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  • 251. Hall, Hardy C.
    et al.
    Fakhrzadeh, Azadeh
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Fischer, Urs
    Precision automation of cell type classification and sub-cellular fluorescence quantification from laser scanning confocal images2016In: Frontiers in Plant Science, ISSN 1664-462X, E-ISSN 1664-462X, Vol. 7, article id 119Article in journal (Refereed)
    Abstract [en]

    While novel whole-plant phenotyping technologies have been successfully implemented into functional genomics and breeding programs, the potential of automated phenotyping with cellular resolution is largely unexploited. Laser scanning confocal microscopy has the potential to close this gap by providing spatially highly resolved images containing anatomic as well as chemical information on a subcellular basis. However, in the absence of automated methods, the assessment of the spatial patterns and abundance of fluorescent markers with subcellular resolution is still largely qualitative and time-consuming. Recent advances in image acquisition and analysis, coupled with improvements in microprocessor performance, have brought such automated methods within reach, so that information from thousands of cells per image for hundreds of images may be derived in an experimentally convenient time-frame. Here, we present a MATLAB-based analytical pipeline to (1) segment radial plant organs into individual cells, (2) classify cells into cell type categories based upon Random Forest classification, (3) divide each cell into sub-regions, and (4) quantify fluorescence intensity to a subcellular degree of precision for a separate fluorescence channel. In this research advance, we demonstrate the precision of this analytical process for the relatively complex tissues of Arabidopsis hypocotyls at various stages of development. High speed and robustness make our approach suitable for phenotyping of large collections of stem-like material and other tissue types.

  • 252.
    Hall, Håkan
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Preclinical PET Platform.
    Takahashi, Kayo
    Center for Molecular Imaging Science, Kobe, Japan.
    Erlandsson, Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC.
    Estrada, Sergio
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Preclinical PET Platform.
    Razifar, Pasha
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Bergström, Elisabeth
    Uppsala Imanet, Uppsala, Sweden.
    Långström, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Physical Organic Chemistry.
    Pharmacological characterization of 18F-labeled vorozole analogs2012In: Journal of labelled compounds & radiopharmaceuticals, ISSN 0362-4803, E-ISSN 1099-1344, Vol. 55, no 14, p. 484-490Article in journal (Refereed)
    Abstract [en]

    Two F-18-labeled analogs of vorozole ([F-18]FVOZ and [F-18]FVOO) have been developed as potential tools for the in vivo characterization of aromatase. The pharmacologicalproperties of these radioligands were evaluated using in vitro binding and in vivo distribution studies in the rat and primate. Saturation binding studies using rat ovary gave K-D and B-max values of 0.21 +/- 0.1 nM and 210 +/- 20 fmol/mg, respectively, for [F-18]FVOZ, and 7.6 +/- 1nMand 293 +/- 12fmol/mg, respectively, for [F-18]FVOO. Organ distribution studies in rats showed the highest accumulation in the adrenal glands, with standardized uptake values (SUVs) of 15 to 20, followed by ovaries and liver with SUVs of approximately 5. Ex vivo and in vitro autoradiography of the rat brain showed specific binding of both [F-18]FVOZ and [F-18]FVOO mainly in the amygdala. Positron emission tomography (PET) studies were performed in the Rhesus monkey, and these showed displaceable binding in the amygdala and the hypothalamus preoptic area. The PET images were also analyzed using masked volume-wise principal component analysis. These studies suggest that [F-18]FVOZ might be a suitable tracer for the study of aromatase in vitro and in vivo, and could be an alternative to [C-11]vorozole in human PET studies.

