Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
ORCID: 0000-0002-1402-6899
1 - 1 out of 1Page size: 10
- 2016
- Published
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
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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628
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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
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339
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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