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  • 1. Abela, D
    et al.
    Ritchie, H
    Ababneh, D
    Gavin, C
    Nilsson, Mats F
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Niazi, M Khalid Khan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Carlsson, K
    Webster, WS
    The effect of drugs with ion channel-blocking activity on the early embryonic rat heart2010In: Birth defects research. Part B. Developmental and reproductice toxicology, ISSN 1542-9733, E-ISSN 1542-9741, Vol. 89, no 5, p. 429-440Article in journal (Refereed)
    Abstract [en]

    This study investigated the effects of a range of pharmaceutical drugs with ion channel-blocking activity on the heart of gestation day 13 rat embryos in vitro. The general hypothesis was that the blockade of the IKr/hERG channel, that is highly important for the normal functioning of the embryonic rat heart, would cause bradycardia and arrhythmia. Concomitant blockade of other channels was expected to modify the effects of hERG blockade. Fourteen drugs with varying degrees of specificity and affinity toward potassium, sodium, and calcium channels were tested over a range of concentrations. The rat embryos were maintained for 2 hr in culture, 1 hr to acclimatize, and 1 hr to test the effect of the drug. All the drugs caused a concentration-dependent bradycardia except nifedipine, which primarily caused a negative inotropic effect eventually stopping the heart. A number of drugs induced arrhythmias and these appeared to be related to either sodium channel blockade, which resulted in a double atrial beat for each ventricular beat, or IKr/hERG blockade, which caused irregular atrial and ventricular beats. However, it is difficult to make a precise prediction of the effect of a drug on the embryonic heart just by looking at the polypharmacological action on ion channels. The results indicate that the use of the tested drugs during pregnancy could potentially damage the embryo by causing periods of hypoxia. In general, the effects on the embryonic heart were only seen at concentrations greater than those likely to occur with normal therapeutic dosing.

  • 2.
    Abrate, Matteo
    et al.
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Bacciu, Clara
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    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. CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Marchetti, Andrea
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Minutoli, Salvatore
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Tesconi, Maurizio
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Geomemories - A Platform for Visualizing Historical, Environmental and Geospatial Changes of the Italian Landscape2013In: ISPRS International Journal of Geo-Information. Special issue: Geospatial Monitoring and Modelling of Environmental Change, ISSN 2220-9964, Vol. 2, no 2, p. 432-455Article in journal (Refereed)
    Abstract [en]

    The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the evolution of the Italian landscape throughout the last century. The Web portal allows comparison of recent satellite imagery with several layers of historical maps, obtained from the aerial photos through a complex workflow that merges them together. We present several case studies carried out in collaboration with geologists, historians and archaeologists, that illustrate the great potential of our system in different research fields. Experiments and advances in image processing technologies are envisaged as a key factor in solving the inherent issue of vast amounts of manual work, from georeferencing to mosaicking to analysis.

  • 3. Adinugroho, Sigit
    et al.
    Vallot, Dorothée
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
    Westrin, Pontus
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Strand, Robin
    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.
    Calving events detection and quantification from time-lapse images in Tunabreen glacier2015In: Proc. 9th International Conference on Information & Communication Technology and Systems, Piscataway, NJ: IEEE , 2015, p. 61-65Conference paper (Refereed)
  • 4.
    Al-Jaff, Mohammad
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Civil and Industrial Engineering, Industrial Engineering and Management.
    Messing With The Gap: On The Modality Gap Phenomenon In Multimodal Contrastive Representation Learning2023Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In machine learning, a sub-field of computer science, a two-tower architecture model is a specialised type of neural network model that encodes paired data from different modalities (like text and images, sound and video, or proteomics and gene expression profiles) into a shared latent representation space. However, when training these models using a specific contrastive loss function, known as the multimodalinfoNCE loss, seems to often lead to a unique geometric phenomenon known as the modality gap. This gap is a clear geometric separation of the embeddings of the modalities in the joint contrastive latent space. This thesis investigates the modality gap in multimodal machine learning, specifically in two-tower neural networks trained with multimodal-infoNCE loss. We examine the adequacy of the current definition of the modality gap, the conditions under which the modality gap phenomenon manifests, and its impact on representation quality and downstream task performance.