  • 253. Hall, Lynne
    et al.
    Hume, Colette
    Tazzyman, Sarah
    Deshmukh, Amol
    Janarthanam, Srinivasan
    Hastie, Helen
    Aylett, Ruth
    Castellano, Ginevra
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Papadopoulos, Fotios
    Jones, Aidan
    Corrigan, Lee J.
    Paiva, Ana
    Alves-Oliveira, Patrícia
    Ribeiro, Tiago
    Barendregt, Wolmet
    Serholt, Sofia
    Kappas, Arvid
    Map reading with and empathic robot tutor2016In: Proc. 11th ACM/IEEE International Conference on Human Robot Interaction, Piscataway, NJ: IEEE Press, 2016, p. 567-567Conference paper (Refereed)
  • 254.
    Hamid Muhammed, Hamed
    et al.
    School of Technology and Health (STH), Royal Institute of Technology (KTH), Alfred Nobels Alle 10, SE-141 52 Huddinge, Sweden.
    Azar, Jimmy C
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Automatic Characterization of the Physiological Condition of the Carotid Artery in 2D Ultrasound Image Sequences Using Spatiotemporal and Spatiospectral 2D Maps.2014In: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, Vol. 2014, article id 876267Article in journal (Refereed)
    Abstract [en]

    A novel method for characterizing and visualizing the progression of waves along the walls of the carotid artery is presented. The new approach is noninvasive and able to simultaneously capture the spatial and the temporal propagation of wavy patterns along the walls of the carotid artery in a completely automated manner. Spatiotemporal and spatiospectral 2D maps describing these patterns (in both the spatial and the frequency domains, resp.) were generated and analyzed by visual inspection as well as automatic feature extraction and classification. Three categories of cases were considered: pathological elderly, healthy elderly, and healthy young cases. Automatic differentiation, between cases of these three categories, was achieved with a sensitivity of 97.1% and a specificity of 74.5%. Two features were proposed and computed to measure the homogeneity of the spatiospectral 2D map which presents the spectral characteristics of the carotid artery wall's wavy motion pattern which are related to the physical, mechanical (e.g., elasticity), and physiological properties and conditions along the artery. These results are promising and confirm the potential of the proposed method in providing useful information which can help in revealing the physiological condition of the cardiovascular system.

  • 255.
    Hanstorp, Anna
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sjögren, Lina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Trots ByggR så byggS det inte: En kvalitativ fallstudie av bygglovsprocessen, processledning och verktyget ByggR.2017Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the digital transformation the importance of well-adapted systems and casemanagement tools in the building permit process has increased. This study aims toexamine how Swedish municipalities’ work processes differ regarding handlingbuilding permit applications and work process development. Further, the studyinvolves the user's perspective of interacting with the case management tool,ByggR, and how the tool affects their work processes with building permits. Lastly,the study aims to differentiate how municipalities’ work with internal processes andprocess management. The underlying theoretical framework for the study consistsof socio-technical systems theories, theories on focal relationships, processmanagement and finally theories about usability in IT-systems. A qualitativeapproach has been used with two selected municipalities and the major datacollection is based on interviews with respondents in each municipality. The resultof the analysis shows that to succeed with the digital development within thebuilding permit process the supplier and the municipality need to define the jointexternal actors that influence the focal relationship. Furthermore, it appears that itwould be beneficial for municipalities work with process management in order todevelop the internal processes. Municipalities should also take advantage ofexperience and share information and knowledge between themselves. Therefore, atighter relationship and communication between municipalities is needed. Sokigoshould also focus on how to make the usage easier by developing automaticfeatures and making it easier for users to get an overview of applications in the casemanagement tool. Finally, in order to effectively develop ByggR and to streamlinethe development process, Sokigo should to try to converge requirements fromseveral municipalities simultaneously.

  • 256.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    How to Promote Student Creativity and Learning using Tutorials in Teaching Graphics and Visualisation2014In: Proc. 16th International Conference on Geometry and Graphics, Innsbruck University Press, 2014, p. 626-633Conference paper (Other academic)
  • 257.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    How to promote student creativity and learning using tutorials in teaching graphics and visualisation2014In: Journal for Geometry and Graphics, ISSN 1433-8157, Vol. 18, no 2, p. 237-245Article in journal (Refereed)
    Abstract [en]

    Course assignments play an important role in the learning process. However, they can be constructed in such a way that they prohibit creativity, rather than promoting it. Therefore it was investigated how programming assignments are set up that students encounter in computer science education and which approach could help the students in problem solving and whether these would help or prohibit them to be creative or not. Especially, an online tutorial about visualisation using VTK and Python was used as an example in different courses on visualisation. It was also examined how students in the computer graphics courses that did not have access to such tutorial answered questions about assignments. 

