional methods, our method shows better robustness to noise and good ability to resolve signals that are spatially close. Tests on image data show that the method has equivalent accuracy in signal detection in comparison to Visual detection by experts. The proposed method can be used as an efficient point-like signal detection tool for various types of biological 3D image data.

  • 4.
    Allalou, Amin
    et al.
    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.
    van de Rijke, Frans
    Jahangir Tafrechi, Roos
    Raap, Anton
    Wählby, Carolina
    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.
    Image based measurements of single cell mtDNA mutation load MTD 20072007In: Medicinteknikdagarna 2007, 2007Conference paper (Other (popular science, discussion, etc.))
    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. These differences among cells in a population may be essential to quantify when looking at, e.g., protein expression and mutations in tumor cells which often show high degree of heterogeneity.

    Single nucleotide mutations in the mithochondrial DNA (mtDNA) can accumulate and later be present in large proportions of the mithocondria causing devastating diseases. To study mtDNA accumulation and segregation one needs to measure the amount of mtDNA mutations in each cell in multiple serial cell culture passages. The different degrees of mutation in a cell culture can be quantified by making measurements on individual cells as an alternative to looking at an average of a population. Fluorescence microscopy in combination with automated digital image analysis provides an efficient approach to this type of single cell analysis.

    Image analysis software for these types of applications are often complicated and not easy to use for persons lacking extensive knowledge in image analysis, e.g., laboratory personnel. This paper presents a user friendly implementation of an automated method for image based measurements of mtDNA mutations in individual cells detected with padlock probes and rolling-circle amplification (RCA). The mitochondria are present in the cell’s cytoplasm, and here each cytoplasm has to be delineated without the presence of a cytoplasmic stain. 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%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.

  • 5.
    Allalou, Amin
    et al.
    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.
    van de Rijke, Frans M.
    Jahangir Tafrechi, Roos
    Raap, Anton K.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Image Based Measurements of Single Cell mtDNA Mutation Load2007In: Image Analysis, Proceedings / [ed] Ersboll BK, Pedersen KS, 2007, p. 631-640Conference paper (Refereed)
    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 image based measurements of mitochondiral DNA (mtDNA) mutations in individual cells. The mitochondria are present in the cell’s cytoplasm, and each cytoplasm has to be delineated. 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%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.

  • 6.
    Allalou, Amin
    et al.
    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.
    Wählby, Carolina
    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.
    BlobFinder, a tool for fluorescence microscopy image cytometry2009In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 94, no 1, p. 58-65Article in journal (Refereed)
    Abstract [en]

    Images can be acquired at high rates with modern fluorescence microscopy hardware, giving rise to a demand for high-speed analysis of image data. Digital image cytometry, i.e., automated measurements and extraction of quantitative data from images of cells, provides valuable information for many types of biomedical analysis. There exists a number of different image analysis software packages that can be programmed to perform a wide array of useful measurements. However, the multi-application capability often compromises the simplicity of the tool. Also, the gain in speed of analysis is often compromised by time spent learning complicated software. We provide a free software called BlobFinder that is intended for a limited type of application, making it easy to use, easy to learn and optimized for its particular task. BlobFinder can perform batch processing of image data and quantify as well as localize cells and point like source signals in fluorescence microscopy images, e.g., from FISH, in situ PLA and padlock probing, in a fast and easy way.

  • 7.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Signal Detection in 3D by Stable Wave Signal VerificationIn:  Proceedings of SSBA 2009Conference paper (Other academic)
    Abstract [en]

    Detection and localization of point-source signals is an important task in many image analysis applications. These types of signals can commonly be seen in fluorescent microscopy when studying functions of biomolecules. Visual detection and localization of point-source signals in 3D is limited and time consuming, making automated methods an important task. The 3D Stable Wave Detector (3DSWD) is a new method that combines signal enhancement with a verifier/separator. The verifier/separator examines the intensity gradient around a signal, making the detection less sensitive to noise and better at separating spatially close signals. Conventional methods such as; TopHat, Difference of Gaussian, and Multiscale Product consist only of signal enhancement. In this paper we compare the 3DSWD to these conventional methods with and without the addition of a verifier/separator. We can see that the 3DSWD has the highest robustness to noise among all the methods and that the other methods are improved when a verifier/separator is added.

