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  • 1.
    Malmberg, Filip
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Vidholm, Erik
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nyström, Ingela
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A 3D live-wire segmentation method for volume images using haptic interaction2006In: DISCRETE GEOMETRY FOR COMPUTER IMAGERY, PROCEEDINGS 4245, 2006, p. 663-673Conference paper (Refereed)
    Abstract [en]

    Designing interactive segmentation methods for digital volume images is difficult, mainly because efficient 3D interaction is much

    harder to achieve than interaction with 2D images. To overcome this issue, we use a system that combines stereo graphics and haptics to facilitate efficient 3D interaction. We propose a new method, based on the 2D live-wire method, for segmenting volume images. Our method consists of two parts: an interface for drawing 3D live-wire curves onto the boundary of an object in a volume image, and an algorithm for connecting two such curves to create a discrete surface.

  • 2.
    Vidholm, Erik
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A tool for filtering and visualization of digital images in the Fourier domain2003Report (Other scientific)
    Abstract [en]

    A software application for image filtering in the 2D and 3D

  • 3.
    Vidholm, Erik
    Uppsala University.
    Haptic interaction with deformable simplex meshes for 3D segmentation2007In: Swedish symposium on image analysis (SSBA), 2007, p. 1-4Conference paper (Other scientific)
    Abstract [en]

    We present a tool for interactive 3D segmentation using deformable

    surfaces represented by simplex meshes. The interaction is performed directly in 3D with a haptic device. Haptic feedback is generated from image data in order to provide the user with information that can facilitate tuning of model parameters. It is also possible to directly interact with the mesh by grabbing vertices and move them in order to initialize the model properly or guide it during deformation.

  • 4.
    Vidholm, Erik
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Agmund, Jonas
    Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Fast surface rendering for interactive medical image segmentation with haptic feedback2004In: Proceedings of SIGRAD 2004: Special theme - Environmental visualization, 2004Conference paper (Refereed)
    Abstract [en]

    In this work, we present a haptic-enabled application

    for interactive editing in medical

    image segmentation. We use a fast surface rendering algorithm to

    display the different segmented objects, and we apply a

    proxy-based volume haptics algorithm to be able to touch and edit these

    objects at interactive rates. As an application example,

    we show how the system can be used to initialize a fast marching

    segmentation algorithm for extracting the liver in magnetic resonance (MR)

    images and then edit the result if it is incorrect.

  • 5.
    Vidholm, Erik
    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.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Nyström, Ingela
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    A toolkit for interactive medical image visualization and segmentation with haptics2008Manuscript (preprint) (Other academic)
  • 6.
    Vidholm, Erik
    et al.
    Uppsala University.
    Mehnert, Andrew
    ITEE, The University of Queensland, Brisbane, Australia.
    Bengtsson, Ewert
    Uppsala University.
    Wildermoth, Michael
    ITEE, The University of Queensland, Brisbane, Australia.
    McMahon, Kerry
    Queensland X-Ray, Greenslopes Private Hospital, Brisbane, Australia.
    Wilson, Steven
    ITEE, The University of Queensland, Brisbane, Australia.
    Crozier, Stuart
    ITEE, The University of Queensland, Brisbane, Australia.
    Hardware-accelerated volume visualisation of parametrically mapped dynamic breast MRI data2007In: MICCAI 2007: Workshop on Interaction in medical image analysis and visualization, 2007, p. 33-40Conference paper (Refereed)
    Abstract [en]

    We present a new approach to visualising parametric volumes obtained in voxel-wise model fitting of dynamic contrast-enhanced

    (DCE) MRI data of the breast. The visualisation makes use of hardware accelerated rendering to obtain an interactive, 3D colour-correct maximum intensity projection (MIP). The method has been realised in software that permits the user to not only interactively visualise the parametric volume but also to delineate 3D regions of interest using a 2D slicewise interface. Experimental results, based on 14 DCE-MRI data sets from routine clinical practice, show that using the visualisation/tracing tool a medically qualified operator can achieve the same sensitivity for the detection of malignancy as a radiologist using conventional manual interpretation, but with better specificity. The results demonstrate that the visualisation methodology/software has potential as a tool for assisting the radiologist with the task of interpreting 4D DCE-MRI data in the routine clinical setting.