  • 258.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Interest Point Detection Based on the Extended Structure Tensor with a Scale Space Parameter2015In: International Conference on Computer Vision Theory and Applications, 2015, p. 1-8Conference paper (Refereed)
  • 259.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Mathematics + Computer Science = True2015Conference paper (Refereed)
  • 260.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Robust and Invariant Phase Based Local Feature Matching2014In: 22nd International Conference on Pattern Recognition (ICPR), 2014, 2014, p. 809-814Conference paper (Refereed)
    Abstract [en]

    Any feature matching algorithm needs to be robust, producing few false positives but also needs to be invariant to changes in rotation, illumination and scale. Several improvements are proposed to a previously published Phase Correlation based algorithm, which operates on local disc areas, using the Log Polar Transform to sample the disc neighborhood and the FFT to obtain the phase. It will be shown that the matching can be done in the frequency domain directly, using the Chi-squared distance, instead of computing the cross power spectrum. Moreover, it will be shown how combining these methods yields an algorithm that sorts out a majority of the false positives. The need for a peak to sub lobe ratio computation in order to cope with sub pixel accuracy will be discussed as well as how the FFT of the periodic component can enhance the matching. The result is a robust local feature matcher that is able to cope with rotational, illumination and scale differences to a certain degree.

  • 261.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Simple filter design for first and second order derivatives by a double filtering approach2014In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 42, p. 65-71Article in journal (Refereed)
    Abstract [en]

    Spline filters are usually implemented in two steps, where in the first step the basis coefficients are computed by deconvolving the sampled function with a factorized filter and the second step reconstructs the sampled function. It will be shown how separable spline filters using different splines can be constructed with fixed kernels, requiring no inverse filtering. Especially, it is discussed how first and second order derivatives can be computed correctly using cubic or trigonometric splines by a double filtering approach giving filters of length 7.

  • 262.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Towards Automatic Stereo Pair Extraction for 3D Visualisation of Historical Aerial Photographs2014In: IC3D, the International Conference on 3D Imaging, 2014, p. 1-8Conference paper (Refereed)
    Abstract [en]

    An efficient and almost automatic method for stereo pair extraction of aerial photos is proposed. There are several challenging problems that needs to be taken into consideration when creating stereo pairs from historical aerial photos. These problems are discussed and solutions are proposed in order to obtain an almost automatic procedure with as little input as possible needed from the user.  The result is a rectified and illumination corrected stereo pair. It will be discussed why viewing aerial photos in stereo is important since the depth cue gives more information than single photos do.

  • 263.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Capurro, Carlotta
    Nollet, Dries
    Pletinckx, Daniel
    Estevez, B.
    Pazos, M.
    Franco, J. M.
    Marchetti, Andrea
    Stereo Visualisation of Historical Aerial Photos: A Useful and Important Aerial Archeology Research Tool2016Conference paper (Refereed)
  • 264.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Cullhed, Per
    Uppsala University, University Library.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    TexT – Text extractor tool for handwritten document transcription and annotation2018In: Digital Libraries and Multimedia Archives, Springer, 2018, p. 81-92Conference paper (Refereed)
    Abstract [en]

    This paper presents a framework for semi-automatic transcription of large-scale historical handwritten documents and proposes a simple user-friendly text extractor tool, TexT for transcription. The proposed approach provides a quick and easy transcription of text using computer assisted interactive technique. The algorithm finds multiple occurrences of the marked text on-the-fly using a word spotting system. TexT is also capable of performing on-the-fly annotation of handwritten text with automatic generation of ground truth labels, and dynamic adjustment and correction of user generated bounding box annotations with the word being perfectly encapsulated. The user can view the document and the found words in the original form or with background noise removed for easier visualization of transcription results. The effectiveness of TexT is demonstrated on an archival manuscript collection from well-known publicly available dataset.