  • 8.
    Allalou, Amin
    et al.
    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.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    van de Rijke, Frans
    Jahangir Tafrechi, Roos
    Raap, Anton
    Segmentation of Cytoplasms of Cultured Cells2007In: In Proceedings SSBA 2007, Symposium on image analysis, Linköping, 2007Conference 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.

  • 9.
    Almgren, K.M
    et al.
    STFI-Packforsk AB.
    Gamstedt, E.K.
    Department of Polymer and Fibre Technology, Royal Institute of Technology .
    Nygård, P.
    PFI Paper and Fibre Research Institute.
    Malmberg, Filip
    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.
    Lindblad, Joakim
    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.
    Lindström, M.
    STFI-Packforsk AB.
    Role of fibre–fibre and fibre–matrix adhesion in stress transfer in composites made from resin-impregnated paper sheets2009In: International Journal of Adhesion and Adhesives, ISSN 0143-7496, E-ISSN 1879-0127, Vol. 29, no 5, p. 551-557Article in journal (Refereed)
    Abstract [en]

    Paper-reinforced plastics are gaining increased interest as packaging materials, where mechanical properties are of great importance. Strength and stress transfer in paper sheets are controlled by fibre–fibre bonds. In paper-reinforced plastics, where the sheet is impregnated with a polymer resin, other stress-transfer mechanisms may be more important. The influence of fibre–fibre bonds on the strength of paper-reinforced plastics was therefore investigated. Paper sheets with different degrees of fibre–fibre bonding were manufactured and used as reinforcement in a polymeric matrix. Image analysis tools were used to verify that the difference in the degree of fibre–fibre bonding had been preserved in the composite materials. Strength and stiffness of the composites were experimentally determined and showed no correlation to the degree of fibre–fibre bonding, in contrast to the behaviour of unimpregnated paper sheets. The degree of fibre–fibre bonding is therefore believed to have little importance in this type of material, where stress is mainly transferred through the fibre–matrix interface.

  • 10.
    Ammenberg, P.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Analysis of CASI Data - A Case Study From the Archipelago of Stockholm, Sweden2001In: 6th International Conference, Remote Sensing for Marine and Coastal Environments 2000, Charleston, South Caro, 2001, p. 8 pages-Conference paper (Other scientific)
  • 11.
    Ammenberg, P.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Analysis of CASI data - A case study from the archipelago of Stockholm, Sweden2000In: 6th International Conference, Remote Sensing for Marine and CoastalEnvironments, Charleston, South Carolina, USA, 2000Conference paper (Other scientific)
  • 12.
    Ammenberg, P.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Evolution, Limnology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Flink, P
    Lindell, T.
    Strömbeck, N.
    Bio-optical Modelling Combined with Remote Sensing to Assess Water Quality2002In: International Journal of Remote Sensing, ISSN 0143-1161, Vol. 23, no 8, p. 1621-1638Article in journal (Refereed)
  • 13.
    Ammenberg, Petra
    et al.
    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.
    Lindell, Tommy
    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.
    Automated change detection of bleached coral reef areas2002In: Proceedings of 7th International Conference, Remote Sensing for Marine and Coastal Environments, 2002Conference paper (Other academic)
    Abstract [en]

    Recent dramatic bleaching events on coral reefs have enhanced the need for global environmental monitoring. This paper investigates the value of present high spatial resolution satellites to detect coral bleaching using a change detection technique. We compared an IRS LISS-III image taken during the 1998 bleaching event in Belize to images taken before the bleaching event. The sensitivity of the sensors was investigated and a simulation was made to estimate the effect of sub-pixel changes. A manual interpretation of coral bleaching, based on differences between the images, was performed and the outcome were compared to field observations. The spectral characteristics of the pixels corresponding to the field observations and the manually interpreted bleachings have been analysed and compared to pixels from unaffected areas.