    The approach to address these questions consists of a two-phase experimental strategy. Phase I involves a series of experiments, ranging from toy synthetic simulations to true multimodal machine learning with complex datasets, to explore and characterise the modality gap under varying conditions. Phase II focuses on modifying the modality gap and analysing representation quality, evaluating different loss functions and their impact on the modality gap. This methodical exploration allows us to systematically dissect the emergence and implications of the modality gap phenomenon, providing insights into its impact on downstream tasks, measured with proxy metrics based on semantic clustering in the shared latent representation space and modality-specific linear probe evaluation.

    Our findings reveal that the modality gap definition proposed by W. Liang et al. 2022, is insufficient. We demonstrate that similar modality gap magnitudes can exhibit varying linear separability between modality embeddings in the contrastive latent space and varying embedding topologies, indicating the need for additional metrics to capture the true essence of the gap.

    Furthermore, our experiments show that the temperature hyperparameter in the multimodal infoNCE loss function plays a crucial role in the emergence of the modality gap, and this effect varies with different data sets. This suggests that individual dataset characteristics significantly influence the modality gap's manifestation. A key finding is the consistent emergence of modality gaps with small temperature settings in the fixed temperature mode of the loss function and almost invariably under learned temperature mode settings, regardless of the initial temperature value. Additionally, we observe that the magnitude of the modality gap is influenced by distribution shifts, with the gap magnitude increasing progressively from the training set to the validation set, then to the test set, and finally to more distributionally shifted datasets.

    We discover that the choice of contrastive learning method, temperature settings, and temperature values is crucial in influencing the modality gap. However, reducing the gap does not consistently improve downstream task performance, suggesting its role may be more nuanced than previously understood. This insight indicates that the modality gap might be a geometric by-product of the learning methods rather than a critical determinant of representation quality. Our results encourage the need to reevaluate the modality gap's significance in multimodal contrastive learning, emphasising the importance of dataset characteristics and contrastive learning methodology.

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  • 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.

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    FULLTEXT01
  • 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 Verification2009In: Proceedings of SSBA 2009, 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.
    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.

  • 9.
    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)
  • 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, Sweden2000In: 6th International Conference, Remote Sensing for Marine and CoastalEnvironments, Charleston, South Carolina, USA, 2000Conference paper (Other scientific)
  • 11.
    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)
  • 12.
    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.

  • 13.
    Andersson, Carl R.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Wahlström, Niklas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Schön, Thomas B.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Learning deep autoregressive models for hierarchical data2021In: IFAC PapersOnLine, Elsevier BV Elsevier, 2021, Vol. 54, no 7, p. 529-534Conference paper (Refereed)
    Abstract [en]

    We propose a model for hierarchical structured data as an extension to the stochastic temporal convolutional network. The proposed model combines an autoregressive model with a hierarchical variational autoencoder and downsampling to achieve superior computational complexity. We evaluate the proposed model on two different types of sequential data: speech and handwritten text. The results are promising with the proposed model achieving state-of-the-art performance.

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    fulltext
  • 14. Andersson, Jan-Olov
    et al.
    Hasselid, Sara
    Widen, Per
    Bax, Gerhard
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Environment and Landscape Dynamics. ELD.
    Is the Snow Leopard (Unica unica) endangered?: A study of popular viability and distribution using vulnerability and GIS analysis methods2004In: Proceedings of the 7th International Symposium on High Mountain Remote Sensing Cartography, 2004, p. 224-Conference paper (Refereed)
  • 15.
    Andersson, Jonathan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Radiology.
    Methods for automatic analysis of glucose uptake in adipose tissue using quantitative PET/MRI data2014Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Brown adipose tissue (BAT) is the main tissue involved in non-shivering heat production. A greater understanding of BAT could possibly lead to new ways of prevention and treatment of obesity and type 2 diabetes. The increasing prevalence of these conditions and the problems they cause society and individuals make the study of the subject important.