  • 265.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Cullhed, Per
    Uppsala University, University Library.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Abrate, Matteo
    Making large collections of handwritten material easily accessible and searchable2019In: Digital Libraries: Supporting Open Science, Springer, 2019, p. 18-28Conference paper (Refereed)
  • 266.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Fornés, Alicia
    Univ Autonoma Barcelona, Comp Vis Ctr, Dept Comp Sci, Bellaterra, Spain.
    A segmentation-free handwritten word spotting approach by relaxed feature matching2016In: Proc. 12th IAPR Workshop on Document Analysis Systems, IEEE, 2016, p. 150-155Conference paper (Refereed)
    Abstract [en]

    The automatic recognition of historical handwritten documents is still considered a challenging task. For this reason, word spotting emerges as a good alternative for making the information contained in these documents available to the user. Word spotting is defined as the task of retrieving all instances of the query word in a document collection, becoming a useful tool for information retrieval. In this paper we propose a segmentation-free word spotting approach able to deal with large document collections. Our method is inspired on feature matching algorithms that have been applied to image matching and retrieval. Since handwritten words have different shape, there is no exact transformation to be obtained. However, the sufficient degree of relaxation is achieved by using a Fourier based descriptor and an alternative approach to RANSAC called PUMA. The proposed approach is evaluated on historical marriage records, achieving promising results.

  • 267.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hanke, Michael
    Royal Inst Technol, KTH, Dept Math, Sch Engn Sci, Stockholm, Sweden.
    Karlsson, Hans O.
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Theoretical Chemistry.
    Swedish eScience Education – a Graduate School in eScience2015In: Proc. 11th International Conference on e-Science, IEEE Computer Society, 2015, p. 31-35Conference paper (Refereed)
    Abstract [en]

    Swedish eScience Education (SeSE) is a national graduate school in eScience in Sweden. It comes from the collaboration between two major research initiatives in eScience and the school has turned out to be very successful. It has made it possible for students at different universities to get access to education that is not normally available at their home universities. With SeSE they get access to education by the top experts within their respective field. We argue why such graduate school is important and how it is different from training offered by many HPC centres in Europe. Furthermore, examples of courses and their structure is discussed as well as lessons learned from SeSE and its two predecessors in Sweden.

  • 268.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Jenke, Peter
    University of Gävle.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Shortest Diagonal Triangulation of Convex Layers2013In: The IASTED International Conference on Signal Processing, Pattern Recognition and Applications., 2013, p. 1-7Conference paper (Refereed)
  • 269.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kylberg, Gustav
    Clustering in 2D as a Fast Deterministic Alternative to RANSAC2015Conference paper (Refereed)
  • 270.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kylberg, Gustav
    Vironova AB, Stockholm, Sweden.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Vironova AB, Stockholm, Sweden.
    An efficient descriptor based on radial line integration for fast non invariant matching and registration of microscopy images2017In: Advanced Concepts for Intelligent Vision Systems, Springer, 2017, p. 723-734Conference paper (Refereed)
    Abstract [en]

    Descriptors such as SURF and SIFT contain a framework for handling rotation and scale invariance, which generally is not needed when registration and stitching of images in microscopy is the focus. Instead speed and efficiency are more important factors. We propose a descriptor that performs very well for these criteria, which is based on the idea of radial line integration. The result is a descriptor that outperforms both SURF and SIFT when it comes to speed and the number of inliers, even for rather short descriptors.

  • 271.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lind, Mats
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Embedded Prototype Subspace Classification: A subspace learning framework2019In: Computer Analysis of Images and Patterns, Springer, 2019Conference paper (Refereed)
  • 272.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lind, Mats
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Embedded Prototype Subspace Classification: A subspace learning framework2019In: Computer Analysis of Images and Patterns, Springer, 2019, p. 581-592Conference paper (Refereed)
  • 273.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lind, Mats
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Subspace Learning and Classification2019In: Proc. 3rd Swedish Symposium on Deep Learning, 2019Conference paper (Other academic)
  • 274.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    IIT, CNR.
    An Efficient Preconditioner and a Modified RANSAC for Fast and Robust Feature Matching.2012In: International Conferences in Central Europe on Computer Graphics, Visualization and Computer Vision: Communcations Paper, 2012, p. 11-18Conference paper (Refereed)
  • 275.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    Improved illumination correction that preserves medium sized objects2014In: Machine Graphics & Vision, ISSN 1230-0535, Vol. 23, no 1/2, p. 3-20Article in journal (Refereed)
  • 276.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    IIT, CNR.
    Invariant Interest Point Detection Based on Variations of the Spinor Tensor2014In: WSCG, Communication papers proceedings , ISBN 978-80-86943-71-8, 2014, p. 49-56Conference paper (Refereed)
    Abstract [en]