  • 14.
    Andersson, JLR
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Thurfjell, Lennart
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A multivariate approach to registration of dissimilar tomographic images1999In: European Journal of Nuclear Medicine, ISSN 0340-6997, E-ISSN 1432-105X, Vol. 26, no 7, p. 718-733Article in journal (Refereed)
    Abstract [en]

    We devised a method to allow for retrospective registration of tomographic images with very different information content, the main emphasis being on sets of positron emission tomography images obtained with different tracers. A multivariate cost-function

  • 15.
    Andersson, JLR
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Thurfjell, Lennart
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Implementation and validation of a fully automatic system for intra- and interindividual registration of PET brain scans1997In: Journal of computer assisted tomography, ISSN 0363-8715, E-ISSN 1532-3145, Vol. 21, no 1, p. 136-144Article in journal (Other academic)
    Abstract [en]

    Purpose: Stereotactic coordinate spaces and methods to adapt subjects to that space are required when performing averaging of functional studies across subjects. Methods: A rapid and fully automatic method to perform intersubject registration and adaptati

  • 16. Arcelli, Carlo
    et al.
    Sanniti di Baja, Gabriella
    Svensson, Stina
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Computing and analysing convex deficiencies to characterise 3D complex objects2005In: Image and Vision Computing: Discrete Geometry for Computer Imagery, Vol. 23, no 2, p. 203-211Article in journal (Refereed)
    Abstract [en]

    Entities such as object components, cavities, tunnels and concavities in 3D digital images can be useful in the framework of object analysis. For each object component, we first identify its convex deficiencies, by subtracting the object component from a covering polyhedron approximating the convex hull. Watershed segmentation is then used to decompose complex convex deficiencies into simpler parts, corresponding to individual cavities, concavities and tunnels of the object component. These entities are finally described by means of a representation system accounting for the shape features characterising them.

  • 17.
    Aronsson, M.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, G.
    2D Segmentation and Labelling of Clustered Ring-Shaped Objects2001Conference paper (Refereed)
    Abstract [en]

    A robust segmentation and labelling method to identify individual ring shaped

  • 18.
    Aronsson, M.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Fayyazi, A.
    Comparison of two different approaches for paper volume assembly2000In: Symposium on Image Analysis - SSAB 2000, 2000, p. 57-60Conference paper (Other scientific)
  • 19.
    Aronsson, M.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Larsson, K.-A.
    Titta inuti papper -- Looking inside Paper2001In: Nordisk Papper och Massa, no 2, p. 44-45Article in journal (Other scientific)
  • 20.
    Aronsson, Mattias
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Estimating Fibre Twist and Aspect Ratios in 3D Voxel Volumes2002In: International Conference on Pattern Recognition (ICPR'02), 2002Conference paper (Refereed)
  • 21.
    Aronsson Mattias, Henningsson Olle, Sävborg Örjan
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Slice-based Digital Volume Assembly of a Small Paper Sample2002In: Nordic Pulp and Paper Research Journal, Vol. 17, no 1Article in journal (Refereed)
    Abstract [en]

    Digital volume images can be created by assembling a stack of 2D images. By using a microtome for slicing, a Scanning Electron Microscope for imaging and digital analysis tools, we were able to create a small digital volume from a paper sample of Duplex-b

  • 22.
    Aronsson Mattias, Sintorn Ida-Maria
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Ring Shaped Object Detector for Non-Isotropic 2D Images Using Optimized Distance Transform Weights2002Conference paper (Refereed)
    Abstract [en]

    A detector for finding ring shaped objects occurring in clus-ters in 2D images with non-isotropic pixel dimensions have been developed. The rings are characterized as having a closed border and a void interior. We assume that the thick-ness of the rings s