    An ongoing study performed at the Turku University Hospital uses images acquired using PET/MRI with 18F-FDG as the tracer. Scans are performed on sedentary and athlete subjects during normal room temperature and during cold stimulation. Sedentary subjects then undergo scanning during cold stimulation again after a six weeks long exercise training intervention. This degree project used images from this study.

    The objective of this degree project was to examine methods to automatically and objectively quantify parameters relevant for activation of BAT in combined PET/MRI data. A secondary goal was to create images showing glucose uptake changes in subjects from images taken at different times.

    Parameters were quantified in adipose tissue directly without registration (image matching), and for neck scans also after registration. Results for the first three subjects who have completed the study are presented. Larger registration errors were encountered near moving organs and in regions with less information.

    The creation of images showing changes in glucose uptake seem to be working well for the neck scans, and somewhat well for other sub-volumes. These images can be useful for identification of BAT. Examples of these images are shown in the report.

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    Andersson Methods for automatic analysis of glucose uptake in adipose tissue using quantitative PET MRI data
  • 16. Andrée, Martin
    et al.
    Paasch, Jesper M.
    Paulsson, Jenny
    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.
    BIM and 3D property visualisation2018In: Proc. FIG Congress 2018, 2018, article id 9367Conference paper (Refereed)
  • 17. 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.

  • 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.
    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

  • 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.
    Fayyazi, A.
    Comparison of two different approaches for paper volume assembly2000In: Symposium on Image Analysis - SSAB 2000, 2000, p. 57-60Conference paper (Other scientific)
  • 20.
    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)
  • 21.
    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)
  • 22.
    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

  • 23.
    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

  • 24.
    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

  • 25.
    Asai, Ryoko
    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.
    Kavathatzopoulos, Iordanis
    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.
    Robots as companions in feelings and discussions2017In: Retfærdighed – Justice, Robophilosophy / [ed] Martin Mose Bentzen, Copenhagen, 2017, p. 42-42Conference paper (Refereed)
    Abstract [en]

    Robots are used in emotional relationships. On the other hand, it is not very common to think that robots can be used as partners in a philosophical dialog. It would be challenging to find the conditions under which a robot can be one of the parts in an emotional relationship or in a Socratic dialog. Robots usable as emotional or philosophical companions need probably to function well at both dimensions, providing continuous and interchanging support for feelings and reasoning. Our aim here is not to investigate the technical possibilities for such a machine but the theoretical requirements and ethical conditions for its creation and use.

  • 26. Astruc, Marine
    et al.
    Malm, Patrik
    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.
    Kumar, Rajesh
    Bengtsson, Ewert
    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.
    Cluster detection and field-of-view quality rating: Applied to automated Pap-smear analysis2013In: Proc. 2nd International Conference on Pattern Recognition Applications and Methods, SciTePress, 2013, p. 355-364Conference paper (Refereed)
    Abstract [en]

    Automated cervical cancer screening systems require high resolution analysis of a large number of epithelial cells, involving complex algorithms, mainly analysing the shape and texture of cell nuclei. This can be a very time consuming process. An initial selection of relevant fields-of-view in low resolution images could limit the number of fields to be further analysed at a high resolution. In particular, the detection of cell clusters is of interest for nuclei segmentation improvement, and for diagnostic purpose, malignant and endometrial cells being more prone to stick together in clusters than other cells. In this paper, we propose methods aiming at evaluating the quality of fields-of-view in bright-field microscope images of cervical cells. The approach consists in the construction of neighbourhood graphs using the nuclei as the set of vertices. Transformations are then applied on such graphs in order to highlight the main structures in the image. The methods result in the delineation of regions with varying cell density and the identification of cell clusters. Clustering methods are evaluated using a dataset of manually delineated clusters and compared to a related work.