    Image features are obtained by using some kind of interest point detector, which often is based on a symmetric matrix such as the structure tensor or the Hessian matrix. These features need to be invariant to rotation and to some degree also to scaling in order to be useful for feature matching in applications such as image registration. Recently, the spinor tensor has been proposed for edge detection. It was investigated herein how it also can be used for feature matching and it will be proven that some simplifications, leading to variations of the response function based on the tensor, will improve its characteristics. The result is a set of different approaches that will be compared to the well known methods using the Hessian and the structure tensor. Most importantly the invariance when it comes to rotation and scaling will be compared.

  • 277.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    Institute of Informatics and Telematics, Pisa, Italy.
    Putative Match Analysis: A Repeatable Alternative to RANSAC for Matching of Aerial Images2012In: VISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications, Volume 2 / [ed] Gabriela Csurka, José Braz, SciTePress , 2012, p. 341-344Conference paper (Refereed)
    Abstract [en]

     One disadvantage with RANSAC is that it is based on randomness and will therefore often yield a different set of inliers in each run, especially if the dataset contains a large number of outliers. A repeatable algorithm for finding both matches and the homography is proposed, which in our case is used for image stitching and the obtained points are also used for georeferencing. This algorithm will yield the same set of matches every time and is therefore a useful tool when trying to evaluate other algorithms involved and their parameters. Moreover a refining step is proposed that finds the best matches depending on what geometric transformation is used, which also can be utilized as a refining step for RANSAC. 

  • 278.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    IIT, CNR.
    Rotation Invariant Feature Matching - Based on Gaussian Filtered Log Polar Transform and Phase Correlation.2013In: 8th International Symposium on Image and Signal Processing and Analysis: (ISPA 2013), 2013, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Rotation invariance is an important property for any feature matching method and it has been implemented in different ways for different methods. The Log Polar Transform has primarily been used for image registration where it is applied after phase correlation, which in its turn is applied on the whole images or in the case of template matching, applied on major parts of them followed by an exhaustive search. We investigate how this transform can be used on local neighborhoods of features and how phase correlation as well as normalized cross correlation can be applied on the result. Thus, the order is reversed and we argue why it is important to do so. We demonstrate a common problem with the log polar transform and that many implementations of it are not suitable for local feature detectors. We propose an implementation of it based on Gaussian filtering. We also show that phase correlation generally will perform better than normalized cross correlation. Both handles illumination differences well, but changes in scale is handled better by the phase correlation approach. 

  • 279.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    CNR, Ist Informat & Telemat, Pisa, Italy.
    Stereo Visualisation of Historical Aerial Photos – a Valuable Digital Heritage Research Tool2015In: 2015 Digital Heritage International Congress, Vol 2: Analysis & Interpretation Theory, Methodologies, Preservation & Standards Digital Heritage Projects & Applications, 2015, p. 663-666Conference paper (Refereed)
    Abstract [en]

    We demonstrate with several examples how historical aerial photos can benefit from being viewed in stereo and how this can be useful as tool in digital heritage research. The main reason why stereo images are important is that they give a much better understanding of what is actually in the scene than single photos can. The important factor is the depth cue that helps understanding the content and adds the ability to distinguish between objects such as houses and trees and the ground as well as estimating heights of objects. There are however still challenges but also possibilities that will be discussed.