  • 7.
    Vidholm, Erik
    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.
    Nilsson, Sven
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology, Radiology.
    Nyström, Ingela
    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.
    Fast and robust semi-automatic liver segmentation with haptic interaction2006In: MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2006, PROCEEDINGS 4191, 2006, p. 774-781Conference paper (Refereed)
    Abstract [en]

    We present a method for semi-automatic segmentation of the liver from CT scans. True 3D interaction with haptic feedback is used to facilitate initialization, i.e., seeding of a fast marching algorithm. Four users initialized 52 datasets and the mean interaction time was 40 seconds. The segmentation accuracy was verified by a radiologist. Volume measurements and segmentation precision show that the method has a high reproducibility.

  • 8.
    Vidholm, Erik
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis.
    Nyström, Ingela
    Uppsala University, Interfaculty Units, Centre for Image Analysis.
    A haptic interaction technique for volume images based on gradient diffusion2005In: World Haptics Conference, 2005, p. 336-341Conference paper (Refereed)
    Abstract [en]

    The manual step in semi-automatic segmentation of medical volume images typically involves initialization procedures such as placement of seed-points or positioning of surface models inside the object to be segmented. The initialization is then used as input to an automatic algorithm. We investigate how such initialization tasks can be facilitated by using haptic feedback. This paper describes a haptic interaction technique based on gradient vector flow (GVF) that allows a user to feel object boundaries while still being centered inside the object. Our method is not limited to elongated structures, which is a common restriction for other approaches. Initial tests of the method shows encouraging results for differently shaped objects.

  • 9.
    Vidholm, Erik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nyström, Ingela
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Haptic interaction with deformable models for 3D liver segmentation2007In: Proceedings of MICCAI Workshop: Interaction in Medical Image Analysis and Visualization 2007, 2007, p. 41-48Conference paper (Refereed)
    Abstract [en]

    We present a tool for interactive 3D liver segmentation using deformable surface models represented by simplex meshes. The interaction is performed directly in 3D with a haptic device. We use volume haptics to convey information about the volumetric data used for external force computations. This helps us to better understand the data and adjust the deformation weights. It is also possible to interact directly with the mesh during deformation. By pointing the haptic probe like a “torch” at the mesh, vertices and faces in a user specified neighbourhood are selected and forces can be applied to the selected sub-mesh only. We performed an experiment where 10 segmentations of the liver from CT data was performed. The segmentation results show high sensitivity and

    specificity when compared to manual delineations made by a radiologist.

  • 10.
    Vidholm, Erik
    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.
    Nyström, Ingela
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Haptic volume rendering based on gradient vector flow2005In: Proceedings of SSBA (Swedish Society for Automated Image Analysis) Symposium on Image Analysis, Malmö, Sweden, 2005, p. 97-100Conference paper (Other academic)
  • 11.
    Vidholm, Erik
    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.
    Sundqvist, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Nyström, Ingela
    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.
    Accelerating the Computation of 3D Gradient Vector Flow Fields2006In: Proc, IEEE , 2006, p. 677-680Conference paper (Refereed)
  • 12.
    Vidholm, Erik
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Tizon, Xavier
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nyström, Ingela
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Haptic guided seeding of MRA images for semi-automatic segmentation2004In: Proceedings of IEEE international symposium on biomedical imaging: From nano to macro, 2004, p. 288-291Conference paper (Refereed)
    Abstract [en]

    We investigate how stereo graphics

    and haptics can be combined to facilitate the seeding procedure

    in semi-automatic segmentation of magnetic resonance angiography (MRA)

    images. Real-time volume rendering using maximum intensity

    projections (MIPs) has been implemented together with a haptic

    rendering method that provides force feedback based on local

    gradients and intensity values. This combination allows a

    user to trace vessels in the image, and to

    place seed-points directly in the 3D data set. Seed-regions

    are propagated from the seed-points

    according to an algorithm that favors bright voxels.

    An experienced user have tested the interface

    on whole-body MRA images with promising results.

1 - 12 of 12
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  • nn-NO
  • nn-NB
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