Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
ORCID: 0000-0002-1402-6899
1 - 4 out of 4Page size: 100
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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, In: SPIE Journal of Medical Imaging. 3, 1, 11 p., 014005.Research output: Contribution to journal › Journal article › Research › peer-review
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Learning density independent texture features
Kallenberg, M. G. J., Nielsen, Mads, Holland, K., Karssemeijer, N., Igel, Christian & Lillholm, Martin, 2016, Breast Imaging: 13th International Workshop, IWDM 2016, Malmö, Sweden, June 19-22, 2016, Proceedings. Tingberg, A., Lång, K. & Timberg, P. (eds.). Springer, p. 299-306 8 p. (Lecture notes in computer science, Vol. 9699).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case-control study
Winkel, R. R., von Euler-Chelpin, My Catarina, Nielsen, Mads, Petersen, P. K., Lillholm, Martin, Nielsen, Michael Bachmann, Lynge, Elsebeth, Uldall, W. Y. & Vejborg, I. M. M., 2016, In: B M C Cancer. 16, 12 p., 414.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring
Kallenberg, M. G. J., Petersen, P. K., Nielsen, Mads, Ng, A. Y., Diao, P., Igel, Christian, Vachon, C. M., Holland, K., Winkel, R. R., Karssemeijer, N. & Lillholm, Martin, 2016, In: IEEE Transactions on Medical Imaging. 35, 5, p. 1322-1331 10 p.Research output: Contribution to journal › Journal article › Research › peer-review
ID: 152298477
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Mammographic texture resemblance generalizes as an independent risk factor for breast cancer
Research output: Contribution to journal › Journal article › Research › peer-review
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643
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Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case-control study
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
355
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Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative
Research output: Contribution to journal › Journal article › Research › peer-review
Published