  • 280.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    Stereo Visualisation of Historical Aerial Photos as a Valuable Tool for Archeological Research2015In: Computer Applications and Quantitative Methods in Archaeology, CAA, 2015, p. 1-3Conference paper (Refereed)
  • 281.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    The Challenges and Advantages with a Parallel Implementation of Feature Matching2016In: Proc. 11th International Conference on Computer Vision Theory and Applications, 2016Conference paper (Refereed)
  • 282.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    IIT, CNR.
    Rapisarda, Beatrice
    IIT, CNR.
    Sheperd, J
    Aerofototeca nazionale dell'Istituto centrale per il catalogo e la documentazione di Roma.
    Tesconi, Maurizio
    IIT, CNR.
    Geomemories - a Spatial-Temporal Atlas of the Italian Landscape.2011In: International Symposium on Virtual Reality, Archaeology and Cultural Heritage, 2011, p. 41-44Conference paper (Refereed)
  • 283.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Mårtensson, Lasse
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Heil, Raphaela
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Creating an Atlas over Handwritten Script Signs2019In: Digital Humanities in the Nordic Countries, 2019Conference paper (Refereed)
  • 284.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Nysjö, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Optimal RANSAC - Towards a Repeatable Algorithm for Finding the Optimal Set2013In: Journal of WSCG, ISSN 1213-6972, E-ISSN 1213-6964, Vol. 21, no 1, p. 21-30Article in journal (Refereed)
  • 285.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sablina, Victoria A.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kylberg, Gustaf
    A fast Fourier based feature descriptor and a cascade nearest neighbour search with an efficient matching pipeline for mosaicing of microscopy images2018In: Pattern Recognition and Image Analysis, ISSN 1054-6618, Vol. 28, no 2, p. 261-272Article in journal (Refereed)
  • 286.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sablina, Victoria
    Kylberg, Gustav
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    A Simple and Efficient Feature Descriptor for Fast Matching2015In: WSCG / [ed] V. Skala, 2015, p. 135-142Conference paper (Refereed)
  • 287.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    An intelligent user interface for efficient semi-automatic transcription of historical handwritten documents2018In: Proc. 23rd International Conference on Intelligent User Interfaces Companion, New York: ACM Press, 2018, article id 48Conference paper (Refereed)
    Abstract [en]

    Transcription of large-scale historical handwritten document images is a tedious task. Machine learning techniques, such as deep learning, are popularly used for quick transcription, but often require a substantial amount of pre-transcribed word examples for training. Instead of line-by-line word transcription, this paper proposes a simple training-free gamification strategy where all occurrences of each arbitrarily selected word is transcribed once, using an intelligent user interface implemented in this work. The proposed approach offers a fast and user-friendly semi-automatic transcription that allows multiple users to work on the same document collection simultaneously.

  • 288.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Radial line Fourier descriptor for historical handwritten text representation2018In: Journal of WSCG, ISSN 1213-6972, E-ISSN 1213-6964, Vol. 26, no 1, p. 31-40Article in journal (Refereed)
  • 289.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Radial line Fourier descriptor for historical handwritten text representation2018In: Proc. 26th International Conference on Computer Graphics: Visualization and Computer Vision, 2018Conference paper (Other academic)
    Abstract [en]

    Automatic recognition of historical handwritten manuscripts is a daunting task due to paper degradation over time. Recognition-free retrieval or word spotting is popularly used for information retrieval and digitization of the historical handwritten documents. However, the performance of word spotting algorithms depends heavily on feature detection and representation methods. Although there exist popular feature descriptors such as Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the invariant properties of these descriptors amplify the noise in the degraded document images, rendering them more sensitive to noise and complex characteristics of historical manuscripts. Therefore, an efficient and relaxed feature descriptor is required as handwritten words across different documents are indeed similar, but not identical. This paper introduces a Radial Line Fourier (RLF) descriptor for handwritten word representation, with a short feature vector of 32 dimensions. A segmentation-free and training-free handwritten word spotting method is studied herein that relies on the proposed RLF descriptor, takes into account different keypoint representations and uses a simple preconditioner-based feature matching algorithm. The effectiveness of the RLF descriptor for segmentation-free handwritten word spotting is empirically evaluated on well-known historical handwritten datasets using standard evaluation measures.

  • 290.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Weidendorfer, Josef
    Weiss, Jan-Philipp
    UCHPC 2012: Fifth Workshop on UnConventional High Performance Computing2013In: Euro-Par 2012: Parallel Processing Workshops, Springer Berlin/Heidelberg, 2013, Vol. 7640, p. 505-506Conference paper (Refereed)
  • 291.
    Heil, Raphaela
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Exploring the Applicability of Capsule Networks for WordSpotting in Historical Handwritten Manuscripts2018Conference paper (Other academic)
  • 292.
    Heil, Raphaela
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Word Spotting in Historical Handwritten Manuscripts using Capsule Networks2018Conference paper (Other academic)
    Abstract [en]

