Martin Lillholm
Martin Lillholm

Viceinstitutleder


  1. Udgivet

    Automatic measurement of wrist synovitis from contrast-enhanced MRI: a registration-centered approach

    Mysling, P., Darkner, Sune, Sporring, Jon, Dam, E. & Lillholm, Martin, 2013, Medical Imaging 2013: Image Processing. Ourselin, S. & Haynor, D. R. (red.). SPIE - International Society for Optical Engineering, 6 s. 86692U. (Progress in Biomedical Optics and Imaging; Nr. 36, Bind 14).

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  2. Udgivet

    Automatic quantification of tibio-femoral contact area and congruity

    Tummala, S., Nielsen, Mads, Lillholm, Martin, Christiansen, C. & Dam, Erik Bjørnager, 2012, I : I E E E Transactions on Medical Imaging. 31, 7, s. 1404-1412 9 s.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  3. 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

  4. Udgivet

    Automatic segmentation of vertebrae from radiographs: a sample-driven active shape model approach

    Mysling, P., Petersen, P. K., Nielsen, Mads & Lillholm, Martin, 2011, Machine Learning in Medical Imaging: Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011. Proceedings. Suzuki, K., Wang, F., Shen, D. & Yan, P. (red.). Springer, s. 10-17 8 s. (Lecture notes in computer science, Bind 7009).

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  5. 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

  6. Udgivet

    Breast tissue segmentation and mammographic risk scoring using deep learning

    Petersen, P. K., Nielsen, Mads, Diao, Pengfei, Karssemeijer, N. & Lillholm, Martin, 2014, Breast imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings. Fujita, H., Hara, T. & Muramatsu, C. (red.). Springer Science+Business Media, s. 88-94 7 s. (Lecture notes in computer science, Bind 8539).

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  7. Brownian Images: a generic background model

    Pedersen, Kim Steenstrup & Lillholm, Martin, 2004, Proceedings of the ECCV'04 Workshop on Statistical Learning in Computer Vision.

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  8. Udgivet

    Change in mammographic density across birth cohorts of Dutch breast cancer screening participants

    Napolitano, George, Lynge, Elsebeth, Lillholm, Martin, Vejborg, I. M. M., van Gils, C. H., Nielsen, Mads & Karssemeijer, N., 2019, I : International Journal of Cancer. 145, 11, s. 2954-2962 9 s.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  9. 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

  10. Udgivet

ID: 152298477