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  • 27.
    Augustsson, Louise
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Study and Analysis of Convolutional Neural Networks for Pedestrian Detection in Autonomous Vehicles2018Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The automotive industry is heading towards more automation. This puts high demands on many systems like Pedestrian Detection Systems. Such systems need to operate in real time with high accuracy and in embedded systems with limited power, memory resources and compute power. This in turn puts high demands on model size and model design. Lately Convolutional Neural Networks (ConvNets) have dominated the field of object detection and therefore it is reasonable to believe that they are suited for pedestrian detection as well. Therefore, this thesis investigates how ConvNets have been used for pedestrian detection and how such solutions can be implemented in embedded systems on FPGAs (Field Programmable Gate Arrays). The conclusions drawn are that ConvNets indeed perform well on pedestrian detection in terms of accuracy but to a cost of large model sizes and heavy computations. This thesis also comes up with a design proposal of a ConvNet for pedestrian detection with the implementation in an embedded system in mind. The proposed network performs well on pedestrian classification and the performance looks promising for detection as well, but further development is required.

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  • 28.
    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)
  • 29.
    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.

  • 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.
    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.

  • 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.
    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.

  • 32.
    Ayyalasomayajula, Kalyan Ram
    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.
    Brun, 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.
    Document Binarization Combining with Graph Cuts and Deep Neural Networks2017Conference paper (Other academic)
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  • 33.
    Ayyalasomayajula, Kalyan Ram
    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.
    Brun, 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.
    Historical document binarization combining semantic labeling and graph cuts2017In: Image Analysis: Part I, Springer, 2017, p. 386-396Conference paper (Refereed)
    Abstract [en]

    Most data mining applications on collections of historical documents require binarization of the digitized images as a pre-processing step. Historical documents are often subjected to degradations such as parchment aging, smudges and bleed through from the other side. The text is sometimes printed, but more often handwritten. Mathematical modeling of appearance of the text, background and all kinds of degradations, is challenging. In the current work we try to tackle binarization as pixel classification problem. We first apply semantic segmentation, using fully convolutional neural networks. In order to improve the sharpness of the result, we then apply a graph cut algorithm. The labels from the semantic segmentation are used as approximate estimates of the text and background, with the probability map of background used for pruning the edges in the graph cut. The results obtained show significant improvement over the state of the art approach.

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  • 34.
    Ayyalasomayajula, Kalyan Ram
    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.
    Brun, 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.
    Semantic Labeling using Convolutional Networks coupled with Graph-Cuts for Document binarization2017Conference paper (Other academic)
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  • 35.
    Ayyalasomayajula, Kalyan Ram
    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.
    Brun, 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.
    Topological clustering guided document binarization2015Report (Other academic)
    Abstract [en]

    The current approach for text binarization proposes a clustering algorithm as a preprocessing stage to an energy-based segmentation method. It uses a clustering algorithm to obtain a coarse estimate of the background (BG) and foreground (FG) pixels. These estimates are usedas a prior for the source and sink points of a graph cut implementation, which is used to efficiently find the minimum energy solution of an objective function to separate the BG and FG. The binary image thus obtained is used to refine the edge map that guides the graph cut algorithm. A final binary image is obtained by once again performing the graph cut guided by the refined edges on Laplacian of the image.

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  • 36.
    Ayyalasomayajula, Kalyan Ram
    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.
    Malmberg, Filip
    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.
    Brun, 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.
    PDNet: Semantic segmentation integrated with a primal-dual network for document binarization2019In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 121, p. 52-60Article in journal (Refereed)
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  • 37.
    Ayyalasomayajula, Kalyan Ram
    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.
    Nettelblad, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Brun, 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.
    Feature evaluation for handwritten character recognition with regressive and generative Hidden Markov Models2016In: Advances in Visual Computing: Part I, Springer, 2016, p. 278-287Conference paper (Refereed)
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  • 38.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    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. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Sladoje, Natasa
    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, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Single image super-resolution reconstruction in presence of mixed Poisson-Gaussian noise2016In: 2016 SIXTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA), IEEE, 2016Conference paper (Refereed)
    Abstract [en]

    Single image super-resolution (SR) reconstructionaims to estimate a noise-free and blur-free high resolution imagefrom a single blurred and noisy lower resolution observation.Most existing SR reconstruction methods assume that noise in theimage is white Gaussian. Noise resulting from photon countingdevices, as commonly used in image acquisition, is, however,better modelled with a mixed Poisson-Gaussian distribution. Inthis study we propose a single image SR reconstruction methodbased on energy minimization for images degraded by mixedPoisson-Gaussian noise.We evaluate performance of the proposedmethod on synthetic images, for different levels of blur andnoise, and compare it with recent methods for non-Gaussiannoise. Analysis shows that the appropriate treatment of signaldependentnoise, provided by our proposed method, leads tosignificant improvement in reconstruction performance.