    Word spotting is popularly used for digitisation and transcription of historical handwritten documents. Recently, deep learning based methods have dominated the current state-of-the-art in learning-based word spotting. However, deep learning architectures such as Convolutional Neural Networks (CNNs) require a large amount of training data, and suffer from translation invariance. Capsule Networks (CapsNet) have been recently introduced as a data-efficient alternative to CNNs. This work explores the applicability of CapsNets for segmentation-based word spotting, and is the first such effort in the Handwritten Text Recognition (HTR) community to the best of authors' knowledge. The effectiveness of CapsNets will be empirically evaluated on well-known historical handwritten datasets using standard evaluation measures. The impact of varying amounts of training data on the recognition performance will be investigated, along with a comparison with the state-of-the-art methods.

  • 293. Hesse, Bernhard
    et al.
    Langer, Max
    Varga, Peter
    Pacureanu, Alexandra
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Dong, Pei
    Schrof, Susanne
    Maennicke, Nils
    Suhonen, Heikki
    Olivier, Cecile
    Maurer, Peter
    Kazakia, Galateia J.
    Raum, Kay
    Peyrin, Francoise
    Alterations of Mass Density and 3D Osteocyte Lacunar Properties in Bisphosphonate- Related Osteonecrotic Human Jaw Bone, a Synchrotron mu CT Study2014In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 2, p. e88481-Article in journal (Refereed)
    Abstract [en]

    Osteonecrosis of the jaw, in association with bisphosphonates (BRONJ) used for treating osteoporosis or cancer, is a severe and most often irreversible side effect whose underlying pathophysiological mechanisms remain largely unknown. Osteocytes are involved in bone remodeling and mineralization where they orchestrate the delicate equilibrium between osteoclast and osteoblast activity and through the active process called osteocytic osteolysis. Here, we hypothesized that (i) changes of the mineralized tissue matrix play a substantial role in the pathogenesis of BRONJ, and (ii) the osteocyte lacunar morphology is altered in BRONJ. Synchrotron mu CT with phase contrast is an appropriate tool for assessing both the 3D morphology of the osteocyte lacunae and the bone matrix mass density. Here, we used this technique to investigate the mass density distribution and 3D osteocyte lacunar properties at the sub-micrometer scale in human bone samples from the jaw, femur and tibia. First, we compared healthy human jaw bone to human tibia and femur in order to assess the specific differences and address potential explanations of why the jaw bone is exclusively targeted by the necrosis as a side effect of BP treatment. Second, we investigated the differences between BRONJ and control jaw bone samples to detect potential differences which could aid an improved understanding of the course of BRONJ. We found that the apparent mass density of jaw bone was significantly smaller compared to that of tibia, consistent with a higher bone turnover in the jaw bone. The variance of the lacunar volume distribution was significantly different depending on the anatomical site. The comparison between BRONJ and control jaw specimens revealed no significant increase in mineralization after BP. We found a significant decrease in osteocyte-lacunar density in the BRONJ group compared to the control jaw. Interestingly, the osteocyte-lacunar volume distribution was not altered after BP treatment.

  • 294. Hesse, Bernhard
    et al.
    Maennicke, Nils
    Pacureanu, Alexandra
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Varga, Peter
    Langer, Max
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Maurer, Peter
    Peyrin, Francoise
    Raum, Kay
    Accessing osteocyte lacunar geometrical properties in human jaw bone on the submicron length scale using synchrotron radiation mu CT2014In: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 255, no 3, p. 158-168Article in journal (Refereed)
    Abstract [en]