  • 23.
    Aronsson, Mattias
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Svensson, Stina
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Curvature Measurements for fibres in 3D Images of Paper2002In: Proceedings SSAB'02 Symposium on Image Analysis, 2002, p. 165-168Conference paper (Other scientific)
    Abstract [en]

    When analysing fibres in paper using computerised image analysis applied to 3D i mages of paper, one measure of interest is the curvature along each individual fibre and how the curvature changes due to interaction with adjacent fibres. Starting from a cu

  • 24.
    Axelsson, Maria
    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.
    3D Tracking of Cellulose Fibres in Volume Images2007In: IEEE International Conference on Image Processing, 2007. ICIP 2007., 2007, p. IV-309Conference paper (Refereed)
    Abstract [en]

    Segmentation of individual fibres in volume images is important when analysing the three dimensional (3D) fibre structure in paper and cellulose based composite materials. This paper presents a novel method for 3D tracking of individual fibres which can be used as a pre-segmentation step to a full cell wall segmentation or be used to estimate the fibre orientation. The tracking starts in one seed in each fibre and automatically extracts the local fibre orientation and the fibre centre point in each step using 3D information. Good results are obtained for cellulose fibres that are partially collapsed, cracked or irregularly shaped. The proposed method can also be used in other applications where tracking of tubular structures is of interest.

  • 25.
    Axelsson, Maria
    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.
    An evaluation of scale and noise sensitivity of fibre orientation estimation in volume images2009In: Image Analysis and Processing - ICIAP 2009, Berlin: Springer , 2009, p. 975-984Conference paper (Refereed)
  • 26.
    Axelsson, Maria
    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.
    Estimating 3D Fibre Orientation in Volume Images2008In: Proceedings of the 19th International Conference on Pattern Recognition, IEEE, 2008Conference paper (Refereed)
    Abstract [en]

    Fibre orientation is an important structural property of fibre-based materials. For example, in paper the orientation of the fibres influences the dimensional strength of the sheet and the tendency of the sheet to curl and twist at moisture changes. Here, we present a threedimensional image analysis method for estimating the fibre orientation and the orientation anisotropy. The proposed method can be applied directly to greyscale volume images and is based on local orientation estimates using quadrature filters and structure tensors. From the tensor field the fibre orientation can be estimated together with a corresponding certainty measurement. Good results are obtained for both synthetic fibre data sets and fibre based materials imaged using X-ray microtomography.

  • 27.
    Axelsson, Maria
    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.
    Tracking Tubular Structures in Volume Image Data2008In: Proceedings SSBA 2008: Symposium on Image Analysis, Lund, March 12-14, 2008, 2008, p. 51-54Conference paper (Other academic)
  • 28.
    Axelsson, Maria
    et al.
    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.
    Chinga, Gary
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Nygård, Per
    Malmberg, Filip
    Solheim, Olav
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Detailed quantification of the 3D structure of newsprints in X-ray synchrotron radiation microtomography images2006In: Progress in Paper Physics Seminar, Oxford, Ohio, 2006, 2006Conference paper (Other academic)
  • 29.
    Axelsson, Maria
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Sintorn, Ida-Maria
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Svensson, Stina
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Individual pore segmentation in 3D volumes of fibrous materials2005In: SSBA Symposium on Image Analysis 2005, 2005Conference paper (Other scientific)
  • 30.
    Axelsson, Maria
    et al.
    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.
    Svensson, Stina
    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.
    3D pore structure characterisation of paper2010In: Pattern Analysis and Applications, ISSN 1433-7541, E-ISSN 1433-755X, Vol. 13, no 2, p. 159-172Article in journal (Refereed)
    Abstract [en]

    Pore structure characterisation of paper, using automated image analysis methods, has previously been performed in two-dimensional images. Three dimensional (3D) images have become available and thereby new representations and corresponding measurements are needed for 3D pore structure characterisation. In this article, we present a new pore structure representation, the individual pore-based skeleton, and new quantitative measurements for individual pores in 3D, such as surface area, orientation, anisotropy, and size distributions. We also present measurements for network relations, like tortuosity and connectivity. The data used to illustrate the pore structure representations and corresponding measurements are high resolution X-ray microtomography volume images of a layered duplex board imaged at the European Synchrotron Radiation Facility (ESRF). Quantification of the pore structure is exemplified and the results show that differences in pore structure between the layers in the cardboard can be characterised using the presented methods.