  • 39.
    Bajic, Buda
    et al.
    Univ Novi Sad, Fac Tech Sci, Novi Sad, Serbia.
    Lindblad, Joakim
    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, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Sladoje, Natasa
    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, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Sparsity promoting super-resolution coverage segmentation by linear unmixing in presence of blur and noise2019In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 28, no 1, article id 013046Article in journal (Refereed)
    Abstract [en]

    We present a segmentation method that estimates the relative coverage of each pixel in a sensed image by each image component. The proposed super-resolution blur-aware model (utilizes a priori knowledge of the image blur) for linear unmixing of image intensities relies on a sparsity promoting approach expressed by two main requirements: (i) minimization of Huberized total variation, providing smooth object boundaries and noise removal, and (ii) minimization of nonedge image fuzziness, responding to an assumption that imaged objects are crisp and that fuzziness is mainly due to the imaging and digitization process. Edge fuzziness due to partial coverage is allowed, enabling subpixel precise feature estimates. The segmentation is formulated as an energy minimization problem and solved by the spectral projected gradient method, utilizing a graduated nonconvexity scheme. Quantitative and qualitative evaluation on synthetic and real multichannel images confirms good performance, particularly relevant when subpixel precision in segmentation and subsequent analysis is a requirement. (C) 2019 SPIE and IS&T

  • 40.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    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. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Sladoje, Nataša
    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, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Blind restoration of images degraded with mixed poisson-Gaussian noise with application in transmission electron microscopy2016In: 2016 Ieee 13Th International Symposium On Biomedical Imaging (ISBI), IEEE, 2016, p. 123-127Conference paper (Refereed)
    Abstract [en]

    Noise and blur, present in images after acquisition, negatively affect their further analysis. For image enhancement when the Point Spread Function (PSF) is unknown, blind deblurring is suitable, where both the PSF and the original image are simultaneously reconstructed. In many realistic imaging conditions, noise is modelled as a mixture of Poisson (signal-dependent) and Gaussian (signal independent) noise. In this paper we propose a blind deconvolution method for images degraded by such mixed noise. The method is based on regularized energy minimization. We evaluate its performance on synthetic images, for different blur kernels and different levels of noise, and compare with non-blind restoration. We illustrate the performance of the method on Transmission Electron Microscopy images of cilia, used in clinical practice for diagnosis of a particular type of genetic disorders.

  • 41.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    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. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Sladoje, Nataša
    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, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Restoration of images degraded by signal-dependent noise based on energy minimization: an empirical study2016In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 25, no 4, article id 043020Article in journal (Refereed)
    Abstract [en]

    Most energy minimization-based restoration methods are developed for signal-independent Gaussian noise. The assumption of Gaussian noise distribution leads to a quadratic data fidelity term, which is appealing in optimization. When an image is acquired with a photon counting device, it contains signal-dependent Poisson or mixed Poisson–Gaussian noise. We quantify the loss in performance that occurs when a restoration method suited for Gaussian noise is utilized for mixed noise. Signal-dependent noise can be treated by methods based on either classical maximum a posteriori (MAP) probability approach or on a variance stabilization approach (VST). We compare performances of these approaches on a large image material and observe that VST-based methods outperform those based on MAP in both quality of restoration and in computational efficiency. We quantify improvement achieved by utilizing Huber regularization instead of classical total variation regularization. The conclusion from our study is a recommendation to utilize a VST-based approach combined with regularization by Huber potential for restoration of images degraded by blur and signal-dependent noise. This combination provides a robust and flexible method with good performance and high speed.

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  • 42.
    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

  • 43.
    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

  • 44.
    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

  • 45.
    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)
  • 46.
    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

  • 47.
    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)
  • 48.
    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)
  • 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.
    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)
  • 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.
    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

1234567 1 - 50 of 681
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