    The architectural properties of the osteocyte cell network provide a valuable basis for understanding the mechanisms of bone remodelling, mineral homeostasis, ageing and pathologies. Recent advances in synchrotron microtomography enable unprecedented three-dimensional imaging of both the bone lacunar network and the extracellular matrix. Here, we investigate the three-dimensional morphological properties of osteocyte lacunae in human healthy and bisphosphonate-related osteonecrotic jaw bone based on synchrotron X-ray computed tomography images, with a spatial isotropic voxel size of 300 nm. Bisphosphonate-related osteonecrosis of the jaw is a relatively new disease with increasing incidence, which remains poorly understood. A step forward in elucidating this malady is to assess whether, and how, the morphology of the osteocyte lacunar network is modified in the affected jaw tissue. We evaluate thousands of cell lacunae from five specimens of which three originate from patients diagnosed with bisphosphonate-associated osteonecrosis. In this exploratory study, we report three-dimensional quantitative results on lacunar volumes (296-502 mu m(3)), shape (approximated by an ellipsoidal shape with principal axes a > b > c, such that a = 2.2b and a = 4c) and spatial distribution (i.e., 50% of the mineralized matrix volume is located within 12 mu m to the closest lacunar boundary) at submicron resolution on such specimens. We observe that the average lacunar volumes of the bisphosphonate-related osteonecrotic jaw specimens were within the range of volumes found in the two specimens originating from healthy donors and conclude that lacunar volumes are not the key element in the course of bisphosphonate-related osteonecrotic jaw. In three out of five specimens we observe lacunar volume sizes in segmented osteons to be significantly different compared to lacunar volumes in the adjacent tissue regions. Furthermore, we quantify the number of lacunae containing small dense objects (on average 9%). In contrast to lacunar morphology we report the lacunar density (16 000-50 000 per mm(3)) to be different in jaw bone tissue compared to what has been reported in femoral sites.

  • 295.
    Hirsch, Linda
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media.
    Björsell, Anton
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media.
    Laaksoharju, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Obaid, Mohammad
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Investigating design implications towards a social robot as a memory trainer2017In: Proc. 5th International Conference on Human Agent Interaction, New York: ACM Press, 2017, p. 5-10Conference paper (Refereed)
    Abstract [en]

    Most currently existing tools for cognitive memory therapy require physical interaction or at least the presence of another person. The goal of this paper is to investigate whether a social robot might be an acceptable solution for a more inclusive therapy for people with memory disorder and severe physical limitations. Applying a user-centered design approach, we conducted semi-structured interviews with five healthcare professionals; four medical doctors and a psychologist, in three iterations followed by a focus group activity. An analysis of the collected data suggests several implications for design with an emphasis on embodiment, social skills, interaction, and memory training exercises.

  • 296. Holzwarth, Karolin
    et al.
    Köhler, Ralf
    Philipsen, Lars
    Tokoyoda, Koji
    Ladyhina, Valeriia
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Niesner, Raluca A.
    Hauser, Anja E.
    Multiplexed fluorescence microscopy reveals heterogeneity among stromal cells in mouse bone marrow sections2018In: Cytometry Part A, ISSN 1552-4922, E-ISSN 1552-4930, Vol. 93, no 9, p. 876-888Article in journal (Refereed)
  • 297.
    Huvila, Isto
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of ALM.
    Cajander, Åsa
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Daniels, Mats
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Åhlfeldt, Rose-Mharie
    Patients' perceptions of their medical records from different subject positions2015In: Journal of the Association for Information Science and Technology, ISSN 2330-1635, E-ISSN 2330-1643, Vol. 66, no 12, p. 2456-2470Article in journal (Refereed)
  • 298. Huvila, Isto
    et al.
    Daniels, Mats
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Cajander, Åsa
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Åhlfeldt, Rose-Marie
    Experiences and attitudes of patients reading their medical records: Differences between readers and recurrent readers2013In: Information: Interactions and Impact (i3) 2013, Aberdeen, UK: Robert Gordon University , 2013Conference paper (Refereed)
  • 299.
    Huvila, Isto
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of ALM.
    Daniels, Mats
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Cajander, Åsa
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Åhlfeldt, Rose-Mharie
    Patients reading their medical records: Differences in experiences and attitudes between regular and inexperienced readers2016In: Information research, ISSN 1368-1613, E-ISSN 1368-1613, Vol. 21, no 1, article id 706Article in journal (Refereed)
  • 300.
    Huvila, Isto
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of ALM.
    Eriksson-Backa, Kristina
    Moll, Jonas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Myreteg, Gunilla
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Business Studies.
    Hägglund, Maria
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health.
    Differences in the experiences of reading medical records online: Elderly, Older and Younger Adults compared2018In: Informaatiotutkimus, ISSN 1797-9129, Vol. 37, no 3, p. 51-54Article in journal (Refereed)
3456789 251 - 300 of 935
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