Martin Lillholm

Martin Lillholm

Viceinstitutleder


  1. Natural image profiles are most likely to be step edges

    Griffin, L. D., Lillholm, Martin & Nielsen, Mads, 2004, I : Vision Research. 44, 4, s. 407-421 15 s.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  2. Basic image features (BIFs) arising from approximate symmetry type

    Griffin, L. D., Lillholm, Martin, Crosier, M. & van Sande, J., 2009, Scale Space and Variational Methods in Computer Vision: Second International Conference, SSVM 2009, Voss, Norway, June 1-5, 2009. Proceedings. Tai, X-C., Mørken, K., Lysaker, M. & Lie, K-A. (red.). Springer, s. 343-355 13 s. (Lecture notes in computer science, Bind 5567).

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  3. Mode estimation using pessimistic scale space tracking

    Griffin, L. D. & Lillholm, Martin, 2003, Scale Space Methods in Computer Vision: 4th International Conference, Scale Space 2003 Isle of Skye, UK, June 10–12, 2003 Proceedings. Griffin, L. D. & Lillholm, M. (red.). Springer, s. 266-280 15 s. (Lecture notes in computer science, Bind 2695).

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  4. Classifying local image symmetry using a co-localised family of linear filters

    Griffin, L. D. & Lillholm, Martin, 2008, I : Perception. 37, Supplement, s. 122-122 1 s.

    Publikation: Bidrag til tidsskriftKonferenceabstrakt i tidsskriftForskning

  5. Udgivet

    Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative

    Dam, Erik Bjørnager, Lillholm, Martin, Marques, J. & Nielsen, Mads, 2015, I : SPIE Journal of Medical Imaging. 2, 2, 13 s., 024001.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  6. Udgivet

    Method for identifying region of interest (ROI) in human organ for performing e.g. knee cartilage quantification, involves calculating weight of feature of image in map for minimizing sample size needed to discriminate between groups

    Dam, E. B., Nielsen, Mads, Qazi, A. A., Lillholm, Martin & Jørgensen, D. R., 2010, IPC nr. G06K-009/00, Patentnr. US2010232671-A1, 16 sep. 2010, Prioritetsdato 17 dec. 2008, Prioritetsnr. US203094P

    Publikation: Patent

  7. Method for analyzing magnetic resonance imaging (MRI) image of bone to identify e.g. osteoarthritis, involves combining features of textural information within region of interest (ROI) to estimate level of disease

    Dam, E. B., Granlund, R. L. & Lillholm, Martin, 2011, IPC nr. G06T-007/00, Patentnr. WO2011151242-A1, 8 dec. 2011, Prioritetsdato 1 jun. 2010, Prioritetsnr. GB009101

    Publikation: Patent

  8. Udgivet

    Quaternions, interpolation and animation

    Dam, E., Koch, M. & Lillholm, Martin, 1998, Datalogisk Institut, Københavns Universitet, 103 s. (DIKU teknisk rapport; Nr. 5, Bind 98).

    Publikation: Working paperForskning

  9. Udgivet

    Fully automatic cartilage morphometry for knee MRI from the OAI

    Dam, E., Marques, J., Zaim, S., Fuerst, T., Genant, H., Lillholm, Martin & Nielsen, Mads, 2012. 1 s.

    Publikation: KonferencebidragKonferenceabstrakt til konferenceForskningfagfællebedømt

  10. Udgivet

    Maximum a posteriori estimation of linear shape variation with application to vertebra and cartilage modeling

    Crimi, A., Lillholm, Martin, Nielsen, Mads, Ghosh, A., de Bruijne, Marleen, Dam, E. B. & Sporring, Jon, 2011, I : IEEE transactions on medical imaging. 30, 8, s. 1514-1526 13 s.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

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