  • 31.
    Axelsson, Maria
    et al.
    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.
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Reduction of Ring Artifacts in High Resolution X-Ray Microtomography Images2006In: Pattern Recognition: 28th DAGM Symposium, Berlin, Germany, September 2006, Proceedings, 2006, p. 61-70Conference paper (Refereed)
    Abstract [en]

    Ring artifacts can occur in reconstructed images from X-ray microtomography as full or partial circles centred on the rotation axis. In this paper, a 2D method is proposed that reduces these ring artifacts in the reconstructed images. The method consists of two main parts. First, the artifacts are localised in the image using local orientation estimation of the image structures and filtering to find ring patterns in the orientation information. Second, the map of the located artifacts is used to calculate a correction image using normalised convolution. The method is evaluated on 2D images from volume data of paper fibre imaged at the European Synchrotron Radiation Facility (ESRF) with high resolution X-ray microtomography. The results show that the proposed method reduces the artifacts and restores the pixel values for all types of partial and complete ring artifacts where the signal is not completely saturated.

  • 32.
    Axelsson, Maria
    et al.
    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.
    Östlund, Catherine
    Vomhoff, Hannes
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Estimation of the pore volume at the interface between paper web and press felt2006In: Nordic Pulp & Paper Research Journal, ISSN 0283-2631, E-ISSN 2000-0669, Vol. 21, no 3, p. 395-402Article in journal (Refereed)
    Abstract [en]

    A method for determining the water content at the interface between a press felt and a paper web has been developed. The water content was obtained by subtracting the estimated volume of the indented fibre web from the measured felt surface porosity of the press felt. The felt surface porosity was calculated from a topography map that was imaged with a Confocal Laser Scanning Microscope (CLSM) method. Here, the press felt was compressed against a smooth surface using a stress in the range of 0 to 10 MPa. Artefacts in the CLSM images were reduced using an image analysis method. The indentation of paper webs into the measured felt surface pores at different applied pressures was estimated using another image analysis method, simulating a rolling ball, with different radii of curvature for the different pressures and grammages, rolling over the felt surface. The ball radii were determined for a low and a high grammage web using the STFI-Packforsk Dewatering model. The method was evaluated in a case study with four press felts that had batt fibre diameters in a range between 22 and 78 μm. The indentation was calculated for webs with a low (15 g/m2) and a high grammage (105 g/m2), respectively. The evaluation showed that a considerable amount of porespace is available at the interface between the web and the felt. In most cases, the volume of the water-filled pores accounted for approximately 50% of the total surface porosity of the felt. Assuming a complete water saturation of the web/felt interface, approximately 10 g/m2 of water for the finest felt surface up to 40 g/m2 for the coarsest felt surface, could be located at the interface between the press felt and the paper web at a load of 10 MPa. This implies that a considerable amount of water is available for separation rewetting.

  • 33.
    Axelsson, Maria
    et al.
    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.
    Östlund, Catherine
    Vomhoff, Hannes
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Volume estimation of the interface pores between paper web and press felt2006In: Proceedings SSBA 2006: Symposium on Image Analysis, 2006Conference paper (Other academic)
  • 34.
    Ballerini, L.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A Simple Method to Measure Homogeneity of Fat Distribution in Meat2001Conference paper (Refereed)
    Abstract [en]

    Fat distribution is an important criterium for meat quality evaluation and

  • 35.
    Ballerini, L.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Detection and quantification of foveal avascular zone alterations in diabetic retinopathy2000In: 1st Int. Workshop on Computer Assisted Fundus Image Analysis (CAFIA), 2000Conference paper (Refereed)
    Abstract [en]

    In this work a computational approach for detecting and quantifying diabetic

  • 36.
    Ballerini, L.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Determination of fat content in NMR images of meat2000Conference paper (Refereed)
    Abstract [en]

    In this paper we present an application to food science of image processing

  • 37.
    Ballerini, L.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Determination of fat contents in NMR images of meat: preliminary results2000In: Symposium on Image Analysis - SSAB 2000, 2000, p. 79-82Conference paper (Other scientific)
  • 38.
    Ballerini, L.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Genetic Snakes for Color Image Segmentation2001Conference paper (Refereed)
    Abstract [en]

    The world of meat faces a permanent need for new methods of meat quality

  • 39.
    Ballerini, L.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    How Do People Choose Meat?2001In: Swedish Society for Automated Image Analysis Symposium - SSAB 2001,ITN, Campus Norrköping, LinköpingUniversity, 2001, p. 119-122Conference paper (Other scientific)
  • 40.
    Ballerini, L.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Image Analysis for the Food Industry: Digital Camera Photographs and Nuclear Magnetic Resonance Images2001In: Electronic Imaging, Vol. 11, no 2, p. 7-Article in journal (Refereed)
  • 41.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Barone, L.T.
    Bianchetti, M.
    Monforti Ferrario, F.
    Sacca', F.
    Usai, C.
    Cervelli in fuga (Brains on the run - Stories of Italian researchers fled abroad)2001Book (Other scientific)
  • 42.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bocchi, L.
    A Fractal Approach to Predict Fat Content in Meat Images2001Conference paper (Refereed)
    Abstract [en]

    Intramuscular fat content in meat influences some important meat quality

  • 43.
    Ballerini. L., Bocchi
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    L.,
    Segmentation of liver images by texture and genetic snakes2002Conference paper (Refereed)
  • 44.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bocchi, L.
    Hullberg, A.
    Determination of Pores in Pig Meat Images2002In: International Conference on Computer Vision and Graphics, Zakopane, Poland, 2002, p. 70-78Conference paper (Refereed)
    Abstract [en]

    In this paper we present an image processing application for

  • 45.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, G.
    Theory and Applications of Image Analysis at the Centre for Image Analysis2001In: 5th Korea-Germany JointWorkshop on Advanced Medical Image Processing, Seoul, Korea, 2001Conference paper (Other scientific)
  • 46.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Hullberg, A.
    Determination of holes in pig meat images2002In: Proceedings SSAB'02 Symposium on Image Analysis, 2002, p. 53-56Conference paper (Other scientific)
    Abstract [en]

    In this paper we present an image processing application for

  • 47.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Högberg, A.
    How Do People Choose Meat?2001Conference paper (Refereed)
    Abstract [en]

    In this paper we present a survey carried out to understand the choice of

  • 48.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Högberg, A.
    Borgefors., G.
    Bylund, A.-C.
    Lindgård, A.
    Lundström, K.
    Rakotonirainy, O.
    Soussi, B.
    A Segmentation Technique to Determine Fat Content in NMR Images of Beef Meat2002In: IEEE Transactions on Nuclear Science, Vol. 49, no 1, p. 195-199Article in journal (Refereed)
    Abstract [en]

    The world of meat faces a permanent need for new methods of meat

  • 49.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Högberg, A.
    Borgefors, G.
    Bylund, A.-C.
    Lindgård, A.
    Lundström, K.
    Rakotonirainy, O.
    Soussi, B.
    Testing MRI and image analysis techniques for fat quantification in meat science2000Conference paper (Refereed)
    Abstract [en]

    The world of meat faces a permanent need for new methods of meat quality

  • 50.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Högberg, A.
    Lundström, K.
    Borgefors, G.
    Colour Image Analysis Technique for Measuring of Fat in Meat: An Application forthe Meat Industry2001Conference paper (Refereed)
    Abstract [en]

    Intramuscular fat content in meat influences some important meat quality

1234567 1 - 50 of 645
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