Martin Lillholm

Martin Lillholm

Viceinstitutleder


  1. Udgivet
  2. Udgivet

    Dementia diagnosis using MRI cortical thickness, shape, texture, and volumetry

    Sørensen, L., Pai, A. S. U., Anker, C., Balas, I., Lillholm, Martin, Igel, Christian & Nielsen, Mads, 2014, MICCAI 2014 Workshop Proceedings: Challenge on Computer-Aided Diagnosis of Dementia Based on Structural MRI Data. Bron, E. E., Smits, M., van Swieten, J. C., Niessen, W. J. & Klein, S. (red.). Erasmus Universiteit Rotterdam, s. 111-118 8 s.

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  3. Udgivet

    Deformation-based atrophy computation by surface propagation and its application to Alzheimer’s disease

    Pai, A. S. U., Sporring, Jon, Darkner, Sune, Dam, Erik Bjørnager, Lillholm, Martin, Jørgensen, D., Oh, J., Chen, G., Suhy, J., Sørensen, L. & Nielsen, Mads, 2016, I: SPIE Journal of Medical Imaging. 3, 1, 11 s., 014005.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  4. Udgivet

    Cube propagation for focal brain atrophy estimation

    Pai, A. S. U., Sørensen, L., Darkner, Sune, Mysling, P., Jørgensen, D. R., Dam, E. B., Lillholm, Martin, Oh, J., Chen, G., Suhy, J., Sporring, Jon & Nielsen, Mads, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging. IEEE, s. 402-405 4 s.

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  5. Udgivet

    Computer based method for determining the size of an objects in an image

    Pai, A. S. U., Sørensen, L., Dam, E. B., Lillholm, Martin & Nielsen, Mads, 4 dec. 2014, Prioritetsdato 4 dec. 2014

    Publikation: Patent

  6. Udgivet

    Computer analysis method for analyzing images involves applying algorithm to aligned images to extract quantitative estimate of difference in volume of object shown in second image by calculating change in volume of object

    Pai, A. S. U., Sørensen, L., Dam, E., Lillholm, Martin & Nielsen, Mads, 2014, IPC nr. A61B-005/00, Patentnr. US2014357978-A1, 4 dec. 2014, Prioritetsdato 4 jun. 2013, Prioritetsnr. US909666

    Publikation: Patent

  7. 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

  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. Brownian Images: a generic background model

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

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  10. Udgivet

    Breast tissue segmentation and mammographic risk scoring using deep learning

    Petersen, P. K., Nielsen, Mads, Diao, P., 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

ID: 152298477