liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 4 of 4
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Danielsson, Per-Erik
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Lin, Qingfen
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    A modified fast marching method2003In: Image Analysis: 13th Scandinavian Conference, SCIA 2003 Halmstad, Sweden, June 29 – July 2, 2003 Proceedings / [ed] Josef Bigun and Tomas Gustavsson, Springer Berlin/Heidelberg, 2003, Vol. 2749, p. 1154-1161Chapter in book (Refereed)
    Abstract [en]

    In most, if not all fast marching methods published hitherto, the input,cost function and the output arrival time are sampled on exactly the same grid. But since the input data samples are differences of the output samples. we found it natural to separate the input and output grid half a sampling unit in all coordinates (two or three). We also employ 8-neighborhood (26-neighborhood in the 3D-case) in the basic updating step of the algorithm. Some simple numerical experiments verify that the modified method improves the accuracy considerably. However, we also feel the modified method leads itself more naturally to image processing applications like tracking and segmentation.

  • 2.
    Danielsson, Per-Erik
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Lin, Qingfen
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Ye, Qin-Zhong
    Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.
    Efficient detection of second-degree variations in 2D and 3D images2001In: Journal of Visual Communication and Image Representation, ISSN 1047-3203, E-ISSN 1095-9076, Vol. 12, no 3, p. 255-305Article in journal (Refereed)
    Abstract [en]

    Estimation of local second-degree variation should be a natural first step in computerized image analysis, just as it seems to be in human vision. A prevailing obstacle is that the second derivatives entangle the three features signal strength (i.e. magnitude or energy), orientation and shape. To disentangle these features we propose a technique where the orientation of an arbitrary pattern f is identified with the rotation required to align the pattern with its prototype p. This is more strictly formulated as solving the derotating equation. The set of all possible prototypes spans the shape-space of second degree variation. This space is one-dimensional for 2Dimages, two-dimensional for 3D-images. The derotation decreases the original dimensionality of the response vector from three to two in the 2D-case and from six to three in the 3D-case, in both cases leaving room only for magnitude and shape in the prototype. The solution to the derotation and a full understanding of the result requires i) mapping the derivatives of the pattern f onto the orthonormal basis of spherical harmonics, and ii) identifying the eigenvalues of the Hessian with the derivatives of the prototype p. But once the shape-space is established the possibilities to put together independent discriminators for magnitude, orientation, and shape are easy and almost limitless.

  • 3. Order onlineBuy this publication >>
    Lin, Qingfen
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Enhancement, Extraction, and Visualization of 3D Volume Data2003Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Three-dimensional (3D) volume data has become increasingly common with the emergence and wide availability of modern 3D image acquisition techniques. The demand for computerized analysis and visualization techniques is constantly growing to utilize the abundant information embedded in these data.

    This thesis consists of three parts. The first part presents methods of analyzing  3D volume data by using second derivatives. Harmonic functions are used to combine the non-orthogonal second derivative operators into an orthogonal basis. Three basic features, magnitude, shape, and orientation, are extracted from the second derivative responses after diagonalizing the Hessian matrix. Two applications on magnetic resonance angiography (MRA) data are presented. One of them utilizes a scale-space and the second order variation to enhance the vascular  system by discriminating for string structures. The other one employs the local shape information to detect cases of stenosis.

    The second part of the thesis discusses some modifications of the fast marching method in 2D and 3D space. By shifting the input and output grids relative to each other, we show that the sampled cost functions are used in a more consistent way. We present new algorithms for anisotropic fast marching which incorporate orientation information during the marching process. Three applications illustrate the usage of the fast marching methods. The first one extracts a guide wire as a minimum-cost path on a salience distance map of a line detection result of a flouroscopy image. The second application extracts the vascular tree from a whole bodyMRA volume. In the third application, a 3D guide wire is reconstructed from a pair of biplane images using the minimum-cost path formulation.

    The third part of the thesis proposes a new frame-coherent volume rendering algorithm. It is an extension of the algorithm by Gudmundsson and Rand´en (1990). The new algorithm is capable of efficiently generating rotation sequences around an arbitrary axis. Essentially, it enables the ray-casting procedure to quickly approach the hull of the object using the so called shadow-lines recorded from the previous frame.

  • 4.
    Tizon, X.
    et al.
    Centre for Image Analysis, SLU/Uppsala University, Uppsala, Sweden.
    Lin, Qingfen
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Hansen, T.
    Department of Oncology, Radiology and Clinical Immunology, Uppsala University Hospital, Uppsala, Sweden.
    Borgefors, G.
    Centre for Image Analysis, SLU/Uppsala University, Uppsala, Sweden.
    Johansson, L.
    Department of Oncology, Radiology and Clinical Immunology, Uppsala University Hospital, Uppsala, Sweden.
    Ahlstrom, H.
    Ahlström, H., Department of Oncology, Radiology and Clinical Immunology, Uppsala University Hospital, Uppsala, Sweden.
    Frimmel, H.
    Department of Oncology, Radiology and Clinical Immunology, Uppsala University Hospital, Uppsala, Sweden, Biomedialab, ICT Centre, CSIRO, 300 Adelaide St., Brisbane, QLD 4000, Australia.
    Identification of the main arterial branches by whole-body contrast-enhanced MRA in elderly subjects using limited user interaction fast marching2007In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 25, no 4, p. 806-814Article in journal (Refereed)
    Abstract [en]

    Purpose: To extract a graph model corresponding to a predefined set of arterial branches from whole-body contrast-enhanced magnetic resonance angiography (CE-MRA) data sets in elderly asymptomatic subjects, a high-incidence group. Materials and Methods: Maximum intensity projections (MIPs) were used as an interface to place landmarks in the three-dimensional (3D) data sets. These landmarks were linked together using fast marching to form a graph model of the arterial tree. Only vessels of interest were identified. Results: We tested our method on 10 subjects. We were able to build a graph model of the main arterial branches that performed well in the presence of vascular pathologies, such as stenosis and aneurysm. The results were rated by an experienced radiologist, with an overall success rate of 80%. Conclusion: We were able to extract chosen arterial branches in 3D whole-body CE-MRA images with a moderate amount of interaction using a single MIP projection. © 2007 Wiley-Liss, Inc.

1 - 4 of 4
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf