Martin Lillholm

Martin Lillholm

Professor


  1. 2012
  2. Published

    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 p.

    Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

  3. Published

    Shape-based assessment of vertebral fracture risk in postmenopausal women using discriminative shape alignment

    Crimi, A., Loog, M., de Bruijne, Marleen, Nielsen, Mads & Lillholm, Martin, 2012, In: Academic Radiology. 19, 4, p. 446-454 9 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. 2011
  5. Published

    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. (eds.). Springer, p. 10-17 8 p. (Lecture notes in computer science, Vol. 7009).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  6. Published

    Finding discriminative regions that optimally separate healthy and osteoarthritis knees

    Jørgensen, D. R., Lillholm, Martin & Dam, E. B., 2011, In: Osteoarthritis and Cartilage. 19, Supplement 1, p. S192 414.

    Research output: Contribution to journalConference abstract in journalResearchpeer-review

  7. Published

    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, In: IEEE transactions on medical imaging. 30, 8, p. 1514-1526 13 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  8. 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 No. G06T-007/00, Patent No. WO2011151242-A1, 8 Dec 2011, Priority date 1 Jun 2010, Priority No. GB009101

    Research output: Patent

  9. Published

    Vertebral fracture risk (VFR) score for fracture prediction in postmenopausal Women

    Lillholm, Martin, Ghosh, A., Pettersen, P. C., de Bruijne, Marleen, Dam, E. B., Karsdal, M. A., Christiansen, C., Genant, H. K. & Nielsen, Mads, 2011, In: Osteoporosis International. 22, 7, p. 2119-2128 10 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  10. 2010
  11. Published

    A framework for optimizing measurement weight maps to minimize the required sample size

    Qazi, A. A., Jørgensen, D. R., Lillholm, Martin, Loog, M., Nielsen, Mads & Dam, Erik Bjørnager, 2010, In: Medical Image Analysis. 14, 3, p. 255-264 10 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  12. Published

    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 No. G06K-009/00, Patent No. US2010232671-A1, 16 Sep 2010, Priority date 17 Dec 2008, Priority No. US203094P

    Research output: Patent

  13. Single gaze gestures

    Møllenbach, E., Lillholm, Martin, Gail, A. & Hansen, J. P., 2010, Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications. Association for Computing Machinery, p. 177-180 4 p.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

ID: 152298477